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Summary: Patients with cancer are at increased risk of death from COVID-19 and have reduced immune responses to SARS-CoV2 vaccines, necessitating regular boosters. We performed comprehensive chart reviews, surveys of patients attitudes, serology for SARS-CoV-2 antibodies and T cell receptor (TCR) β sequencing for cellular responses on a cohort of 982 cancer patients receiving active cancer therapy accrued between November-3-2020 and Mar-31-2023. We found that 92 · 3% of patients received the primer vaccine, 70 · 8% received one monovalent booster, but only 30 · 1% received a bivalent booster. Booster uptake was lower under age 50, and among African American or Hispanic patients. Nearly all patients seroconverted after 2+ booster vaccinations (>99%) and improved cellular responses, demonstrating that repeated boosters could overcome poor response to vaccination. Receipt of booster vaccinations was associated with a lower risk of all-cause mortality (HR = 0 · 61, p = 0 · 024). Booster uptake in high-risk cancer patients remains low and strategies to encourage booster uptake are needed.

Summary: Background: Post-acute COVID-19 syndrome (PACS) is linked to severe organ damage. The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate care. This exploratory study looks for a potential liquid biopsy signal for PACS using both manual and machine learning approaches. Methods: Using a high definition single cell assay (HDSCA) workflow for liquid biopsy, we analysed 100 Post-COVID patients and 19 pre-pandemic normal donor (ND) controls. Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection. We stratified the COVID patients into 25 asymptomatic, 22 symptomatic COVID-19 but not suspected for PACS and 53 PACS suspected. All COVID-19 patients investigated in this study were diagnosed between April 2020 and January 2022 with a median 243 days (range 16–669) from diagnosis to their blood draw. We did a histopathological examination of rare events in the peripheral blood and used a machine learning model to evaluate predictors of PACS. Findings: The manual classification found rare cellular and acellular events consistent with features of endothelial cells and platelet structures in the PACS-suspected cohort. The three categories encompassing the hypothesised events were observed at a significantly higher incidence in the PACS-suspected cohort compared to the ND (p-value < 0.05). The machine learning classifier performed well when separating the NDs from Post-COVID with an accuracy of 90.1%, but poorly when separating the patients suspected and not suspected of PACS with an accuracy of 58.7%. Interpretation: Both the manual and the machine learning model found differences in the Post-COVID cohort and the NDs, suggesting the existence of a liquid biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and its subsyndromes. Funding: This work was funded in whole or in part by Fulgent Genetics, Kathy and Richard Leventhal and Vassiliadis Research Fund. This work was also supported by the National Cancer Institute U54CA260591.