Cancer Driver Log (CanDL): Catalog of Potentially Actionable Cancer Mutations

Abstract

Massively parallel sequencing technologies have enabled characterization of genomic alterations across multiple tumor types. Efforts have focused on identifying driver mutations because they represent potential targets for therapy. However, because of the presence of driver and passenger mutations, it is often challenging to assign the clinical relevance of specific mutations observed in patients. Currently, there are multiple databases and tools that provide in silico assessment for potential drivers; however, there is no comprehensive resource for mutations with functional characterization. Therefore, we created an expert-curated database of potentially actionable driver mutations for molecular pathologists to facilitate annotation of cancer genomic testing. We reviewed scientific literature to identify variants that have been functionally characterized in vitro or in vivo as driver mutations. We obtained the chromosome location and all possible nucleotide positions for each amino acid change and uploaded them to the Cancer Driver Log (CanDL) database with associated literature reference indicating functional driver evidence. In addition to a simple interface, the database allows users to download all or selected genes as a comma-separated values file for incorporation into their own analysis pipeline. Furthermore, the database includes a mechanism for third-party contributions to support updates for novel driver mutations. Overall, this freely available database will facilitate rapid annotation of cancer genomic testing in molecular pathology laboratories for mutations.

Figure 1

Prevalence of the Cancer Drive Log (CanDL) mutations in cBioPortal. The color shade in each box corresponds to the number of samples in cBioPortal that had at least one CanDL mutation for a given gene and tumor type. The gradient scale is on the right. Genes were sorted in descending order, and the top 10 are represented on the y axis. The x axis represents tumor type.

Figure 2

Distribution of the Cancer Driver Log (CanDL) mutations across protein domains. The distribution of domains for mutations that are listed in CanDL, as defined by InterPro database, are shown. The y axis (// denotes break) represents the percentage of genes. Protein kinase (PK) domain mutations were the most common followed by small GTP-binding (SGBP) domain mutations. ATF, Armadillo-type fold; B4.1, band 4.1 domain; CF, coagulation factor 5/8 C-terminal type domain; EGFR, epidermal growth factor receptor, L domain; FB, T3, fibronectin type III; FL, CR, Furin-like cysteine-rich domain; GPAS, HI, G-protein α-subunit, helical insertion; GPCR, G protein coupled receptor; F2L, family 2-like; IDL, isopropylmalate dehydrogenase–like domain; IG I-S, immunoglobulin I set; IG S-2, immunoglobulin subtype 2; IGFB, insulin-like growth factor binding protein, N-terminal; NHR, LB, nuclear hormone receptor, ligand-binding; P3K, C2, phosphatidylinositol 3-kinase, C2 domain; PH, pleckstrin homology domain; PH, CD, phosphatidylinositol 3-/4-kinase, catalytic domain; PI3K ABD, phosphatidylinositol 3-kinase adaptor-binding domain; PIK-R, PIK-related kinase; PK, protein kinase domain; PKL, protein kinase–like domain; RGTPase, Rho GTPase activation protein; SET, SET domain; SGBP, small GTP-binding protein domain; SH2, SH2 domain; TIR, Toll/interleukin-1 receptor homology domain.