Detection and Functional Characterization of Genetic Variations in Diffuse Large B cell Lymphoma

Abstract

In the course of evolution, human genome has been disrupted and rearranged as a consequence of various genetic events making each individual s genome unique. The accumulated genetic variations are known to play a significant role in shaping population-specific phenotypes and pre-disposition to various lethal diseases including cancer. Advancements in next generation sequencing (NGS) technologies have made it possible to carry out variant profiling of individuals. However, NGS techniques demonstrate inherent challenges. To address some of the issues, we have developed two open-source, integrated platforms, SeqVItA and iCopyDAV, for the detection of small sequence variations (SSVs) and copy number variations (CNVs), respectively. Our tools are tailored to quickly identify and annotate variations from large NGS data. Diffuse Large B-cell Lymphoma (DLBCL) is the most aggressive form of haematological malignancies, mostly develops because of accumulation of several genetic variations. The cell-of-origin classification system categorized DLBCL into Germinal Center B-cell and Activated B-cell subtypes, identified with distinct outcomes when treated with standard immunochemotherapy. Despite several studies carried out to characterize subtype-specific genetic variations, the complete spectrum of these alterations and their relationship with clinicopathological characteristics remains to be elucidated. Detection and analysis of genetic variations is carried out in 12 DLBCL cell lines with the objective of identifying molecular markers implicated in tumor initiation and progression in these subtypes. We observe large differences in the variation profiles of the cell lines indicating differences in the genes and associated pathways affected across the cell lines. Novel set of recurrent genetic variations that may play a key role in lymphomagenesis are identified. Integration of SSVs and CNVs revealed subgroups of shared variations among the cell lines analysed which help in understanding their effect on tumorigenesis.