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Background: Emerging data suggest variability in susceptibility and outcome to coronavirus disease 2019 (COVID-19) infection. Identifying risk factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations.Methods: We analyzed electronic health records of the US Veterans Affairs Healthcare System and assessed the prevalence of COVID-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for COVID-19 who were positive, as well as outcome attributable to COVID-19, and stratified by clinical characteristics including demographics, comorbidities, cancer treatment, and cancer type. All statistical tests are 2-sided.Results: Of 22 914 cancer patients tested for COVID-19, 1794 (7.8%) were positive. The prevalence of COVID-19 was similar across age. Higher prevalence was observed in African American (15.0%) compared with White (5.5%; P < .001) and in patients with hematologic malignancy compared with those with solid tumors (10.9% vs 7.8%; P < .001). Conversely, prevalence was lower in current smokers and patients who recently received cancer therapy (<6 months). The COVID-19-attributable mortality was 10.9%. Higher attributable mortality rates were observed in older patients, those with higher Charlson comorbidity score, and in certain cancer types. Recent (<6 months) or past treatment did not influence attributable mortality. Importantly, African American patients had 3.5-fold higher COVID-19-attributable hospitalization; however, they had similar attributable mortality as White patients.Conclusion: Preexistence of cancer affects both susceptibility to COVID-19 infection and eventual outcome. The overall COVID-19-attributable mortality in cancer patients is affected by age, comorbidity, and specific cancer types; however, race or recent treatment including immunotherapy do not impact outcome. [ABSTRACT FROM AUTHOR]

Specific niches within the tumor bone marrow (BM) microenvironment afford a sanctuary for multiple myeloma (MM) clones due to stromal cell-tumor cell interactions, which confer survival advantage and drug resistance. Defining the sequelae of tumor cell interactions within the MM niches on an individualized basis may provide the rationale for personalized therapies. To mimic the MM niche, we here describe a new 3D co-culture ex-vivo model in which primary MM patient BM cells are co-cultured with mesenchymal stem cells (MSC) in a hydrogel 3D system. In the 3D model, MSC with conserved phenotype (CD73+CD90+CD105+) formed compact clusters with active fibrous connections, and retained lineage differentiation capacity. Extracellular matrix molecules, integrins, and niche related molecules including N-cadherin and CXCL12 are expressed in 3D MSC model. Furthermore, activation of osteogenesis (MMP13, SPP1, ADAMTS4, and MGP genes) and osteoblastogenic differentiation was confirmed in 3D MSC model. Co-culture of patient-derived BM mononuclear cells with either autologous or allogeneic MSC in 3D model increased proliferation of MM cells, CXCR4 expression, and SP cells. We carried out immune profiling to show that distribution of immune cell subsets was similar in 3D and 2D MSC model systems. Importantly, resistance to novel agents (IMiDs, bortezomib, carfilzomib) and conventional agents (doxorubicin, dexamethasone, melphalan) was observed in 3D MSC system, reflective of clinical resistance. This 3D MSC model may therefore allow for studies of MM pathogenesis and drug resistance within the BM niche. Importantly, ongoing prospective trials are evaluating its utility to inform personalized targeted and immune therapy in MM.