An alternative fully human anti-BCMA CAR-T shows response for relapsed or refractory multiple myeloma with anti-BCMA CAR-T exposures previously.
Qing Ming WangRunhong WeiShu-Fang GuoChao MinXiong ZhongHui HuangZhi ChengPublished in: Cancer gene therapy (2023)
Chimeric antigen receptor T (CAR-T) cells therapy has made remarkable progress in relapsed/refractory multiple myeloma (R/R MM) treatment. Unfortunately, patients still eventually experience disease progression or relapse even after receiving anti-BCMA CAR-T therapy. At present, there are limited data on available treatment options for patients who have progressed on anti-BCMA CAR-T therapy. In this study, we evaluated the safety and efficacy of fully human anti-BCMA CAR-T (HRC0202) in seven R/R MM patients who were previously exposed to anti-BCMA CAR-T therapy. Three patients received 6.0 × 10 6 CAR + T cells/kg, one patient received 10.0 × 10 6 CAR + T cells/kg and three patients received 15.0 × 10 6 CAR + T cells/kg. Cytokine release syndrome (CRS) of grades 1-2 occurred in three patients (42.9%) and grade ≥3 in two patients (28.6%). Immune effector cell-associated neurotoxic syndrome (ICANS) was not observed in any of the patients. The best overall response rate (ORR) was 71.4% (5/7), with a stringent complete response/complete response (sCR/CR) achieved in three patients. The median progression-free survival (PFS) was 269 days, and median overall survival (OS) for all patients was not reached. The median peak concentration (C max ) of HRC0202 was 30117.70 (range, 6084.35-147415.10) copies/μg DNA. This study indicated that fully human anti-BCMA CAR-T (HRC0202) is a promising treatment for R/R MM patients who relapsed or refractory from prior anti-BCMA CAR-T infusion.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- multiple myeloma
- peritoneal dialysis
- prognostic factors
- endothelial cells
- acute myeloid leukemia
- acute lymphoblastic leukemia
- stem cells
- low dose
- diffuse large b cell lymphoma
- machine learning
- free survival
- mesenchymal stem cells
- big data
- single cell
- air pollution