Clinical-Preclinical Connections Solidified the Foundation Supporting PRMT5 as a Reliable Lymphoma Prognosis Biomarker

Objectives: To understand the clinical relationship between PRMT5 and cancer, and to explore an accurate prediction of a cancer patient’s survival and response to individualized treatment therapy. Methods: We analyzed clinical data from The Cancer Genome Atlas (TCGA) in comparison with previous preclinical studies on PRMT5. Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to investigate the correlation between PRMT5 expression and clinicopathologic information in lymphoma. GSEA was used to detect the pathways in which genes are primarily enriched. LASSO-COX regression was used to evaluate if PRMT5 is a credible survival prediction index for lymphoma. Results: Our results showed that PRMT5 was upregulated in multiple cancers including diffuse large B cell lymphoma (DLBCL) compared with normal tissues. And increased expression of PRMT5 in lymphomas was significantly associated with poor overall survival. Then we performed GSEA algorithm which inferred that high PRMT5 was correlated with cell cycle, ribosome, cytosolic DNA sensing pathway, autophagy regulation and olfactory transduction. Four types of immune cells, namely, macrophages M1 (R = 0.29, p = 0.0072), neutrophils (R = 0.29, p = 0.0077), macrophages M2 (R = 0.23, p = 0.034), and resting mast cells (R = 0.23, p = 0.037) in lymphoma showed correlation with PRMT5 expression. Conclusions: Our results have bridged the gap between preclinical and clinical data of PRMT5 and thus consolidated the knowledge supporting the role of PRMT5 in lymphoma prognosis prediction.