  Cancer is a heterogeneous disease with different combinations of genetic and
epigenetic alterations driving the development of cancer in different
individuals. While these alterations are believed to converge on genes in key
cellular signaling and regulatory pathways, our knowledge of these pathways
remains incomplete, making it difficult to identify driver alterations by their
recurrence across genes or known pathways. We introduce Combinations of
Mutually Exclusive Alterations (CoMEt), an algorithm to identify combinations
of alterations de novo, without any prior biological knowledge (e.g. pathways
or protein interactions). CoMEt searches for combinations of mutations that
exhibit mutual exclusivity, a pattern expected for mutations in pathways. CoMEt
has several important feature that distinguish it from existing approaches to
analyze mutual exclusivity among alterations. These include: an exact
statistical test for mutual exclusivity that is more sensitive in detecting
combinations containing rare alterations; simultaneous identification of
collections of one or more combinations of mutually exclusive alterations;
simultaneous analysis of subtype-specific mutations; and summarization over an
ensemble of collections of mutually exclusive alterations. These features
enable CoMEt to robustly identify alterations affecting multiple pathways, or
hallmarks of cancer. We show that CoMEt outperforms existing approaches on
simulated and real data. Application of CoMEt to hundreds of samples from four
different cancer types from TCGA reveals multiple mutually exclusive sets
within each cancer type. Many of these overlap known pathways, but others
reveal novel putative cancer genes. *Equal contribution.
