Multi-omics Integration for Gene Fusion Discovery and Somatic Mutation Haplotyping in Cancer

Cancer is a disease caused by changes to the genome and dysregulation of gene expression. Among many types of mutations, including point mutations, small insertions and deletions, large scale structural variants, and copy number changes, gene fusions are another category of genomic and transcriptomic alteration that can lead to cancer and which can serve as therapeutic targets. We studied gene fusion events using data from The Cancer Genome Atlas, including over 9,000 patients from 33 cancer types, finding patterns of gene fusion events and dysregulation of gene expression within and across cancer types. With data from the CoMMpass study (Multiple Myeloma Research Foundation), we generated the largest gene fusion study in multiple myeloma (742 patients), which is the second most common type of blood cancer, and which is driven by recurrent translocations. We then developed a novel tool for analyzing the haplotype context of somatic mutations. Linked-read whole genome sequencing enables haplotype resolution for analyzing somatic mutation patterns, which is lost during typical short-read sequencing and alignment. We analyzed a cohort of 14 multiple myeloma patients across disease stages, phasing three-quarters of high confidence somatic mutations and enabling us to interpret clonal evolution models at higher resolution. Finally, we also studied the co-evolution of the multiple myeloma tumor and microenvironment using single-cell RNA-sequencing, finding distinct patterns of tumor subclone evolution between disease stages in 14 patients. Our methods and results demonstrate the power of integrating data types to study complex and dynamic evolutionary pressures in cancer and point to future directions of research that aim to bridge gaps in research and clinical applications