Faculty, Staff and Student Publications
Language
English
Publication Date
11-21-2025
Journal
npj Precision Oncology
DOI
10.1038/s41698-025-01158-3
PMID
41272086
PMCID
PMC12639073
PubMedCentral® Posted Date
11-21-2025
PubMedCentral® Full Text Version
Post-print
Abstract
Mantle cell lymphoma (MCL) responds to frontline therapy but is susceptible to relapse. While Bruton's tyrosine kinase inhibitors (BTKi) achieve high response rates, most patients eventually experience disease progression. Predicting responses to subsequent treatments remains challenging due to the lack of an established platform. Heterogeneity in gene alterations and cellular pathways contribute to resistance, complicating treatment approaches. Here, we present a multi-modal profiling platform, targeting key pathways rather than focusing on singular DNA-associated lesions. We identified dysregulated signaling pathways by performing gene expression profiling on 20 MCL samples using a custom MCL MATCH gene set and analyzed the data with gene-set variation analysis. We also screened 22 therapeutics in vitro to assess their efficacy. Whole exome sequencing was conducted to identify prevalent and actionable mutations linked to enriched pathways. Finally, we tested selected therapeutics in patient-derived xenograft mouse models to predict potential response in corresponding patients. Based on our integrative profiling, we identified the top therapeutic candidates for three patients in this study. This integrative platform may help identify targeted therapies for BTKi-relapsed/refractory MCL patients in clinical settings.
Keywords
Targeted therapies, B-cell lymphoma
Published Open-Access
yes
Recommended Citation
Liu, Yang; Hill, Holly A; Li, Yijing; et al., "Integrative Profiling Strategies to Guide Personalized Therapy in Mantle Cell Lymphoma: A Pilot Study" (2025). Faculty, Staff and Student Publications. 5448.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5448
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Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons