Cancer and COVID-19: A review of immune insights and partnerships to inform public health strategy.

Introduction

Respiratory viral infections in people with cancer: a major concern for cancer patients
Infectious diseases are a serious concern in cancer clinics, with a mortality rate up to three times as high in people with cancer compared to healthy populations [1,2]. Respiratory viral infections (RVIs) pose a particular threat due to their high transmissibility and have been associated with rapid in-hospital spread in hematology and transplant hospital units. Studies have shown that RVIs can result in progression from upper to lower respiratory infections (LRI) and pneumonia in as many as 35% of CRT-diagnosed hematopoietic cell transplant and hematologic malignancy patients, and that pneumonia and influenza make up ∼45.9% of mortal infection cases in patients with cancer [3]. Other studies have also identified pneumonia as a particular hazard to patients with metastatic disease and/or recent cancer diagnosis [2,4]. These respiratory infections are often attributed to common viruses such as Influenza, Respiratory Syncytial Virus, Parainfluenza, metapneumovirus, and more recently SARS-CoV-2. Meanwhile, studies are showing that patients with cancer who contract SARS-CoV-2 infection and COVID-19 present with even worse outcomes and higher death rates compared to patients with cancer who contract influenza [5] or to healthy patients who contract COVID-19 [6,7].

COVID-19 in people with cancer

Acute infection and outcomes
Studies show that immunocompromised patients have high rates of hospitalization, poor outcomes, and protracted SARS-CoV-2 infections [6,7]. Patients with cancer have also been demonstrated to have a high risk of developing severe COVID-19 and COVID-19-related mortality compared to otherwise healthy patients hospitalized for COVID-19 [8,9] (Table 1). In addition, patients with hematological malignancies may also have an increased risk of Intensive Care Unit (ICU) admission and ventilation compared to those with solid cancer [10]. Among patients with solid cancer who developed COVID-19, those with skin and gastrointestinal (GI) cancers exhibited lower 30-day survival compared to patients with breast cancer. Skin, GI, and prostate cancers showed lower 90-day survival relative to breast cancer [9]. Cancer severity also appears to play a role, as patients with “active and progressing” or “metastatic” cancers demonstrate two to five times the risk of 30-day mortality compared to patients in remission [8,11,12]. Meanwhile, cancer treatments can have significant effects on COVID-19 outcomes (Table 2): chemotherapy or surgery may be significantly associated with a higher risk of ICU admission and mortality (although Lee et al. [13] reports chemotherapy to have no significant effects), while Immune Checkpoint Inhibitors (ICI) appear to either decrease severe outcomes or have little effect. Interestingly, hormonal or endocrine-based therapies may be associated with more positive outcomes [9,12]. The variable and sometimes controversial results for therapies such as radiation and targeted cancer therapies may be due, in part, to the many different types of therapies included in these categories (Table 2). Other risk factors for severe outcomes in patients with cancer include increased age, male sex-at-birth, comorbidities, and lymphopenia [9,11]. Results on these associations vary in the literature [12–14], therefore, larger, carefully designed studies are still needed to fully understand the relationships between these risk factors and COVID-19 outcomes.

Long-term implications
There are few available options for treating COVID-19 in people with cancer, and cancer treatment cannot be compromised to treat SARS-CoV-2 infection. Remdesivir has been approved for the treatment of patients hospitalized with COVID-19 [15], and monoclonal antibodies, such as pemivibart (Pemgarda), may be considered for pre-exposure prophylaxis caused by susceptible SARS-CoV-2 variants like JN.1 for immunocompromised patients [16]. However, the effectiveness of these therapies in people with cancer, as well as how long they remain effective against currently circulating variants, continues to be under investigation. Meanwhile, as acute infections proceed without effective treatment, the risks of severe disease and long-term effects become higher.
COVID-19 in people with cancer has effects beyond the duration of acute disease. Studies from the NIH Researching COVID to Enhance Recovery (RECOVER) electronic health records (EHR) cohorts reported that cancer was likely to be associated with increased risk of developing Long COVID [17], which is a recognized disability-causing condition that affects multiple organ systems. This finding is supported by other studies, such as one that reported Postacute Sequelae of COVID (PASC) symptoms in more than half of the cancer patients in their cohort (particularly in female patients) [18]. These patients can also present with prolonged viral shedding long after resolution of symptoms, raising concerns for ongoing transmissibility and increased viral evolution that can lead to new infectious variants [19].

Protecting people with cancer from the effects of COVID-19

Vaccination
Prevention of infection with SARS-CoV-2 is extremely important to protect people with cancer who face heightened risks of severe illness and complications. Currently, the most effective method of infection prevention is immunization with available anti-COVID-19 vaccines. Large cohort studies have shown that vaccination improves outcomes in patients with cancer, with breakthrough infection, hospitalization, ICU and mechanical ventilation, and 30-day mortality rates decreasing with vaccine dose [20]. Rates of positive antibody responses significantly increase after two doses of vaccine, and binding and neutralizing levels augment after the third and additional doses [21,22]. T-cell cytokine response rates significantly increase with dosage number, and T cell responses reach measurable levels in ∼60–78% of patients with solid cancer after partial or complete primary vaccination [21,23]. Meanwhile, patients with multiple myeloma (MM) demonstrate higher specific CD8+ T cell responses post-vaccination (although patients with chronic lymphocytic leukemia (CLL) show no specific T-cell improvement post-vaccination) [22]. Overall, although vaccination is associated with improved responses and outcomes among patients with cancer, there is a more profound benefit for patients who received three or more vaccine doses [20]. However, studies have shown that people with cancer do not achieve the same levels of benefit compared to the healthy population, even with higher numbers of doses (Table 3).
Research has shown that patients with cancer not only have a poorer vaccine response than the general population, but that their responses to COVID-19 vaccination vary depending on cancer and treatment type. Among vaccinated patients, those with hematological malignancies or active cancers are more likely to experience hospitalization, admission to ICU, and mortality compared to patients with solid cancers or cancers in remission [10]. In addition, patients with hematological cancers, even with boosters, tend to have lower rates of seroconversion or antibody responses to vaccination compared to those with solid cancer [24].
Emerging evidence indicates that patients who have received recent anti-cancer therapy have compromised responses to COVID-19 vaccination, with lower rates of seropositivity or antibody responses and lower antibody levels than those without recent treatment [25]. Recent anti-cancer therapy can affect the risk of hospitalization and death post-vaccination. Patients receiving immunosuppressants have a high risk of breakthrough infection, and those with recent anti-CD20 or anti-CD38 treatments are significantly more likely to have poor antibody responses to vaccination than those receiving no such therapy [25–28]. Patients receiving immunomodulatory therapy demonstrate a higher risk of breakthrough infections and lower antibody levels until the third vaccination with levels that are still significantly lower compared to untreated patients [26,28]. (ICI treatments, meanwhile, are associated with a lower risk of breakthrough infections and higher seroconversion rates after a second vaccine dose compared to chemotherapy [28]. Recent bone marrow or hematopoietic stem cell transplant recipients have shown impaired antibody increases, lower seropositivity rates, and a high risk of breakthrough infection post-vaccination [27,28].

Better understanding is key
A comprehensive understanding of vaccine immune responses and development of optimization approaches will be extremely important for protecting people with cancer or immunocompromising conditions as variants emerge. Consequently, carefully designed studies using validated and standardized assays to measure humoral and cellular immunity to SARS-CoV-2 infection are still needed (Table 4).

Assessing humoral immunity
Neutralizing antibody titers and binding antibody levels are known to correlate with protection against severe COVID-19 disease. Although booster doses restore immune protection, circulating antibody levels and vaccine effectiveness are temporary and decline over time [29]. Real-world evidence highlights the importance of timely booster administration in cancer populations, with those up to date on vaccination showing significantly reduced risks of hospitalization and death during the Omicron waves [30]. In addition, individuals with cancer, especially those with hematological cancers, have exhibited poorer responses to both the primary series and booster vaccinations compared to non-cancer populations [28,31]. These variations in antibody responses are believed to be correlated with effective immunity against severe COVID-19 and consequently are of interest to those looking to optimize vaccine efficacy in these populations.
Most studies of SARS-CoV-2 vaccine responses utilize binding assays such as enzyme-linked immunosorbent assays (ELISAs), which measure total antibody levels regardless of neutralizing activity. However, measurements obtained from these assays may not fully reflect protection against the latest variants, as viral mutations enable SARS-CoV-2 variants to evade the immune response. Understanding neutralizing antibodies is crucial for defining a possible correlate of protection for SARS-CoV-2, requiring comparison of large immunological datasets from different clinical trials using validated assays. However, differences in assays, target antigens, numerical readouts, and endpoints have rendered such studies difficult [32]. In addition, neutralization assays are time-consuming, labor-intensive, expensive, and significantly variable when compared to ELISAs. The live-virus neutralization assays (the gold standard for detecting neutralizing antibodies) require Biosafety Level 3 laboratory conditions, limiting assay access and high-throughput screenings [33]. Alternatively, pseudovirus-based virus neutralization assays (PBNAs) for SARS-CoV-2 are higher-throughput and can be used in Biosafety Level 2 laboratories; however, their cell-based nature also results in high cost and variability [33]. This variability could be minimized through assay validation and data harmonization against the World Health Organization International Standard (WHO IS) for anti-SARS-CoV-2 immunoglobulin or the US Serology Standard to express results in international units [32].

Assessing cellular immunity

T cell responses in cancer
T cells, which can be resident in mucosal and barrier sites as well as in the blood and lymphatic systems, also play a role in the body’s defense against viral respiratory infections. Studies have indicated that T cell responses, in combination with neutralizing antibodies and memory B cell responses, contribute to protection against symptomatic SARS-CoV-2 infection [34]. Some data also attribute the increased resistance to severe COVID-19 seen in children compared to adults to the presence of tissue-resident T cells in the upper airway, providing a local adaptive defense that can synergize with innate responses to prevent progression to severe disease [35,36].
T cells recognize not only spike antigens targeted by neutralizing antibodies, but also more conserved, less-mutating structural and non-structural epitopes such as nucleocapsid, membrane, ORF3a and RNA polymerase [37]. Longitudinal studies reported that virus-specific T cell responses may remain detectable even in individuals who have lost neutralizing antibody activity at 12 months post-infection [38]. In addition, these T cell responses could persist up to 20 months post-infection and retain cross-reactivity to variants of concern [38]. Meanwhile, robust T cell responses could provide protection in the absence of antibodies in immunocompromised individuals. For instance, individuals with CLL could have negligible antibody levels yet still retain functional T cell immune responses [39]. Another study further indicated that CLL patients who retained functional CD4+ T cell memory responses experienced significantly milder COVID-19 infections [40]. These findings suggest that broad and functional T cell immunity may provide long-term protection, especially in immunocompromised populations.
There is increasing evidence that the potency of T cell-based adaptive responses and ultimately the efficacy of SARS-CoV-2 vaccines in protecting against the severity of disease and mortality vary by the cancer type, particularly between hematologic and solid cancers. While patients with solid cancers exhibit, in general, lower seroconversion rates compared to healthy individuals (depending on certain risk factors, e.g., treatment status, solid cancer subtype and age), they generally have better clinical outcomes following SARS-CoV-2 vaccination than those with hematologic cancers [10,23]. This disparity could result in part from the depletion of particular immune cell populations in hematologic malignancies, although further studies are needed to substantiate these observations.
Conversely, patients undergoing cancer immunotherapy, such as with ICIs may show unexpectedly high immune responses after SARS-CoV-2 vaccination, while patients undergoing chemotherapy not associated with stimulating immunity did not [41]. This observation aligns with the role of T cell exhaustion in prolonged viral infections and cancer progression, a pathway targeted by ICIs, and highlights the convergence of antiviral vaccination and cancer immunotherapy in enhancing T cell-mediated immunity. Emerging evidence indicates that SARS-CoV-2 mRNA vaccination administered prior to or during ICI therapy may contribute to enhanced immune response [42]. However, this effect cannot be generalized across all cancer types, as ICI therapy is administered only to certain subsets of patients. Future studies are needed for a better understanding of associations between immunotherapy and vaccine-induced immunity.

Measuring and standardizing T cell assays
To quantify functional immune memory, cellular assays are needed. Cellular immunity assessment for SARS-CoV-2 relies on diverse methodologies, each with distinct advantages and limitations. Enzyme-linked immunospot (ELISPOT) assays offer high sensitivity for detecting IFN-γ -secreting T cells but under-represent the total SARS-CoV-2-specific repertoire, as approximately 49% of antigen-responsive spot-forming units do not express IFNγ but instead express other cytokines, such as IL-2 and TNFα alone or in combination [43]. Interferon-gamma release assays (IGRAs), including QuantiFERON and Covi-FERON, provide automated, scalable platforms for detecting Th1 type responses. MHC multimer staining enables direct detection of epitope-specific T cells; however, this approach can miss functional T cells with low-affinity receptors and is restricted by HLA diversity. Emerging approaches like qPCR-based T cell activation tests (qTACT) quantify activation transcripts (IFNγ, CXCL10) for population-level monitoring but lack single-cell resolution required for researching clinical context (e.g., CD4 and CD8 subsets) [44].
Activation-Induced Marker (AIM) assays overcome these limitations by detecting upregulated surface markers (e.g., CD69+CD137+ for CD8+, OX40L+CD25+ for CD4+) with rapid antigen exposure, preserving native phenotypes and capturing antigen-specific T cells without the need for pre-determined epitopes or HLA types [43]. When using SARS-CoV-2 spike peptides alongside non-spike peptides, AIM assays can differentiate vaccine-induced from infection-induced T cell responses. AIM assays can be combined with intracellular cytokine staining (ICS) in the same sample, enabling detailed flow cytometric analysis of cytokine profiles (e.g., IFNγ, TNFα, IL-2) of different T cell subsets. AIM assay uniquely enables the resolving of naïve, central memory, effector memory, and “Terminally-differentiated Effector Memory T cells Re-expressing CD45RA” (TEMRA) cells in both CD4 and CD8 T cell populations [45]. This multidimensional capability makes AIM assays a powerful tool for evaluating vaccine immunogenicity and tracking immune response durability. While ELISPOT and IGRAs remain the most used assays in clinical studies, AIM assays (combined with ICS) when validated and standardized for clinical use can provide unparalleled breadth by capturing polyfunctional responses, making them vital in vaccine immunogenicity studies and long-term immunity monitoring across diverse populations.
As more studies adopt antigen-specific approaches such as AIM assays to investigate the interplay between SARS-CoV-2 vaccination and cancer immunity, these efforts can help determine optimal dosing strategies and scheduling for cancer patients receiving immunotherapy. Gaining such insights depends on the accurate and reproducible measurement of T cell responses. However, every step involved in measuring participant T cells, from sample collection to data analysis, can contribute to the great variability associated with cell-based tests, which currently lack robust standardization due to their complexity. While blood collection of peripheral blood mononuclear cells (PBMCs) isolation is common, different laboratories and studies use varying collection and processing procedures, resulting in possible variation in data. If oral or nasal fluids are needed, their collection requires mucosal sampling, which is not yet fully standardized. T cells can be isolated from lung mucosa using bronchoalveolar lavage, but in the absence of validated and standardized protocols, it is difficult to interpret and compare test results. Although proficiency panels and harmonization guidelines have been developed for ELISpot assays, there are still many gaps in T cell immunity assay standardization and validation. ICS and AIM assays are both flow-cytometry-based tests, which are subject to a number of variables that can lead to inconsistent results. Advances in standardization of flow-cytometry-based assays include the use of centralized analysis/standardized gating strategies, quality control and panel harmonization, critical reagent qualification and consistency. Unfortunately, while these methods allow for assay standardization if participating laboratories follow the guidelines, data harmonization between laboratories is still difficult without the use of appropriate sets of T cell standards, controls, and critical reagents, such as those available for SARS-CoV-2 serology [32].
Another challenge is that, unlike antibodies which can be conveniently measured and stored, T cell assays require optimally cryopreserved, live cells that must be carefully stored in sufficient amounts to study and are subject to change depending on culture and assay conditions. This sensitivity underscores the need for standardized protocols to ensure reliable use and reproducible findings. Nevertheless, T cells appear to play key roles in protection against COVID-19, so efforts to move T-cell-based assays to the clinical setting are worth pursuing. T cell standards development and T cell assay standardization are critical to fully leveraging the information generated by these types of tests to better understand the immunity against severe disease afforded by currently available vaccines. However, the best protection would be to prevent the initiation of the disease in the first place, which may lie in building a strong immune response at the mucosal sites of initial infection with the SARS-CoV-2 virus.

Assessing mucosal immunity
Currently available COVID-19 vaccines have been successful at preventing severe disease, hospitalization, and death in patients with cancer, when given additional doses of the vaccines. However, mounting evidence suggests that the key to preventing infection may lie in the local immune system of the mucous membrane of the nose or site of initial viral entry and infection. Unfortunately, despite the relative accessibility of oral and nasal mucosal samples, standardization of the collection and analysis of these samples is highly complex. While significant progress has been made in the field due to the pandemic, most research has focused on understanding mucosal immunity against SARS-CoV-2 in healthy populations rather than immunocompromised individuals. Some studies reported that natural infection could induce both serum and mucosal antibodies while mRNA vaccination only induced serum antibodies [46]. In contrast, a mucosal vaccine strategy could activate local immunity with evidence from a clinical trial [47]. While some of the findings may be generalizable, there is a significant need to confirm and expand these studies into cohorts representing people diagnosed with different types of cancer and receiving different anti-cancer therapies. Standardized assays, such as nasal/oral IgA and IgG ELISAs, mucosal neutralization assays, and multiplex mucosal antibody profiling, are needed to study SARS-CoV-2 immunity in cancer patients. Once available, large well-designed studies with cancers of interest and controls and appropriate statistical power should be conducted. To expedite execution of these types of studies, large well-coordinated collaborative studies across different cancer centers will likely be required.

What’s next? The role of consortia, sample repositories and developed tools

Potential roles for research consortia
The COVID-19 pandemic resulted in the development of multiple COVID-19 consortia with multidisciplinary expertise and high-quality sample repositories, potentially offering solutions to address complex questions regarding the immunology of SARS-CoV-2 infection and vaccination in patients with cancer and controls. A number of large sample repositories were developed, including NCI’s SeroNet, Duke University, University of Colorado in Denver, USC COVID-19 Biorepository, Boston Medical COVID-19 Biorepository, Medical University of South Carolina COVID-19 Biorepository, Massachusetts Consortium on Pathogen Readiness COVID-19 Biorepository Sample Sharing System, Tufts Medicine COVID-19 Biorepository and Comprehensive Database, Jackson Laboratory JAX COVID-19 Biorepository, and the PATH Washington COVID-19 Biorepository. Even after the end of the public health emergency, these samples may still prove invaluable to dissecting immune responses to different variants or different COVID-19 vaccine formulations in future efforts. In addition, these repositories could prove extremely important as future sources of “Pre-pandemic” samples should new viruses emerge. These consortia represent a new era of collaborative science facilitated by the rapid development of convenient videoconferencing platforms brought on by the quarantine, enabling collaboration and frequent discussions across continents and time zones.
Another important contribution of these COVID-19 partnerships included large collaborative studies that both demonstrated the power of these relationships and significantly advanced the scientific response to the pandemic. Examples include SeroNet’s Assay Standardization Study, which evaluated assay performance across many laboratories, and The Coronovirus Immunotherapy Consortium (CoVIC), which worked to accelerate discovery, optimization, and delivery of antibody-based therapeutics against SARS-CoV-2. In addition, the COVID-19 and Cancer Consortium (CCC19), which consisted of over 120 cancer centers and other organizations, worked to collect data about patients with cancer who have been diagnosed with COVID-19 [20]. The COVID Treatment Quick-start Consortium partnered with governments to rapidly introduce and scale access to COVID-19 oral antiviral therapies, particularly in vulnerable and high-risk populations presenting with mild to moderate symptoms. The National Institute of Allergy and Infectious Diseases’ SARS-CoV-2 Assessment of Viral Evolution (SAVE) Program functioned as a risk-assessment pipeline for SARS-CoV-2 viruses, providing a comprehensive real-time risk assessment of emerging mutations that could impact transmissibility, virulence, and susceptibility to infection. Collaborative research and shared biospecimens create opportunities to not only develop and standardize essential assays, but also to address complex questions regarding patients with cancer and SARS-CoV-2 infection. In addition, developed analytical tools will increase the understanding of real-world effects of COVID-19 in cancer populations.

Real-world data networks
A number of Real-World Data Networks were established to study the impact of COVID-19 in healthy and immunocompromised populations. Efforts such as the Consortium for Clinical Characterization of COVID-19 by EHR (4CE), NHS England Data Collection, National Clinical Cohort Collaborative (N3C), and the COVID Real-World Repository Infrastructure (CRWDi) represent invaluable resources in teasing out the real-world effects of SARS-CoV-2 infection and/or vaccination in special patient populations [48]. For example, the CRWDi initiative integrates de-identified US medical and pharmacy claims, laboratory data, vaccination records, and cancer registry data, covering 5.2 million unique patients, which enables longitudinal analysis across immunocompromised populations [48]. Studies using real-world data have led to interesting findings on treatment effectiveness, such as a study using the US PINC AI Healthcare Database that demonstrated that remdesivir treatment significantly increased survival of COVID-19 disease, including in people with immunocompromising conditions [49]. Meanwhile, a retrospective cohort study using data from the Municipal Department for Public Health Services of Vienna, Austria, found that older (≥60 years) patients with COVID-19 during the Omicron wave had a lower risk of hospitalization and all-cause death within 28 days with nirmatrelvir-ritonavir treatment, while younger patients or those treated with molnupiravir alone did not show similar effects [50].

Conclusion
The COVID-19 pandemic presented the world with an unprecedented challenge, which was met by impressive developments and dedication by public health professionals, scientists, and clinicians. The data, questions, tools and overall knowledge gained during the pandemic were unparalleled, and will contribute to new assays and technologies, treatment strategies, and improvements in the management of new viral respiratory infections threatening people with cancer. These individuals face worse infection outcomes, increased hospitalization rates, higher incidence of death, and higher risk of long-term implications when infected with these viruses, adding to the already severe implications of cancer diagnosis and treatment. The advances and collaborative networks built during such challenging times illustrate the power of science, collaboration and present the community with models that can be implemented to face future public challenges in various areas of interest for which rapid and effective responses are needed.