The proto-oncogene KRAS is a member of the RTK/RAS/RAF proliferative pathway and plays a key signalling role mediated through several downstream targets. KRAS is the most frequently mutated driver gene in lung adenocarcinoma (LUAD), accounting for more than 30% of cases, and current therapies demonstrate limited clinical efficacy in patients with KRAS-mutant LUAD. Previous exome studies have identified molecular features associated with KRAS-mutated LUAD. These include allele-specific phenotypes [1] and recurrent co-occurring alterations associated with distinct transcriptomic signatures and immune microenvironment characteristics that may influence treatment response [2,3]. However, a lack of large-scale whole-genome-sequencing (WGS) datasets in lung cancer, until recently, has precluded analysis to variants and mutation events within exons, which only account for approximately 1% of the human genome.
We performed a comprehensive analysis of the somatic mutational landscape in LUAD to better characterise KRAS alterations and determine the impact of complex structural variation and alterations in non-coding regions. Our current patient cohort is curated from publicly available and in-house WGS datasets, including TCGA (N=303) and Genomics England 100k Genomes Project. Our initial analysis of 117 matched tumour-normal cases has revealed a three-fold higher prevalence of KRAS mutations (19%) than reported by exome analysis (6%) and identified tumours with high gains (copy number >=6) of wild-type KRAS alleles. Analysis of copy number states identified unique significant co-occurring focal alterations spanning known cancer genes PRKCI and MECOM in KRAS-altered cases. Structural variant data has identified multiple breakpoints proximal to KRAS which are being investigated further for functional significance as potential gene-fusions and translocation-mediated gene activation events.
We will also characterise the genomic distinctions between primary and metastatic LUAD tumours using WGS data from the Hartwig Medical Foundation (N=609) [4], to elucidate mutational events that may drive metastases and identify features that may be reflective of tumour evolution. Finally, we aim to validate the oncogenic dependency and molecular effects of key findings with CRISPR screens and/or genetically engineered mouse models. Overall, this project seeks to uncover novel genomic events that may influence treatment response in LUAD and identify molecular features that may serve as viable treatment targets for inhibition.