Single-Cell RNA-Seq Analysis Reveals Distinct Tumor and Immunosuppressive T Cell Phenotypes in CLL Patients Treated with Ibrutinib

• Published in: Blood 2023-11, Vol.142 (Supplement 1), p.3262-3262
• Main Authors: Thangavadivel, Shanmugapriya, Misra, Shrilekha, Benrashid, Samon, Gordon, Britten, He, Alexander, Lai, Tzung-Huei, Rogers, Kerry A, Bhat, Seema A, Kittai, Adam S, Byrd, John C., Blachly, James S., Woyach, Jennifer A., Blaser, Bradley Wayne
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2023-186604

Introduction: The development of Bruton tyrosine kinase inhibitors (BTKIs) and their introduction into clinical practice represents a major advance in the treatment of chronic lymphocytic leukemia (CLL). Monotherapy with ibrutinib or other BTKIs generally do not induce complete remissions or undetectable minimal residual disease (uMRD) even with extended therapy. The reason why some patients relapse, and some have minimal residual disease is unknown. Therefore, there is a need to understand the differences between ibrutinib sensitive and resistant CLL cells along with the immune microenvironment to identify novel therapeutic targets. Methods: Here, we investigate the cellular heterogeneity of peripheral blood mononuclear cells from patients with CLL treated with ibrutinib using single-cell RNA sequencing. To understand ibrutinib resistance mechanisms, samples were collected from 8 patients at baseline (before treatment) (1), where BTK C481S is present with low variant allele frequency (VAF) (2) and at time of relapse (3). Data from these were compared to ibrutinib sensitive patient samples at baseline (1) (before treatment), 3yr (2) and 5yr (3) on treatment timepoints. Single cells were isolated using the 10X Genomics 5' immune profiling kit. Data were processed with CellRanger v3.1.0. Poor quality cells were filtered out based on a high proportion of mitochondrial reads and low overall feature count. Sample variation was reduced using Batchelor to aid clustering. Clustering was performed using the partitioning and Leiden methods. Cluster top markers were calculated using functions from monocle3. Identity mapping was performed using Seurat and a published PBMC reference dataset. Results: Single-cell RNA sequencing revealed transcriptional heterogeneity within the B cell cluster (Fig 1A). Three subpopulations of B cells were defined based on differential representation in the ibrutinib-sensitive and resistant patients. Ibrutinib sensitive cells showed enrichment of B cell populations with upregulation of MHC I molecules and TNF family members. We also identified that inflammatory response and metabolic-related pathways were decreased, whereas cellular response to stress and DNA repair programs were increased in the ibrutinib resistance samples. Gene module analysis showed that ibrutinib sensitive samples had an increase in T cell activation, RNA splicing, cell adhesion and migration programs during therapy. We hypothesized that the emergence of BTK C481S mu