Translational genomics in pancreatic ductal adenocarcinoma: A review with re-analysis of TCGA dataset

Malignancy of the pancreas is a leading cause of cancer-related mortality, with the highest case-fatality of all cancers. Nevertheless, the lack of sensitive biomarkers and presence of biological heterogeneity precludes its early detection and effective treatment. The recent introduction of next-generation sequencing allows characterization of multiple driver mutations at genome- and exome-wide levels. Sequencing of DNA and RNA from circulating tumour cells has also opened an exciting era of non-invasive procedures for tumour detection and prognostication. This massively-parallel sequencing technology has uncovered the previously obscure molecular mechanisms, providing clues for better stratification of patients and identification of druggable targets for the disease. Identification of active oncogenic pathways and gene-gene interactions may reveal oncogene addiction and synthetic lethality. Relevant findings can be extrapolated to develop targeted and personalized therapeutic interventions. In addition to known mutational events, the role of chromosomal rearrangements in pancreatic neoplasms is gradually uncovered. Coupled with bioinformatics pipelines and epidemiological analyses, a better framework for risk stratification and prognostication of pancreatic cancer will be possible in the near future. In this review, we discuss how translational genomic studies facilitate our understanding of pathobiology, and development of novel diagnostics and therapeutics for pancreatic ductal adenocarcinoma with emphases on whole genome sequencing, whole exome sequencing, and liquid biopsies. We have also re-analyzed The Cancer Genome Atlas (TCGA) dataset to look for genetic features associated with altered survival in patients with pancreatic ductal adenocarcinoma.