![Annual incidence rates of non-Hodgkin lymphoma (NHL) subtypes among active-component U.S. service members, 2017-2023. Figure adapted from Russell et al. [85] using Defense Medical Surveillance System data demonstrating rise in specified/unspecified NHL and mature T/NK-cell subtypes. Vertical lines denote key timepoints: the onset of the COVID-19 pandemic (early 2020) and the beginning of the Department of Defense vaccine mandate (late 2020-early 2021).](https://www.researchgate.net/profile/Charlotte-Kuperwasser/publication/399498474/figure/fig3/AS:11431281837642092@1767724457867/Annual-incidence-rates-of-non-Hodgkin-lymphoma-NHL-subtypes-among-active-component-US_Q320.jpg)
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www.oncotarget.com Oncotarget, 2026, Vol. 17, pp: 1-29
Review
COVID vaccination and post-infection cancer signals: Evaluating
patterns and potential biological mechanisms
Charlotte Kuperwasser1,2 and Wafik S. El-Deiry3,4,5
1Department of Developmental, Molecular and Chemical Biology, Tufts University School of Medicine, Boston, MA 02111, USA
2Laboratory for the Convergence of Biomedical, Physical, and Engineering Sciences, Tufts University School of Medicine,
Boston, MA 02111, USA
3Laboratory of Translational Oncology and Experimental Cancer Therapeutics, Department of Pathology and Laboratory
Medicine, The Warren Alpert Medical School of Brown University, Providence, RI 029121, USA
4Hematology-Oncology Division, Department of Medicine, Brown University Health and The Warren Alpert Medical School of
Brown University, Providence, RI 029121, USA
5Legorreta Cancer Center at Brown University, The Warren Alpert Medical School of Brown University, Providence, RI 029121,
USA
Correspondence to: Charlotte Kuperwasser, email: charlotte.kuperwasser@tufts.edu
Wafik S. El-Deiry, email: wafik@brown.edu
Keywords: COVID; vaccine; cancer; infection; lymphoma; leukemia; sarcoma; carcinoma
Received: November 26, 2025 Accepted: December 26, 2025 Published: January 03, 2026
Copyright: © 2026 Kuperwasser and El-Deiry. This is an open access article distributed under the terms of the Creative Commons Attribution
License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source
are credited.
ABSTRACT
A growing number of peer-reviewed publications have reported diverse cancer
types appearing in temporal association with COVID-19 vaccination or infection. To
characterize the nature and scope of these reports, a systematic literature search from
January 2020 to October 2025 was conducted based on specified eligibility criteria.
A total of 69 publications met inclusion criteria: 66 article-level reports describing
333 patients across 27 countries, 2 retrospective population-level investigations
(Italy: ~300,000 cohort, and Korea: ~8.4 million cohort) quantified cancer incidence
and mortality trends among vaccinated populations, and one longitudinal analysis of
~1.3 million US miliary service members spanning the pre-pandemic through post-
pandemic periods. Most of the studies documented hematologic malignancies (non-
Hodgkin’s lymphomas, cutaneous lymphomas, leukemias), solid tumors (breast, lung,
melanoma, sarcoma, pancreatic cancer, and glioblastoma), and virus-associated
cancers (Kaposi and Merkel cell carcinoma). Across reports, several recurrent
themes emerged: (1) unusually rapid progression, recurrence, or reactivation of
preexisting indolent or controlled disease, (2) atypical or localized histopathologic
findings, including involvement of vaccine injection sites or regional lymph nodes,
and (3) proposed immunologic links between acute infection or vaccination and tumor
dormancy, immune escape, or microenvironmental shifts. The predominance of case-
level observations and early population-level data demonstrates an early phase of
potential safety-signal detection. These findings underscore the need for rigorous
epidemiologic, longitudinal, clinical, histopathological, forensic, and mechanistic
studies to assess whether and under what conditions COVID-19 vaccination or
infection may be linked with cancer.
INTRODUCTION
The COVID-19 pandemic and the widespread
deployment of novel mRNA- and viral-vector based
vaccines have reshaped the landscape of human
immunology [1–4]. Never has such a large proportion
of the global population been exposed simultaneously to
nucleic acid–based immunogens, lipid nanoparticle (LNP)
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delivery systems, and repeated booster regimens over a
relatively short period. The unprecedented scale that
was marshaled in response to the COVID-19 pandemic
has generated and continues to generate extensive
clinical, molecular, and epidemiologic data, revealing
biological responses that extend beyond traditional
vaccine-induced immune activation and responses. These
include a spectrum of post-infection and post-vaccination
neurological, autoimmune, and inflammatory syndromes,
including myocarditis, immune-mediated neuropathies,
autoimmune cytopenias, systemic inflammatory responses
[5–7], as well as temporal co-occurrence with cancer
diagnoses, recurrences, or unexpectedly rapid disease
trajectories [8–11]. These events have prompted extensive
clinical investigation and underscore the capacity of
vaccine-induced immune activation to perturb immune
homeostasis in susceptible individuals. Importantly,
many of these conditions are characterized by cytokine
dysregulation, altered innate and adaptive immune
signaling, and tissue-specific inflammatory responses;
pathways that are also implicated in tumor initiation,
progression, and immune surveillance. The present
review focuses specifically on cancer-related observations
within this broader context of post-vaccination immune
perturbation.
After nearly six years since the pandemic was
recognized in early 2020, the current world’s literature
addressing COVID-19 infection or vaccination and
cancer remains sparse, heterogeneous, and largely
limited to case reports and small case series, insufficient
to support definitive conclusions regarding causation
or quantification of risk. Package inserts for COVID19
vaccines posted by the Food and Drug Administration
(FDA) [12–15] specifically state that they have not
been evaluated for carcinogenicity or genotoxicity, nor
have they been studied after multiple vaccine doses and
boosters or in combination with subsequent SARS-CoV-2
infection.
During the COVID pandemic, it was predicted
that cancer rates would rise during and after COVID due
to reduced screening and reduced access to treatment
during the pandemic. However, rates of cancer among
younger individuals for example with early onset colon
cancer have been rising for two decades [16, 17]. Rates
of cholangiocarcinoma and endometrial cancer have been
rising as well. Cancer deaths exceeded 600,000 in US
for 1st time in 2024 and in 2025 are predicted to rise as
well [18]. As of the writing of this review, there are no
published population studies in the US with mortality or
cancer incidence follow-up beyond 42 days for outcomes
after Covid infection versus no Covid infection or Covid
vaccinated versus not Covid vaccinated. This is in part due
to lack of good quality databases that would have such
information. There is a National Cancer Institute (NCI)-
funded Covid and Cancer Consortium (CCC) but it has not
published on this topic specifically.
Against the backdrop of limited clinical evidence
and incomplete preclinical toxicology, a recent study
reported that SARS-CoV-2 mRNA vaccines may
actually sensitize tumors to immune checkpoint
blockade [19] prompting broad interpretation that
COVID-19 mRNA vaccination may actually potentiate
antitumor responses in patients with melanoma or non–
small cell lung cancer (NSCLC) undergoing immune
checkpoint inhibition. Moreover, in the analysis,
mRNA vaccination was associated with increased
Type I interferon signaling and elevated tumor PD-L1
expression. However, PD-L1 upregulation in the absence
of checkpoint inhibitor therapy is generally associated
with enhanced tumor immune evasion and resistance
to T-cell–mediated cytotoxicity, raising questions
about the biological interpretation of these findings.
Although interferon-based therapies have established
clinical utility in melanoma, the study did not provide
comparative analyses between interferon treatment and
the combination of mRNA vaccination with checkpoint
blockade. Furthermore, the study did not address key
limitations, alternative mechanistic explanations, or the
broader clinical context necessary to fully interpret the
reported effects.
This absence of evaluation of COVID19 vaccines
for carcinogenicity or genotoxicity motivated a systematic
review and synthesis of the available evidence from
2020–2025 concerning COVID-19 vaccination, SARS-
CoV-2 infection, and cancer. Specifically, we sought to (i)
categorize malignancies reported in temporal proximity to
vaccination or infection, (ii) evaluate temporal and clinical
patterns across tumor types for relevant signals among
patients exposed to the COVID vaccines, and (iii) outline
plausible immunologic and molecular mechanisms that
could underlie these phenomena.
Across the published literature, we identified
reports involving hematologic malignancies, including
lymphomas and leukemias, solid tumors such as breast,
lung, pancreatic, and glial cancers, virus-associated
malignancies including Kaposi sarcoma and Merkel cell
carcinoma, and rare entities such as sarcomas, melanomas,
and adenoid cystic carcinomas. While the number of
studies or their temporal association does not establish
causation, understanding whether these associations
represent coincidence, immune dysregulation, or a broader
biologic effect linking infection, vaccination, and cancer
development is now of pressing importance.
Importantly, regarding reported adverse events
and potential risks, awareness of what has occurred,
even if ultimately this proves to be extremely rare, is
a necessary component of informed consent at a time
when there is no longer a public health emergency from
COVID-19. Cancer risk is likely based on heterogeneity
among individuals, the impact of genetics, environment,
and interacting social determinants of health that varies
among individuals and this is an area where this article
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could form a foundation for future studies to refine
individualized risk. As such, the goal of this article is
to systematically synthesize and contextualize findings
from the published literature regarding malignancies
temporally associated with COVID-19 vaccination or
SARS-CoV-2 infection, without attempting to estimate
risk, establish causality, or inform individual clinical or
vaccination decisions.
RESULTS
This scoping review, covering the period of January
2020 until April 2025, was not designed to estimate cancer
risk or incidence, nor to draw causal inferences, but rather
to systematically assemble, categorize, and contextualize
published reports of malignancies temporally associated
with COVID-19 vaccination or SARS-CoV-2 infection.
It identified 69 publications [8, 20–87] describing
malignancies or malignant progression in temporal
association with COVID-19 vaccination or SARS-CoV-2
infection, encompassing a total of 333 patients (excluding
population-level studies [8, 20]. In addition, one
population-level publication which offered a longitudinal
assessment of cancer incidence across the pandemic and
immediate post-pandemic period was identified [85].
Among the 69 studies, most reports were single-patient
case reports or small series (55/69, 81%), with a small
number of systematic or narrative reviews (3/69, 4.5%),
mechanistic/experimental studies (2/69, 3%), and larger
case series, multicenter, or database-level analyses (8/69,
12%) (Table 1). Consistent with an early signal-detection
phase, the underlying evidence base is therefore heavily
weighted toward documenting occurrences of potentially
adverse events and hypothesis-generating case-level
observations rather than population-based epidemiologic
studies.
Geographic distribution
Reports originated from a wide range of countries
spanning Asia, Europe, the Middle East, Africa, and
North and South America. The countries with the highest
number of publications were Japan (n = 11) and the
United States (n = 11), followed by China (n = 7) and
Italy (n = 4). Additional single-patient cases or small
series were identified from Spain, South Korea, Saudi
Arabia, India, Nigeria, Brazil, Turkey, Singapore,
Lebanon, Egypt, Bulgaria, Taiwan, Ukraine, Iran, Russia,
Greece, Austria, Germany, Poland/Ukraine, as well as
multi-institutional or international collaborations. This
broad geographic distribution indicates that the reported
temporal associations between COVID-19 vaccination
or infection and oncologic events are not confined to a
particular region or healthcare system but have been
observed across diverse clinical settings and diagnostic
infrastructures around the globe.
Exposure types: Vaccination versus infection
Most publications identified in the search focused on
oncologic events occurring after COVID-19 vaccination
(56/69; 89%), with the remainder describing associations
following SARS-CoV-2 infection (5/69; 7%), and SARS-
CoV-2 infection with prior vaccination (7/69; 10%). One
publication (1/69; 1%) did not explicitly specify whether
the reported oncologic event followed vaccination, SARS-
CoV-2 infection, or a combination of both exposures. These
included case reports and mechanistic studies evaluating
post-infectious tumor behavior, immune perturbation, or
disease acceleration along with SARS-CoV-2 infection but
in the absence of vaccination or associated with a SARS-
CoV2 infection but with prior vaccination or boosting. The
predominance of vaccination-associated case reports may
reflect reporting patterns rather than comparative biological
risk, and the available data lack sufficient individual-level
detail to determine whether or how oncologic responses
differ between infection or vaccination.
Across the published literature, reported vaccine
formulations and exposure types were heterogeneous
but could be grouped into broad platform categories
(Figure 1). Among vaccine-related reports, the majority
involved mRNA vaccines, with approximately 56%
following the Pfizer-BioNTech vaccine (BNT162b2) and
25% following the Moderna vaccine (mRNA-1273). An
additional 5% involved patients who had received both
Pfizer and Moderna products across different doses.
Adenovirus vector vaccines represented the next largest
category, including AstraZeneca (ChAdOx1/Covishield)
(5.8%), Johnson & Johnson (Ad26.COV2.S) (2.9%) and
the Russian, Sputnik-V (1.4%). Inactivated vaccines
(e.g., Sinopharm BBIBP-CorV, CoronaVac, or other
formulations) and studies in which the specific vaccine
type was not reported were least represented (2.6% and
1.1%, respectively). This distribution indicates that the
published literature is heavily weighted toward mRNA
vaccine platforms, particularly Pfizer-BioNTech and
Moderna, which together account for the vast majority
of vaccine-associated reports. This pattern closely
mirrors global vaccination practices where mRNA
vaccines were most widely deployed. The relatively
smaller representation of adenoviral vector vaccines and
inactivated platforms likely reflects both their more limited
use in certain regions and differential reporting practices,
rather than a comparative assessment of biological risk.
Cancer types and clinical spectrum
Approximately 43% (30/69) of publications reported
lymphoid malignancies, encompassing both lymphomas
and leukemias (Figure 2 and Table 2). These included a
wide spectrum of lymphoid neoplasms such as diffuse large
B-cell lymphoma (DLBCL), various T-cell lymphomas
(e.g., angioimmunoblastic T-cell lymphoma, subcutaneous
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panniculitis-like T-cell lymphoma), chronic lymphocytic
leukemia/small lymphocytic lymphoma (CLL/SLL), and
cutaneous T-cell lymphomas (CTCL). Several reports
emphasized unexpectedly rapid progression, atypical
presentations, or unusually aggressive courses of disease.
Solid tumors accounted for 41% of publications
(28/69) and represented a diverse group of malignancies,
including melanoma, breast cancer, lung cancer,
glioblastoma and other glial tumors, sarcomas, and
various organ-specific carcinomas, such as pancreatic
cancer (Figures 2 and 3). In multiple reports, the authors
described unusually rapid onset, short-latency recurrence,
or aggressive clinical progression for tumor types such
as pancreatic adenocarcinoma and glioblastoma; features
that are atypical for these cancers highlighted as notable
temporal observations.
A subset of reports described tumor formation or
recurrence at or near vaccine injection sites, the deltoid
region, axilla, or draining lymphatic basins, including
cases where axillary lymphadenopathy coincided with
solid-tumor metastasis. Virus-associated malignancies
such as Kaposi sarcoma, Merkel cell carcinoma, and EBV-
Table 1: Summary of reports linking COVID-19 vaccination or infection to cancer
Study type N% of Total
(N = 69) Comments
Case reports 50 72% Dominant study type; mostly single-patient descriptions
Case series 5 7% Typically 2-several patients
Systematic/narrative reviews 3 4% Summaries or literature syntheses
Cohort/retrospective/
observational population studies 8 12% Larger-scale data (e.g., population cohort, single center
cohort)
Mechanistic/translational studies
(tissue, organoids, mouse) 3 4% Experimental or preclinical mechanistic work
Figure 1: Distribution of reported malignancies by COVID-19 vaccine type. Distribution of vaccine formulations among
vaccinated patients with reported cancer following COVID-19 immunization. Most cases involved Pfizer-BioNTech (BNT162b2; 56%)
and Moderna (mRNA-1273; 25%) vaccines, followed by AstraZeneca/ChAdOx1 (Covishield; 17%) and Johnson & Johnson/Ad26.
COV2.S (8%). A small fraction of reports involved Sinovac (CoronaVac), Sinopharm (BBIBP-CorV), or other inactivated vaccines, as
well as unspecified mRNA or COVID-19 vaccine types. The predominance of mRNA vaccines reflects their widespread global use during
the study period.
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positive lymphomas were also identified across several
reports. The remaining 16% of publications (11/69) were
categorized as other or unspecified, which included mixed
or indeterminate cases, non-malignant proliferations,
studies referencing “cancer”, “tumor”, or “malignancy”
without definitive histopathologic classification, and
population-level analyses in which tumor type was not
explicitly delineated.
Figure 2: Distribution of post-vaccination and post-infection malignancies by tumor type. Distribution of reports with
malignancy or tumor-like lesions temporally associated with COVID-19 vaccination, SARS-CoV-2 infection, or SARS-CoV-2 infection
and vaccination. Pie charts depict the proportional representation of major cancer categories observed. (A) Accross all studies. (B)
COVID-19 vaccination, (C) SARS-CoV-2 infection, and (D) combined SARS-CoV-2 infection and COVID-19 vaccination. Cancer types
were consolidated into seven high-level categories. Carcinoma includes: breast cancer, prostate cancer, colon cancer, pancreatic cancer,
lung cancer, Merkel cell carcinoma, GI neoplasia/polyposis. Lymphoma also includes lymphoid neoplasms, cutaneous lymphoproliferative
disorders, lymphoproliferative disorder. Other includes benign tumors, pseudotumors, mixed tumors, heart tumors, inflammatory and non-
specific tumors (e.g., myofibroblastic).
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Specific examples of cancers and their
association with COVID vaccination
Lymphoma
Cavanna et al. [26] reports the review of a series of
eight patients who developed Non-Hodgkin’s Lymphoma
after COVID-19 vaccination (Table 3), including four
males and four women. Five patients were vaccinated with
the BNT162b2 vaccine (Pfizer), one with the ChAdOx1
nCOV-19 vaccine (AstraZeneca, Cambridge, UK), one
with mRNA 1273/Spikevax (ModernaTX) and one patient
with the recombinant replication-incompetent adenovirus
type 26 (Ad26) viral-vector-based COVID-19 vaccine
(Janssen Pharmaceuticals, Beerse, Belgium). One of the
NHL cases presented with large right axillary adenopathy
shortly after COVID-19 vaccination (Figure 3A).
Sekizawa et al. [28] describe a case of marginal
zone B-Cell lymphoma in an 80-year-old Japanese woman
who presented with a right temporal mass that appeared
the morning after she was administered her first mRNA
COVID-19 vaccination (BNT162b2) (Figure 3B). The
mass gradually decreased in size but persisted over 6
weeks after her first vaccination (3 weeks after her second
vaccination). At her first visit, ultrasound revealed the
size of the mass to be 28.5 Å~ 5.7 mm, and computed
tomography revealed multiple lymphadenopathies in the
right parotid, submandibular, jugular, and supraclavicular
regions. This case brings up the possibility that an initial
mass may not be composed entirely of cancer cells and
may have an element of a host response that may limit the
progression depending on immune or other factors. In this
case, the patient had marginal zone B-cell lymphoma after
BNT162B2 COVID-19 vaccination.
Sarcoma
Bae et al. [21] reported the development of high
grade sarcoma after the second dose of the Moderna
vaccine. A 73-year-old female with a past medical history
of hypertension, hyperlipidemia, and renal angiomyolipoma
status post resection in 2019 presented with worsening
right upper arm swelling for the past two weeks. She
noticed the swelling two to four days after receiving her
second dose of the Moderna vaccine within 1 cm from the
prior injection site. Physical examination was remarkable
for a 6 cm, circular, mobile, soft mass present in the
right upper arm. (Figure 3C). Li et al. [23] reported the
development of classic cutaneous Kaposi’s sarcoma in a
79-year-old male following the first dose of the ChAdOx1
nCov-19 vaccine, without prior SARS-CoV-2 infection or
history of HIV infection. The patient developed multiple
reddish-blue papules on his legs and feet, confirmed
as KS through histopathology (Figure 3D). Treatment
included radiotherapy and sequential chemotherapy with
doxorubicin. The potential reactivation of latent HHV-8 by
the vaccine is suggested through mechanisms involving the
SARS-CoV-2 spike protein and adenovirus vector, which
may induce immune responses and inflammatory pathways.
Carcinoma
Abue et al. [32] describe a case series of 96 patients
with the diagnosis of pancreatic ductal adenocarcinoma
(Figure 3E). Repeated COVID-19 booster vaccinations
were associated with worse overall survival in the patients
with pancreatic cancer. Analysis revealed that high levels
of IgG4, induced by vaccination, correlate with a poor
prognosis. Sano [36] described an 85-year-old woman
who presented with an asymptomatic skin lesion in the
right chest within one month immediately after the 6th
dose of (Pfizer-BioNTech) vaccination. The patient had
been diagnosed with right breast cancer two years prior
and underwent partial mastectomy, hormone therapies, and
was deemed to be in remission. The lesion was confirmed
as a skin metastasis deemed to have developed through
potential local recurrence at surgical margins (Figure 3F).
Melanoma
Wagle et al. [56] described a 49-year-old Indian
male who developed rapidly progressive vision loss
Table 2: Clinicopathologic spectrum of lymphomas in post-vaccination reports
Lineage Subtypes Key features
T-cell lymphomas
CTCL, LyP, ALCL, AITL, SPTCL,
TFH-type, PCGDTCL, T-ALL,
T- cellNOS
Dominated by cutaneous and TFH-derived entities; several at
injection sites; many indolentor self-resolving (CD30+).
B-cell lymphomas DLBCL, Follicular, MZL, CLL Primarily DLBCL; often nodal or axillary post-mRNAvaccine;
typically de novo; most treated with R-CHOP.
NK/NK-T-cell
lymphomas ENKL (nasal-type), NK/T overlap EBV+ nasal lesions; one partial response to SMILE +
radiation; suggest EBV reactivation.
Mixed/
Unspecified LPDs
Large “unspecified/other” cohort
from systematic review (Cui 2024)
and PCLDs
Aggregate data without cell-lineage resolution; largely
literature or registry series.
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Figure 3: Representative examples of cancers reported in temporal association with COVID-19 vaccination. Figures
were reproduced with permissions (Supplementary Table 1). Lymphoma: (A) Axillary adenopathy and i) 18-FDG-PET/CT at baseline
in the right axillary adenopathy mass and ii) in multiple axillary adenopathies and subsequent NHL diagnosis following vaccination.
Image reproduced from Cavanna et al., Medicina, 2023. © MDPI. (B) Temporal mass after her first BNT162b2 dose, with persistent
lymphadenopathy on imaging. Axial computed tomography image shows (i, ii) submandibular and jugular regions. Image reproduced from
Sekizawa et al., Front Med, 2022. © Frontiers. Sarcoma (C) High-grade sarcoma arising near injection site. A 6-cm right upper-arm mass
after second Moderna dose, near the prior injection site; pathology confirmed high-grade sarcoma. Image adapted with permission from
Bae et al., Cureus, 2023 © Springer Nature. (D) Classic cutaneous Kaposi’s sarcoma adapted from Li et al. Front Med, 2022 © Frontiers. A
79-year-old man developed violaceous papules on the legs after the first ChAdOx1 vaccine dose; biopsy confirmed KS. Treatment included
radiotherapy and doxorubicin. Clinical images of Kaposi sarcoma (i) with dark brown macules over the left foot, (ii) the right foot and
larger reddish erythematous papules on his left calf (iii, iv). Carcinoma (E) In a 96-patient cohort, repeated booster vaccination correlated
with poorer overall survival and elevated IgG4 level of pancreatic ductal adenocarcinoma. Kaplan–Meier analysis of 96 PC patients with
known vaccination history and measured IgG4 levels, total IgG4 levels by number of vaccinations, and Kaplan–Meier analysis in PC
patients by IgG4 levels. Image adapted with permission from Abue et al. Cancers 2025 © MDPI. (F) A case of metastatic breast carcinoma
to the skin expressing SARS-CoV-2 spike protein. Histopathology of skin metasstatis along with IHC for nucleocapsid and Spike protein.
Images adapted from Sano, S., J. Derm Sci, 2025. © Elsevier. Melanoma (G) Gross examination of specimen shows extensive intraocular
hemorrhage involving both anterior and posterior chambers, accompanied by complete retinal detachment. H&E stained section shows
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severely degenerated, necrotic melanocytic lesion located with widespread necrosis within the melanocytic tumor. SOX10 IHC confirms
melanocytic cells containing cytoplasmic melanin, interspersed among numerous SOX10-negative melanophages. Image adapted with
permission from Wagle et al. Indian J Ophthalmo 2022 © Wolters Kluwer. (H) Maximum-intensity projection PET image shows markedly
increased radiotracer uptake within the left axillary and supraclavicular lymph nodes. Representative axial CT and corresponding fused
PET/CT images highlight the dominant nodal conglomerate. The patient had received a COVID-19 vaccination in the left upper arm within
two months prior to imaging. Image adapted from Gullotti et al. Radiol Case Rep. 2022 © Elsevier. Glioblastoma (I) Two patients (ages 40
and 31) presented with new neurologic deficits and frontal-lobe masses shortly after mRNA vaccination. Image adapted from O’Sullivan
et al. J of Neurology. 2021 © Elsevier. Other (J) Gastrointestinal polyposis identified following COVID-19 vaccination. Image adapted
with permission from Kim et al. Clin Endosc 2024 © Korean Society of Gastrointestinal Endoscopy (K) Axillary lymphangioma in an
80-year-old woman three months after her second Pfizer-BioNTech dose; imaging showed a cystic lymphangioma. Image adapted with
permission from Sasa et al. Surg Case Rep 2022 © Springer Nature.
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one day after receiving a second dose of the BNT162b2
mRNA COVID-19 vaccine (Pfizer–BioNTech, USA).
Ophthalmologic exam revealed secondary angle-closure
glaucoma, bullous retinal detachment, and extensive
intraocular hemorrhage. Ocular imaging and confirmed
magnetic resonance imaging (MRI) revealed an ill-defined
heterogeneous subretinal lesion, with histopathology
confirming necrotic uveal melanoma (Figure 3G).
Gullotti et al. [55] also described an otherwise healthy
53-year-old man who presented with ipsilateral axillary
lymphadenopathy and associated discomfort shortly after
receiving a COVID-19 vaccine. Fine-needle aspiration
performed within two months of vaccination revealed
metastatic melanoma, and subsequent 18F-FDG PET/
CT imaging demonstrated intensely hypermetabolic
axillary and supraclavicular lymphadenopathy without
identification of a primary tumor (Figure 3H).
Glioblastoma
Tosun et al. [29] reported a 40-year-old man
presenting with left hemiparesis. He had received
COVID-19 vaccination 3 weeks before. Brain MRI
showed a central cystic necrotic lesion with indistinct
borders in the right frontal lobe as mild peripheral contrast
enhancement surrounded by smaller nodular lesions.
O Sullivan et al. [84] also describe a 31-year-old female
who first noted a slight weakness of her right leg about 7
days after receiving the first dose of a COVID-19 mRNA
vaccine (Comirnaty®BioNTech Manufacturing GmbH,
Germany). She initially reported slight drowsiness and
headache without fever following vaccination, which
resolved within 24 h. Following the administration of the
second intramuscular dose of the vaccination, 21 days after
the first, the preexisting weakness of the right leg rapidly
worsened and was accompanied by severe headache and
night chills. Neurological examination on day 28 showed
a mild central paresis of the right leg and numbness of the
plantar surface of the foot (Figure 3I).
Other
Kim et al. [31] describe two cases of gastrointestinal
polyposis (Cronkhite–Canada syndrome) shortly
after administration of an mRNA booster vaccine for
COVID19. Both showed numerous erythematous gastric
and colonic polyps with villous atrophy throughout the
small intestine (Figure 3J). The authors note that the
timing, autoimmune features, and steroid responsiveness
raise the possibility that mRNA vaccination may trigger
Cronkhite–Canada syndrome in genetically susceptible
individuals, warranting clinical vigilance. Sasa et al. [33]
Table 3: Summary of case series describing malignant lymphoma following mRNA COVID-19
vaccination
Case
N
Gender/
Age
(Year)
Time from Vaccination
to Onset of
Lymphoproliferative
Disorder
Histopathological
Examination
Type of COVID-19
Vaccine
Site and Diameter of
Lymphadenopathy
Treatment of
Lymphoma
1 M/67 1 day after 1 dose DLBCL BNT162b2 Left axilla 6.0 cm Chemotherapy
plus rituximab
2 F/80 2 days after 1 dose DLBCL BNT162b2 Left axilla 4.1 cm Chemotherapy
plus rituximab
3 F/58 7 days after 2 dose DLBCL BNT162b2 Left cervical area 4 cm Radical surgery
plus radiotherapy
4 M/53 3 days after 1 dose
Extranodal
NK/T-cell
lymphoma
BNT162b2 Erosive lesions upper
lip up to 5 mm
Chemotherapy
plus radiotherapy
5 M/51 7 days after 1 dose EBV-positive
DLBCL ChAdox1 nCOV-19 Mediastinal mass 5 cm Rituximab
6 F/28 “A few days after
1 dose” SPTCL Ad26 viral-vector-
based
Injection site,
upper arm
Cyclosporine
plus prednisone
7 F/80 1 day after 1 dose EMZL BNT162b2 Right temporal mass No treatment
8 M/76 10 days after the booster
dose PC-ALCL mRNA-1273*Right arm upper-
external surface 6 cm No treatment
Table reproduced from Cavanna et al., Medicina, 2023. © MDPI. Abbreviations: ALCL: anaplastic large-cell lymphoma; DLBCL: diffuse
large B-cell lymphoma; EBV: Epstein-Barr virus; EMZL: extranodal marginal zone lymphoma; PC-ALCL: primary cutaneous anaplastic
large-cell lymphoma; SPTCL: subcutaneous panniculitis-like T-cell lymphoma. *The two previous vaccination doses were BNT162b2.)
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report on axillary lymphangioma following COVID-19
in a Japanese woman in her 80s who received a second
injection of the Pfizer-BioNTech COVID-19 vaccine
in her left deltoid muscle in 2021 (Figure 3K). She
had a history of right breast cancer (T1N0M0) and had
undergone breast-conserving surgery and sentinel node
biopsy in her 70’s. Postoperative follow-up examinations
were continued, and no sign of recurrence, including
in the left axial region, was observed until 2021. There
was no evidence of trauma to the left axial region. Her
early adverse reaction following vaccination was mild
pain at the inoculation site on the day of vaccination and
the following day. However, 3 months after the second
vaccination, she noticed left axillary swelling.
De novo disease versus recurrence or progression
Most publications, including all the examples
above, described de novo malignancies or apparent
“unmasking” or activation of previously subclinical
disease. A smaller subset focused predominantly on
recurrence, progression, or metastatic reactivation in
patients with a documented cancer history. An additional
13 publications reported mixed cohorts, including both
new diagnoses and recurrences or provided explicit
quantification of both categories. Only one publication
did not clearly distinguish between new-onset and
recurrent disease.
Taken together, these patterns indicate that the
observed signal in the literature is not restricted to
recurrence or flare of known malignancies. Rather,
a substantial proportion of reports involve first-time
cancer diagnoses temporally associated with COVID-19
vaccination or SARS-CoV-2 infection, highlighting
the need to evaluate potential mechanisms that could
contribute to disease initiation, unmasking, or acceleration.
Timing of onset
Across the included studies, the timing of
cancer onset following COVID-19 vaccination varied
substantially, indicating that latency was not confined
to a single early window. Approximately half of the
case reports described diagnoses occurring within 2–4
weeks of vaccination, with some reported as early as
7–14 days. However, many reports also documented
longer intervals, including diagnoses at 2–3 months,
4–6 months, and beyond eight months after vaccination.
Importantly, reports with short intervals are inherently
more likely to be recognized and published as temporally
notable.
In addition, in many reports describing diagnoses
within the first month, the event occurred after a second
dose or booster, complicating attribution to any specific
exposure and precluding definition of a uniform latency
period. Multicenter analyses frequently characterized
latency as variable, spanning weeks to months, and several
reviews or population-level studies reported mean onset
intervals of approximately 8–9 weeks.
Tumor growth rates vary significantly among tumor
types from the fastest growing lymphomas and leukemias
to slower growing solid tumors [87–92]. Accordingly,
while a subset of published cases report diagnoses within
weeks of vaccination, the broader literature reflects a
continuum of reported latencies over several months,
often in the context of cumulative exposure. These
observations are therefore best interpreted as descriptive
and hypothesis-generating, underscoring the need for
standardized latency definitions and systematic evaluation
in appropriately controlled studies.
Population-level and registry-based studies
Three large-scale population-level analyses provided
broader epidemiologic context to complement the case-
based literature. Two retrospective population-level
investigations, one in Italy [20] and one in South Korea
[8], quantified cancer incidence and mortality trends
among vaccinated populations. Kim et al. [8] analyzed
approximately 8.4 million individuals between 2021
and 2023 to assess 1-year cumulative cancer incidence
following COVID-19 vaccination using the South Korean
National Health Insurance Service database. The authors
reported statistically significant associations between
vaccination and six specific cancers, including thyroid
(HR 1.35), gastric (HR 1.34), colorectal (HR 1.28), lung
(HR 1.53), breast (HR 1.20), and prostate cancer (HR
1.69) using propensity score matching and multivariable
Cox proportional hazards models. Associations varied by
vaccine platform, with mRNA vaccines linked to thyroid,
colorectal, lung, and breast cancers, and cDNA/adenoviral
vaccines associated with thyroid, gastric, colorectal,
lung, and prostate cancers; heterologous vaccination
was associated with thyroid and breast cancer. Stratified
analyses suggested effect modification by sex and age,
and booster-dose analyses identified increased risks for
gastric and pancreatic cancer. The authors emphasized
that despite adjustment for measured confounders,
residual confounding, detection bias, and limited follow-
up preclude causal inference, and that the findings should
be interpreted as epidemiologic associations warranting
further study rather than evidence of vaccine-induced
cancer risk.
Acuti Martellucci et al. [20] evaluated associations
between SARS-CoV-2 vaccination, all-cause mortality,
and hospitalization for cancer using multivariable Cox
proportional hazards models in a population-wide
retrospective cohort study of 296,015 residents of the
Pescara province in Italy followed for up to 30 months
(June 2021–December 2023). Hospitalization for cancer
of any site was found to be modestly higher among
vaccinated individuals compared to unvaccinated (≥1
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dose: HR 1.23, 95% CI 1.11–1.37; ≥3 doses: HR 1.09,
95% CI 1.02–1.16), with site-specific increases observed
primarily for colorectal (HR 1.35), breast (HR 1.54), and
bladder cancer (HR 1.62) after ≥1 dose, and for breast and
bladder cancer after ≥3 doses. These associations varied
by sex, prior SARS-CoV-2 infection, vaccine type, and
lag time between vaccination and outcome, and were
attenuated or reversed when a longer minimum latency of
365 days was applied. The analyses adjusted for age, sex,
prior SARS-CoV-2 infection, and multiple comorbidities
(including cardiovascular disease, diabetes, COPD, kidney
disease, and prior cancer), but lacked information on key
behavioral and healthcare-utilization confounders such
as smoking, cancer screening, and healthcare-seeking
behavior. The authors explicitly note that residual
confounding, healthy-vaccine bias, detection bias, and
reliance on hospitalization data as a proxy for cancer
incidence limit causal interpretation, and they characterize
the findings as preliminary and hypothesis-generating
rather than evidence of vaccine-induced cancer risk. Both
studies provide early, population-level associations rather
than causal estimates and underscore the importance
of long-term follow-up and molecular correlation to
distinguish true biological effects from health-system or
behavioral confounders.
In addition to these population-level studies, a
recent US Armed Forces Health Surveillance Division
(AFHSD) report was also identified that presented
population-level analyses of non-Hodgkin lymphoma
(NHL) incidence among active-duty U.S. service members
from 2017 through 2023 [85]. The U.S. Department of
Defense (DoD) mandated COVID-19 vaccination for all
active-duty service members (~1.3 million) beginning in
late 2020, with near-universal compliance achieved by
mid-2020; this cohort offers a rare longitudinal view of
cancer incidence across this transition. Using data from
the Defense Medical Surveillance System (DMSS),
the authors calculated annual incidence rates (IRs) per
100,000 person-years and categorized cases by lymphoma
subtype and the 2017–2020 interval largely represents
a pre-vaccine baseline, whereas 2021–2023 reflects a
fully vaccinated, post-pandemic cancer incidence [86]
(Figure 4).
Notably, a rise in mature T/NK-cell lymphomas
began across the 2020–2021 transition which spans the
period of COVID-19 infection and the beginning of
widespread vaccination in the military. Beginning in
2021, a ~50% increase in specified/unspecified and non-
follicular NHL subtypes, accompanied by a persistently
elevated incidence of mature T/NK-cell lymphomas
relative to pre-pandemic years was observed. Notably,
the authors did not attribute the observed changes in NHL
incidence to vaccination or infection, and the analysis was
not designed to establish causality at the individual level.
Changes in diagnostic practices, healthcare access and
utilization, and pandemic-related disruptions to routine
medical care cannot be excluded from this time-trend
analysis as with others conducted during the pandemic
period. However, these findings provide descriptive
temporal trends within a unique and highly structured
population, providing an epidemiologic framework for
future controlled analyses.
Taken together, these population-level analyses
combined with the case-based literature indicate that a
cancer signal warrants further prospective evaluation to
determine whether COVID-19 vaccination confers any
measurable cancer risk or merely reflects surveillance and
reporting biases.
Figure 4: Annual incidence rates of non-Hodgkin lymphoma (NHL) subtypes among active-component U.S. service
members, 2017–2023. Figure adapted from Russell et al. [85] using Defense Medical Surveillance System data demonstrating rise in
specified/unspecified NHL and mature T/NK-cell subtypes. Vertical lines denote key timepoints: the onset of the COVID-19 pandemic
(early 2020) and the beginning of the Department of Defense vaccine mandate (late 2020–early 2021).
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MATERIALS AND METHODS
A comprehensive search of the world’s literature
was conducted using PubMed, Scopus, Web of Science,
Google Scholar, and React19 between January 2020
and April 2025. Eligible publications included case
reports, case series, cohort or population-level analyses,
systematic reviews, and mechanistic or preclinical studies
that described either (i) new-onset, recurrent, or rapidly
progressive malignancy temporally associated with
COVID-19 vaccination or SARS-CoV-2 infection, or (ii)
experimental evidence implicating vaccine or infection-
induced immune perturbations in oncogenic, proliferative,
or metastatic processes.
Initial searches in PubMed using conventional
keyword combinations such as “COVID-19 vaccine
and cancer,” “vaccination and cancer,” “COVID-19
vaccine and tumor,” or cancer-specific terms paired with
“COVID-19 vaccine” yielded little to no indexed results.
Even when known case reports were used as anchors for
“similar articles,” PubMed returned no related entries. This
highlighted a structural limitation in standard indexing
pathways and necessitated a broader, more strategic search
approach.
A general web-based search (e.g., Google) returned
an autogenerated AI summary when queried for the
terms “COVID vaccine and cancer” indicating that
major health agencies, including the Centers for Disease
Control and Prevention (CDC) and the National Cancer
Institute (NCI), recommend COVID-19 vaccination for
individuals with cancer and assert that the vaccines are
considered safe for this population and are not believed
to cause cancer or precipitate recurrence. Therefore,
an expanded search strategy was implemented using
combinations of general and tumor-specific terms,
including: “COVID-19,” “SARS-CoV-2,” “spike,”
“vaccination,” “vaccine,” “tumor,” “cancer,” “neoplasia,”
“malignancy,” “recurrence,” “progression,” “lymphoma,”
“leukemia,” “melanoma,” “glioma,” “adenocarcinoma,”
“sarcoma,” “Kaposi,” “Merkel cell,” “cardiac”, and related
descriptors. Databases were searched using Boolean
operators, varied term order, and MeSH/non-MeSH
variants to overcome incomplete tagging or atypical
indexing of case reports.
Studies were included irrespective of patient
age, sex, geographic region, cancer histology, or
vaccine platform (mRNA, viral-vector, or inactivated).
Exclusion criteria consisted of commentaries, opinion
correspondence, purely theoretical articles lacking clinical
or experimental data, and duplicate case entries across
publications. Studies labeled as “COVID-associated”
or “COVID-related”, particularly for cardiac tumors
ultimately described patients who tested negative for
SARS-CoV-2 [93]. For methodological consistency, we
excluded such reports from the infection-focused section
of the analysis, as the absence of virologic confirmation
precludes attributing the observed malignancy to active
or recent infection. Reference lists of systematic reviews
and larger case compilations were manually screened to
identify secondary citations not captured in the primary
search. All included articles were independently cross-
referenced in PubMed when possible, to confirm indexing
status and ensure completeness.
Mechanistic hypotheses linking COVID-19
vaccination or infection to oncogenic events
The case studies and emerging population-level
data described above may represent an early signal of a
possible association between vaccination or infection
and cancer that warrants further investigation. This raises
the question: if there is an association, what might be the
mechanistic basis for it?
Viruses can cause cancer [94–97]. The relationship
between viral infection and cancer has been well-
documented for Human Papilloma Virus (HPV) that causes
cervical cancer, head and neck cancer, as well as anal
cancer that is increased among HIV-infected individuals.
Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV)
cause liver cancer. Epstein Barr Virus (EBV) causes
nasopharyngeal cancer, Burkitt’s Lymphoma, and other
cancers. The human herpes virus KSHV/HHV-8 causes
Kaposi’s sarcoma, the Human T-cell Leukemia Virus
(HTLV-1) causes adult T-cell leukemia or lymphoma,
and the Merkle Cell Virus (MCV) causes Merkle cell
skin cancer. Several viruses are suspected of causing
cancer including SV40 (mesothelioma, primary brain and
bone cancers, among others) and HCMV (glioblastoma,
medulloblastoma, breast, colon and prostate cancer). HIV
is strongly associated with Kaposi’s sarcoma, cervical
cancer, lymphoma, anal cancer, and other malignancies,
largely though immunosuppression and co-infection
with oncogenic viruses. It has been known for decades
that viral proteins target host tumor suppressors such as
p53 and Rb, suppress the immune system, and activate
oncogenic signals.
In addition, the COVID mRNA vaccines work by
instructing the target cells to produce the SARS-CoV-2
spike protein. This occurs by introducing a synthetic,
modified mRNA (mod-mRNA) which incorporates non-
natural pseudouridine into its coding region to prolongs
the stability of the mRNA beyond that of natural mRNA.
Introduction of the mod-RNA is accomplished using
lipid-based transfection in the form of lipid nanoparticles
(LNPs). The result is highly efficient transfection of
the mod-mRNA into target cells with biochemical and
pharmacological behavior different from naturally
occurring mRNA. Consequently, the mod-RNA is
transcribed into the foreign spike protein (as well as
other frameshifted protein products), which elicits a
robust immune response [98–102]. Given the stability of
pseudouridine modified mRNA, along with the residual
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DNA in the mRNA vaccine formulations [103–108], the
mRNA vaccines are delivering exogenous genetic material
(DNA and RNA (in the form of engineered nucleic acids))
into a patient’s cells. The COVID19 mRNA vaccines
produce Spike protein that is encoded by a stable mRNA
and has been found to be long-lived in the human body
[109, 110]. These nucleic acid elements have been reported
to contribute to Post-Covid Vaccine Syndrome (PCVS/
PVS) [110, 111]. Thus, these vaccines fit the definition of
gene therapy [112, 113]. Despite this, there are efforts by
the EU to modify the definition of gene therapy to exempt
mRNA vaccines from this category [114].
While there are no studies demonstrating a direct
causal mechanism by which the mRNA vaccines induce
cancer, cumulative molecular effects from persistent
spike protein [115, 116], the immune activation and
inflammation from repeated vaccination [117–119], or
the potential for genomic integration events [120] might
contribute to events that could in theory manifest in
cancers following vaccination or infection. Given the rapid
onset of aggressive and rare tumors from the literature,
cancers arising weeks to months after vaccination would
be perhaps more consistent with mechanisms involving
tumor promotion rather tumor initiation per se. However,
mechanisms involving initiation are also considered. Here
we present least three biologically plausible mechanisms
that might explain an association between COVID-19
vaccination and cancer; two of them overlapping with
covid infection, immune dysfunction and spike protein
biology, and reactions due to DNA impurities restricted
to vaccination.
Immune dysregulation
The rapid appearance of cancer, the anatomical
proximity of the tumors to vaccine sites, and the
histologic signatures of inflammation the support immune
mechanisms that promote the progression of latent clones
rather than de novo carcinogenesis. We hypothesize
two interrelated processes: localized inflammation and
modulation of the tumor microenvironment with transient
functional immunosuppression that relaxes immune
surveillance. Might account for hyperprogression of latent
or occult cancer cells (Figure 5).
Numerous studies (both human and animal) have
shown that COVID mRNA vaccines and infection trigger
production of proinflammatory cytokines including
interleukin-6 (IL-6), TNF-α, and IL-1β within 1-3 days
after vaccination [121–124]. In the case of vaccination,
the reaction is due to the innate immune response to
the mRNA and lipid nanoparticle (LNP) components,
which activate pattern-recognition receptors TLR7/8 and
NLRP3 [125–128]. Therefore, local production of these
cytokines will occur wherever the mRNA and LNPs are
biodistributed, which include the injection site, draining
lymph nodes, as well as other distant sites [129].
IL6 activates STAT3 which drives cancer cell
proliferation, survival, angiogenesis, and immune
suppression in the tumor microenvironment [130]. TNF-α
activates NF-κB and AP-1 that also drives cell survival,
proliferation, angiogenesis, and immune evasion. TNF-α
can create a self-sustaining inflammatory loop by
recruiting myeloid-derived suppressor cells (MDSCs),
tumor-associated macrophages (TAMs), and regulatory
T cells (Tregs) that suppress cytotoxic T-cell activity and
produce additional TNF-α, IL-6, and IL-10. TNF-α induces
further expression of IL-6, CXCL1/2/8, and COX-2,
which fosters further proliferation, angiogenesis, and
immune evasion [130]. IL-1β upregulates VEGF,
MMPs, and integrins, promoting neovascularization and
extracellular matrix remodeling. IL-1β drives polarization
of macrophages toward the M2-like (tumor-promoting)
phenotype, expands Th17 cells and an neutrophils,
thereby contributing to chronic inflammation and
immunosuppressive tumor microenvironment [130].
Together IL-6, TNF-α, and IL-1β constitute
a synergistic pro-inflammatory circuit capable of
stimulating proliferation and angiogenesis. Together,
this circuit is known to rapidly promote the development
of cancer if transformed or pre-malignant cells already
exist. Indeed, there are several reports demonstrating
acceleration of pre-existing disease or reawakening from
dormancy following inflammation [74, 131–134]. A
synchronized surge of these three cytokines could provide
a coordinated inflammatory storm that converts indolent or
dormant transformed cells into rapidly proliferating, and
angiogenic, malignancies (Figure 5). Therefore, research
is needed to better understand whether the hypothesis that
an inflammatory cytokine cascade is unleashed by mRNA
vaccination could contribute to or even lead to post-
vaccination cancer events.
In addition to influencing the behavior of pre-
existing neoplastic cells, this transient cytokine-driven
inflammatory surge could also modulate antiviral or
antitumor immune surveillance. IL-6, TNF-α, and IL-
1β recruit immunosuppressive myeloid populations
and expand regulatory T cells, while dampening
cytotoxic T-cell activity, functions that are essential for
maintaining control of latent oncogenic viruses such as
EBV, HHV-8, and MCV [135–137]. Accordingly, the
observation that several post-vaccination cases involved
virus-associated cancers (EBV, HHV-8, MCV) raises
the possibility that short-lived alterations in immune
surveillance may permit episodic viral reactivation or
progression of virus-driven tumors. Mechanistically,
transient impairment of cytotoxic T-cell surveillance
prevents reactivation and replication of latent oncogenic
viruses, leading to expression of viral oncogenes and
proliferation of infected host cells. Similar processes are
well documented in states of clinical immunosuppression,
or hyperprogression in patients receiving immune
checkpoint inhibitors [138–140].
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Beyond innate cytokine induction, several studies
have described transient adaptive immune changes
following mRNA vaccination or acute infection [110, 141–
145]. Although these findings are generally interpreted as
reflecting physiological immunoregulation rather than
overt immune dysfunction, they may correspond to short
periods of reduced immune responsiveness [146–149]. If
such windows occur, whether systemically or localized
to specific tissue niches, they could, in theory, allow
transient expansion of latent viral or neoplastic clones. At
present, whether transient functional immunosuppression
occurs after mRNA vaccination, and whether it is
localized or systemic, remains unclear. Direct studies are
needed to determine whether innate cytokine induction
and adaptive immune modulation could contribute to or
influence post-vaccination cancer events in susceptible
individuals.
Evidence supporting these mechanisms have been
suggested after SARS-CoV-2 infection itself. For example,
Gregory et al. [74] reported aggressive glioblastoma
at a median of 35 days following COVID-19 infection,
an in one patient documented COVID-19 vaccine
prior to diagnosis. The rapid onset of glioblastoma was
attributed to immune disruption which may be in part
due to the neurotropism of SARS-CoV-2 [150, 151] or
the biodistribution of the LNPs [125, 127, 129] and the
immune response to this. Indeed, Spike protein as has
been localized to brain tissue as well as glioblastoma cells
and macrophages surrounding the tumor cells [87]. Hu et
al. [72] similarly demonstrated that direct viral exposure,
and the presence of Spike protein, with cytokine-
mediated injury in glioma organoids enhanced tumor cell
proliferation and invasiveness, supporting a model of
infection-driven tumor stimulation. For breast cancer, Chia
Figure 5: Proposed mechanism of tumor hyperprogression following COVID-19 vaccination. (A) Conceptual model
illustrating how inoculation with mRNA vaccine leads to immune reactions depending on its biodistribution. Strong immunostimulation can
override immunosurveillance of latent cancer cells and trigger tumor hyperprogression. (B) Schematic representation of the major immune
cell types influencing tumor growth and immune regulation following mRNA vaccine exposure. LNP–encapsulated modified mRNA
(modRNA/mRNA) interacts with innate immune sensors altering cytokine signaling (TNF-α, IL-1β, IL-6) and immune-cell polarization
leading to immunosuppression and reduced cytotoxic CD8⁺ T-cell activity. Expansion of myeloid suppressor populations, along with pro-
tumor cytokine feedback loops, fosters accelerated tumor cell proliferation and immune evasion. The imbalance between anti-tumor (M1,
CD8⁺, NK) and pro-tumor (M2, Treg, MDSC) networks favors tumor hyperprogression.
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et al. [74] showed that respiratory viral infections including
SARS-CoV-2, could rapidly awaken dormant metastatic
breast cancer cells in the lung through interferon-driven
activation of the STAT1–NF-κB axis, which remodels the
local niche into a pro-metastatic state. Both the virus and
the mRNA vaccines engage innate immune sensors and
elicit complex cytokine and interferon responses that can
remodel the tumor–immune interface.
Together, these observations suggest that acute
inflammatory activation, short-lived immune refractoriness,
and transient lapses in cytotoxic surveillance form a
biologically plausible framework through which vaccination
could influence and promote the behavior of pre-existing
or latent neoplastic cells. The immunological mechanism
suggests that infection and vaccination may operate along
a common biological continuum, differing primarily in
intensity, biodistribution, and persistence of the immune
and molecular perturbations they induce. Although direct
causal evidence is not yet available, the convergence of
innate cytokine surges, transient modulation of T- and B-cell
dynamics, and signals associated with immune regulation
highlights the importance of further study. Clarifying the
magnitude, duration, and tissue specificity of these post-
vaccination immune states will be essential for determining
whether, and in which individuals, they have clinical
relevance for cancer progression or recurrence.
Spike protein biology
The transformation of a normal cell into a cancer
cell involves disruption of multiple safeguards controlling
cell growth, survival, and DNA repair. Laboratory
studies have reported that the spike protein, whether it is
produced by infection or by vaccination, has biological
activities [110, 145, 152–158] with oncogenic potential
[159–161]. For example, in addition to interacting with
ACE2 receptors, spike protein fragments have been shown
to interact with NRP-1, integrins, and TLRs leading to
VEGF/NRP-1 signaling [155, 162, 163]. Spike protein
has also been reported to induce DNA damage [160, 164,
165] and modify p53 pathway under oxidative stress
[164, 166]. Therefore, in theory, such interactions of spike
protein with these pathways could contribute to cellular
transformation, both from the vaccine but also from
infection, especially if the spike protein remains present
long after vaccination or from multiple COVID infections.
The spike protein produced by the vaccines has been
reported to persist for weeks, months and even years [109,
110, 116, 167–170] after vaccination, providing potential
long-term activity in cells. Moreover, the stabilized Spike
protein produced by the covid vaccines (Spike-2P), differs
from the natural protein in SARS-CoV-2 as it contains
two proline substitutions (K986P and V987P) that enable
stabilization [171]. Because of this, it will be important to
assess whether cancer incidence correlates with the variant
spike protein expression (or persistence) in the body but
also whether it is this version that is present in tumors as
has been reported in glioma and astrocytoma [73] as well
as metastatic breast cancer [36]. In a recent case report of
metastatic breast cancer to the skin, the lesion appeared
within one month after the 6th dose of vaccination (Pfizer-
BioNTech) and the metastatic cancer cells stained for
spike protein, but not for nucleocapsid protein of SARS-
Cov-2 virus ([36], Figure 3F) suggesting it was vaccine-
derived spike protein. Hence, chronic exposure to an
agent with biological activity that disrupts cell cycle
and DNA damage response pathways could represent a
novel etiological factor to cancer. Of note and relevance
to glioblastoma or other central nervous system (CNS)
pathologies after either COVID infection or vaccination
could be the CNS-tropism of spike protein [150, 151, 172].
DNA contaminants
Residual DNA in biologics is a well-established and
acknowledged byproduct of vaccine manufacturing, with
limits set forth by the FDA and World Health Organization
(WHO), but only for naked DNA, not LNP encapsulated
DNA [173]. The DNA impurities in mRNA vaccines arise
due to the byproduct of in-vitro transcription [174], and
can include double strand DNA (dsDNA), abortive RNAs
and RNA:DNA hybrids [103, 174]. They are encapsulated
by nanolipids allowing for more stable and efficient access
into cells increasing the risk of integration [128, 175, 176].
Furthermore, the residual DNA in the mRNA vaccine
formulations [103–108] from the manufacturing process
exceed the established limits even for naked DNA. Studies
have directly compared the transfection efficiency of
naked DNA to LNP encapsulated DNA and shown that
integration of lipid-based transfection is significantly
higher than naked DNA [175]. Moreover, skeletal and
cardiac muscles are well known to take up (and even
express naked plasmid DNA) in vivo [177–179]. Notably,
a study of cardiac tumors in the post-COVID period
revealed both a 1.5% increase in tumor incidence and the
expression of spike protein with the tumors, particularly in
those associated with vaccination [86].
The quantity of residual DNA reported in several
independent assessments exceeds recognized limits for
naked DNA, and the size distribution of DNA fragments,
when combined with enhanced transfection efficiency
due to LNPs raises the possibility of genomic insertion. In
addition, because SV40 regulatory elements are present in
the BNT2b vaccine impurities [180], when inserted into
genome this DNA can alter the expression of adjacent
sequences and/or normal gene regulation and increases
tumorigenic potential [120, 181]. Foreign DNA, especially
when delivered in the highly inflammatory LNPs [182]
can activate innate immune sensing pathways, including
the cytosolic cGAS–STING and endosomal Toll-like
receptor 9 (TLR9), leading to type I interferon and
inflammatory cytokine responses [183, 184].
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The limits on DNA impurities were established
for naked DNA [185], not LNP-encapsulated DNA
which causes enhanced cellular uptake and intracellular
persistence of DNA fragments. This will increase the
opportunity for insertional mutagenesis leading to
possible genomic rearrangements, as well as integration
and expression of persistent spike protein, disruption of
normal gene regulation, as well as possible activation
of proto-oncogenic pathways, or inactivation of tumor
suppressors. In fact, in vitro studies demonstrate genomic
integration rates of ~1–10% of initially transfected cells
with lipid-based delivery systems [120]. No studies have
been conducted demonstrating that the level of DNA
impurities present in the vaccines are insufficient to
transfect cells, nor have studies ruled out the possibility
of integration.
Gaps in knowledge
Despite the unprecedented global scale of
COVID-19 vaccination, profound gaps remain in
our understanding of how mRNA vaccine platforms
interact with fundamental pathways of host defense,
tissue homeostasis, and tumor biology. These gaps span
molecular, cellular, organismal, and population level
biology. There is an absence of data linking mRNA
vaccines, and especially COVID-19 mRNA vaccines to
downstream biological consequences.
At the molecular level, major knowledge gaps
concerning how chemical and structural modifications
of the SARS-CoV-2 spike protein, nucleoside and amino
acid substitutions (e.g., N1-methylpseudouridine), and
LNP formulations influence host-cell signaling, genomic
stability, and immune regulation. Vaccine engineering
has focused on maximizing antiviral immunogenicity, yet
far less is known about potential collateral interactions
between spike protein expression, tumor-suppressive,
DNA damage or stress response pathways that could be
inadvertently modulated during intense immune activation
or altered cellular signaling that impacts on host defenses
against cancer.
The distinction between vaccination associated
tumor initiation and promotion also remains unresolved.
There is no empirical validation that vaccination only
accelerates pre-existing disease rather than also initiating
new malignancies. Because somatic mutations and
dormant neoplastic cells are ubiquitous in adult tissues,
short-latency tumor emergence over weeks to months
may reflect the promotion of latent clones rather than
de novo carcinogenesis, a phenomenon consistent with
hyperprogression observed in subsets of patients receiving
immune checkpoint inhibitors [138, 139]. Oncogenic
drivers such as MDM2/MDM4 amplification or EGFR
amplification, overexpression, or mutations have been
implicated in hyperprogression [138, 140, 186] and
metastatic aggressiveness [187, 188], suggesting that
vaccine-induced cytokine or checkpoint shifts could
theoretically converge on similar oncogenic pathways.
Also unclear is how mRNA vaccines targeting SARS-
CoV-2 might be sensitizing tumors to immune checkpoint
inhibitors as has been recently suggested [19].
Cellular and immunologic gaps
At the cellular level, there is limited mechanistic
understanding of how mRNA vaccine components, spike
protein persistence, or repeated immune activation shape
innate–adaptive immune crosstalk, particularly in dendritic
cells, macrophages, and stromal compartments. The
molecular triggers and long-term immune consequences
of a hyperinflammatory response observed in both severe
COVID-19 and rare post-vaccination events [189] remain
poorly characterized. Equally unexplored is the role of
the microbiome in modulating vaccine responsiveness,
systemic inflammation, and tumor promotion.
Understanding how antigen persistence, cytokine
polarization, and pattern-recognition receptor activation
influence local tissue remodeling, cellular senescence, and
pro-tumorigenic inflammation represents a critical unmet
need.
Host susceptibility and biodistribution
At the organismal level, the greatest uncertainty
lies in the heterogeneity of host susceptibility. For
example, the heterogeneity of individual differences
in baseline state of activation, responsiveness, and
regulation in response to COVID-19 vaccination has
been reported [190]. Furthermore, heterogeneity of
DNA repair, epigenetic plasticity, and cytokine response
level is also not well understood and likely modulates
vaccine response and risk. Variable LNP biodistribution,
including uptake in liver, spleen, bone marrow, and
lymphoid tissues, may alter both immune potency and
potential off-target effects, yet these parameters have
not been systematically profiled in humans. There is
also a lack of data on how vaccination during or shortly
after SARS-CoV-2 infection, or cumulative exposure
to multiple mRNA doses, affects long-term immune
homeostasis and tumor surveillance. Interactions between
vaccine-induced inflammation and latent oncogenic
viruses (e.g., EBV, HHV-8, MCPyV) remain particularly
underexplored.
Population and epidemiologic gaps
At the population level, large-scale epidemiologic
studies remain limited and often inconclusive. Existing
registries rarely integrate molecular or immunologic
correlates, hindering causal inference. Moreover, current
pharmacovigilance systems were not designed to detect
rare but biologically informative oncologic events,
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creating a blind spot between individual case reporting and
aggregated safety analyses. Robust longitudinal follow-up
of vaccinated cohorts with integrated molecular profiling
will be essential to distinguish true biological signals
from background incidence and to identify susceptible
subgroups.
Alternative preventive and therapeutic strategies
Addressing key knowledge gaps will require
exploration of complementary antiviral strategies that
reduce infection risk while minimizing host perturbation.
For example, MEK inhibitors have been shown to
suppress ACE2 expression and viral entry [191], yet
host-directed antivirals have received little attention.
Likewise, enhancing innate immunity through agents that
boost pattern-recognition receptor signaling or interferon
responses could theoretically mitigate both COVID-19
infection and cancer risk by restoring balanced immune
surveillance. Indeed, there are approaches validated by
FDA of approved immunomodulators [192] and emerging
analogs [193].
Major gaps exist in forensic evidence to evaluate
the spread of COVID infection or COVID vaccine Spike
protein into cancer tissues as well as effects on cellular
growth control pathways in vivo. We currently do not have
tissue-level, mechanistic, or molecular studies that trace
where spike protein localizes in the body after infection or
vaccination, especially in tumors. No systematic research
has mapped spike protein distribution within tumors (solid
or hematologic), either through immunohistochemistry,
mass spectrometry, RNA in situ hybridization, or other
molecular tissue-tracking methods. There have been
essentially no in-vivo studies (animal or human tumor
samples) showing how spike protein exposure affects
proliferation, signaling, apoptosis pathways, tumor–
immune interactions, or oncogene/tumor suppressor
regulation.
In sum, the field faces interlocking knowledge gaps
encompassing incomplete molecular characterization of
vaccine–host interactions, insufficient mechanistic study
of immune dysregulation and tissue remodeling, poorly
defined host susceptibility factors, and limited longitudinal
surveillance. Bridging these gaps will require multi-scale,
interdisciplinary research.
Limitations
The findings of this review should be interpreted
within several important limitations inherent to the
available literature and study design. First, although there
are larger studies published, most reports are single-patient
case descriptions or small case series. Many reports
lack documentation of pre-existing conditions, prior
oncologic history, concurrent infections, or medications
that could confound interpretation. Therefore, while these
observations are valuable for early signal detection, they
are highly susceptible to publication bias and selective
reporting. It is plausible that cases perceived as unusual
or temporally linked to vaccination are preferentially
submitted for publication, while the absence of comparable
control observations limits inference regarding incidence
or relative risk.
Second, the heterogeneity of the studies that span
both mRNA and non-mRNA vaccine platforms, doses,
populations, and diagnostic standardization introduces
important variabilities when it comes to the associations
between mRNA vaccines and other COVID-19
vaccines. The mechanistic hypotheses proposed here
remain speculative in the absence of direct in vivo
validation. No current studies have demonstrated oncogenic
transformation or tumor initiation causally attributable to
the COVID mRNA vaccine or its components. Nor have
animal studies demonstrated vaccine-induced tumor
promotion either. These mechanisms should therefore be
regarded as biologically plausible models that warrant
targeted experimental study.
Finally, this literature review relied on publicly
available literature that lacked standard medical subject
headings (MeSH) indexing for peer-reviewed papers.
The results of this review demonstrate that there indeed
exists a body of literature on this subject matter across
many journals that not well indexed or cross-referenced
using obvious indexing vocabularies that prevent
them from being retrieved by conventional database
queries. This imposes inherent limitations on both data
completeness and verification but also in identifying
knowledge gaps.
Ethical considerations
Different disciplines adopt different standards
for evidence used to determine standard of care that
should be shared widely. In 2025, there is a major divide
about published evidence that doesn’t reach a certain
standard at a population level being viewed by some
as “misinformation,” or “fearmongering.” In the field
of Oncology, there is a standard that has been in place
for decades regarding how adverse events are viewed in
the process of drug development as well as in clinical
practice. A single serious adverse event is reportable
to institutional review boards (IRB’s) and regulatory
agencies such as the FDA. The mRNA vaccines
incorporate mechanisms commonly associated with
gene-therapy technologies, though their regulatory review
followed the vaccine pathway rather than the criteria
normally applied to human gene-therapy products,
which rigorously evaluate. Cancer (including insertional
mutagenesis, clonal expansion, leukemogenesis, and
treatment-related malignancy) is a key safety endpoint
that gene-therapy regulations are explicitly designed to
monitor, but vaccines are not.
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Regarding COVID mRNA vaccines, in the US
and globally, there is no informed consent that captures
all known and potential adverse events. All known and
potentially serious adverse events are required to be
disclosed in vaccine information sheets, informed consent
forms, and it is important for physicians and other health
care providers to be well-educated concerning risks
regardless of how rare they are. An important example
that led to practice change in the US after decades which
lacked DPYD testing. This now mandated test identifies
pathogenic or reduced-function variants in the DPYD
(dihydropyrimidine dehydrogenase) gene that impairs
5-FU/capecitabine metabolism. Changes in practice
occurred recently and has become in line with European
practice to reduce the risk of severe toxicity from exposure
to 5-fluorouracil chemotherapy.
Cancer susceptibility varies among individuals in
the population as governed by genetic and environmental
factors and a growing body of literature adds
socioeconomic factors that interact with the other two
factors in complex ways. It is likely that the susceptibility
to cancer following COVID vaccines varies greatly within
the population with some individuals at greater risk. It is
important to recognize these issues and to study them in
order to develop improved guidance for a risk: benefit
analysis in the setting of informed consent.
The long timeline required to establish or exclude
causality in oncology is often measured in years or decades.
This should not lessen the immediate ethical responsibility
to provide accurate and current information to individuals
considering vaccination or additional boosters. The fact
that definitive causal inference demands mechanistic
studies, longitudinal cohorts, and large epidemiologic
analyses should not be taken as a rationale for withholding
emerging clinical observations or biologically plausible
concerns. Ensuring that clinicians and patients have access
to evolving evidence, including rare but mechanistically
credible adverse events, is consistent with the core
principles of medical ethics and reinforces public trust
by clearly delineating what is known, what remains
unresolved, and what work is ongoing. Informed consent
must adapt as new data accumulate, even when causal
questions remain open, and doing so does not assume bias
to what future investigation will ultimately show.
CONCLUSIONS
The collective world-wide evidence from 2020–
2025 underscores a biologically plausible connection
between COVID-19 vaccination and cancer. The
recurring clinical findings documented across many
reports of de-novo cancer onset, rapid tumor progression,
viral reactivation, and reawakening of dormant disease,
highlight critical gaps in knowledge and understanding of
how large-scale immune changes produced by the vaccine
interacts with cancer biology.
Both SARS-CoV-2 infection and COVID-19
vaccination engage overlapping biological pathways
that could, in principle, influence cancer risk, yet they
differ in mechanism, magnitude, biodistribution, and
duration of their effects. Shared mechanisms include
activation of the innate immune system, robust interferon
signaling, cytokine induction, oxidative stress, and
transient disruption of immune-cell homeostasis. These
changes can theoretically expose latent malignancies,
promote clonal expansion of preexisting mutant cells, or
create microenvironmental contexts permissive to tumor
progression.
In addition, both infection and vaccination induce
spike protein expression, which interacts with ACE2-
expressing tissues and can trigger endothelial activation,
inflammation, and cellular stress pathways implicated
in oncogenic signaling. Both can also lead to prolonged
inflammatory and tissue-injury states, all of which could
contribute to genomic instability, epigenetic remodeling,
and chronic immune dysregulation.
However, unique mechanisms distinguish
COVID-19 vaccination from natural infection. Vaccination
involves widespread biodistribution, intracellular uptake
and persistence of modified nucleic acid templates that
drive synthesis of an unnatural Spike protein both at the
injection site but also throughout the body. The presence of
the residual or fragmented DNA combined with the LNP-
mediated delivery to immune and non-immune tissues, and
sustained spike expression for month to years represent
vaccine-specific factors that could theoretically promote
insertional mutagenesis, perturb immune surveillance,
or accelerate growth of preexisting malignant clones. As
such there is much to be learned from human tissue and
blood samples as well as autopsies to better understand
the interplay between COVID infection, vaccination and
cancer mechanisms.
To this end, Spike protein presence and persistence
along with the biological effects that are cell autonomous
or that depend on host immune interactions need to be
studied to establish connections to cancer initiation and
progression. Accordingly, we propose that tumors arising
after documented SARS-CoV-2 infection or following
COVID-19 vaccination be evaluated using a standardized
immunohistochemical classification framework.
At minimum, this should include assessment of
viral antigen expression patterns by IHC. Spike-positive/
nucleocapsid-positive, spike-positive/nucleocapsid-
negative, and spike-negative/nucleocapsid-negative
phenotypes should be defined. This assessment
should be integrated with detailed characterization
of proliferative activity (e.g., Ki-67), cell-death and
DNA-damage response markers, tumor-suppressor and
oncogene pathway signatures, and the immune tumor
microenvironment.
Implementing this type of reporting across clinical
pathology and autopsy evaluations would allow more
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precise discrimination among tumors potentially driven
by infection, by vaccine-related antigen expression, or
by unrelated oncogenic processes, and would enable
aggregation of comparable cases across institutions.
Establishing uniform criteria of this kind is essential for
building a coherent evidence base, supporting mechanistic
research, and ultimately determining whether observed
associations reflect coincidence, unmasking of latent
disease, immune perturbation, or true causal relationships.
Establishing causality between SARS-CoV-2
infection, COVID-19 vaccination, and cancer requires
a level of evidence far beyond temporal association. In
oncology, causation is never determined by a single
observation or study; it emerges only when multiple,
independent lines of evidence converge over time. This
includes mechanistic data (such as genomic integration
analyses, clonal evolution trajectories, immune-profiling,
and epigenetic changes), pathology-based findings
(including autopsies with molecular characterization),
experimental models that accurately reflect human
tissue biology (organoids, humanized systems, long-
read sequencing of exposed tissues), and population-
level epidemiologic studies capable of detecting small
but meaningful signals against background incidence.
Only by integrating these approaches can we distinguish
coincidence from unmasking of latent disease, expansion
of preexisting malignant clones, or true de novo
oncogenesis. Importantly, the need for rigorous evidence
should not be used to dismiss emerging patterns.
Transparent discussion of biologically plausible
mechanisms and surveillance strategies is essential to
determine if this temporal association is causally linked.
Current reliable epidemiologic data is lacking to provide
evidence that vaccination does not increase population-
level cancer incidence. Peer-reviewed literature is not
completely or easily indexed. Establishing a framework
for post-vaccination cancer surveillance, could help detect
rare adverse patterns early and enable mechanistic follow-
up without compromising public confidence. The goal
of this review is not to estimate population-level cancer
risk but to provide a structured synthesis of the existing
peer-reviewed literature, identify recurring clinical and
biological themes, and delineate critical gaps that require
rigorous epidemiologic and mechanistic follow-up. This
will enable a better understanding of the full spectrum of
immune responses to inform safer immunization strategies
and illuminate previously underappreciated links between
immunity and cancer biology.
The scientific imperative moving forward should
be a coordinated framework combining longitudinal
surveillance and mechanistic experimentation to allow
us to distinguish coincidence from causality and to refine
future vaccine platforms accordingly. In doing so, we
stand to gain not only a clearer understanding of vaccine
safety, but also a deeper insight into the fundamental links
between immunity, infection, and cancer emergence.
AUTHOR CONTRIBUTIONS
C.K. and W.E-D. conceived the review, conducted
the literature search, data extraction, and synthesis, drafted
and approved the final version of the manuscript.
ACKNOWLEDGMENTS
W.S.E-D. is an American Cancer Society Research
Professor and is supported by the Mencoff Family
University Professorship at Brown University.
CK is the Director of the Tufts University
Convergence Laboratory of Biomedical, Physical, and
Engineering Sciences.
CONFLICTS OF INTEREST
W.S.E-D., co-Editor-in-Chief of Oncotarget, was not
involved in the review of this manuscript or the decision
to accept it.
EDITORIAL NOTE
The Editor-in-Chief, Dr. Wafik S. El-Deiry, was
not involved in the peer-review process or the decision-
making for this paper. Dr. El-Deiry shared the submitted
manuscript with National Cancer Institute (NCI) Director
Anthony Letai by email electronically on December 12,
2025.
REFERENCES
1. Saha A, Ghosh Roy S, Dwivedi R, Tripathi P, Kumar K,
Nambiar SM, Pathak R. Beyond the Pandemic Era: Recent
Advances and Efficacy of SARS-CoV-2 Vaccines Against
Emerging Variants of Concern. Vaccines (Basel). 2025;
13:424. https://doi.org/10.3390/vaccines13040424. [PubMed]
2. Chakraborty C, Lo YH, Bhattacharya M, Das A, Wen ZH.
Looking beyond the origin of SARS-CoV-2: Significant
strategic aspects during the five-year journey of COVID-19
vaccine development. Mol Ther Nucleic Acids. 2025;
36:102527. https://doi.org/10.1016/j.omtn.2025.102527.
[PubMed]
3. Kumar A, Ahmad F, Sah BK, Aljabali AAA, Mishra Y,
Mishra V. Advancements in viral vaccine development:
from traditional to modern approaches. Explor Immunol.
2025; 5:1003203. https://doi.org/10.37349/ei.2025.1003203.
4. Papadatou I, Michos A. Advances in Biotechnology and the
Development of Novel Human Vaccines. Vaccines (Basel).
2025; 13:989. https://doi.org/10.3390/vaccines13090989.
[PubMed]
5. Yang D, Tian J, Shen C, Li Q. An overview and single-arm
meta-analysis of immune-mediated adverse events following
COVID-19 vaccination. Front Pharmacol. 2024; 15:1308768.
https://doi.org/10.3389/fphar.2024.1308768. [PubMed]
Oncotarget21
www.oncotarget.com
6. Buoninfante A, Andeweg A, Genov G, Cavaleri M.
Myocarditis associated with COVID-19 vaccination. NPJ
Vaccines. 2024; 9:122. https://doi.org/10.1038/s41541-024-
00893-1. [PubMed]
7. Tayebi A, Samimisedeh P, Jafari Afshar E, Mahmoudnia
S, Milan N, Ayati A, Madady A, Rastad H. Neuromuscular
diseases associated with COVID-19 vaccines: a systematic
review and pooled analysis of 258 patients. BMC Neurol.
2023; 23:437. https://doi.org/10.1186/s12883-023-03486-y.
[PubMed]
8. Kim HJ, Kim MH, Choi MG, Chun EM. 1-year risks of
cancers associated with COVID-19 vaccination: a large
population-based cohort study in South Korea. Biomark
Res. 2025; 13:114. https://doi.org/10.1186/s40364-025-
00831-w. [PubMed]
9. Naffaa MM, Al-Ewaidat OA. The viral oncogenesis of
COVID-19 and its impact on cancer progression, long-
term risks, treatment complexities, and research strategies.
Explor Med. 2025; 6:1001314. https://doi.org/10.37349/
emed.2025.1001314.
10. Soleimani P, Yadollahifarsani S, Motieian M, Moghadam
MSC, Alimohammadi S, Khayyat A, Pour MAE, Sina
Neshat S, Marashi NA, Mahmoodnia L, Masomi R.
Cancer recurrence or aggravation following COVID-19
vaccination. J Nephropharmacol. 2023; 12:e10593. https://
doi.org/10.34172/npj.2023.10593.
11. Shi Y, Shi M, Wang Y, You J. Progress and prospects of
mRNA-based drugs in pre-clinical and clinical applications.
Signal Transduct Target Ther. 2024; 9:322. https://doi.
org/10.1038/s41392-024-02002-z. [PubMed]
12. Comirnaty, t. P.-B. C.-m. v. https://www.fda.gov/
media/151707/download.
13. Spikevax, t. M. C.-m. v. https://www.fda.gov/media/155675/
download.
14. Mnexspike t. M. C.-l. d. m. v. https://www.fda.gov/files/
vaccines%2C%20blood%20%26%20biologics/published/
Package-Insert-MNEXSPIKE.pdf.
15. Nuvaxovid t. N. C.-p.-b. v. https://www.fda.gov/files/
vaccines%2C%20blood%20%26%20biologics/published/
Package-Insert-and-Patient-Package-Insert-NUVAXOVID.
pdf.
16. Sung H, Jiang C, Bandi P, Minihan A, Fidler-Benaoudia M,
Islami F, Siegel RL, Jemal A. Differences in cancer rates
among adults born between 1920 and 1990 in the USA: an
analysis of population-based cancer registry data. Lancet
Public Health. 2024; 9:e583–93. https://doi.org/10.1016/
S2468-2667(24)00156-7. [PubMed]
17. Koh B, Tan DJH, Ng CH, Fu CE, Lim WH, Zeng RW,
Yong JN, Koh JH, Syn N, Meng W, Wijarnpreecha K,
Liu K, Chong CS, et al. Patterns in Cancer Incidence
Among People Younger Than 50 Years in the US, 2010 to
2019. JAMA Netw Open. 2023; 6:e2328171. https://doi.
org/10.1001/jamanetworkopen.2023.28171. [PubMed]
18. Siegel RL, Kratzer TB, Giaquinto AN, Sung H, Jemal A.
Cancer statistics, 2025. CA Cancer J Clin. 2025; 75:10–45.
https://doi.org/10.3322/caac.21871. [PubMed]
19. Grippin AJ, Marconi C, Copling S, Li N, Braun C, Woody
C, Young E, Gupta P, Wang M, Wu A, Jeong SD, Soni D,
Weidert F, et al, and D3CODE Team. SARS-CoV-2 mRNA
vaccines sensitize tumours to immune checkpoint blockade.
Nature. 2025; 647:488–97. https://doi.org/10.1038/s41586-
025-09655-y. [PubMed]
20. Acuti Martellucci C, Capodici A, Soldato G, Fiore M, Zauli
E, Carota R, De Benedictis M, Di Marco G, Di Luzio R,
Flacco ME, Manzoli L. COVID-19 vaccination, all-cause
mortality, and hospitalization for cancer: 30-month cohort
study in an Italian province. EXCLI J. 2025; 24:690–707.
https://doi.org/10.17179/excli2025-8400. [PubMed]
21. Bae E, Bae S, Vaysblat M, Abdelwahed M, Sarkar K, Bae
S. Development of High-Grade Sarcoma After Second Dose
of Moderna Vaccine. Cureus. 2023; 15:e37612. https://doi.
org/10.7759/cureus.37612. [PubMed]
22. Quintero D, Patel N, Harris G, Maristany A, Alani A,
Rosenberg AE, Conway SA, Jose J. COVID-19 vaccine-
associated ganulomatous mass mimicking a sarcoma: a
case report. Radiol Case Rep. 2022; 17:2775–78. https://
doi.org/10.1016/j.radcr.2022.05.035. [PubMed]
23. Li YH, Lin YT, Chuang SH, Yang HJ. Kaposi Sarcoma as a
Possible Cutaneous Adverse Effect of ChAdOx1 nCov-19
Vaccine: A Case Report. Vaccines (Basel). 2024; 12:1168.
https://doi.org/10.3390/vaccines12101168. [PubMed]
24. White E, Fazio N, Tourmouzis K, Ryu S, Finger PT,
Sassoon J, Keresztes R, Chou T, Kaplowitz K, Honkanen R.
Unilateral conjunctival Classic Kaposi Sarcoma following
a COVID 19 booster. Am J Ophthalmol Case Rep. 2023;
34:101986. https://doi.org/10.1016/j.ajoc.2023.101986.
[PubMed]
25. Martínez-Ortega JI, Ramirez Cibrian AG, Martinez-
Jaramillo E, García Silva MDC. Sporadic Kaposi Sarcoma
Following a COVID-19 Vaccine: Mere Coincidence or
Something More? Cureus. 2024; 16:e53925. https://doi.
org/10.7759/cureus.53925. [PubMed]
26. Cavanna L, Grassi SO, Ruffini L, Michieletti E, Carella E,
Palli D, Zangrandi A, Inzerilli N, Bernuzzi P, Di Nunzio
C, Citterio C. Non-Hodgkin Lymphoma Developed Shortly
after mRNA COVID-19 Vaccination: Report of a Case and
Review of the Literature. Medicina (Kaunas). 2023; 59:157.
https://doi.org/10.3390/medicina59010157. [PubMed]
27. Olszewska B, Zaryczańska A, Nowicki RJ, Sokołowska-
Wojdyło M. Rare COVID-19 vaccine side effects got lost
in the shuffle. Primary cutaneous lymphomas following
COVID-19 vaccination: a systematic review. Front Med
(Lausanne). 2024; 11:1325478. https://doi.org/10.3389/
fmed.2024.1325478. [PubMed]
28. Sekizawa A, Hashimoto K, Kobayashi S, Kozono S,
Kobayashi T, Kawamura Y, Kimata M, Fujita N, Ono
Y, Obuchi Y, Tanaka Y. Rapid progression of marginal
zone B-cell lymphoma after COVID-19 vaccination
(BNT162b2): A case report. Front Med (Lausanne). 2022;
9:963393. https://doi.org/10.3389/fmed.2022.963393.
[PubMed]
Oncotarget22
www.oncotarget.com
29. Tosun A, Tasdemir MN. Glioblastoma misdiagnosed
as acute disseminated encephalomyelitis following
coronavirus disease vaccination. Rev Soc Bras Med Trop.
2022; 55:e0400–2022. https://doi.org/10.1590/0037-8682-
0400-2022. [PubMed]
30. Akkus E, Karaoglan B, Akyol C, Ünal AE, Kuzu MA, Savaş
B, Utkan G. Types and Rates of COVID-19 Vaccination
in Patients With Newly Diagnosed Microsatellite Stable
and Instable Non-Metastatic Colon Cancer. Cureus. 2024;
16:e61780. https://doi.org/10.7759/cureus.61780. [PubMed]
31. Kim JH, Oh EH, Han DS. Polyposis of gastrointestinal tract
after COVID-19 mRNA vaccination: a report of two cases.
Clin Endosc. 2024; 57:402–6. https://doi.org/10.5946/
ce.2023.268. [PubMed]
32. Abue M, Mochizuki M, Shibuya-Takahashi R, Ota K, Wakui
Y, Iwai W, Kusaka J, Saito M, Suzuki S, Sato I, Tamai K.
Repeated COVID-19 Vaccination as a Poor Prognostic
Factor in Pancreatic Cancer: A Retrospective, Single-Center
Cohort Study. Cancers (Basel). 2025; 17:2006. https://doi.
org/10.3390/cancers17122006. [PubMed]
33. Sasa S, Inoue H, Inui T, Miyamoto N, Aoyama M, Okumura
K, Toba H, Yoshida T, Tezuka M, Hirose C, Saijo Y, Uehara
H, Izumori A, et al. Axillary lymphangioma that developed
following COVID-19 vaccination: a case report. Surg Case
Rep. 2022; 8:131. https://doi.org/10.1186/s40792-022-
01488-5. [PubMed]
34. Ang SY, Huang YF, Chang CT. Ph-Positive B-Cell Acute
Lymphoblastic Leukemia Occurring after Receipt of
Bivalent SARS-CoV-2 mRNA Vaccine Booster: A Case
Report. Medicina (Kaunas). 2023; 59:627. https://doi.
org/10.3390/medicina59030627. [PubMed]
35. Yanagida E, Kubota A, Miyoshi H, Ohshima K, Kawakita
T, Murayama T. The case of T-ALL presenting with
NK phenotype after COVID-19 vaccination. Pathol
Res Pract. 2023; 242:154310. https://doi.org/10.1016/j.
prp.2023.154310. [PubMed]
36. Sano S. A case of metastatic breast carcinoma to the skin
expressing SARS-CoV-2 spike protein possibly derived
from mRNA vaccine. J Dermatol Sci. 2025; 120:71–73.
https://doi.org/10.1016/j.jdermsci.2025.09.007. [PubMed]
37. Mizutani M, Mitsui H, Amano T, Ogawa Y, Deguchi N,
Shimada S, Miwa A, Kawamura T, Ogido Y. Two cases of
axillary lymphadenopathy diagnosed as diffuse large B-cell
lymphoma developed shortly after BNT162b2 COVID-19
vaccination. J Eur Acad Dermatol Venereol. 2022; 36:e613–
15. https://doi.org/10.1111/jdv.18136. [PubMed]
38. Peacock JG, Banks EA, McWhorter N.
18
F-Fluciclovine-
Avid Axillary Lymph Nodes After COVID-19 Vaccination
on PET/CT for Suspected Recurrence of Prostate Cancer.
J Nucl Med Technol. 2022; 50:73–74. https://doi.
org/10.2967/jnmt.121.263001. [PubMed]
39. Revenga-Porcel L, Peñate Y, Granados-Pacheco F.
Anaplastic large cell lymphoma at the SARS-CoV2 vaccine
injection site. J Eur Acad Dermatol Venereol. 2023; 37:e32–
34. https://doi.org/10.1111/jdv.18615. [PubMed]
40. Hsieh CY, Yu SC, Lee JA, Tsai TF. Nodal T-Follicular
Helper Cell Lymphoma, Angioimmunoblastic-Type,
Diagnosed in a Patient with Psoriasis Following COVID-19
Vaccination under Adalimumab Treatment: A Causal
Association? Indian J Dermatol. 2024; 69:264–67. https://
doi.org/10.4103/ijd.ijd_93_23. [PubMed]
41. Tachita T, Takahata T, Yamashita S, Ebina T, Kamata K,
Yamagata K, Tamai Y, Sakuraba H. Newly diagnosed
extranodal NK/T-cell lymphoma, nasal type, at the injected
left arm after BNT162b2 mRNA COVID-19 vaccination.
Int J Hematol. 2023; 118:503–507. https://doi.org/10.1007/
s12185-023-03607-w. [PubMed]
42. Tanaka A, Kawaguchi T, Imadome KI, Hara S. [Epstein-
Barr virus-associated lymphoproliferative disorders after
BNT162b2 mRNA COVID-19 vaccination]. Rinsho
Ketsueki. 2023; 64:277–82. https://doi.org/10.11406/
rinketsu.64.277. [PubMed]
43. Gambichler T, Boms S, Hessam S, Tischoff I, Tannapfel
A, Lüttringhaus T, Beckman J, Stranzenbach R. Primary
cutaneous anaplastic large-cell lymphoma with marked
spontaneous regression of organ manifestation after SARS-
CoV-2 vaccination. Br J Dermatol. 2021; 185:1259–62.
https://doi.org/10.1111/bjd.20630. [PubMed]
44. Goldman S, Bron D, Tousseyn T, Vierasu I, Dewispelaere
L, Heimann P, Cogan E, Goldman M. Rapid Progression
of Angioimmunoblastic T Cell Lymphoma Following
BNT162b2 mRNA Vaccine Booster Shot: A Case Report.
Front Med (Lausanne). 2021; 8:798095. https://doi.
org/10.3389/fmed.2021.798095. [PubMed]
45. Dyagil I, Martina Z, Movchan A, Abramenko I, Chumak
A, Bazyka D. Rapid progression of angioimmunoblastic
T cell lymphoma after Covid-19 vaccination
(Chadox1-S): a case report. J Clin Case Rep Med Image
Health Sci. 2023; 5:2. https://dx.doi.org/10.55920/
JCRMHS.2023.05.001201.
46. Panou E, Nikolaou V, Marinos L, Kallambou S,
Sidiropoulou P, Gerochristou M, Stratigos A. Recurrence
of cutaneous T-cell lymphoma post viral vector COVID-19
vaccination. J Eur Acad Dermatol Venereol. 2022; 36:e91–
93. https://doi.org/10.1111/jdv.17736. [PubMed]
47. Kreher MA, Ahn J, Werbel T, Motaparthi K. Subcutaneous
panniculitis-like T-cell lymphoma after COVID-19
vaccination. JAAD Case Rep. 2022; 28:18–20. https://doi.
org/10.1016/j.jdcr.2022.08.006. [PubMed]
48. Ukishima S, Miyagami T, Arikawa M, Kushiro S, Takaku
T, Naito T. Subcutaneous panniculitis-like T-cell lymphoma
post-mRNA-1273 COVID-19 vaccination. Clin Case Rep.
2023; 11:e7143. https://doi.org/10.1002/ccr3.7143. [PubMed]
49. Veeraballi S, Patel A, Are G, Ramahi A, Chittamuri S, Shaaban
H. A Case of Chronic Myelomonocytic Leukemia Unmasked
After Receiving J&J COVID-19 Vaccine. Cureus. 2022;
14:e26070. https://doi.org/10.7759/cureus.26070. [PubMed]
50. Plüß M, Mitteldorf C, Szuszies CJ, Tampe B. Case
Report: Acquired Haemophilia A Following mRNA-
1273 Booster Vaccination Against SARS-CoV-2 With
Oncotarget23
www.oncotarget.com
Concurrent Diagnosis of Pleomorphic Dermal Sarcoma.
Front Immunol. 2022; 13:868133. https://doi.org/10.3389/
fimmu.2022.868133. [PubMed]
51. Sumi T, Nagahisa Y, Matsuura K, Sekikawa M, Yamada Y,
Nakata H, Chiba H. Lung squamous cell carcinoma with
hemoptysis after vaccination with tozinameran (BNT162b2,
Pfizer-BioNTech). Thorac Cancer. 2021; 12:3072–75.
https://doi.org/10.1111/1759-7714.14179. [PubMed]
52. Eens S, Van Hecke M, Favere K, Tousseyn T, Guns PJ,
Roskams T, Heidbuchel H. B-cell lymphoblastic lymphoma
following intravenous BNT162b2 mRNA booster in a BALB/c
mouse: A case report. Front Oncol. 2023; 13:1158124. https://
doi.org/10.3389/fonc.2023.1158124. [PubMed]
53. Cui Z, Cheng J. A systematic review of lymphoma
secondary to COVID-19 vaccination. Authorea. 2024.
https://doi.org/10.22541/au.172543425.59165134/v1.
54. Barnett C, Mehta N, Towne WS, Babagbemi K, Sales RM.
Metastatic melanoma in the breast and axilla: A case report.
Clin Imaging. 2022; 85:78–82. https://doi.org/10.1016/j.
clinimag.2022.02.014. [PubMed]
55. Gullotti DM, Lipson EJ, Fishman EK, Rowe SP.
Acute axillary lymphadenopathy detected shortly
after COVID-19 vaccination found to be due to newly
diagnosed metastatic melanoma. Radiol Case Rep. 2022;
17:878–80. https://doi.org/10.1016/j.radcr.2021.12.002.
[PubMed]
56. Wagle AM, Wu BC, Gopal L, Sundar G. Necrosis of
uveal melanoma post-COVID-19 vaccination. Indian J
Ophthalmol. 2022; 70:1837–40. https://doi.org/10.4103/
ijo.IJO_3040_21. [PubMed]
57. Leis AA, Montesi AP, Khan SM, Montesi M. Case Report:
Malignant Melanoma Associated With COVID-19: A
Coincidence or a Clue? Front Med (Lausanne). 2022;
9:845558. https://doi.org/10.3389/fmed.2022.845558.
[PubMed]
58. Avram A, Scurtu LG, Costache M, Simionescu O. A
Disguising Fast-Growing Metachronous Melanoma
and COVID-19. Cureus. 2023; 15:e36108. https://doi.
org/10.7759/cureus.36108. [PubMed]
59. Sprenger F, Sanches DP, Bacarin JV, de Almeida Teixeira
BC. Prevertebral Inflammatory Myofibroblastic Tumor
Following COVID Vaccine Booster Dose. Indian J
Otolaryngol Head Neck Surg. 2023; 75:1–4. https://doi.
org/10.1007/s12070-023-03718-0. [PubMed]
60. Sugasawa S, Kimura T, Bae Y, Kumasaka T, Ichi S.
Two Cases of Rare Intratumoral Hemorrhage Following
COVID-19 Vaccination. Cureus. 2022; 14:e32400. https://
doi.org/10.7759/cureus.32400. [PubMed]
61. Gable AD, Hughes SM, Miller RJ. A 24-Year-Old Man With
Hemoptysis Found to Have a Chest Mass and Contralateral
Axillary Lymphadenopathy. Chest. 2021; 160:e289–93.
https://doi.org/10.1016/j.chest.2021.04.055. [PubMed]
62. Xu W, Nian W. A rare adverse effects of COVID-19
vaccine in a patient with a latent tumor: A case report and
literature review. Front Oncol. 2023; 13:1269735. https://
doi.org/10.3389/fonc.2023.1269735. [PubMed]
63. Farhat M, Zouein J, Abou Khater J, Sarkis AS, Helou J.
A Case of Rapid Transformation of a Nail Matrix Nevi to
Melanoma After Messenger RNA COVID-19 Vaccine: A
Cause or a Coincidence? Cureus. 2024; 16:e76312. https://
doi.org/10.7759/cureus.76312. [PubMed]
64. Bogomolets O, Rojczyk E, Hryshchenko R, Bogomolets
C, Berezkin O. Covid-19, leukemia, and secondary
malignancies of the skin - is there a connection: a case report
and literature analysis. Front Oncol. 2023; 13:1265479.
https://doi.org/10.3389/fonc.2023.1265479. [PubMed]
65. Abbas AM, Caicedo ML, Damron TA. Right Biceps Pseudo-
Tumor from COVID-19 Vaccination. Vaccines (Basel).
2024; 12:160. https://doi.org/10.3390/vaccines12020160.
[PubMed]
66. Iliadis AS, Koletsa T, Vounotrypidis P, Fassas A, Apostolidis
A, Apostolidis S, Fotiadou A, Hytiroglou P. Inflammatory
Pseudotumor of the Spleen in a Patient With Psoriatic
Arthritis: A Diagnostic Challenge in the COVID-19
Era. Cureus. 2024; 16:e73121. https://doi.org/10.7759/
cureus.73121. [PubMed]
67. Evangelista FB. Dermatofibrosarcoma Protuberans
following COVID-19 and Influenza vaccination: A
Case Report. Int J Med Rev Case Rep. 2025; 25:1–6.
https://www.researchgate.net/publication/390665272_
Dermatofibrosarcoma_Protuberans_following_COVID-19_
and_Influenza_vaccination_A_Case_Report.
68. Yilmaz A, Goker B, Gedikoglu MG, Ayvaz M,
Tokgozoglu AM. Primary Cutaneous Adenoid Cystic
Carcinoma in a Rare Location With an Immune
Response to a BNT162b2 Vaccine: A Case Report. JBJS
Case Connect. 2024; 14. https://doi.org/10.2106/JBJS.
CC.23.00499. [PubMed]
69. Rashid B, Baig I, Feroze MD, Chaudhry M, Hassan MSZ.
Incidental Atrial Myxoma in the Shadow of COVID-19:
Coincidence or an Emerging Pattern? Cureus. 2025;
17:e93617. https://doi.org/10.7759/cureus.93617. [PubMed]
70. Kawamoto H, Saito-Sasaki N, Sawada Y. Recurrent Merkel
Cell Carcinoma Following COVID-19 Treatment. Cureus.
2024; 16:e64863. https://doi.org/10.7759/cureus.64863.
[PubMed]
71. Bharathidasan K, Tran V, Ghafouri SR, Rehman S, Brandi
L. Metastatic prostatic adenocarcinoma presenting as
generalized lymphadenopathy unmasked by a COVID
booster vaccine. Clin Case Rep. 2023; 11:e8278. https://
doi.org/10.1002/ccr3.8278. [PubMed]
72. Hu H, Wang C, Tao R, Liu B, Peng D, Chen Y, Zhang W.
Evidences of neurological injury caused by COVID-19
from glioma tissues and glioma organoids. CNS Neurosci
Ther. 2024; 30:e14822. https://doi.org/10.1111/cns.14822.
[PubMed]
73. Gregory TA, Knight SR, Aaroe AE, Highsmith KN,
Janatpour ZC, O’Brien BJ, Majd NK, Loghin ME, Patel
Oncotarget24
www.oncotarget.com
CB, Weathers SP, Puduvalli VK, Kamiya-Matsuoka C.
Accelerated tumor progression after COVID-19 infection
in patients with glioblastoma: A retrospective case-control
study. Neurooncol Pract. 2024; 11:475–83. https://doi.
org/10.1093/nop/npae029. [PubMed]
74. Chia SB, Johnson BJ, Hu J, Valença-Pereira F, Chadeau-
Hyam M, Guntoro F, Montgomery H, Boorgula MP,
Sreekanth V, Goodspeed A, Davenport B, De Dominici M,
Zaberezhnyy V, et al. Respiratory viral infections awaken
metastatic breast cancer cells in lungs. Nature. 2025;
645:496–506. https://doi.org/10.1038/s41586-025-09332-0.
[PubMed]
75. Khatri JK, Tahboub I, Anwar K, Masoudi M, Graffeo
V, Jamil MO. Diagnosis of Angioimmunoblastic T Cell
Lymphoma After Receiving First Dose of Pfizer/BioNTech
(BNT162b2) Vaccine: A Case Report. J Investig Med High
Impact Case Rep. 2024; 12:23247096241231645. https://
doi.org/10.1177/23247096241231645. [PubMed]
76. Obodo OI, Ocheni S, Obodo CO, Duru AN, Okoye
HC, Nonyelu CE, Anigbogu IO, Nwagha TU, Madu
AJ. Lymphoid Neoplasms and COVID-19 Vaccination.
Oncol Adv. 2025; 3:e00005. https://doi.org/10.14218/
OnA.2025.00005.
77. Ueda Y, Sakai T, Yamada K, Arita K, Ishige Y, Hoshi D,
Yanagisawa H, Iwao-Kawanami H, Kawanami T, Mizuta
S, Fukushima T, Yamada S, Yachie A, Masaki Y. Fatal
hemophagocytic lymphohistiocytosis with intravascular
large B-cell lymphoma following coronavirus disease
2019 vaccination in a patient with systemic lupus
erythematosus: an intertwined case. Immunol Med. 2024;
47:192–99. https://doi.org/10.1080/25785826.2024.23385
94. [PubMed]
78. Embaby A, Ibrahim A, Elsheikh H, AlMalki M, Kashif
M, Althomali M, Babateen A. Diffuse Large B-Cell
Lymphoma Developed Shortly After mRNA COVID-19
Vaccination in a Patient with Sickle Cell Disease: A
Chicken-and-Egg Problem. Bratisl Lek Listy. 2025;
126:1997–83. https://link.springer.com/article/10.1007/
s44411-025-00174-w.
79. Avallone G, Maronese CA, Conforti C, Fava P, Gargiulo L,
Marzano AV, Massone C, Mastorino L, Paradisi A, Pileri A,
Quaglino P, Rizzo N, Ribero S, et al. Real-world data on
primary cutaneous lymphoproliferative disorders following
SARS-CoV-2 vaccination: A multicentre experience from
tertiary referral hospitals. J Eur Acad Dermatol Venereol.
2023; 37:e451–55. https://doi.org/10.1111/jdv.18806.
[PubMed]
80. Gordon ER, Kwinta BD, Schreidah CM, Fahmy LM,
Adeuyan O, Queen D, Trager MH, Magro CM, Geskin LJ.
Cutaneous lymphoproliferative disorders after COVID-19
vaccination: clinical presentation, histopathology, and
outcomes. Leuk Lymphoma. 2024; 65:48–54. https://doi.or
g/10.1080/10428194.2023.2270766. [PubMed]
81. Hobayan CG, Chung CG. Indolent cutaneous lymphoma
with gamma/delta expression after COVID-19 vaccination.
JAAD Case Rep. 2023; 32:74–76. https://doi.org/10.1016/j.
jdcr.2022.12.001. [PubMed]
82. Moneva-Sakelarieva M, Kobakova Y, Konstantinov S,
Semerdzhieva NE, Ivanova SA, Atanasova VP, Atanasov
PY, Becheva MSV. Lymphoma with skin localization
and COVID 19 – a clinical case and review of literature.
Pharmacia. 2024; 71:1–7. https://doi.org/10.3897/
pharmacia.71.e135467.
83. Montoya VHG, Cardona LG, Morales S, Ospina JA, Rueda
X. SARSCOV-2 vaccine associated with primary cutaneous
peripheral T cell lymphoma. Eur J Cancer. 2022. https://doi.
org/10.1016/S0959-8049(22)00617-7.
84. O Sullivan C, Zach F, Moser T, Pilz G, Harrer A, Trinka
E, Enzinger C, Pfaff JAR, Wipfler P. Misinterpretation of
glioblastoma as ADEM: potentially harmful consequences
of over-diagnosis of COVID-19 vaccine-associated
adverse events. J Neurol. 2022; 269:616–18. https://doi.
org/10.1007/s00415-021-10707-2. [PubMed]
85. Russell SJ, Mabila SL. Non-Hodgkin lymphoma incidence
in active component U.S. service members, 2017-2023.
MSMR. 2025; 32:16–17. [PubMed]
86. Mitrofanova L, Makarov I, Goncharova E, Makarova T,
Starshinova A, Kudlay D, Shlaykhto E. High Risk of Heart
Tumors after COVID-19. Life (Basel). 2023; 13:2087.
https://doi.org/10.3390/life13102087. [PubMed]
87. Zeyen T, Friker LL, Paech D, Schaefer N, Weller J,
Zschernack V, Layer JP, Schneider M, Potthoff AL,
Bernhardt M, Sanders C, Kristiansen G, Hoelzel M, et al.
Transient MRI changes and neurological deterioration in
glioblastoma upon SARS-CoV-2 infection. J Cancer Res
Clin Oncol. 2024; 150:437. https://doi.org/10.1007/s00432-
024-05963-4. [PubMed]
88. Bradford PT, Devesa SS, Anderson WF, Toro JR. Cutaneous
lymphoma incidence patterns in the United States: a
population-based study of 3884 cases. Blood. 2009;
113:5064–73. https://doi.org/10.1182/blood-2008-10-184168.
[PubMed]
89. Molyneux EM, Rochford R, Griffin B, Newton R, Jackson
G, Menon G, Harrison CJ, Israels T, Bailey S. Burkitt’s
lymphoma. Lancet. 2012; 379:1234–44. https://doi.
org/10.1016/S0140-6736(11)61177-X. [PubMed]
90. Stoyanov GS, Lyutfi E, Georgiev R, Dzhenkov DL,
Kaprelyan A. The Rapid Development of Glioblastoma: A
Report of Two Cases. Cureus. 2022; 14:e26319. https://doi.
org/10.7759/cureus.26319. [PubMed]
91. Stein WD, Figg WD, Dahut W, Stein AD, Hoshen MB,
Price D, Bates SE, Fojo T. Tumor growth rates derived
from data for patients in a clinical trial correlate strongly
with patient survival: a novel strategy for evaluation of
clinical trial data. Oncologist. 2008; 13:1046–54. https://
doi.org/10.1634/theoncologist.2008-0075. [PubMed]
92. He LN, Zhang X, Li H, Chen T, Chen C, Zhou Y, Lin Z,
Du W, Fang W, Yang Y, Huang Y, Zhao H, Hong S, Zhang
L. Pre-Treatment Tumor Growth Rate Predicts Clinical
Oncotarget25
www.oncotarget.com
Outcomes of Patients With Advanced Non-Small Cell
Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy.
Front Oncol. 2021; 10:621329. https://doi.org/10.3389/
fonc.2020.621329. [PubMed]
93. Endara SA, Dávalos GA, Molina GA, Zavala AB, Ponton
PM, Brito M, Nieto C, Ullauri VE. COVID-19 infection
and cardiac angiosarcoma: a dangerous combination-a
case report. Cardiothorac Surg. 2021; 29:5. https://doi.
org/10.1186/s43057-021-00042-7. [PubMed]
94. Hu M, Wang B, Li J, Wu C. Editorial: The association
between viral infection and human cancers. Front
Microbiol. 2024; 15:1371581. https://doi.org/10.3389/
fmicb.2024.1371581. [PubMed]
95. Ameya G, Birri DJ. The molecular mechanisms of virus-
induced human cancers. Microb Pathog. 2023; 183:106292.
https://doi.org/10.1016/j.micpath.2023.106292. [PubMed]
96. McLaughlin-Drubin ME, Munger K. Viruses associated
with human cancer. Biochim Biophys Acta. 2008;
1782:127–50. https://doi.org/10.1016/j.bbadis.2007.12.005.
[PubMed]
97. Moore PS, Chang Y. Why do viruses cause cancer?
Highlights of the first century of human tumour virology.
Nat Rev Cancer. 2010; 10:878–89. https://doi.org/10.1038/
nrc2961. [PubMed]
98. Morais P, Adachi H, Yu YT. The Critical Contribution
of Pseudouridine to mRNA COVID-19 Vaccines. Front
Cell Dev Biol. 2021; 9:789427. https://doi.org/10.3389/
fcell.2021.789427. [PubMed]
99. Bettini E, Locci M. SARS-CoV-2 mRNA Vaccines:
Immunological Mechanism and Beyond. Vaccines (Basel).
2021; 9:147. https://doi.org/10.3390/vaccines9020147.
[PubMed]
100. Boros LG, Kyriakopoulos AM, Brogna C, Piscopo M,
McCullough PA, Seneff S. Long-lasting, biochemically
modified mRNA, and its frameshifted recombinant spike
proteins in human tissues and circulation after COVID-19
vaccination. Pharmacol Res Perspect. 2024; 12:e1218.
https://doi.org/10.1002/prp2.1218. [PubMed]
101. Mulroney TE, Pöyry T, Yam-Puc JC, Rust M, Harvey
RF, Kalmar L, Horner E, Booth L, Ferreira AP, Stoneley
M, Sawarkar R, Mentzer AJ, Lilley KS, et al. N
1
-
methylpseudouridylation of mRNA causes +1 ribosomal
frameshifting. Nature. 2024; 625:189–94. https://doi.
org/10.1038/s41586-023-06800-3. [PubMed]
102. Jackson LA, Anderson EJ, Rouphael NG, Roberts PC,
Makhene M, Coler RN, McCullough MP, Chappell JD,
Denison MR, Stevens LJ, Pruijssers AJ, McDermott A,
Flach B, et al, and mRNA-1273 Study Group. An mRNA
Vaccine against SARS-CoV-2 - Preliminary Report. N
Engl J Med. 2020; 383:1920–31. https://doi.org/10.1056/
NEJMoa2022483. [PubMed]
103. Speicher DJ, Rose J, McKernan K. Quantification of
residual plasmid DNA and SV40 promoter-enhancer
sequences in Pfizer/BioNTech and Moderna modRNA
COVID-19 vaccines from Ontario, Canada. Autoimmunity.
2025; 58:2551517. https://doi.org/10.1080/08916934.2025
.2551517. [PubMed]
104. Raoult D. Confirmation of the presence of vaccine DNA
in the Pfizer anti-COVID-19 vaccine. 2024. https://hal.
science/hal-04778576v1.
105. Kaiser S, Kaiser S, Reis J, Marschalek R. Quantification
of objective concentrations of DNA impurities in
mRNA vaccines. Vaccine. 2025; 55:127022. https://doi.
org/10.1016/j.vaccine.2025.127022. [PubMed]
106. Science, Public Health Policy, and the Law Volume:
v5.2019-2024. December 2024. https://www.researchgate.
net/publication/386414408_BioNTech_RNA-Based_
COVID-19_Injections_Contain_Large_Amounts_Of_
Residual_DNA_Including_An_SV40_PromoterEnhancer_
Sequence.
107. König B, Kirchner JO. Methodological Considerations
Regarding the Quantification of DNA Impurities in the
COVID-19 mRNA Vaccine Comirnaty
®
. Methods Protoc.
2024; 7:41. https://doi.org/10.3390/mps7030041. [PubMed]
108. Wang TJ, Kim A, Kim K. A rapid detection method of
replication-competent plasmid DNA from COVID-19
mRNA vaccines for quality control. JHSS. 2024; 8. https://
www.researchgate.net/publication/393592852_A_rapid_
detection_method_of_replication-competent_plasmid_
DNA_from_COVID-19_mRNA_vaccines_for_quality_
control.
109. Patterson BK, Yogendra R, Francisco EB, Guevara-Coto J,
Long E, Pise A, Osgood E, Bream J, Kreimer M, Jeffers D,
Beaty C, Vander Heide R, Mora-Rodríguez RA. Detection
of S1 spike protein in CD16+ monocytes up to 245 days in
SARS-CoV-2-negative post-COVID-19 vaccine syndrome
(PCVS) individuals. Hum Vaccin Immunother. 2025;
21:2494934. https://doi.org/10.1080/21645515.2025.2494
934. [PubMed]
110. Bhattacharjee S. Immunological and Antigenic Signatures
Associated with Chronic Illnesses after COVID-19
Vaccination. medRxiv. 2025. https://www.medrxiv.org/con
tent/10.1101/2025.02.18.25322379v1.
111. Halma M, Varon J. Breaking the silence: Recognizing post-
vaccination syndrome. Heliyon. 2025; 11:e43478. https://
doi.org/https://doi.org/10.1016/j.heliyon.2025.e43478.
112. Banoun H. mRNA: Vaccine or Gene Therapy? The Safety
Regulatory Issues. Int J Mol Sci. 2023; 24:10514. https://
doi.org/10.3390/ijms241310514. [PubMed]
113. https://www.fda.gov/vaccines-blood-biologics/cellular-
gene-therapy-products/what-gene-therapy.
114. https://www.europarl.europa.eu/doceo/
document/E-9-2024-000355_EN.html.
115. Azzarone B, Landolina N, Mariotti FR, Moretta L, Maggi
E. Soluble SARS-CoV-2 Spike glycoprotein: considering
some potential pathogenic effects. Front Immunol. 2025;
16:1616106. https://doi.org/10.3389/fimmu.2025.1616106.
[PubMed]
Oncotarget26
www.oncotarget.com
116. Swank Z, Senussi Y, Alter G, Walt DR. Persistent
circulating SARS-CoV-2 spike is associated with post-acute
COVID-19 sequelae. medrxiv. 2022. https://doi.org/10.110
1/2022.06.14.22276401.
117. Cabău G, Badii M, Mirea AM, Gaal OI, van Emst L, Popp
RA, Crișan TO, Joosten LAB. Long-Lasting Enhanced
Cytokine Responses Following SARS-CoV-2 BNT162b2
mRNA Vaccination. Vaccines (Basel). 2024; 12:736. https://
doi.org/10.3390/vaccines12070736. [PubMed]
118. Mung SM, Goh TL, Hughes M, Jude EB. Inflammatory
Arthritis Associated with COVID-19 Vaccination. Cureus.
2023; 15:e35951. https://doi.org/10.7759/cureus.35951.
[PubMed]
119. Jagtap K, Naveen R, Day J, Sen P, Vaidya B, Nune A,
Nikiphorou E, Tan AL, Agarwal V, Saha S, Shinjo SK,
Ziade N, Joshi M, et al, and COVAD Study Group. Flares
in autoimmune rheumatic diseases in the post-COVID-19
vaccination period-a cross-sequential study based on COVAD
surveys. Rheumatology (Oxford). 2023; 62:3838–48. https://
doi.org/10.1093/rheumatology/kead144. [PubMed]
120. Lim S, Yocum RR, Silver PA, Way JC. High spontaneous
integration rates of end-modified linear DNAs upon
mammalian cell transfection. Sci Rep. 2023; 13:6835.
https://doi.org/10.1038/s41598-023-33862-0. [PubMed]
121. Tahtinen S, Tong AJ, Himmels P, Oh J, Paler-Martinez A,
Kim L, Wichner S, Oei Y, McCarron MJ, Freund EC, Amir
ZA, de la Cruz CC, Haley B, et al. IL-1 and IL-1ra are key
regulators of the inflammatory response to RNA vaccines.
Nat Immunol. 2022; 23:532–42. https://doi.org/10.1038/
s41590-022-01160-y. [PubMed]
122. Rosati M, Terpos E, Homan P, Bergamaschi C, Karaliota S,
Ntanasis-Stathopoulos I, Devasundaram S, Bear J, Burns
R, Bagratuni T, Trougakos IP, Dimopoulos MA, Pavlakis
GN, Felber BK. Rapid transient and longer-lasting innate
cytokine changes associated with adaptive immunity after
repeated SARS-CoV-2 BNT162b2 mRNA vaccinations.
Front Immunol. 2023; 14:1292568. https://doi.org/10.3389/
fimmu.2023.1292568. [PubMed]
123. Kim S, Jeon JH, Kim M, Lee Y, Hwang YH, Park M, Li
CH, Lee T, Lee JA, Kim YM, Kim D, Lee H, Kim YJ, et al.
Innate immune responses against mRNA vaccine promote
cellular immunity through IFN-β at the injection site. Nat
Commun. 2024; 15:7226. https://doi.org/10.1038/s41467-
024-51411-9. [PubMed]
124. Faraj SS, Jalal PJ. IL1β, IL-6, and TNF-α cytokines
cooperate to modulate a complicated medical condition
among COVID-19 patients: case-control study. Ann Med
Surg (Lond). 2023; 85:2291–97. https://doi.org/10.1097/
MS9.0000000000000679. [PubMed]
125. Korzun T, Moses AS, Jozic A, Grigoriev V, Newton
S, Kim J, Diba P, Sattler A, Levasseur PR, Le N, Singh
P, Sharma KS, Goo YT, et al. Lipid Nanoparticles Elicit
Reactogenicity and Sickness Behavior in Mice Via Toll-
Like Receptor 4 and Myeloid Differentiation Protein
88 Axis. ACS Nano. 2024; 18:24842–59. https://doi.
org/10.1021/acsnano.4c05088. [PubMed]
126. Zhang L, More KR, Ojha A, Jackson CB, Quinlan BD, Li H,
He W, Farzan M, Pardi N, Choe H. Effect of mRNA-LNP
components of two globally-marketed COVID-19 vaccines
on efficacy and stability. NPJ Vaccines. 2023; 8:156. https://
doi.org/10.1038/s41541-023-00751-6. [PubMed]
127. Nguyen HM, Alexander KE, Collinge M, Hickey JC, Lanz
TA, Li J, Sheehan MJ, Newman LC, Thorn M. mRNA-
LNPs induce immune activation and cytokine release in
human whole blood assays across diverse health conditions.
Mol Ther. 2025; 33:2872–85. https://doi.org/10.1016/j.
ymthe.2024.12.019. [PubMed]
128. Amoako K, Mokhammad A, Malik A, Yesudasan S, Wheba
A, Olagunju O, Gu SX, Yarovinsky T, Faustino EVS,
Nguyen J, Hwa J. Enhancing nucleic acid delivery by the
integration of artificial intelligence into lipid nanoparticle
formulation. Front Med Technol. 2025; 7:1591119. https://
doi.org/10.3389/fmedt.2025.1591119. [PubMed]
129. Pateev I, Seregina K, Ivanov R, Reshetnikov V.
Biodistribution of RNA Vaccines and of Their
Products: Evidence from Human and Animal Studies.
Biomedicines. 2023; 12:59. https://doi.org/10.3390/
biomedicines12010059. [PubMed]
130. Landskron G, De la Fuente M, Thuwajit P, Thuwajit
C, Hermoso MA. Chronic inflammation and cytokines
in the tumor microenvironment. J Immunol Res. 2014;
2014:149185. https://doi.org/10.1155/2014/149185.
[PubMed]
131. Manjili SH, Isbell M, Ghochaghi N, Perkinson T, Manjili
MH. Multifaceted functions of chronic inflammation
in regulating tumor dormancy and relapse. Semin
Cancer Biol. 2022; 78:17–22. https://doi.org/10.1016/j.
semcancer.2021.03.023. [PubMed]
132. Albrengues J, Shields MA, Ng D, Park CG, Ambrico A,
Poindexter ME, Upadhyay P, Uyeminami DL, Pommier
A, Küttner V, Bružas E, Maiorino L, Bautista C, et al.
Neutrophil extracellular traps produced during inflammation
awaken dormant cancer cells in mice. Science. 2018;
361:eaao4227. https://doi.org/10.1126/science.aao4227.
[PubMed]
133. Perego M, Tyurin VA, Tyurina YY, Yellets J, Nacarelli T,
Lin C, Nefedova Y, Kossenkov A, Liu Q, Sreedhar S, Pass
H, Roth J, Vogl T, et al. Reactivation of dormant tumor
cells by modified lipids derived from stress-activated
neutrophils. Sci Transl Med. 2020; 12:eabb5817. https://
doi.org/10.1126/scitranslmed.abb5817. [PubMed]
134. Maier JA, Castiglioni S, Petrelli A, Cannatelli R, Ferretti
F, Pellegrino G, Sarzi Puttini P, Fiorina P, Ardizzone S.
Immune-Mediated Inflammatory Diseases and Cancer -
a dangerous liaison. Front Immunol. 2024; 15:1436581.
https://doi.org/10.3389/fimmu.2024.1436581. [PubMed]
135. Sausen DG, Poirier MC, Spiers LM, Smith EN. Mechanisms
of T cell evasion by Epstein-Barr virus and implications for
Oncotarget27
www.oncotarget.com
tumor survival. Front Immunol. 2023; 14:1289313. https://
doi.org/10.3389/fimmu.2023.1289313. [PubMed]
136. Aneja KK, Yuan Y. Reactivation and Lytic Replication of
Kaposi’s Sarcoma-Associated Herpesvirus: An Update.
Front Microbiol. 2017; 8:613. https://doi.org/10.3389/
fmicb.2017.00613. [PubMed]
137. Traylen CM, Patel HR, Fondaw W, Mahatme S, Williams
JF, Walker LR, Dyson OF, Arce S, Akula SM. Virus
reactivation: a panoramic view in human infections. Future
Virol. 2011; 6:451–63. https://doi.org/10.2217/fvl.11.21.
[PubMed]
138. Okan Cakir M, Kirca O, Gunduz S, Ozdogan M.
Hyperprogression after immunotherapy: A comprehensive
review. J BUON. 2019; 24:2232–41. [PubMed]
139. Shen P, Han L, Ba X, Qin K, Tu S. Hyperprogressive
Disease in Cancers Treated With Immune Checkpoint
Inhibitors. Front Pharmacol. 2021; 12:678409. https://doi.
org/10.3389/fphar.2021.678409. [PubMed]
140. Adashek JJ, Kato S, Ferrara R, Lo Russo G, Kurzrock R.
Hyperprogression and Immune Checkpoint Inhibitors:
Hype or Progress? Oncologist. 2020; 25:94–98. https://doi.
org/10.1634/theoncologist.2019-0636. [PubMed]
141. Brooks DG, Teyton L, Oldstone MB, McGavern DB.
Intrinsic functional dysregulation of CD4 T cells occurs
rapidly following persistent viral infection. J Virol. 2005;
79:10514–27. https://doi.org/10.1128/JVI.79.16.10514-
10527.2005. [PubMed]
142. Zhou S, Ou R, Huang L, Price GE, Moskophidis D.
Differential tissue-specific regulation of antiviral CD8+
T-cell immune responses during chronic viral infection.
J Virol. 2004; 78:3578–600. https://doi.org/10.1128/
jvi.78.7.3578-3600.2004. [PubMed]
143. Zhou Y, Liao X, Song X, He M, Xiao F, Jin X, Xie X,
Zhang Z, Wang B, Zhou C, Kang Y, Zhang W. Severe
Adaptive Immune Suppression May Be Why Patients With
Severe COVID-19 Cannot Be Discharged From the ICU
Even After Negative Viral Tests. Front Immunol. 2021;
12:755579. https://doi.org/10.3389/fimmu.2021.755579.
[PubMed]
144. Hotchkiss RS, Monneret G, Payen D. Sepsis-induced
immunosuppression: from cellular dysfunctions to
immunotherapy. Nat Rev Immunol. 2013; 13:862–74.
https://doi.org/10.1038/nri3552. [PubMed]
145. Irrgang P, Gerling J, Kocher K, Lapuente D, Steininger P,
Habenicht K, Wytopil M, Beileke S, Schäfer S, Zhong J,
Ssebyatika G, Krey T, Falcone V, et al. Class switch toward
noninflammatory, spike-specific IgG4 antibodies after
repeated SARS-CoV-2 mRNA vaccination. Sci Immunol.
2023; 8:eade2798. https://doi.org/10.1126/sciimmunol.
ade2798. [PubMed]
146. Shi P, Yu Y, Xie H, Yin X, Chen X, Zhao Y, Zhao H. Recent
advances in regulatory immune cells: exploring the world
beyond Tregs. Front Immunol. 2025; 16:1530301. https://
doi.org/10.3389/fimmu.2025.1530301. [PubMed]
147. Facciabene A, Motz GT, Coukos G. T-regulatory cells: key
players in tumor immune escape and angiogenesis. Cancer
Res. 2012; 72:2162–71. https://doi.org/10.1158/0008-5472.
CAN-11-3687. [PubMed]
148. Devaud C, John LB, Westwood JA, Darcy PK, Kershaw
MH. Immune modulation of the tumor microenvironment
for enhancing cancer immunotherapy. Oncoimmunology.
2013; 2:e25961. https://doi.org/10.4161/onci.25961.
[PubMed]
149. Yang Y, Li S, To KKW, Zhu S, Wang F, Fu L. Tumor-
associated macrophages remodel the suppressive
tumor immune microenvironment and targeted therapy
for immunotherapy. J Exp Clin Cancer Res. 2025;
44:145. https://doi.org/10.1186/s13046-025-03377-9.
[PubMed]
150. Veleri S. Neurotropism of SARS-CoV-2 and neurological
diseases of the central nervous system in COVID-19
patients. Exp Brain Res. 2022; 240:9–25. https://doi.
org/10.1007/s00221-021-06244-z. [PubMed]
151. Erickson MA, Logsdon AF, Rhea EM, Hansen KM, Holden
SJ, Banks WA, Smith JL, German C, Farr SA, Morley JE,
Weaver RR, Hirsch AJ, Kovac A, et al. Blood-brain barrier
penetration of non-replicating SARS-CoV-2 and S1 variants
of concern induce neuroinflammation which is accentuated
in a mouse model of Alzheimer’s disease. Brain Behav
Immun. 2023; 109:251–68. https://doi.org/10.1016/j.
bbi.2023.01.010. [PubMed]
152. Lei Y, Zhang J, Schiavon CR, He M, Chen L, Shen H,
Zhang Y, Yin Q, Cho Y, Andrade L, Shadel GS, Hepokoski
M, Lei T, et al. SARS-CoV-2 Spike Protein Impairs
Endothelial Function via Downregulation of ACE 2.
Circ Res. 2021; 128:1323–26. https://doi.org/10.1161/
CIRCRESAHA.121.318902. [PubMed]
153. Perico L, Morigi M, Galbusera M, Pezzotta A, Gastoldi S,
Imberti B, Perna A, Ruggenenti P, Donadelli R, Benigni
A, Remuzzi G. SARS-CoV-2 Spike Protein 1 Activates
Microvascular Endothelial Cells and Complement System
Leading to Platelet Aggregation. Front Immunol. 2022;
13:827146. https://doi.org/10.3389/fimmu.2022.827146.
[PubMed]
154. Perico L, Morigi M, Pezzotta A, Locatelli M, Imberti B,
Corna D, Cerullo D, Benigni A, Remuzzi G. SARS-CoV-2
spike protein induces lung endothelial cell dysfunction
and thrombo-inflammation depending on the C3a/C3a
receptor signalling. Sci Rep. 2023; 13:11392. https://doi.
org/10.1038/s41598-023-38382-5. [PubMed]
155. Robles JP, Zamora M, Adan-Castro E, Siqueiros-Marquez
L, Martinez de la Escalera G, Clapp C. The spike protein
of SARS-CoV-2 induces endothelial inflammation through
integrin α5β1 and NF-κB signaling. J Biol Chem. 2022;
298:101695. https://doi.org/10.1016/j.jbc.2022.101695.
[PubMed]
156. Ghazanfari D, Courreges MC, Belinski LE, Hogrell MJ,
Lloyd J, C Bergmeier S, McCall KD, Goetz DJ. Mechanistic
insights into SARS-CoV-2 spike protein induction of the
Oncotarget28
www.oncotarget.com
chemokine CXCL10. Sci Rep. 2024; 14:11179. https://doi.
org/10.1038/s41598-024-61906-6. [PubMed]
157. Gultom M, Lin L, Brandt CB, Milusev A, Despont A,
Shaw J, Döring Y, Luo Y, Rieben R. Sustained Vascular
Inflammatory Effects of SARS-CoV-2 Spike Protein
on Human Endothelial Cells. Inflammation. 2025;
48:2531–47. https://doi.org/10.1007/s10753-024-02208-x.
[PubMed]
158. Li H, Wan L, Liu M, Ma E, Huang L, Yang Y, Li Q, Fang
Y, Li J, Han B, Zhang C, Sun L, Hou X, et al. SARS-CoV-2
spike-induced syncytia are senescent and contribute to
exacerbated heart failure. PLoS Pathog. 2024; 20:e1012291.
https://doi.org/10.1371/journal.ppat.1012291. [PubMed]
159. Jaiswal A, Shrivastav S, Kushwaha HR, Chaturvedi R,
Singh RP. Oncogenic potential of SARS-CoV-2-targeting
hallmarks of cancer pathways. Cell Commun Signal. 2024;
22:447. https://doi.org/10.1186/s12964-024-01818-0.
160. Grand RJ. SARS-CoV-2 and the DNA damage response.
J Gen Virol. 2023; 104:001918. https://doi.org/10.1099/
jgv.0.001918. [PubMed]
161. Kim MJ, Kim JY, Shin JH, Son J, Kang Y, Jeong SK, Kim
DH, Kim KH, Chun E, Lee KY. The SARS-CoV-2 spike
protein induces lung cancer migration and invasion in a
TLR2-dependent manner. Cancer Commun (Lond). 2024;
44:273–77. https://doi.org/10.1002/cac2.12485. [PubMed]
162. Moutal A, Martin LF, Boinon L, Gomez K, Ran D, Zhou
Y, Stratton HJ, Cai S, Luo S, Gonzalez KB, Perez-Miller
S, Patwardhan A, Ibrahim MM, Khanna R. SARS-CoV-2
spike protein co-opts VEGF-A/neuropilin-1 receptor
signaling to induce analgesia. Pain. 2021; 162:243–52.
https://doi.org/10.1097/j.pain.0000000000002097.
[PubMed]
163. Devaux CA, Camoin-Jau L. Molecular Mimicry of the
Viral Spike in the SARS-CoV-2 Vaccine Possibly Triggers
Transient Dysregulation of ACE2, Leading to Vascular and
Coagulation Dysfunction Similar to SARS-CoV-2 Infection.
Viruses. 2023; 15:1045. https://doi.org/10.3390/v15051045.
[PubMed]
164. Zhang S, El-Deiry WS. Transfected SARS-CoV-2 spike
DNA for mammalian cell expression inhibits p53 activation
of p21(WAF1), TRAIL Death Receptor DR5 and MDM2
proteins in cancer cells and increases cancer cell viability
after chemotherapy exposure. Oncotarget. 2024; 15:275–84.
https://doi.org/10.18632/oncotarget.28582. [PubMed]
165. Gioia U, Tavella S, Martínez-Orellana P, Cicio G, Colliva
A, Ceccon M, Cabrini M, Henriques AC, Fumagalli V,
Paldino A, Presot E, Rajasekharan S, Iacomino N, et al.
SARS-CoV-2 infection induces DNA damage, through
CHK1 degradation and impaired 53BP1 recruitment, and
cellular senescence. Nat Cell Biol. 2023; 25:550–64. https://
doi.org/10.1038/s41556-023-01096-x. [PubMed]
166. Tsuji S, Minami S, Hashimoto R, Konishi Y, Suzuki T,
Kondo T, Sasai M, Torii S, Ono C, Shichinohe S, Sato
S, Wakita M, Okumura S, et al. SARS-CoV-2 infection
triggers paracrine senescence and leads to a sustained
senescence-associated inflammatory response. Nat Aging.
2022; 2:115–24. https://doi.org/10.1038/s43587-022-
00170-7. [PubMed]
167. Ogata AF, Cheng CA, Desjardins M, Senussi Y, Sherman
AC, Powell M, Novack L, Von S, Li X, Baden LR, Walt
DR. Circulating Severe Acute Respiratory Syndrome
Coronavirus 2 (SARS-CoV-2) Vaccine Antigen Detected in
the Plasma of mRNA-1273 Vaccine Recipients. Clin Infect
Dis. 2022; 74:715–18. https://doi.org/10.1093/cid/ciab465.
[PubMed]
168. Fertig TE, Chitoiu L, Marta DS, Ionescu VS, Cismasiu VB,
Radu E, Angheluta G, Dobre M, Serbanescu A, Hinescu
ME, Gherghiceanu M. Vaccine mRNA Can Be Detected in
Blood at 15 Days Post-Vaccination. Biomedicines. 2022;
10:1538. https://doi.org/10.3390/biomedicines10071538.
[PubMed]
169. Yamamoto M, Kase M, Sano H, Kamijima R, Sano
S. Persistent varicella zoster virus infection following
mRNA COVID‐19 vaccination was associated with the
presence of encoded spike protein in the lesion. J Allergy
Clin Immunol. 2022; 6:18–23. https://doi.org/10.1002/
cia2.12278.
170. Brogna C, Cristoni S, Marino G, Montano L, Viduto
V, Fabrowski M, Lettieri G, Piscopo M. Detection of
recombinant Spike protein in the blood of individuals
vaccinated against SARS-CoV-2: Possible molecular
mechanisms. Proteomics Clin Appl. 2023; 17:e2300048.
https://doi.org/10.1002/prca.202300048. [PubMed]
171. Chakraborty D, Singh R, Rajmani RS, Kumar S, Ringe
RP, Varadarajan R. Stabilizing Prefusion SARS-CoV-2
Spike by Destabilizing the Postfusion Conformation.
Vaccines (Basel). 2025; 13:315. https://doi.org/10.3390/
vaccines13030315. [PubMed]
172. Rong Z, Mai H, Ebert G, Kapoor S, Puelles VG, Czogalla J,
Hu S, Su J, Prtvar D, Singh I, Schädler J, Delbridge C, Steinke
H, et al. Persistence of spike protein at the skull-meninges-
brain axis may contribute to the neurological sequelae of
COVID-19. Cell Host Microbe. 2024; 32:2112–30.e10.
https://doi.org/10.1016/j.chom.2024.11.007. [PubMed]
173. Report of the WHO Study Group on Cell Substrates for
Production of Biologicals. World Health Organization. 2024.
174. Lenk R, Kleindienst W, Szabó GT, Baiersdörfer M, Boros
G, Keller JM, Mahiny AJ, Vlatkovic I. Understanding
the impact of in vitro transcription byproducts and
contaminants. Front Mol Biosci. 2024; 11:1426129. https://
doi.org/10.3389/fmolb.2024.1426129. [PubMed]
175. Maurisse R, De Semir D, Emamekhoo H, Bedayat B,
Abdolmohammadi A, Parsi H, Gruenert DC. Comparative
transfection of DNA into primary and transformed
mammalian cells from different lineages. BMC Biotechnol.
2010; 10:9. https://doi.org/10.1186/1472-6750-10-9.
[PubMed]
176. Patel MN, Tiwari S, Wang Y, O’Neill S, Wu J, Omo-
Lamai S, Espy C, Chase LS, Majumdar A, Hoffman E,
Shah A, Sárközy A, Katzen J, et al. Enabling non-viral
Oncotarget29
www.oncotarget.com
DNA delivery using lipid nanoparticles co-loaded with
endogenous anti-inflammatory lipids. bioRxiv. 2024.
https://doi.org/10.1101/2024.06.11.598533.
177. Wolff JA, Malone RW, Williams P, Chong W, Acsadi G, Jani
A, Felgner PL. Direct gene transfer into mouse muscle in
vivo. Science. 1990; 247:1465–68. https://doi.org/10.1126/
science.1690918. [PubMed]
178. Acsadi G, Jiao SS, Jani A, Duke D, Williams P, Chong W,
Wolff JA. Direct gene transfer and expression into rat heart
in vivo. New Biol. 1991; 3:71–81. [PubMed]
179. Wang J, Jiao S, Wolff JA, Knechtle SJ. Gene transfer and
expression in rat cardiac transplants. Transplantation. 1992;
53:703–5. [PubMed]
180. (Comirnaty), I. P.-. Residual DNA Characterization Report.
https://www.ghr.agency/wp-content/uploads/2025/08/
comirnaty-residual-dna-characterization-report_en.pdf.
181. Strayer D, Branco F, Zern MA, Yam P, Calarota SA,
Nichols CN, Zaia JA, Rossi J, Li H, Parashar B, Ghosh
S, Chowdhury JR. Durability of transgene expression and
vector integration: recombinant SV40-derived gene therapy
vectors. Mol Ther. 2002; 6:227–37. https://doi.org/10.1006/
mthe.2002.0657. [PubMed]
182. Ndeupen S, Qin Z, Jacobsen S, Bouteau A, Estanbouli H,
Igyártó BZ. The mRNA-LNP platform’s lipid nanoparticle
component used in preclinical vaccine studies is highly
inflammatory. iScience. 2021; 24:103479. https://doi.
org/10.1016/j.isci.2021.103479. [PubMed]
183. Motwani M, Pesiridis S, Fitzgerald KA. DNA sensing by
the cGAS-STING pathway in health and disease. Nat Rev
Genet. 2019; 20:657–74. https://doi.org/10.1038/s41576-
019-0151-1. [PubMed]
184. Kwon J, Bakhoum SF. The Cytosolic DNA-Sensing cGAS-
STING Pathway in Cancer. Cancer Discov. 2020; 10:26–39.
https://doi.org/10.1158/2159-8290.CD-19-0761. [PubMed]
185. Yang H. Establishing acceptable limits of residual DNA.
PDA J Pharm Sci Technol. 2013; 67:155–63. https://doi.
org/10.5731/pdajpst.2013.00910. [PubMed]
186. El-Deiry WS. A pancancer analysis of impact of MDM2/
MDM4 on immune checkpoint blockade ICB. J Clin Oncol.
2022; 40:2630.
187. Arnoff TE, El-Deiry WS. MDM2/MDM4 amplification and
CDKN2A deletion in metastatic melanoma and glioblastoma
multiforme may have implications for targeted therapeutics
and immunotherapy. Am J Cancer Res. 2022; 12:2102–17.
[PubMed]
188. El-Deiry WS, Horowitch B, Lou E, Subbiah V, Carneiro
BA, Safran H, Gokaslan ZL, Sobol RW, Mani SA, Lawler
SE, Chen CC, Wong ET, Kurzrock R, et al. Therapeutic
insights for the aggressive subset of high-grade gliomas
(HGG) driven by chromosome 1q32 MDM4-containing
amplicon and unmethylated MGMT. J Clin Oncol.
2024; 42:2080. https://doi.org/10.1200/JCO.2024.42.16_
suppl.2080.
189. Huntington KE, Louie AD, Lee CG, Elias JA, Ross EA,
El-Deiry WS. Cytokine ranking via mutual information
algorithm correlates cytokine profiles with presenting
disease severity in patients infected with SARS-
CoV-2. Elife. 2021; 10:e64958. https://doi.org/10.7554/
eLife.64958. [PubMed]
190. Park H, Nakamura N, Miyamoto S, Sato Y, Kim KS,
Kitagawa K, Kobashi Y, Tani Y, Shimazu Y, Zhao T,
Nishikawa Y, Omata F, Kawashima M, et al. Longitudinal
antibody titers measured after COVID-19 mRNA
vaccination can identify individuals at risk for subsequent
infection. Sci Transl Med. 2025; 17:eadv4214. https://doi.
org/10.1126/scitranslmed.adv4214. [PubMed]
191. Zhou L, Huntington K, Zhang S, Carlsen L, So EY,
Parker C, Sahin I, Safran H, Kamle S, Lee CM, Geun
Lee C, A Elias J, S Campbell K, et al. MEK inhibitors
reduce cellular expression of ACE2, pERK, pRb while
stimulating NK-mediated cytotoxicity and attenuating
inflammatory cytokines relevant to SARS-CoV-2 infection.
Oncotarget. 2020; 11:4201–23. https://doi.org/10.18632/
oncotarget.27799. [PubMed]
192. Prabhu VV, Morrow S, Rahman Kawakibi A, Zhou
L, Ralff M, Ray J, Jhaveri A, Ferrarini I, Lee Y, Parker
C, Zhang Y, Borsuk R, Chang WI, et al. ONC201 and
imipridones: Anti-cancer compounds with clinical efficacy.
Neoplasia. 2020; 22:725–44. https://doi.org/10.1016/j.
neo.2020.09.005. [PubMed]
193. Strandberg J, Louie A, Lee S, Hahn M, Srinivasan P,
George A, De La Cruz A, Zhang L, Hernandez Borrero L,
Huntington KE, De La Cruz P, Seyhan AA, Koffer PP, et
al. TRAIL agonists rescue mice from radiation-induced
lung, skin, or esophageal injury. J Clin Invest. 2025;
135:e173649. https://doi.org/10.1172/JCI173649. [PubMed]
www.oncotarget.com Oncotarget, Supplementary Materials
SUPPLEMENTARY MATERIALS
COVID vaccination and post-infection cancer signals: Evaluating
patterns and potential biological mechanisms
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Point-by-Point Response to Reviewers
COVID vaccination and post-infection cancer signals: Evaluating
patterns and potential biological mechanisms
We thank the reviewers for their thoughtful, detailed, and constructive evaluation of our manuscript, and appreciate
their recognition of the importance and timeliness of this topic. Below, we provide a point-by-point response and
indicate how the manuscript has been revised or clarified accordingly.
We believe these revisions strengthen the manuscript by sharpening its scope, clarifying its intent as a scoping review,
while also preserving the central scientific motivation.
Reviewer #1
Kuperwasser and El-Deiry
COVID vaccination and post-infection cancer signals: Evaluating patterns and potential biological mechanisms
This review is a well written comprehensive approach to one of the most critical questions on the horizon bridging SARS-
CoV2 infection, and mRNA vaccination across the globe linked to the promotion or initiation of a range of different cancers.
It takes a difficult but first attempt at elucidating many of the underlying complexities that now exist and the critical need to
address this evolving issue in the world after such a difficult and highly disastrous pandemic.
The authors have done a stringently addressed this question based on current literature, which in itself was difficult due to the
lack or searchable indices. I believe it will be important and timely review that will have wide readership in infectious disease
and cancer fields. I have some suggestions to help enhance the overall ease of reading as well as its balance.
1. Some mention should be made about the other major neurological, autoimmune and inflammatory consequences due to the
mRNA vaccine a bit more and state that this will be focused on cancer. It mentions them but does not really help put them in
context. Discuss them early in a paragraph so that the reader have a more complete view of the major problems that are now
being dealt with in the medical field due to vaccination.
We agree and have revised the first paragraph of the Introduction to briefly contextualize the manuscript within
the broader spectrum of post-vaccination neurological, autoimmune, and inflammatory syndromes that have been
reported in the literature, while clearly stating that the present review focuses specifically on oncologic outcomes.
2. Page 7, fix fractions and percentages across the 69 studies with fractions first followed by percentages to be consistent
across the statements.
This has been revised.
3. It may be good to examine the differences in vaccination, infection and both with what differences they may entail on page
10 so that it’s clear that there are key differences in how individuals may respond to each.
We agree that distinguishing responses to vaccination alone, infection alone, and combined exposure is important and
highly relevant. However, the current literature does not provide sufficiently detailed or standardized individual-level
data to support a such a comparison. Most published reports are case-based and lack consistent documentation of
prior infection status, timing relative to vaccination, cumulative exposure, baseline immune status, or relevant clinical
covariates, precluding meaningful stratified analysis.
Accordingly, while we describe vaccination-associated, infection-associated, and combined exposure reports where
available, we feel that attempting to infer differential biological responses across these groups is beyond the scope of
the paper.
We have a comment in the paper about this limitation.
4. Some mechanisms in HHV-8 may lead to bypass of cell cycle arrest during abortive lytic infection and expression of some
lytic antigens including VGPCR (Mesri etal) or Spike induced lytic reactivation.
We thank the reviewer for this important insight.
5. I would suggest to discuss the examples of cancers based on categories in figure 2 with better organization of the figure
panels in figure 3 (separate into groups based on cancer types). It’s a bit difficult to follow as arranged. The table should be
separated out of the figure.
We have reorganized Figure 3 into panels grouped by cancer type (lymphoma, sarcoma, carcinoma, melanoma,
glioblastoma and other) based on categories in figure 2. We have also moved the tabular content into a standalone
table to improve readability. We have also revised the revised text to parallel the grouping of the cancer types.
6. HIV is a major contributor but I don’t believe its accepted as yet that it’s a direct causative agent of cancer. Some thinks
that way and others still have not accepted this as true.
We have revised this to “HIV is strongly associated with Kaposi’s sarcoma, cervical cancer, lymphoma, anal cancer, and
other malignancies, largely though immunosuppression and co-infection with oncogenic viruses.”
7. HCMV has strong evidence in its association with glioblastoma and breast. See the use of ganciclovir for treatment of
glioblastoma in the NEJM paper). The work unproven should be removed and replaced with a more nuanced statement that
geographic and molecular methodological differences across studies have hampered consistency across findings.
We revised the wording to reflect available evidence linking HCMV to glioblastoma and breast cancer.
8. Page 173rd paragraph. I would suggest stating that vaccinations were mandated across many countries limiting unvaccinated
cohorts. This was basically directly linked to the livelihood of many individuals to take a vaccine.
We appreciate (and agree) with the reviewer’s point regarding the impact of vaccine mandates on the availability of
unvaccinated comparison groups. This issue is already addressed conceptually in the manuscript through discussion
of the limited size and representativeness of unvaccinated cohorts and the resulting constraints on epidemiologic
inference. We also agree that widespread vaccination policies influenced cohort composition in many countries,
but our intent was to describe this limitation in neutral methodological terms rather than to expand into policy or
socioeconomic considerations, which fall outside the scope of the present review. We believe the current framing
appropriately captures the relevant study-design implications without detracting from the manuscript’s scientific focus.
9. Page 21, great point, which should also focus on connecting with the known prolonged recovery for many individuals after
vaccinations. Can this be a cytokine storm that existed in these individuals?
It is indeed plausible that immune dysregulation and sustained inflammatory signaling are potential contributors in
some individuals, the current literature does not provide sufficient evidence to conclude that a classical or persistent
cytokine storm underlies these prolonged recovery states, nor to directly link such mechanisms to the oncologic
observations discussed here.
Given the speculative nature of this hypothesis and the absence of consistent mechanistic or longitudinal data
connecting prolonged post-vaccination recovery, cytokine dynamics, and cancer-related outcomes, we chose to limit
the discussion to well-described immune perturbations supported by the existing literature. We believe this approach
maintains appropriate scientific restraint and keeps the manuscript focused on cancer-related observations and
mechanisms directly relevant to the scope of this review.
10. Figure 1, please label the color palates for completeness across the vent diagram. You labeled 6 palates and I could 9 or
maybe 10 color palates. Please also complete in the legend.
Addressed
11. Figure 2, reorganize into panels A, B, C, D as well as the color palates and cancer types across the 4 panels. Two top and
2 bottom. Its organized with wasted space as shown now.
Addressed
12. Figure 3, remove table (panel D) into a separate table. Reorganize this into cancer types and different figures. It will be
easier to navigate as you reorganize the text to match as well.
We appreciate the reviewer’s suggestion to reorganize Figure 3 for navigability. We have done this.
13. Figure 4, Can data be included from other cancers besides the hematologic malignancies? It may make it more complete
if its available.
Figure 4 is the data from the US Armed Forces Health Surveillance Division (AFHSD) report. They only looked at
NHL.
14. Figure 5, include viral antigens from oncogenic viruses that can drive paracrine and other tumor promoting effects...in
the bot I suggest you include VGEF, MMPs, TNF signaling know pathways driving oncogenic activities (place next to the
vessel and tumor)
We thank the reviewer for the suggestion. We already indicated TNFα as well as IL1β and IL6 but have included the
text “viral antigens” and “MMPs” in the revised figure.
Reviewer #2
This scoping review by Kuperwasser and Deiry identified 69 peer-reviewed publications (January 2020-October 2025)
describing cancers temporally associated with COVID-19 vaccination or infection. The evidence base consisted mainly of
333 case-level reports from 27 countries, along with two large population-based cohort studies and one longitudinal cohort
study of U.S. military personnel.
Although the authors frame these findings as hypothesis-generating rather than causal, the review does not adequately account
for multiple key confounding factors. In addition, their analysis lacks the denominators and reference comparisons needed
to estimate risk or incidence. Hence, the claim that the observed temporal patterns are “difficult to attribute to background
incidence alone” is not supported by the data.
We thank Reviewer #2 for their detailed critique and for raising important points regarding epidemiologic
interpretation, confounding, and study design. We agree that the available literature does not permit estimation of
cancer risk or incidence, nor does it allow adjustment for key confounders using denominators or reference populations.
Importantly, however, this manuscript was not designed to estimate risk or to draw causal inferences. Rather, it is a
scoping review intended to systematically assemble, categorize, and contextualize published reports of malignancies
temporally associated with COVID-19 vaccination or SARS-CoV-2 infection, and to outline biologically plausible
mechanisms that could warrant further investigation. We specifically state in the introduction “The goal of this article is
to provide factual information from published literature without bias, and without intent to influence any individual’s choices
regarding vaccines or risk mitigation.”We recognize that case reports and small series are inherently subject to reporting
bias and lack appropriate denominators.
In fact, these issues are explicitly addressed in the Limitations section of the manuscript, where we state that the
predominance of case reports and small series precludes estimation of incidence or relative risk, that observations are
highly susceptible to reporting bias, and that the absence of appropriate control populations limits inference regarding
background rates or causality.
Thus, the intent of this scoping review is not to control for confounding or to estimate population-level risk, but
to catalog and synthesize published reports for early signal detection and hypothesis generation. Accordingly,
all mechanistic interpretations are explicitly described as speculative, and the manuscript states that no causal
relationship has been demonstrated. We believe the existing Limitations section accurately and transparently frames
these constraints but have added the following sentence to the start of the Results section to avoid any confusion “This
scoping review covering the period of January 2020 until April 2025 was not designed to estimate cancer risk or incidence,
nor to draw causal inferences, but rather to systematically assemble, categorize, and contextualize published reports of
malignancies temporally associated with COVID-19 vaccination or SARS-CoV-2 infection.” In addition, we have added the
following statement in the conclusion section: “The goal of this review is not to estimate population-level cancer risk but to
provide a structured synthesis of the existing peer-reviewed literature, identify recurring clinical and biological themes, and
delineate critical gaps that require rigorous epidemiologic and mechanistic follow-up. This will enable a better understanding
of the full spectrum of immune responses to inform safer immunization strategies and illuminate previously underappreciated
links between immunity and cancer biology.”
To address this issue (and the subsequent comments below) we have revised the statement in the introduction to state:
“The goal of this article is to systematically synthesize and contextualize findings from the published literature regarding
malignancies temporally associated with COVID-19 vaccination or SARS-CoV-2 infection, without attempting to estimate
risk, establish causality, or inform individual clinical or vaccination decisions.”
Major Comments:
1. Overall evidence base: The Results section is dominated by counts of case reports and small series (333 patients across 69
publications), but there is no corresponding denominator (e.g., number of vaccinated or infected individuals) or comparison to
expected background cancer incidence. Without such reference rates, these data cannot support any inference about increased
risk.
We agree with this comment, which is why we explicitly state in the conclusion “ The goal is to understand the full
spectrum of immune responses to inform safer immunization strategies and illuminate previously underappreciated
links between immunity and cancer biology.” The goal of this review is not to estimate risk or incidence or provide
denominators as this is beyond the scope of the current literature base. As stated above, we have also revised the
language in the introduction to explicitly frame the manuscript as a scoping review for early signal detection and
hypothesis generation, consistent with established methodologies and does not interpret the evidence nor make claims
as to what they may or may not imply. Nowhere in the manuscript are there claims that vaccination increase risk of
cancer. We have strengthened or added language throughout to avoid any implication of risk quantification.
2. Geographic distribution: The authors state that the broad geographic distribution “indicates that the reported temporal
associations... are not confined to a particular region or healthcare system.” Given global COVID spread and vaccine rollout,
it is expected that cases be reported from multiple countries. Without the proper denominators (e.g., country-level vaccination
rates) or standardized incidence comparisons, the geographic spread primarily reflects patterns of case reporting, not evidence
of a biological signal.
Again, as stated above, geographic distribution of the published literature simply reflects reporting breadth rather than
evidence of differential risk. The intent of this section is to demonstrate that published observations are not confined
to a single healthcare system or region.
3. Exposure types: The breakdown of case reports by vaccine platform is purely descriptive. Counts of reports is not the same
as risk by platform. The author does not compare the fraction of global doses by platform to the fraction of reported cases.
We agree that the vaccine platform breakdown is descriptive only and reflects vaccine availability and uptake rather
than comparative risk. We have added the following language to avoid confusion on this point “This distribution
indicates that the published literature is heavily weighted toward mRNA vaccine platforms, particularly Pfizer-BioNTech
and Moderna, which together account for the vast majority of vaccine-associated reports. This pattern closely mirrors global
vaccination practices where mRNA vaccines were most widely deployed. The relatively smaller representation of adenoviral
vector vaccines and inactivated platforms likely reflects both their more limited use in certain regions and differential
reporting practices, rather than a comparative assessment of biological risk.”
4. Cancer types: The statement that, “... making their temporal clustering around vaccination events unusual and difficult to
attribute to background incidence alone” is not supported by data. Their argument is based primarily on case reports, which
are inherently biased toward unusual reports. Moreover, the authors are counting publications (e.g., 43% of publications
reported lymphoid malignancies) rather than patients, and there is no formal analysis of the time from vaccination/infection to
diagnosis, nor any comparison with reference distributions or expected numbers of cases in specific post-exposure windows.
We have revised the wording of this to emphasize that observations are reported as unusual by the original authors
and are hypothesis-generating, rather than evidence of excess incidence beyond background rates.
5. Timing of onset: The description of latency intervals is purely descriptive and based on a highly selected set of case
reports, which are more likely to be chosen when timing is short. The observed clustering of diagnoses within a few weeks of
vaccination does not in itself provide evidence of causality.
We agree this section is purely descriptive- but was compiled and plotted from data extracted from all of the case
reports that included the information (see data below). Because this was derived from case reports in a qualitative
way, nowhere do we state that the latency intervals and timing between vaccination and diagnosis establishes causality.
Nowhere in this review do we state or establishes causality of cancer from vaccination.
6. Population-level studies: The two retrospective population-level studies are mentioned, but their actual findings (e.g., effect
estimates, cancer types) and extent of confounding control are not summarized. It is difficult to claim “the signal warrants
further prospective evaluation” without supporting evidence.
We agree that additional information and synthesis of the population level studies is needed. We have therefore,
expanded the summary of population-level studies to describe their design, endpoints, and limitations more explicitly,
including confounding control and follow-up duration.
7. For the AFHSD report, the analysis is an ecological time-trend in a specific and highly selected population, and may not
be suitable for drawing individual-level inferences about vaccine-related risk. The review highlights an increase in certain
NHL subtypes, but does not present absolute counts or rates. It does not address alternative explanations such as changes in
diagnostic practices, force composition, or pandemic-related healthcare disruptions.
We agree and do not cite this study to draw individual level inferences about vaccine related risk. This section
explicitly states, “The authors did not analyze or attribute the changes in NHL incidence to vaccination or infection, but the
temporal sequence provides an epidemiologic framework for future comparative analyses.” We agree that these data could
be confounded by diagnostic practices and healthcare disruptions during the pandemic and explicitly discuss this
limitation in the revised manuscript.
8. Related to the comment above, a 2025 meta-analysis clearly documents widespread interruptions in cancer screening,
underscoring the importance of considering this confounder. This could also be true for DoD dataset (figure 4) that the authors
highlight. https://doi.org/10.1038/s43018-024-00880-4
We agree and acknowledge as a limitation.
9. The authors indicate that most of the oncologic effects were associated with vaccination. Could this be due to the inclusion
of REACT19 in their database search?
Yes, the REACT19 database was one of several resources used in our search strategy, and when filtered for “Oncology”
it contains approximately 199 references. Many of the reverences overlap with the peer-reviewed literature identified
through PubMed, Scopus, Web of Science, and Google Scholar but could not be found using conventional searching
on those platforms.
Thus, the rationale for including REACT19 was not to preferentially capture vaccine-associated outcomes, but rather
to address a well-recognized limitation in the discoverability of peer-reviewed publications on SARS-CoV-2 infection,
COVID-19 vaccination, and cancer. As noted in the Methods and Limitations sections, much of the relevant literature
is not consistently indexed with standard Medical Subject Headings (MeSH) or cross-referenced using conventional
oncology or vaccinology search terms. Consequently, reliance on traditional database queries alone fails to retrieve a
substantial portion of the existing peer-reviewed case literature.
We explicitly acknowledge in the manuscript that this reliance on publicly available but incompletely indexed literature
imposes inherent limitations, including potential reporting bias, incomplete capture, and challenges in verification.
We emphasize that this affects both infection- and vaccination-associated reports and reflects structural limitations of
current indexing systems rather than an a priori focus on vaccination. Accordingly, the predominance of vaccination-
associated reports in the assembled literature should be interpreted as descriptive of the published record to date, not
as evidence of differential risk.
Comments on the Methods
1. Aim and estimand: The inclusion criterion of “temporally associated” malignancy after vaccination or infection is reasonable
for collecting case materials, but the methods do not clearly distinguish between (i) describing temporal clustering and clinical
patterns, and (ii) estimating causal effects on cancer incidence or progression.
The manuscript does not seek to estimate causal effects on cancer incidence or progression. Its aim is explicitly
descriptive and hypothesis-generating, consistent with established scoping-review methodologies. We have clearly
stated this at the start of the Results section to avoid any implication of risk quantification and to clearly state that
incidence estimation lies beyond the scope of the available literature.
2. Use of AI-generated summaries: The methods section describes a general Google search that returned an AI-generated
summary stating CDC and NCI statements about vaccine safety. These AI-generated summaries are not curated scientific
databases and can be unreliable. They are more as contextual background rather than as part of the primary evidence base.
The reference to an AI-generated Google summary was included strictly as contextual background to illustrate
prevailing public-health messaging and the contrast with the peer-reviewed literature. These summaries were not
used as data sources, nor were they incorporated into the evidentiary base of the review. All included findings derive
from peer-reviewed publications. We have removed this from the paper.
3. Handling of heterogeneous study designs: The authors list the types of studies included but do not provide an analytic plan
that describes: (i) how studies will be stratified by design, (ii) which designs are considered suitable for estimating risk versus
providing biological plausibility, and (iii) whether any quantitative synthesis of effect measures is planned, and if so, how
heterogeneity will be addressed.
Given the dominance of case reports and small series, no quantitative synthesis or meta-analysis was planned or
performed. Study designs are described and categorized to contextualize evidentiary weight, with population-level
studies clearly distinguished from case-level reports. Only the former are potentially informative for incidence
estimation, and even these are discussed cautiously due to confounding and limited follow-up.
4. Confounding assessment: There is no evaluation of confounding in the included observational studies (e.g., adjustment for
age, sex, comorbidities, prior cancer, immunosuppressive treatment, infection status, calendar time).
Formal confounding adjustment was not feasible or appropriate given the nature of the underlying literature and the
scope of this review. The lack of adjustment for age, comorbidities, prior cancer history, immunosuppression, infection
status, and calendar effects is not relevant and we have described the limitations of this review.
The goal of this review is not to control for confounding or to estimate population-level cancer risk, but to provide
a structured synthesis of the existing peer-reviewed literature, identify recurring clinical and biological themes, and
delineate critical gaps that require rigorous epidemiologic and mechanistic follow-up. We believe the manuscript’s
Methods and Limitations sections accurately and transparently frame these constraints and appropriately limit
inference.
