ABSTRACT
PURPOSE: Cancer patients display reduced humoral responses after double-dose COVID-19 vaccination while their cellular response is more comparable to that in healthy individuals. Recent studies demonstrated that a third vaccination dose boosts these immune responses, both in healthy people and cancer patients. Due to the availability of many different COVID-19 vaccines, many people have been boosted with a different vaccine from the one used for double-dose vaccination. Data on such alternative vaccination schedules are scarce. This prospective study compares a third dose of BNT162b2 after double-dose BNT162b2 (homologous) versus ChAdOx1 (heterologous) vaccination in cancer patients. EXPERIMENTAL DESIGN: 442 subjects (315 patients and 127 healthy) received a third dose of BNT162b2 (230 homologous vs 212 heterologous). Vaccine-induced adverse events (AE) were captured up to 7 days after vaccination. Humoral immunity was assessed by SARS-CoV-2 anti-S1 IgG antibody levels and SARSCoV-2 50% neutralization titers (NT50) against Wuhan and BA.1 Omicron strains. Cellular immunity was examined by analyzing CD4+ and CD8+ T cell responses against SARS-CoV-2 specific S1 and S2 peptides. RESULTS: Local AEs were more common after heterologous boosting. SARS-CoV-2 anti-S1 IgG antibody levels did not differ significantly between homologous and heterologous boosted subjects (GMT 1755.90 BAU/mL [95% CI 1276.95-2414.48] vs 1495.82 BAU/mL (95% CI 1131.48-1977.46)). However, homologous boosted subjects show significantly higher NT50 values against BA.1 Omicron. Subjects receiving heterologous boosting demonstrated increased spike-specific CD8+ T cells, including higher IFNγ and TNFα levels. CONCLUSIONS: In cancer patients who received double-dose ChAdOx1, a third heterologous dose of BNT162b2 was able to close the gap in antibody response.
ABSTRACT
Background: Patients with cancer, especially hematological cancer, are at increased risk for breakthrough COVID-19 infection. So far, a predictive biomarker that can assess compromised vaccine-induced anti-SARS-CoV-2 immunity in cancer patients has not been proposed. Methods: We employed machine learning approaches to identify a biomarker signature based on blood cytokines, chemokines, and immune- and non-immune-related growth factors linked to vaccine immunogenicity in 199 cancer patients receiving the BNT162b2 vaccine. Results: C-reactive protein (general marker of inflammation), interleukin (IL)-15 (a pro-inflammatory cytokine), IL-18 (interferon-gamma inducing factor), and placental growth factor (an angiogenic cytokine) correctly classified patients with a diminished vaccine response assessed at day 49 with >80% accuracy. Amongst these, CRP showed the highest predictive value for poor response to vaccine administration. Importantly, this unique signature of vaccine response was present at different studied timepoints both before and after vaccination and was not majorly affected by different anti-cancer treatments. Conclusion: We propose a blood-based signature of cytokines and growth factors that can be employed in identifying cancer patients at persistent high risk of COVID-19 despite vaccination with BNT162b2. Our data also suggest that such a signature may reflect the inherent immunological constitution of some cancer patients who are refractive to immunotherapy.