2017
DOI: 10.1186/s13073-016-0393-x
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3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets

Abstract: Many mutations in cancer are of unknown functional significance. Standard methods use statistically significant recurrence of mutations in tumor samples as an indicator of functional impact. We extend such analyses into the long tail of rare mutations by considering recurrence of mutations in clusters of spatially close residues in protein structures. Analyzing 10,000 tumor exomes, we identify more than 3000 rarely mutated residues in proteins as potentially functional and experimentally validate several in RA… Show more

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Cited by 187 publications
(191 citation statements)
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“…Of these 16, the only nonsynonymous alteration in a gene previously associated with oncogenic signaling (Brastianos et al, 2015; Futreal et al, 2004) was a clonal missense mutation in PTEN , with evidence of heterozygous loss of the wild-type copy (81 variant reads out of 101 total reads) (Figure 2C). This alteration occurred within a 3D hotspot (Gao et al, 2017) in the tyrosine phosphatase domain of PTEN (Figure 2C) at the same locus as mutations observed in glioblastoma (Brennan et al, 2013) and colorectal cancer (Giannakis et al, 2016), suggesting a functional role. It was not detected in the pre-treatment tumor despite 165 reads at this locus (Figure 2C).…”
Section: Resultsmentioning
confidence: 59%
“…Of these 16, the only nonsynonymous alteration in a gene previously associated with oncogenic signaling (Brastianos et al, 2015; Futreal et al, 2004) was a clonal missense mutation in PTEN , with evidence of heterozygous loss of the wild-type copy (81 variant reads out of 101 total reads) (Figure 2C). This alteration occurred within a 3D hotspot (Gao et al, 2017) in the tyrosine phosphatase domain of PTEN (Figure 2C) at the same locus as mutations observed in glioblastoma (Brennan et al, 2013) and colorectal cancer (Giannakis et al, 2016), suggesting a functional role. It was not detected in the pre-treatment tumor despite 165 reads at this locus (Figure 2C).…”
Section: Resultsmentioning
confidence: 59%
“…Some tools analyze a re-ordered version of the protein's sequence based on the distance between residues in three dimensions 30 or use network algorithms on the graph derived from the structure 31 . However, most Type II algorithms try to identify three-dimensional clusters using the protein structure directly and calculate empirical p-values by re-shuffling the mutations in the structure 32 . Nevertheless, their specific details can be very different, as some use spheres of varying radii 33 , while others use the closeness in the structure-derived residue network 6 , the Shannon entropy of the region 17 or weighted-scoring functions 16 .…”
Section: Resultsmentioning
confidence: 99%
“…These PPP2R1A mutations frequently recurred at the same positions (P179, R183 and S256) across different cancer types, as indicated by several comprehensive studies [143,144,145]. In type II ECs, these so-called PPP2R1A hotspot mutations were recurrently found in codons: P179, R182, R183 (HEAT repeat 5) and S256, W257 (HEAT repeat 7) (Figure 2) [17,44,45,48,52,54,144,146,147].…”
Section: Therapeutic Potential Of Targeting Kinases and Phosphatasmentioning
confidence: 98%