Joint Secondary Transcriptomic Analysis of Non-Hodgkin's B-Cell Lymphomas Predicts Reliance on Pathways Associated with the Extracellular Matrix and Robust Diagnostic Biomarkers.

Autor:	Rapier-Sharman N; Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA., Clancy J; Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA., Pickett BE; Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.
Jazyk:	angličtina
Zdroj:	Journal of bioinformatics and systems biology : Open access [J Bioinform Syst Biol] 2022; Vol. 5 (4), pp. 119-135. Date of Electronic Publication: 2022 Sep 27.
DOI:	10.26502/jbsb.5107040
Abstrakt:	Approximately 450,000 cases of Non-Hodgkin's lymphoma are annually diagnosed worldwide, resulting in ~240,000 deaths. An augmented understanding of the common mechanisms of pathology among larger numbers of B-cell Non-Hodgkin's Lymphoma (BCNHL) patients is sorely needed. We consequently performed a large joint secondary transcriptomic analysis of the available BCNHL RNA-sequencing projects from GEO, consisting of 322 relevant samples across ten distinct public studies, to find common underlying mechanisms and biomarkers across multiple BCNHL subtypes and patient subpopulations; limitations may include lack of diversity in certain ethnicities and age groups and limited clinical subtype diversity due to sample availability. We found ~10,400 significant differentially expressed genes (FDR-adjusted p-value < 0.05) and 33 significantly modulated pathways (Bonferroni-adjusted p-value < 0.05) when comparing BCNHL samples to non-diseased B-cell samples. Our findings included a significant class of proteoglycans not previously associated with lymphomas as well as significant modulation of genes that code for extracellular matrix-associated proteins. Our drug repurposing analysis predicted new candidates for repurposed drugs including ocriplasmin and collagenase. We also used a machine learning approach to identify robust BCNHL biomarkers that include YES1, FERMT2, and FAM98B, which have not previously been associated with BCNHL in the literature, but together provide ~99.9% combined specificity and sensitivity for differentiating lymphoma cells from healthy B-cells based on measurement of transcript expression levels in B-cells. This analysis supports past findings and validates existing knowledge while providing novel insights into the inner workings and mechanisms of transformed B-cell lymphomas that could give rise to improved diagnostics and/or therapeutics. Competing Interests: Conflicts of Interest The authors declare no conflicts of interest.
Databáze:	MEDLINE
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