Multiomics Profiling of T-cell Leukemia and Lymphoma Enables Targeted Therapeutic Discovery

T-cell leukemias and lymphomas (TCL) form a heterogeneous group of rare and often aggressive malignancies. Because of the rarity and heterogeneity of TCL subtypes, clinical trials are challenging to conduct, making pharmacogenomic studies in cell line panels critical for the discovery of targeted therapeutics. The scarcity of data repositories with integrated multiomics and drug screening data hinders the preclinical evaluation of drug vulnerabilities and the identification of molecular markers predictive of responses to monotherapies and combinations. To address this gap, we conducted comprehensive pharmacogenomic profiling on a panel of 38 TCL cell lines, representing major clinical TCL subtypes to capture the molecular and phenotypic diversity. The TCL-38 multiomics data resource includes harmonized genetic, molecular, and epigenetic profiles, with comprehensive annotations and standardized drug response assessment of each cell line. This resource, together with machine learning predictions, was leveraged to identify TCL subtype-specific therapeutic vulnerabilities, including single-agent sensitivities and synergistic drug combinations, which were linked to genetic or epigenetic features as potential predictive biomarkers. This integrated and openly available resource (https://aittokallio.group/tcl38) could help advance the currently limited treatment options for patients with TCL.

Integrated and harmonized multiomics analyses and drug screening across a heterogeneous panel of T-cell leukemias and lymphomas provide a resource to uncover drug targets and predictive biomarkers to improve patient outcomes.