Abstract
8035 Background: Ide-cel, a B-cell maturation antigen chimeric antigen receptor T cell therapy, has demonstrated frequent, deep, and durable responses in pts with RRMM in the KarMMa (NCT03361748), KarMMa-2 (NCT03601078), and KarMMa-3 (NCT03651128) trials. A previous analysis of KarMMa showed comparable efficacy of ide-cel across molecular high-risk/resistance (HR/R) features such as biallelic p53 inactivation, 1q amplification, t(4;14), and CRBN dysregulation, and identified a baseline gene expression pattern (PC4) associated with PFS (Martin N, et al. Hemasphere 2022;6:(S6):1452). We aim to identify additional genomic features associated with ide-cel efficacy in KarMMa and KarMMa-2, and evaluate samples from KarMMa-3 pts as an independent validation cohort. Methods: Transcriptional and genomic profiles were assessed at baseline in CD138+ cells from bone marrow from pts in KarMMa, KarMMa-2 cohort 1, and KarMMa-3. Gene copy number aberrations were evaluated for associations with response. Analyses were post hoc and exploratory, and a P-value, or false discovery rate (FDR), of < 0.05 was used to identify associations of interest. Results: In evaluable pts in KarMMa (n = 70), single copy number loss was observed at 2 loci that associated with PFS, a broad region across 14q (n = 16) and deletion at 1p31.2 (n = 6). These were generally independent and collectively represented 30% (21/70) of pts. Both were associated with shorter median PFS (mPFS) in KarMMa (cohort mPFS, 8.8 mo, n = 128; Munshi et al. N Engl J Med 2021;384:705-16) after FDR correction (del 14q, mPFS, 4.0 mo; del 1p31.2, mPFS, 2.3 mo). No pt with 1p loss achieved a best overall response (BOR) better than partial response. Pts with loss vs non-loss of 14q had similar BOR distribution, but poorer mPFS within each BOR (10.4 vs 29.7 mo for loss vs non-loss in pts with complete response/stringent complete response). Due to small sample size in KarMMa-2 cohort 1 (n = 18), these data were aggregated with those from KarMMa. When combined, previously described associations with HR/R features were maintained except for biallelic p53 inactivation, which showed a stronger association with shorter PFS in the aggregate dataset (n = 83, P = 0.04) than in KarMMa (n = 65, P = 0.09). KarMMa-3 (n = 210) analysis is ongoing and will be used as a validation cohort for these findings. Consistent trends for the association of the PC4 gene signature with PFS were observed in KarMMa-2 but were not statistically significant and limited by sample size. Conclusions: Two novel genomic HR/R features associated with PFS were identified using samples from KarMMa; validation is ongoing using samples from KarMMa-3. The PC4 gene signature was consistent in 2 RRMM cohorts. A modest association between biallelic p53 disruption and PFS emerged with increased sample size and will be studied in KarMMa-3.
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