Abstract Background Risk factors for severe COVID-19 include age, comorbidities, and viral virulence. Despite vaccination reducing severe cases, immunocompromised patients remain at high risk. This study aimed to identify risk factors for SARS-CoV-2 progression based on immune response, microbiome, and metabolomic profiles in patients undergoing hematopoietic cell transplantation (HCT) or diagnosed with hematologic malignancies (HM) or solid tumors (ST).Figure 1.Clinical characteristics of the patient cohort with (A) Hematopoietic Cell Transplantation (HCT) or Hematologic Malignancies (HM), and (B) Solid Tumors (ST).Figure 2.Integrated analysis of immune response, metabolomic, and metagenomic data in patients with Hematopoietic Cell Transplantation (HCT) or Hematologic Malignancies (HM). Methods In this prospective cohort (April–August 2020), immune profiling included: (1) high-dimensional flow cytometry (T/B/myeloid cell activation, exhaustion, regulation); (2) cytokine/chemokine quantification; (3) ELISA for IgG/IgM against viral antigens. Microbiota composition was assessed via 16S rRNA sequencing from stool samples; plasma metabolomics was performed via GC-MS.Figure 3.Integrated analysis of immune response and metabolomic data in patients with Solid Tumors(ST). Results HCT or HM patients who died showed severe leukopenia, low anti-SARS-CoV-2 antibody levels, and increased innate immune activation, with IL-2, IL-13, TNF, IFN-γ, and FGF2 as cytokine hubs. HCT or HM patients who recovered had coordinated antibody networks involving IL-4, IL-5, IL-12A, IL-15, and IL-17A. ST patients who died showed high IL-6 and CXCL8 without leukopenia and lacked coordinated antibody responses. Those who recovered displayed IL-10-correlated regulatory cytokine networks. Alpha diversity was lower in HM or HCT patients with severe COVID-19 but not in ST. Distinct metabolic profiles were observed by GC-MS across mild, moderate, and severe cases. Conclusion HCT or HM, and ST patients showed distinct immune, microbial, and metabolic signatures linked to COVID-19 outcomes. Integrative analysis may help identify high-risk cancer patients and guide future targeted management strategies. Disclosures All Authors: No reported disclosures
Schmidt-Filho et al. (Thu,) studied this question.