Brian graduated from Washington University in St. Louis in 2021, double majoring in Economics and Biology with a concentration in Genomics and Computational Biology. He currently works as a bioinformatics researcher for the Griffith Lab at the McDonnell Genome Institute. Brian’s current projects involve characterizing somatic variants associated with various cancers. Brian plans on applying to medical schools and matriculating in 2023.
Brian Li, Felicia Gomez, Matthew Mosior, Vera Thornton, Zach Skidmore, Kelsy Cotto, Brad Kahl, Malachi Griffith, Obi L. Griffith
Washington University School of Medicine, St. Louis, MO, USA
Mantle Cell Lymphoma (MCL) is a B-cell non-Hodgkin Lymphoma that currently has poor prognosis and few effective treatments. This project was intended to explore the variants that characterize MCL, and potentially identify targets for novel treatments. The patient cohort included 28 individuals who contributed lymph node biopsies and matched skin normal samples. All 28 patients had whole exome sequencing (WES), 10 had whole genome sequencing (WGS), and 8 had RNA sequencing. We used established in-house DNA and RNA analysis pipelines to detect single-nucleotide variants and indels, structural variants, copy number alterations, and RNA fusions. The canonical t(11;14) translocation between CCND1 and IGH was detected in 8 of 10 WGS samples via structural variant analysis. The most recurrently mutated genes include CCND1 (11/27), IGH (9/27), ATM (8/27), TP53 (6/27), IGK (5/27), and KMT2A (4/27). In addition to the t(11;14) translocation, CCND1 also had missense variants in four WES samples. Another gene of interest was ATM due to its diversity of variant types, which included missense variants, frameshift variants, deletions, and duplications. The most recurrent WGS copy number events were amplifications at 7q22.1 (9/10), and deletions at 21q22.3 (8/10) and 11q22.3 (6/10). The most common RNA fusion was a HNRNPU-CDC42EP4 fusion (2/8), and HNRNPU expression has previously been implicated in cancer progression. The results of this study will potentially identify genetic targets for MCL treatment and further integrate genomic and transcriptomic analyses of MCL.