A compendium of mutational cancer driver genes

Abstract

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone in this path is the identification of all the genes with mutations capable of driving tumors. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumors in a cohort deviate from those expected from neutral mutagenesis. These deviations, or signals may be detected by carefully designed bioinformatics methods, which have become state-of-the-art in the identification of driver genes. A systematic approach combining several of these signals could lead to the compendium of mutational cancer genes. We present the IntOGen pipeline, an implementation of this approach to obtain the compendium of mutational drivers, available through intogen.org. Its application to somatic mutations of more than 28,000 tumors of 66 cancer types reveals 568 cancer genes and points to their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumor mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Discovering the drivers of clonal hematopoiesis

“…We reasoned that, as is the case in the clonal expansion related to tumorigenesis 25,37 , the mutational patterns of CH-associated genes should exhibit signals of positive selection across donor blood samples. Therefore, methods that have been developed over the years to identify these signals of positive selection in cancer 25,37–40 could be applied to somatic mutations in blood samples to identify the genes with significant deviations from their expected patterns of mutations. Anchored in these methods, cancer genomics researchers have set the goal of uncovering the compendium of cancer driver genes.…”

“…To test this concept, we applied the IntOGen pipeline 25 (which runs seven state-of-the-art driver discovery methods 41–47 and combines their results) to blood somatic mutations in the primary and metastatic cohorts (Fig. 2a).…”

“…Note). False positive genes identified by a particular method are filtered out by the combination of their outputs through a voting-based approach 25 . Finally, 15 genes that are significant according to the combination approach are filtered out as they are deemed suspicious after a careful vetting that considers gene expression across HSCs, somatic hypermutation processes, common sequencing artifacts and frequent false positive genes of the driver discovery process (Supp.…”

“…(d) Relationship between the fraction of truncating variants identified in genes with 10 or more mutations across blood samples in the primary and metastasis cohorts and across several cohorts of tumors 25 .…”

“…To this end, we used the paired tumor sample as the reference germline genome of the donors in these two cohorts. On the set of blood somatic mutations identified, we then ran the Integrative OncoGenomics (IntOGen 25 ) pipeline that implements seven state-of-the-art driver discovery methods to identify signals of positive selection in the observed pattern of mutations in genes across samples. As a result, known CH-related genes and interesting novel candidates were identified.…”