Sequential Scmultiomics of In Vivo CAR-T Cells Allows Characterization of Transcriptional Differences between Patients, and Identifies IL10 As a Potential Mechanism of Resistance to CAR-T Cells in MM

• Published in: Blood 2023-11, Vol.142 (Supplement 1), p.3433-3433
• Main Authors: Rodriguez-Madoz, Juan Roberto, Jordana-Urriza, Lorea, Serrano, Guillermo, Oliver-Caldes, Aina, Calleja-Cervantes, Maria Erendira, San-Martin, Patxi, Vilas-Zornoza, Amaia, Ullate-Agote, Asier, Zabaleta, Aintzane, Alignani, Diego, Lozano, Teresa, Cabanas Perianes, Valentin, Reguera, Juan Luis, Navarro-Bailon, Almudena, Español-Rego, Marta, Pascal, Mariona, Moraleda, Jose Maria, Perez-Simon, Jose A., Mateos, Maria Victoria, Sanchez-Guijo Martin, Fermin, Urbano-Ispizua, Alvaro, Juan, Manel, Pierola, Ana Alfonso, Rifon, Jose J., Rodriguez Otero, Paula, Paiva, Bruno, Inogés, Susana, López-Díaz De Cerio, Ascensión, Lasarte, Juan J, San Miguel, Jesús, Fernández de Larrea, Carlos, Hernaez, Mikel, Prosper, Felipe
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2023-182887

Background: CAR-T cells have revolutionized cancer immunotherapy, representing a promising option for R/R Multiple Myeloma (MM). Despite high remission rates observed after BCMA CAR-T therapy, many patients still relapse and knowledge of the molecular mechanisms governing CAR-T cell function is very limited. To shed some light on specific transcriptomic programs activated after CAR-T cell administration, we interrogated longitudinal samples of CAR-T cells collected from patients enrolled in CARTBCMA-HCB-01 (NCT04309981) and academic clinical trial in patients with RRMM (Oliver-Caldes A, et al. Lancet Oncol, 2023). Methodology: We characterized 50.805 CAR-T cells from 11 different samples collected from 3 patients, including final infusion products (IP) and CAR-T cells isolated from bone marrow (BM) and peripheral blood (PB), at one and three months after infusion. Single-cell RNA and TCR sequencing was performed using Chromium Single-Cell Immune Profiling solution from 10x Genomics, which allows simultaneous analysis of gene expression and paired T-cell receptors. Gene Regulatory Network (GRN) analysis was performed using SimiC, a novel machine learning method developed by our group, that infers regulatory dissimilarities from single cell data (Peng J, et al. Commun Biol., 2022) Results: scRNA-seq revealed that although CAR-T cells from IP presented similar profiles, with highly proliferative CD4 + and CD8 + memory cells, CAR-T cells remaining after infusion were mainly non-proliferating CD8 + cells, with effector/effector-memory phenotypes. Interestingly, transcriptomic profile of CAR-T cells differed among patients with different degrees of response. Partial responders presented increased presence of terminally differentiated effector cells with an exhausted signature, while complete responders presented CAR-T cells in transition to central or effector memory phenotype. Additionally, we found that BM and PB CAR-T cells presented different phenotypes, potentially due to abrogated regulatory mechanisms. Specifically, CAR-T cells infiltrating BM presented increased expression of cytotoxic and exhaustion markers compared to their PB counterparts. GRN analysis with SimiC identified several regulons ( PRDM1, ARID4B) with increased activity in CAR-T cells from BM, which could be responsible for these differences. PRDM1 has already been associated with CAR-T cell exhaustion and its depletion promotes TCF7-dependent CAR-T cell stemness and proliferation. ARID4B,