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Article

Male Sex as a Predictor of Worse Prognosis and Clinical Evolution in Patients with Cancer and SARS-CoV-2 Infection, Independent of the rs41386349 PDCD1 Polymorphism

by
Caroline Yukari Motoori Fernandes
1,
Bruna Karina Banin Hirata
2,
Glauco Akelinghton Freire Vitiello
1,
Eliza Pizarro Castilha
1,
Nathália de Sousa-Pereira
3,
Roberta Losi Guembarovski
4,
Marla Karine Amarante
5,
Maria Angelica Ehara Watanabe
1,
Mateus Nóbrega Aoki
6 and
Karen Brajão de Oliveira
1,*
1
Department of Immunology, Parasitology and General Pathology, Biological Sciences Center, State University of Londrina, Londrina 86057-970, PR, Brazil
2
Department of Basic Health Sciences, State University of Maringá, Maringá 87020-900, PR, Brazil
3
Department of Microbiology, Biological Sciences Center, State University of Londrina, Londrina 86057-970, PR, Brazil
4
Department of Biological Sciences, Biological Sciences Center, State University of Londrina, Londrina 86057-970, PR, Brazil
5
Health Sciences Center, State University of Londrina, Londrina 86039-440, PR, Brazil
6
Carlos Chagas Institute, FIOCRUZ, Curitiba 81350-010, PR, Brazil
*
Author to whom correspondence should be addressed.
COVID 2025, 5(7), 104; https://doi.org/10.3390/covid5070104
Submission received: 7 May 2025 / Revised: 26 June 2025 / Accepted: 3 July 2025 / Published: 4 July 2025
(This article belongs to the Section COVID Clinical Manifestations and Management)
Versions Notes

Abstract

COVID-19 continues to spread six years after its discovery. Cancer patients are at an increased risk of severe outcomes, likely due to immunosuppression and tumor-related dysregulation. Programmed cell death protein 1 (PD-1), encoded by the PDCD1 gene, is a critical immune checkpoint involved in T-cell regulation. Since genetic polymorphisms can influence immune responses and individual susceptibility to SARS-CoV-2 infection, this case–control study aimed to investigate the association between the PDCD1 rs41386349 polymorphism and COVID-19 severity in individuals with and without cancer. This study included 279 COVID-19-positive and 160 negative individuals, genotyped by qPCR. COVID-19- positive cancer patients were significantly more likely to develop moderate (OR = 13.6) and severe (OR > 200) disease compared to cancer-negative individuals. No association was observed between the PDCD1 polymorphism and SARS-CoV-2 infection or disease severity, even after adjusting for cancer status, age and sex. However, age and sex were independently associated with severe outcomes: each additional year of age increased the odds of severe disease by 5.3%, and male patients had a three times higher risk of severe COVID-19. These findings confirm that cancer, male sex and older age are major predictors of worse prognosis in COVID-19, while the rs41386349 polymorphism alone does not appear to influence susceptibility or disease progression.

1. Introduction

Coronavirus Disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by a variant of the coronavirus, which is a member of the Betacoronavirus genus, similar to two other viruses that also caused pandemic diseases: the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV). Currently, several variants of the virus have been identified and classified as variants of concern (VOCs) and variants of interest (VOIs). VOCs exhibit greater transmissibility, virulence, vaccine resistance and/or ability to evade previous means of transmission detection and diagnosis [1]. There are currently five VOCs: the Alpha (B.1.1.7), the Beta (B1.351), the Gamma (P.1), the Delta (B.1.617.2), and the Omicron (B.1.1.529). This is concerning because transmission, virulence, reinfection rates and the ability to evade natural or induced immunity vary among different variants [1,2].
The clinical spectrum of COVID-19 is broad, ranging from mild flu-like symptoms to life-threatening respiratory failure [3]. Infection prevention and control are critical components of patient management. The World Health Organization (WHO) [4] estimates that most people with COVID-19 experience only mild or moderate symptoms (about 40%), approximately 15% develop severe disease requiring oxygen support, while a minority (5%) experience critical illness with complications such as respiratory failure, acute respiratory distress syndrome (ARDS), sepsis, septic shock, thromboembolism and/or multiple organ failure, including acute kidney injury and cardiac injury [5].
Studies have shown that older individuals and those with comorbidities and chronic non-communicable diseases (NCDs), such as diabetes, hypertension and especially cancer (which will be discussed in this article), are associated with more severe cases of COVID-19 [6,7].
The oncology community is under increasing pressure to protect cancer patients and ensure their safety during treatments. Therefore, it is crucial to study this infection in specific populations to understand its associations with different diseases, make inferences and contribute to specific prognoses for these populations. Furthermore, genetic differences contribute to individual variations in the immune response to pathogens and tissues with high receptor expression for SARS-CoV-2 can experience extensive damage [8,9].
The PD-1 gene, PDCD1, has garnered worldwide attention since Nobel laureate Honjo [10], along with other colleagues, first described the PD-1 molecule in 1992 [11]. PD-1, primarily expressed by T lymphocytes, is part of an essential checkpoint in the immune response and may contribute to tumorigenesis when associated with its ligands PD-L1 or PD-L2, expressed by tumor cells. Among several known polymorphisms within PDCD1, the rs41386349 SNP, located in intron 4, stands out due to its position within a runt-related transcription factor 1 (RUNX-1) binding site [12,13]. RUNX-1 has been shown to play an important role in T lymphocyte differentiation [13,14]. Considering the importance of patient genetics and immune responses, genetic polymorphisms at this site may influence the immune response, affecting PD-1 expression and T-cell activation capacity, thereby contributing to individual variations in the immune response to infections and tumors [12].
Given the relevance of this specific genomic region in immune modulation, the rs41386349 polymorphism was selected for analysis as a biologically plausible candidate for contributing to differences in susceptibility or disease progression in SARS-CoV-2 infection, particularly among cancer patients, where immune exhaustion mechanisms are often exacerbated. The role of PD-1 in cancer has been investigated since its discovery, and it is now considered one of the main targets of immunotherapy. In this context, anti-PD-1 antibodies block the recognition site for its ligand, preventing T-cell inactivation and allowing the antitumor response to develop [15].
It has already been described in the literature that individuals with COVID-19 and cancer are more likely to have severe illness and mortality. Given the risk of serious illness, reports characterizing the presentation and outcomes of COVID-19 in cancer patients are of utmost urgency to guide decision- making. This need is especially relevant for patients who are receiving immunotherapy.
In this context, the PD-1, primarily expressed by T lymphocytes, is a crucial checkpoint in the immune response and can contribute to tumorigenesis when associated with its ligands PD-L1 or PD-L2. Understanding genetic polymorphisms in PDCD1 can reveal structural and quantitative changes that influence the immune response, which is particularly relevant for cancer patients who are at higher risk of severe COVID-19. Additionally, the impact of immunotherapy, specifically PD-1 blockade, on COVID-19 outcomes remains uncertain, making it essential to explore these associations to guide treatment decisions and improve prognosis in vulnerable populations [16].
Within this context, this study aimed to analyze the rs41386349 genetic polymorphism in the PDCD1 gene and its potential association with the pathogenesis and prognosis of SARS-CoV-2 infection in patients with and without cancer. We also evaluated the role of sex in disease severity, seeking to understand whether this polymorphism contributes to the immune imbalance observed in male patients with COVID-19.

2. Materials and Methods

2.1. Sample Selection and Characterization

This study was approved by the Institutional Ethics Committee Involving Humans of the State University of Londrina, under CAAE No. 31656420.0.0000.5231 on 27 May 2020, and by the Curitiba Ethics Committee at Erasto Gaertner Hospital, Paraná League for the Fight against Cancer, under CAAE No. 31592620.4.1001.0098 on 18 September 2020. All sample collections and experimental procedures were conducted in accordance with Brazilian guidelines and regulations. The procedures were explained to all participants and written consent was obtained prior to sample collection.
Peripheral blood samples from 27 9 COVID-19-positive individuals were collected. These patients were evaluated for SARS-CoV-2 infection using Real-Time PCR (RT-PCR), based on the protocol established by Corman [17]. Data regarding patients’ symptoms were also collected. Sample collection was carried out between May 2020 and February 2021, prior to the public availability and administration of SARS-CoV-2 vaccines. Therefore, none of the patients included in this analysis had received vaccination against COVID-19.
The characterization of the study population according to COVID-19 status and oncological condition is presented in Table 1. A total of 279 patients tested positive for COVID-19, and they were categorized by disease severity as mild, moderate or severe. Among them, 51 were oncological patients, of whom 38 had solid (non-hematological) tumors and 13 had hematological malignancies. In the non-oncological subgroup (n = 228), patients with no current or previous history of cancer were categorized as follows: 201 mild, 12 moderate and 15 severe cases.
In parallel, 160 individuals tested negative for COVID-19. Among these, 32 had no history of neoplasms, whereas 128 were oncological patients, of whom 39 had hematological neoplasms and 89 had non-hematological tumors.
The criteria for classifying patients in this study followed the systematization established by the WHO [18], which outlines the management of mild, moderate and severe COVID-19 cases. Additionally, the study referenced by Williamson [19] was used, which separately considered hematologic neoplasms from other cancers to account for their immunosuppressive effects. Following the adoption and validation of these criteria, patients were classified based on the severity of their SARS-CoV-2 infection, stratified into those with no history of neoplasms and those with cancer (including non-hematological or hematological malignancies) [19].

2.2. Peripheral Blood and DNA Obtaining

Peripheral blood samples (4–5 mL) were collected using ethylenediamine tetraacetic acid (EDTA) as an anticoagulant. DNA samples were extracted using the Biopur Mini Spin kit (Biometrix Diagnóstica®, Curitiba, PR, Brazil), according to the manufacturer’s instructions. The concentration of DNA was quantified using a NanoDrop 2000c® Spectrophotometer (ThermoScientific, Wilmington, DE, USA) at wavelengths of 260/280 nm to assess purity. The samples were then stored at appropriate temperatures for subsequent molecular analysis.

2.3. PDCD1 Genotyping

The genetic polymorphism analysis was conducted using quantitative polymerase chain reaction (qPCR) with TaqMan fluorescent probes (VIC™ or FAM™) for the PDCD1 gene variant 7209 C > T (rs41386349) located in intron 4.
The amplification reactions were carried out using 2X TaqMan® Genotyping Master Mix (Applied Biosystems, Life Technologies, Carlsbad, CA, USA) stored at 4 °C to 8 °C. This mix contained dNTP, Mg2+, buffer, Taq DNA polymerase and ROX. Additionally, 40X TaqMan® Genotyping Assay (Applied Biosystems) stored at −20 °C was used, which included forward and reverse primers, as well as highly specific hydrolysis (MGB) probes. Ultrapure water was added to the PCR mix along with approximately 1.1 ng/µL of DNA. The fluorescence levels of the PCR products were monitored in real-time using the Step One thermocycler (Applied Biosystems).

2.4. Statistical Analysis

Association analyses for the case–control study were performed by calculating the Odds Ratio (OR). For individual polymorphisms, the following genetic models were tested: genotypic (variant heterozygotes versus wild homozygotes), dominant (variant heterozygotes and homozygotes versus wild homozygotes) and recessive (variant homozygotes versus wild homozygotes and heterozygotes). Association analyses with clinical parameters were performed using the Chi-square test, comparing association models with categorized clinical parameters. Subsequently, Kendall’s Tau-b correlation coefficient was calculated to identify potential correlations between genetic and clinical variables. All statistical analyses were conducted using GraphPad Prism software version 8.0.0 (San Diego, CA, USA) and SPSS Statistics version 17.0 (SPSS Inc., Chicago, IL, USA), with a significance level set at p < 0.05.

3. Results

A descriptive analysis of the study population, stratified by COVID-19 status and cancer diagnosis, is presented in Table 2. Among COVID-19-positive individuals, oncological patients were significantly older (mean age = 63 ± 13 years) than non-oncological patients (mean age = 46 ± 17 years; p < 0.001) and exhibited a markedly higher mortality rate (47.2% vs. 2.6%; p < 0.001). In the COVID-19- negative group, oncological patients also had a higher mean age (56 ± 16 years) compared to non-oncological individuals (52 ± 19 years); however, this difference was not statistically significant (p = 0.273). Mortality was still significantly higher in cancer patients without COVID-19 compared to non-cancer individuals in the same group (28.5% vs. 6.7%; p = 0.012). Regarding sex distribution, no statistically significant differences were observed between males and females across subgroups, although a higher proportion of males was consistently noted in oncological groups.
A comparison of follow-up duration between COVID-19 patients with mild symptoms and those with moderate or severe disease showed that patients with moderate/severe infections had a significantly longer follow-up period (10.97 ± 12.93 days) than those with mild symptoms (2.01 ± 4.55 days), with the difference reaching statistical significance (t = −5.977, df = 84.41, p < 0.001).

3.1. Impact of SARS-CoV-2 Infection and Presence of Neoplasms on Clinical Outcomes

The initial analysis assessed the correlation between SARS-CoV-2 infection and clinical outcomes in cancer patients (n = 51) compared to patients without the infection (n = 128). Cancer patients were 13.6 times more likely to develop moderate COVID-19 (95% CI: 1.688–110.34; p = 0.014) and over 205 times more likely to experience severe disease (95% CI: 40.673–1036.299; p < 0.001) compared to those without neoplasia. These findings highlight a strong and graded relationship between neoplastic disease and infection severity (see Table 3).
In the stratification analysis based on hematological (n = 13) and non-hematological (n = 38) neoplasms with SARS-CoV-2 infection, no difference was observed regarding COVID-19 severity (p = 0.480).
No statistically significant association was found between the PDCD1 rs41386349 polymorphism and the clinical outcomes of discharge or death among the studied patients. Analysis of these endpoints revealed that the presence of the variant allele did not influence the likelihood of either recovery or mortality. These results are consistent across both oncological and non-oncological groups.

3.2. PDCD1 Genetic Polymorphism and Susceptibility to SARS-CoV-2 Infection in Oncological and Non-Oncological Patients

The next step of the study involved conducting a case–control study evaluating the PDCD1 polymorphism in SARS-CoV-2 infection, adjusted for the presence of cancer, age, and sex, but no association was identified (Table 4).

3.3. Analysis of Association Between PDCD1 Genetic Polymorphism with COVID-19 Severity Controlled by Age, Sex, and Cancer Presence

The association between the PDCD1 rs41386349 (C > T) polymorphism and COVID-19 severity was evaluated by stratifying patients into mild, moderate, and severe clinical categories. Given the low frequency of the variant allele in the study population, the analysis was conducted under a dominant genetic model to ensure adequate statistical power. A multivariate analysis was performed, adjusting for the presence of malignant neoplasms, age, and sex. However, no statistically significant association was observed between the PDCD1 polymorphism and disease severity when considering these covariates (Table 5).

3.4. Aggravation of SARS-CoV-2 Infection in Oncological and Non-Oncological Patients Considering Gender and Age

Although the multivariate analysis for the PDCD1 rs41386349 (7209 C > T) polymorphism did not reach statistical significance, sex and age emerged as important independent predictors of COVID-19 severity, even when controlling for the presence of the variant allele.
In the multinomial logistic regression model, age was not significantly associated with moderate COVID-19 severity (OR = 1.021; 95% CI: 0.987–1.055; p = 0.231). However, a significant association was observed for severe cases (OR = 1.053; 95% CI: 1.022–1.085; p = 0.001), indicating that each additional year of age increased the odds of developing severe COVID-19 by approximately 5.3%.
Regarding sex, male individuals had significantly higher odds of severe disease, even after adjusting for age, cancer status, and PDCD1 polymorphism. Specifically, being male increased the likelihood of severe COVID-19 by approximately threefold (OR = 3.032; 95% CI: 1.048–8.769; p = 0.041).

4. Discussion

This study demonstrated that cancer patients affected by SARS-CoV-2 infection experience a significantly worse clinical course compared to non-infected patients. In this context, several studies have highlighted the impact of the COVID-19 pandemic on cancer patients. Ruan [20] demonstrated that, among patients who died from COVID-19, 63% had an underlying disease, predominantly cancer, while 41% of discharged patients did not have such underlying conditions, corroborating findings of increased mortality due to COVID-19 in cancer patients. Similarly, a prospective, observational multicenter study that included 105 cancer patients and 536 cancer-free controls revealed higher death rates, ICU admissions, development of severe or critical symptoms, and a need for mechanical ventilation among cancer patients compared to age-matched controls [21].
It was observed that cancer patients affected by SARS-CoV-2 infection had significantly worse clinical outcomes than non-infected patients. It has been verified that in COVID-19, clinical parameters can range from mild flu symptoms to life-threatening respiratory failure, with an average incubation period of 5–6 days. The duration between infection onset and hospitalization is typically around 7 days, while respiratory deterioration and ICU admission occur approximately 8 and 10 days after infection, respectively [22,23]. Although cancer and non-cancer patients may have similar infection rates, cancer patients are generally considered to be at a heightened risk of severe COVID-19 and mortality [24,25].
Results from Rüthrich [26] remarked that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions. Also, it has been reported that recent cytotoxic therapy may be associated with an increased risk of mortality [27].
Lee [28] reported that patients with hematological malignancies presented an increased susceptibility to viral infections. In this context, it has been demonstrated that patients with COVID-19 showed a differential prognosis depending on the subtype of cancer, where breast cancers have a better prognosis, and hematologic cancers have a lower survival rate. Whereas hormone therapy has been associated with a reduced risk of mortality and low survival in hematologic cancers [29]. However, in our stratified samples for hematologic cancer, we did not find any association with the adopted parameters. In this context, a study with a larger sample size is necessary to assess this association.
Pestana [30] performed a retrospective study of medical records from 24 patients diagnosed with solid cancer and hematological malignancies with respiratory symptoms at Einstein Family Dayan– Daycoval Oncology and Hematology Center (São Paulo, SP, Brazil) in March 2020. Only three cases of COVID-19 occurred in patients with hematologic malignancies, none of which were under active treatment. This highlights the need for further studies to assess SARS-CoV-2 infection in patients with both solid and hematological malignancies presenting respiratory symptoms, considering the evolving landscape of the current pandemic.
In patients with COVID-19, the CD8+ T-cell population undergoes qualitative and quantitative changes. In addition, a few studies have reported a depleted CD8+ T-cell phenotype in severe disease, with increased expression of inhibitory receptors, particularly PD-1 [31,32,33,34]. However, it remains unclear whether PD-1+ CD8+ T-cells are actually depleted or activated in patients with COVID-19 [35].
Wang [36] showed that the occurrence of the C allele is correlated with a decrease in PD-1 expression. However, Mostowska [37] and Zheng [38] observed that the T allele was predominant in patients with Systemic Lupus Erythematosus (SLE) and viral infections, respectively, leading to the hypothesis that the T allele causes lower transcriptional activity of PD-1 in human T-cells. Such divergence observed in the occurrence of different alleles may be related to population variations, which may or may not be related to autoimmune diseases [39,40] and various types of cancer [41].
No significant association was found between allelic variants of the PDCD1 polymorphism and susceptibility to SARS-CoV-2 infection. Likewise, the analysis of COVID-19 severity—categorized as mild, moderate, or severe—revealed no statistically significant differences between genotype groups. These findings remained consistent even after adjusting for sex, age, and cancer status.
Some studies have investigated the occurrence and correlation of PD-1 blockade on COVID-19 severity in cancer patients, but overall, there was no significant difference in severity regardless of exposure to PD-1 blockade [16]. According to Moore [42], PD-1 blockade could increase the overactive immune phase of COVID-19 and lead to a worse clinical outcome of the results. Alternatively, blocking PD-1 would lead to an improvement in infection outcomes by increasing immune control of viral infections [43]. However, in our study, we did not obtain clinical data about chemotherapy treatments and the cancer stages of patients.
In the regression analysis assessing COVID-19 severity among both oncological and non-oncological COVID-19-positive patients, male sex emerged as a significant independent predictor of disease worsening. Sexual dimorphism in COVID-19 is not new, as men and women tend to respond differently to viral infections [42,44,45]. In this context, it is suggested that the higher morbidity and lethality associated with males is a multifactorial phenomenon, influenced by both biological sex variations, chromosomal and sex steroid variations, and specific risk habits related to sex, such as smoking, alcoholism, and a higher prevalence of comorbidities among men [46,47,48].
Studies have already shown that SARS-CoV-2 primarily binds to host cells via angiotensin-converting enzyme 2 (ACE2), which is widely expressed in various human tissues. In the respiratory system, it is distributed mainly in the nasosinusal cavity regions and on the surface of type II alveolar cells, in which human transmembrane serine protease II (TMPRSS2), a cofactor for virus entry, is also localized [49,50]. The expression of ACE2 is a risk factor for COVID-19 infection [51], already identified in pathological findings of tissues affected by the infection [52]. Interestingly, Bao [53] observed that male patients have higher pulmonary ACE2 expression, which may partially explain the increased severity of COVID-19 in men compared to women.
Androgens, such as testosterone and dihydrotestosterone, are steroid hormones produced by both sexes, but present at higher levels in men, and hypothesized to contribute to COVID-19 pathogenesis [54,55]. Circulating androgens bind to androgen receptors and promote their activation, which, in turn, regulates TMPRSS2, a critical cofactor for virus entry, and may increase its transcription. Consequently, a greater number of host cells become susceptible to virus infection and entry [56].
Sex differences in immune response also play a significant role in COVID-19 severity. According to Bienvenu [57], many immune-related genes are located on the X chromosome, including those involved in the assembly of innate and adaptive immune responses against viral infections, for example, pattern recognition receptors (e.g., TLR7), costimulatory molecules, and transcription factors [58,59]. It is suggested that antiviral responses and viral clearance, mediated by the high expression of Toll Like 7 receptors (TLR7) and subsequent increased production of type I IFN, occur more robustly in women and may be one of the mechanisms that justify the lower susceptibility to severe COVID-19 among women compared to men [57,60,61,62].
Recent genetic studies have further reinforced this hypothesis. Asano et al. [63] identified rare, deleterious X-linked TLR7 variants in young male patients with critical COVID-19 pneumonia, revealing a penetrant monogenic etiology in about 1.8% of severe male cases. These variants impair TLR7-mediated IFN production by plasmacytoid dendritic cells, compromising early antiviral defense mechanisms. Additionally, Martínez-Gómez et al. [64] reported that the ACE2 rs2285666 TT genotype was associated with critical illness and oxygen supplementation needs, particularly in males, suggesting that this polymorphism contributes to disease severity regardless of age or comorbidities.
Takahashi et al. [65] evaluated the differences in the immune response to COVID-19 between genders and found that female patients had more CD4+ and CD3+ monocytes, mature T-cells, and differentiated CD8+ T lymphocytes, while male patients had a poor CD8+ T lymphocyte response during disease progression. Additionally, female patients exhibited greater innate cytokine activity, which may enhance early immune control of the virus. The higher prevalence of dendritic cells in women, linked to both hormonal and genetic factors, may also contribute to their superior antiviral response [66,67].
Collectively, these findings underscore the multifactorial nature of sex-based differences in COVID-19 outcomes. They also support our observation that male sex is associated with worse clinical evolution in COVID-19, independent of the PDCD1 rs41386349 polymorphism evaluated in our study.
While our study was not designed to comprehensively capture all factors involved in the immunogenetic regulation of COVID-19 severity, its focus on the PDCD1 rs41386349 polymorphism was intentional and hypothesis-driven, based on its relevance to immune checkpoint control in cancer and viral infections. We acknowledge that broader genetic screening or functional assays—such as PD-1 expression profiling or T-cell functional analysis—could have enriched the mechanistic understanding of our findings. We also address the absence of detailed clinical data regarding cancer stage and treatment status, such as chemotherapy or immunotherapy, which limits the interpretation of outcomes among cancer patients; however, we emphasize that this study was conducted during the early stages of the COVID-19 pandemic, under significant logistical and biosafety constraints, which limited the feasibility of more complex sample processing. Despite this, the study presents several strengths. It addresses a highly vulnerable population: cancer patients infected with SARS-CoV-2 with laboratory-confirmed diagnoses. All individuals were unvaccinated, eliminating a major confounding factor and allowing for a more homogeneous analysis of host genetic influence on clinical outcomes. The inclusion of multivariate models adjusted for age, sex, and cancer presence strengthens the robustness of our findings. Taken together, the study provides a valuable contribution by highlighting male sex and age as independent predictors of severe outcomes and by exploring the role of a key immune-regulatory polymorphism in a uniquely vulnerable population.

5. Conclusions

Finally, this study demonstrated that cancer patients infected with SARS-CoV-2 experienced a significantly more severe clinical course of COVID-19. Despite the established role of PD-1 in immune regulation, the PDCD1 rs41386349 polymorphism was not associated with susceptibility to SARS-CoV-2 infection or with clinical worsening of COVID-19 in either oncological or non-oncological patients. Multivariate analysis highlighted age and male sex as independent predictors of severe disease, with male patients showing approximately threefold increased risk of severe outcomes. These findings underscore the importance of considering sex-specific immune responses and suggest that, although no direct genetic association with PDCD1 has been identified, immune checkpoint regulation is multifactorial and may be influenced by a complex interplay of genetic, hormonal, and environmental factors. Further studies are needed to explore additional polymorphisms and immunoregulatory mechanisms involved in COVID-19 severity.

Author Contributions

Conceptualization, M.K.A., M.A.E.W. and K.B.d.O.; Data curation, B.K.B.H. and G.A.F.V.; Formal analysis, C.Y.M.F.; Funding acquisition, M.A.E.W. and K.B.d.O.; Investigation, C.Y.M.F.; Methodology, C.Y.M.F. and M.N.A.; Project administration, M.A.E.W., M.N.A. and K.B.d.O.; Supervision, M.A.E.W. and K.B.d.O.; Validation, N.d.S.-P.; Writing—original draft, C.Y.M.F.; Writing—review and editing , E.P.C., R.L.G. and M.K.A. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.

Institutional Review Board Statement

This study was approved by the Institutional Ethics Committee Involving Humans of the State University of Londrina, under CAAE No. 31656420.0.0000.5231 on 27 May 2020, and by the Curitiba Ethics Committee at Erasto Gaertner Hospital, Paraná League for the Fight against Cancer, under CAAE No. 31592620.4.1001.0098 on 18 September 2020. All sample collections and experimental procedures were conducted in accordance with Brazilian guidelines and regulations.

Informed Consent Statement

Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The original data supporting reported results have been placed in a repository and are openly available at https://doi.org/10.2807/1560-7917.ES.2020.25.3.2000045.

Acknowledgments

This work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Londrina State University Coordination for Post-Graduation (PROPPG-UEL). The authors wish to express their gratitude to Fundação Araucária do Paraná and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

COVID-19Coronavirus Disease 2019
SARS-CoV-2Severe Acute Respiratory Syndrome Coronavirus 2
PD-1Programmed Cell Death Protein 1
PDCD1Programmed Cell Death 1
qPCRQuantitative Polymerase Chain Reaction
RT-PCRReal-Time Polymerase Chain Reaction
SNPSingle Nucleotide Polymorphism
VOCsVariants of Concern
VOIsVariants of Interest
NCDsNon-Communicable Diseases
ARDSAcute Respiratory Distress Syndrome
OROdds Ratio
CIConfidence Interval
nNumber of subjects
CANCER+Cancer patients
CANCER-Non-cancer patients
COVID+Positive for COVID-19
COVID-Negative for COVID-19
CTCytotoxic T-cells
TTHomozygous for the T allele
CCHomozygous for the C allele
CTCytotoxic T-cells
Tau-bKendall’s Tau-b Correlation Coefficient
ICUIntensive Care Unit
TLR7Toll-Like Receptor 7
EDTAEthylenediamine Tetraacetic Acid

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Table 1. Characterization of the study population according to COVID-19 severity and oncological condition. COVID+: Positive samples for the Real-Time PCR test; COVID-: Negative samples for the Real-Time PCR test; n: number of individuals from a population; Mild, Moderate, and Severe: clinical severity classifications of COVID-19 infection., Hematological neoplasms: hematologic malignancies; Non-hematological neoplasms: solid tumors or non-hematologic cancers.
Table 1. Characterization of the study population according to COVID-19 severity and oncological condition. COVID+: Positive samples for the Real-Time PCR test; COVID-: Negative samples for the Real-Time PCR test; n: number of individuals from a population; Mild, Moderate, and Severe: clinical severity classifications of COVID-19 infection., Hematological neoplasms: hematologic malignancies; Non-hematological neoplasms: solid tumors or non-hematologic cancers.
COVID-19 POSITIVE
(n = 279)		COVID-19 NEGATIVE
(n = 160)
MildModerateSevere
Non-Oncological (n = 260)201121532
Oncological
(n = 179)		Hematological
Neoplasms
(n = 52)		001339
Non-Hematological
Neoplasms
(n = 127)		033589
Table 2. General characteristics of individuals recruited in the study, stratified by COVID-19 status and oncologic condition.
Table 2. General characteristics of individuals recruited in the study, stratified by COVID-19 status and oncologic condition.
GroupFemale
n (%)		Male
n (%)		Total
n		p (Sex)Mean Age (±SD)Discharge
n (%)		Death
n (%)		p (Prognosis)
COVID
negative		Non-oncologic14 (43.8)18 (56.2)320.52452 ± 1928 (93.3)2 (6.7)0.012
Oncologic47 (37.6)78 (62.4)12556 ± 1688 (71.5)35 (28.5)
COVID
positive		Non-oncologic111 (56.3)86 (43.7)1970.15146 ± 17221 (97.4)6 (2.6)<0.001
Oncologic23 (45.1)28 (54.9)5163 ± 1328 (52.8)25 (47.2)
Total195210405––36568–
For each group, the number of female and male participants, total sample size, mean age with standard deviation (SD), and clinical outcomes (number and percentage of discharges and deaths) are presented. Pearson’s Chi-square test (χ2) results are presented for associations between sex and prognosis within non-oncologic subgroups. The significance level adopted was p < 0.05 (SPSS 17.0 Inc., Chicago, IL, USA).
Table 3. Association between the presence of neoplasia and COVID-19 severity in cancer patients.
Table 3. Association between the presence of neoplasia and COVID-19 severity in cancer patients.
COVID-19 SeverityOR95% CIp Value *
Moderate vs. Mild13.61.688–110.340.017
Severe vs. Mild218.544.479–1073.945 <0.001
OR: Odds R atio; CI: c onfidence interval. * The significance level adopted was p < 0.05 (SPSS 17.0 Inc., Chicago, IL, USA).
Table 4. Case–control association study between the PDCD1 7209 C > T genetic polymorphism and SARS-CoV-2 infection between groups of COVID+/COVID-, controlled for age, sex, and cancer presence.
Table 4. Case–control association study between the PDCD1 7209 C > T genetic polymorphism and SARS-CoV-2 infection between groups of COVID+/COVID-, controlled for age, sex, and cancer presence.
7209 C > T GenotypeCOVID+ (n = 267)
n (%)		COVID-
(n = 160)
n (%)		ORAdjCIAdj 95%pAdj Value
CC217 (81.3)124 (77.5)------
CT46 (17.2)35 (21.9)0.8190.459–1.4620.500
TT4 (1.5)1 (0.6)2.3220.191–28.2620.509
CT + TT50 (18.7)36 (22.5)0.8590.486–1.5170.600
OR: Odds Ratio; CI: confidence interval. Adj = adjusted for age, sex, and cancer presence.
Table 5. Multivariate analysis of the 7209 C > T genetic polymorphism and COVID-19 severity, controlled for malignant neoplasms presence, age, and sex.
Table 5. Multivariate analysis of the 7209 C > T genetic polymorphism and COVID-19 severity, controlled for malignant neoplasms presence, age, and sex.
COVID SEVERITY7209 C > T GenotypeORAdjCIAdj 95%pAdj Value
ModerateCC------
CT + TT1.4290.365–5.5920.608
SevereCC------
CT + TT1.6840.478–5.9340.417
Mild severity was considered the reference. OR: Odds Ratio; CI: confidence interval. Adj = adjusted for age, sex, and cancer presence.
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Fernandes, C.Y.M.; Hirata, B.K.B.; Vitiello, G.A.F.; Castilha, E.P.; de Sousa-Pereira, N.; Guembarovski, R.L.; Amarante, M.K.; Watanabe, M.A.E.; Aoki, M.N.; de Oliveira, K.B. Male Sex as a Predictor of Worse Prognosis and Clinical Evolution in Patients with Cancer and SARS-CoV-2 Infection, Independent of the rs41386349 PDCD1 Polymorphism. COVID 2025, 5, 104. https://doi.org/10.3390/covid5070104

AMA Style

Fernandes CYM, Hirata BKB, Vitiello GAF, Castilha EP, de Sousa-Pereira N, Guembarovski RL, Amarante MK, Watanabe MAE, Aoki MN, de Oliveira KB. Male Sex as a Predictor of Worse Prognosis and Clinical Evolution in Patients with Cancer and SARS-CoV-2 Infection, Independent of the rs41386349 PDCD1 Polymorphism. COVID. 2025; 5(7):104. https://doi.org/10.3390/covid5070104

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Fernandes, Caroline Yukari Motoori, Bruna Karina Banin Hirata, Glauco Akelinghton Freire Vitiello, Eliza Pizarro Castilha, Nathália de Sousa-Pereira, Roberta Losi Guembarovski, Marla Karine Amarante, Maria Angelica Ehara Watanabe, Mateus Nóbrega Aoki, and Karen Brajão de Oliveira. 2025. "Male Sex as a Predictor of Worse Prognosis and Clinical Evolution in Patients with Cancer and SARS-CoV-2 Infection, Independent of the rs41386349 PDCD1 Polymorphism" COVID 5, no. 7: 104. https://doi.org/10.3390/covid5070104

APA Style

Fernandes, C. Y. M., Hirata, B. K. B., Vitiello, G. A. F., Castilha, E. P., de Sousa-Pereira, N., Guembarovski, R. L., Amarante, M. K., Watanabe, M. A. E., Aoki, M. N., & de Oliveira, K. B. (2025). Male Sex as a Predictor of Worse Prognosis and Clinical Evolution in Patients with Cancer and SARS-CoV-2 Infection, Independent of the rs41386349 PDCD1 Polymorphism. COVID, 5(7), 104. https://doi.org/10.3390/covid5070104

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