Our group focuses on integrative analyses of large-scale public 'omics data, leveraging the wealth of cancer genomics data into large-scale pan-cancer analyses.
The advent and exponential cost decrease of massively parallel sequencing technologies over the past years has enabled sequencing entire cancer genomes.
This resulted in unique opportunities for cancer research. Large-scale consortia (TCGA, The Cancer Genome Atlas, and ICGC, the International Cancer Genome Consortium) have produced whole genome sequences of thousands of cancer genomes, and are making their data available to the community. These efforts are now further scaling up, as exemplified by Genomics England's 100,000 Genomes Project.
I argue that we have so far only skimmed the surface of what can be learned from this unprecedented wealth of data. There is therefore a clear need for in-depth large-scale pan-cancer analyses.
Our group focuses on integrative analyses of large-scale public 'omics data, leveraging the wealth of cancer genomics data into large-scale pan-cancer analyses to understand carcinogenesis and cancer evolution.
Many cancer genes are somatically altered in only a very low proportion of tumours, providing a clear rationale for large-scale pan-cancer analyses of driver mutations. We are applying approaches centred on copy number analysis to characterise the landscape of tumour suppressors.
Many tumour suppressors are targeted by homozygous deletions, removing both parental copies. Because any homozygous deletion that includes a gene that confers a survival advantage is eliminated by negative selection, homozygous deletions are rare and often focal.
Admixture of normal cells in tumour samples has historically hindered the reliable identification of homozygous deletions. We previously developed ASCAT (Allele-Specific Copy number Analysis of Tumours), a method to derive copy number profiles of tumour cells, accounting for normal cell admixture and tumour aneuploidy (Figure 1).
Methods such as ASCAT can now effectively deconvolute copy number profiles of tumour cells from those of admixed normal cells and reliably identify homozygous deletions in tumour samples.
We are applying ASCAT to thousands of samples across cancer types, to screen for tumour suppressors through recurrent homozygous deletions. For a subset of these cases, point mutation data, gene expression data and/or DNA methylation data will also be available, which we will correlate with detected homozygous (and hemizygous) deletions, allowing us to more clearly delineate target genes within regions of homozygous deletions.
Through this screen, we aim to characterise the landscape of tumour suppressors and particularly identify rare tumour suppressors.
Tumour suppressors can also be inactivated by a combination of a deleterious germline variant, combined with loss-of-heterozygosity (LOH) of the other allele. We are performing a large-scale pan-cancer screen for this combination of events, as a complementary method to chart the landscape of tumour suppressors.