Citations

Ciltacabtagene autoleucel (cilta-cel) consists of autologous T cells genetically modified to express a two-binding domain chimeric antigen receptor (CAR). The target antigen of the CAR is B-cell maturation antigen (BCMA), which is highly expressed on malignant plasma cells (PC) from multiple myeloma subjects. In the Phase 1b/2 CARTITUDE-1 study, cilta-cel led to early, deep, and durable responses and was approved for the treatment of patients with relapsed or refractory multiple myeloma (RRMM) after four or more prior lines of therapy by FDA. Despite cilta-cel's outstanding overall response rate (97.9%) and duration of response (DOR) in RRMM patients, relapse still occurs. Biomarkers associated with this durable response and acquired resistance remain to be elucidated. We present updated correlative data from the CARTITUDE-1 study. At the ~3 year follow-up (October 2022 data cutoff), 97 patients had received a single infusion of cilta-cel (median 0.71 x10 6 cells/kg [range 0.52 x10 6-0.94 x10 6]); the median follow up was 33.4 months (range 1.5-45.2), median DOR was 33.9 months (95% CI, 25.5-not estimable [NE]) and median PFS was 34.9 months (95% CI, 25.2-NE) (Lin Y et al, ASCO 2023). Drug product (DP), baseline and on-treatment whole blood and bone marrow samples from enrolled patients were analyzed by methods including flow cytometry, MSD immunoassays, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) and TCR sequencing. In CARTITUDE-1, the DP contained a mixture of transduced and non-transduced T cells; the median transduction efficiency was 16% (range 5-32%), with a balanced distribution of CAR+CD4+ and CAR+CD8+ cells, median frequency 12% (range 2-28%) and 6% (range 2-20%), respectively. Further, the DP T cell subset composition was variable but balanced between central (Tcm) and effector memory (Tem) phenotypes. CAR+ T cells expanded reaching a median peak concentration (C max of 730 cells/µL; range 3-13805 cells/µL) in blood between days 12-14 post-infusion and persisted in circulation for a median of 100 days (range 20-912 days). High efficacy (best response) and DOR were achieved despite variable CAR-T cell expansion and lack of detectable CAR-T cell persistence over time. At C max, the CD4:CD8 ratio (based on % of CAR+ cells) was 0.29, demonstrating a CAR+CD8+ T cell preferential expansion, and both CAR+CD4+ and CAR+CD8+ T cells were predominantly of a Tcm phenotype, median 95% (range 62-99.5%) and 96% (range 33-99.7%), respectively. Higher frequency of early-memory T cell phenotypes has been associated with clinical responses to CAR-T therapies in MM (Dancy et al., Blood 2018). CITE-seq analyses showed that DP characteristics such as a high CD8+ stem-like phenotype and a low CD4+ Treg-like phenotype in the CAR+ T cell compartment associated with longer DOR. Some of the most abundant clones in the DP single cell TCR data were CAR+CD8+ T cells expressing granzyme B, suggesting high cytotoxic potential. Additional bulk TCR sequencing data suggest both diversity and individual clonal expansion longitudinally after cilta-cel infusion. We also evaluated tumor and patient intrinsic characteristics at baseline. BCMA expression on bone marrow PC was prevalent and highly variable among RRMM patients; however, expression did not associate with best response or DOR. Further, high ORR was observed in patients with high-risk cytogenetics, high tumor burden (>= 60% bone marrow PC), or baseline plasmacytomas, although with a non-statistically significant shorter PFS. Sustained MRD negativity strongly associated with longer DOR. Conversely, patient-intrinsic characteristics associated with inflammation (CRP, ferritin, neutrophils, pro-inflammatory cytokines) correlated with shorter DOR. Treatment benefit of the magnitude seen with cilta-cel had not been reported with any other approved therapy in this setting. Correlative analyses suggest an emerging profile to help understand such outstanding clinical activity: a balanced CD4/CD8 ratio and Tcm/Tem phenotype of the manufactured DP and preferential expansion of CAR+CD8+ Tcm cells. Further, certain baseline patient-intrinsic and tumor characteristics may explain the longer DOR in the RRMM setting. These investigations help identify markers of response to cilta-cel and may lead to CAR-T cell design or manufacturing strategies that enhance drug product characteristics and thus clinical efficacy.

Interleukin (IL)-17 is a T helper 17 cytokine implicated in the pathogenesis of many autoimmune diseases, including rheumatoid arthritis (RA). Although IL-17A has a well-established role in murine pulmonary fibrosis models, its role in the tissue remodeling and fibrosis occurring in idiopathic pulmonary fibrosis (IPF) and RA-associated interstitial lung disease (RA-ILD) is not very well defined. To address this question, we utilized complimentary studies to determine responsiveness of human normal and pathogenic lung fibroblasts to IL-17A and used lung biopsies acquired from patients with IPF and RA-ILD to determine IL-17A receptor (IL-17RA) expression. Both normal and pathogenic IPF lung fibroblasts express functional IL-17RA and respond to IL-17A stimulation with cell proliferation, generation of extracellular matrix (ECM) proteins, and induction of myofibroblast transdifferentiation. Small interfering RNA (siRNA) silencing of IL-17RA attenuated this fibroblast response to IL-17A on ECM production. These fibroblast responses to IL-17A are dependent on NF-κB-mediated signaling. In addition, inhibiting Janus activated kinase (JAK) 2 by either siRNA or a selective pharmacological inhibitor, AZD1480—but not a JAK1/JAK3 selective inhibitor, tofacitinib—also significantly reduced this IL-17A-induced fibrogenic response. Lung biopsies of RA-ILD patients demonstrate significantly higher IL-17RA expression in areas of fibroblast accumulation and fibrosis, compared with either IPF or normal lung tissue. These observations support a direct role for IL-17A in lung fibrosis that may be particularly relevant in the context of RA-ILD.

Abstract Motivation: Reference genome assemblies are subject to change and refinement from time to time. Generally, researchers need to convert the results that have been analyzed according to old assemblies to newer versions, or vice versa, to facilitate meta-analysis, direct comparison, data integration and visualization. Several useful conversion tools can convert genome interval files in browser extensible data or general feature format, but none have the functionality to convert files in sequence alignment map or BigWig format. This is a significant gap in computational genomics tools, as these formats are the ones most widely used for representing high-throughput sequencing data, such as RNA-seq, chromatin immunoprecipitation sequencing, DNA-seq, etc. Results: Here we developed CrossMap, a versatile and efficient tool for converting genome coordinates between assemblies. CrossMap supports most of the commonly used file formats, including BAM, sequence alignment map, Wiggle, BigWig, browser extensible data, general feature format, gene transfer format and variant call format. Availability and implementation: CrossMap is written in Python and C. Source code and a comprehensive user’s manual are freely available at: http://crossmap.sourceforge.net/. Contact: Kocher.JeanPierre@mayo.edu or wang.liguo@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.