Functional NCMs in PDAC, identifying novel biomarkers with diagnostic/prognostic/therapeutic potential in Pancreatic Cancer

Abstract:
Despite the recent efforts in integrative genomic studies of pancreatic cancer, our understanding of pathogenic noncoding mutations (NCMs) and their contributions to tumourgenesis still remains poor. To identify a small number of genuine functional NCMs from tens of thousands of mutations in each patient is challenging. Here we apply a ChIP-seq and RNA-seq integrative analytical workflow to directly detect functional NCMs from active regulatory sites in patient and cell line samples, followed by independent cohort and functional validation. This work will provide more insights into roles of NCMs and their potential as diagnostic and prognostic targets in pancreatic cancer.

PhD project: Pancreatic Ductal Adenocarcinoma (PDAC) is a devastating disease with a five years survival rate less than 5%. Although the coding part of the pancreatic cancer genomes has been extensively explored through the International Cancer Genome Consortium (ICGC) (1) and The Cancer Genome Atlas (TCGA) (2), very little attention has been given to the extent of involvement of noncoding mutations in cancer development. Identifying bona fide non-coding driver mutations from whole genome sequencing (WGS) data is challenging, due to their abundance, ubiquity and the heterogeneous mutational processes throughout the human genome. Here we will devise a ChIP-seq (e.g., the enhancer-associated histone mark H3K27ac) and RNA-seq integrative analytical workflow to investigate the landscape of functional NCMs with the aim to identify novel noncoding biomarkers in PDAC. The student will:

1- assemble publically available H3K27ac ChIP-seq data of PDAC patients and cell lines, and identify recurrent functional NCMs from active regulatory regions based on our previous genomic pipeline (3). The matched RNA-seq and Cancer Cell Line Encyclopedia (CCLE) expression data will be used to further prioritise those variants with the ability to regulate nearby target genes. Identified functional NCMs and recurrent regulatory elements will be further validated using ICGC WGS and RNA-seq data set (Year 1-2)

2- generate our own matched ChIP-seq and RNA-seq data using patient cells (n=10) from the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB) (4), to further validate top functional candidates from Aim 1 and identify novel clinically relevant biomarkers across cohorts (Year 2)

3- perform functional validation for high-confidence functional mutations in PDAC cell lines using various molecular techniques, e.g., luciferase reporter assays and CRISPR/Cas9 to evaluate how they affect regulatory activities and targeted genes. (Year 3)

This project will systematically explore the functional NCMs in PDAC, identifying novel biomarkers with diagnostic/prognostic/therapeutic potential for this deadly disease.

Skills Priority Alignment: Interdisciplinary and Quantitative Biology