Clinical course and risk factors for mortality from COVID-19 in patients with haematological malignancies.

BACKGROUND: The impact of coronavirus disease 2019 (COVID-19) in haematological patients (HP) has not been comprehensively reported. METHODS: We analysed 39 patients with SARS-CoV-2 infection and haematological malignancies. Clinical characteristics and outcomes were compared to a matched control group of 53 non-cancer patients with COVID-19. Univariate and multivariate analyses were carried out to assess the risk factors associated with poor outcome. RESULTS: The most frequent haematological diseases were lymphoma (30%) and multiple myeloma (30%). Eighty-seven % HP developed moderate or severe disease. Patients with haematological malignancies had a significantly higher mortality rate compared to non-cancer patients (35.9% vs 13.2%; P = .003 (odds ratio 6.652). The worst outcome was observed in chronic lymphocytic leukaemia patients. Only age >70 years and C reactive protein >10 mg/dl at admission were associated with higher risk of death (odds ratio 34.86, P = .003 and 13.56,P = .03). Persistent viral sheddind was detected in 5 HP. Active chemotherapy, viral load at diagnosis and COVID-19 therapy were not predictors of outcome. CONCLUSION: Mortality of COVID-19 is significantly higher in patients with haematological malignancies compared to non-cancer patients. The impact of persistent viral shedding must be considered in order to re-start therapies and maintain infectious control measures.

Targeting high-risk multiple myeloma genotypes with optimized anti-CD70 CAR-T cells.

Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in urgent need of additional therapeutic options. Here, we identify CD70, widely recognized as a favorable immunotherapy target in other cancers, as a specifically upregulated cell surface antigen in high risk myeloma tumors. We use a structure-guided design to define a CD27-based anti-CD70 CAR-T design that outperforms all tested scFv-based CARs, leading to >80-fold improved CAR-T expansion in vivo. Epigenetic analysis via machine learning predicts key transcription factors and transcriptional networks driving CD70 upregulation in high risk myeloma. Dual-targeting CAR-Ts against either CD70 or BCMA demonstrate a potential strategy to avoid antigen escape-mediated resistance. Together, these findings support the promise of targeting CD70 with optimized CAR-Ts in myeloma as well as future clinical translation of this approach.

Corrigendum: Personalized monitoring of circulating tumor DNA with a specific signature of trackable mutations after chimeric antigen receptor T-cell therapy in follicular lymphoma patients.

[This corrects the article DOI: 10.3389/fimmu.2023.1188818.].