Beyond chip: Ccrs predicts prolonged cytopenias and inferior survival following anti-BCMA CAR-T in multiple myeloma
Abstract
Abstract Background: Clonal hematopoiesis of indeterminate potential (CHIP) has been linked to impaired hematopoietic recovery and adverse outcomes in patients with malignancy, though prior studies in anti-BCMA CAR T-cell therapy have not demonstrated strong associations between CHIP status and survival. However, emerging risk models such as the Clonal Cytopenia Risk Score (CCRS, Blood 2024) offer a refined approach by integrating CHIP mutations and cytopenias to stratify hematopoietic vulnerability. In this study, we applied CCRS in a cohort of patients with relapsed/refractory multiple myeloma (RRMM) treated with idecabtagene vicleucel (ide-cel) or ciltacabtagene autoleucel (cilta-cel) to evaluate its association with inflammatory markers, hematologic recovery, and survival outcomes—testing whether CCRS provides additive prognostic value beyond CHIP status, systemic inflammation, and tumor-intrinsic risk features. Methods: We sequenced and analyzed 113 paired samples collected within 30 days before lymphodepletion and 90 days post CAR-T infusion from patients treated with ide-cel (n=80) or cilta-cel (n=33) at our institution. CHIP was assessed using targeted next-generation sequencing (Archer Myeloid Panel, 3000x median depth) on peripheral blood, with a variant allele frequency (VAF) threshold of ≥1%. CHIP risk was stratified by CCRS. Outcomes included inflammatory markers, hematologic recovery, progression-free survival (PFS), and overall survival (OS). Survival was analyzed using Kaplan–Meier and multivariable Cox regression models adjusted for ferritin (>400 ng/mL), MM high-risk genomic features (del17p, t(4;14), t(14;16)), and extramedullary disease (EMD). Results: The median age of the cohort was 66 years (range 38-84), with a slight male predominance (67 men vs. 46 women). Median follow-up was 17.7 months (range 0.4-40.8), during which 38 patients died and 2 developed therapy related myeloid malignancy. At baseline, CHIP was detected in 41 of 113 patients (36%), most commonly involving DNMT3A (n=18), TET2 (n=10), and PPM1D (n=5). Post-infusion, CHIP was detected in 27 patients, with PPM1D emerging as the second most frequent mutation. A total of 22 patients had overlapping mutations at both timepoints. Most variants were stable post CAR T infusion, with median VAF changes of < 1%. Baseline CHIP status was not significantly associated with age, MM genomic risk features, EMD, ferritin, CRP, PFS or OS (all p>0.05). Using the CCRS, 80 patients were classified as low risk, 31 as intermediate, and 2 as high risk; intermediate and high groups were combined for analysis (CCRS int-high). CCRS int–high patients had significantly elevated baseline ferritin (p=0.009) and CRP (p=0.035) compared to the CCRS-low group, although peak values during follow-up did not differ (p=0.235 and p=0.98, respectively). CCRS int–high patients exhibited persistently impaired hematologic recovery. Hemoglobin levels were significantly lower from baseline through Day 90 (all p ≤ 0.001), and differences remained at Day 180 (p ≈ 0.017) and Day 360 (p ≈ 0.00015). Similarly, platelet counts were markedly lower at baseline and remained significantly depressed across all follow-up timepoints (all p≤0.001). ANC was also lower at baseline in the CCRS int-high group (p=0.026), but differences attenuated by Day 30 and were no longer significant thereafter (p > 0.10). In univariable analyses, CCRS int–high status was associated with significantly worse outcomes, including OS (HR 2.24, 95% CI: 1.16–4.29; p=0.016) and PFS (HR 2.23, 95% CI: 1.35–3.71; p=0.0019). In multivariable models adjusting for high ferritin, MM high-risk genomic features, and EMD, CCRS remained the only variable consistently associated with inferior PFS (HR 2.00, 95% CI: 1.20–3.39; p=0.008) and OS (HR 2.00, 95% CI: 1.04–3.92; p=0.008). In contrast, ferritin, genomic risk, and EMD each trended toward worse outcomes but did not reach statistical significance (all p > 0.05). Conclusion: CCRS robustly stratifies clinical outcomes, identifying patients at significantly increased risk for prolonged cytopenias, disease progression, and death—independent of systemic inflammation and tumor-intrinsic high-risk features. These findings suggest that CCRS captures a distinct axis of hematopoietic vulnerability not reflected by CHIP status alone. Integrating CHIP-derived risk metrics into post–CAR-T surveillance may enhance risk-adapted monitoring and inform supportive care strategies for long-term survivorship.
Article Details
Authors (34)
Zhuoer Xie
Moffitt Cancer Center, Tampa, Florida, United States
Omar Alexis Castaneda Puglianini
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Taiga Nishihori
Moffitt Cancer Center, Tampa, Florida, United States
Ariel Grajales-Cruz
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Peter Cheng
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Brandon Blue
Naval Research Enterprise Internship Program Student Residing in the Electronics Sciences and Technology Division, United States Naval Research Laboratory
David Scheiber-Camoretti
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Ken Harada
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Emily Merritt
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Daniel DeAvila
1Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
Brandon Kale
1H. Lee Moffitt Cancer Center and Research Institute, Department of Blood and Marrow Transplant and Cellular Immunotherapy, Tampa, United States
Karla Feliciano Salva
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
David Kaldas
Lucas Lee
1Moffitt Cancer Center, Tampa, United States
Kristy Matte
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Todd Stinard
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Lauren Peres
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Rebecca Gonzalez
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Himara Koelmeyer
University of South Florida, Tampa, Florida, United States
Michael Jain
1H. Lee Moffitt Cancer Center, Hematology and Oncology, Tampa, United States
Seongseok Yun
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
David Sallman
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Rami Komrokji
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Eric Padron
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Jeffrey Lancet
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Fabiana Perna
Moffitt Cancer Center, Tampa, Florida, United States
Hien Liu
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Rachid Baz
1Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
Melissa Alsina
H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States
Ciara Louise Freeman
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Frederick Locke
1H. Lee Moffitt Cancer Center, Hematology and Oncology, Tampa, United States
Kenneth Shain
H. Lee Moffitt Cancer Center and Research Institute
Doris Hansen
1H. Lee Moffitt Cancer Center and Research Institute, Tampa, United States
Dae Hyun Lee
Moffitt Cancer Center and Research Institute, Tampa, Florida, United States