Abstract
TCF3 is a lymphopoietic transcription factor that acquires somatic driver mutations in diffuse large B-cell lymphoma (DLBCL). Hypothesizing that expression patterns of TCF3-regulated genes can inform clinical management, we found that unsupervised clustering analysis with 15 TCF3-regulated genes and eight additional ones resolved local DLBCL cases into two main clusters, denoted Groups A and B, of which Group A manifested inferior overall survival (OS, p = 0.0005). We trained a machine learning model to classify samples into the Groups based on expression of the 23 transcripts in an independent validation cohort of 569 R-CHOP-treated DLBCL cases. Group A overlapped with the ABC cell-of-origin subgroup but its prognostic power was superior. GSEA analysis demonstrated asymmetric expression of 30 gene sets between the Groups, pointing to biological differences. We present, validate and make available a novel method to assign DLBCL cases into biologically-distinct groups with divergent OS following R-CHOP therapy.
Acknowledgments
The authors gratefully acknowledge technical assistance from Brooke Snetsinger and Lee Boudreau in the Queen’s Laboratory for Molecular Pathology. Dr. Sandeep Dave of Duke University graciously shared validation data (EGAS00001002606). The Canadian Foundation for Innovation Leaders Opportunity Fund provided infrastructure support to MJR.
Disclosure statement
No potential conflict of interest was reported by the author(s).