An inflammatory state defines a high-risk T-lineage acute lymphoblastic leukemia subgroup

Mark Gower, Ximing Li, Alicia G. Aguilar-Navarro, Brian Lin, Minerva Fernandez, Gibran Edun, Mursal Nader, Vincent Rondeau, Andrea Arruda, Anne Tierens, Anna Eames Seffernick, Petri Pölönen, Juliette Durocher, Elvin Wagenblast, Lin Yang, Ho Seok Lee, Charles G. Mullighan, David Teachey, Marissa Rashkovan, Cedric S. TremblayDaniel Herranz, Tomer Itkin, Sanam Loghavi, John E. Dick, Gregory Schwartz, Maria Agustina Perusini, Hassan Sibai, Johann Hitzler, Tanja A. Gruber, Mark Minden, Courtney L. Jones, Igor Dolgalev, Soheil Jahangiri, Anastasia N. Tikhonova

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

T-lineage acute lymphoblastic leukemia (ALL) is an aggressive cancer comprising diverse subtypes that are challenging to stratify using conventional immunophenotyping. To gain insights into subset-specific therapeutic vulnerabilities, we performed an integrative multiomics analysis of bone marrow samples from newly diagnosed T cell ALL, early T cell precursor ALL, and T/myeloid mixed phenotype acute leukemia. Leveraging cellular indexing of transcriptomes and epitopes in conjunction with T cell receptor sequencing, we identified a subset of patient samples characterized by activation of inflammatory and stem gene programs. These inflammatory T-lineage samples exhibited distinct biological features compared with other T-lineage ALL samples, including the production of proinflammatory cytokines, prevalence of mutations affecting cytokine signaling and chromatin remodeling, an altered immune microenvironment, and poor treatment responses. Moreover, we found that, although inflammatory T-lineage ALL samples were less sensitive to dexamethasone, they exhibited unique sensitivity to a BCL-2 inhibitor, venetoclax. To facilitate classification of patients with T-lineage ALL, we developed a computational inflammatory gene signature scoring system, which stratified patients and was associated with disease prognosis in three additional patient cohorts. By identifying a high-risk T-lineage ALL subtype on the basis of an inflammatory score, our study provides a framework for targeted therapeutic approaches for these challenging-to-treat cancers.

Original languageEnglish (US)
Article numbereadr2012
JournalScience translational medicine
Volume17
Issue number779
DOIs
StatePublished - Jan 1 2025

ASJC Scopus subject areas

  • General Medicine

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