TY - JOUR
T1 - PertInInt
T2 - An Integrative, Analytical Approach to Rapidly Uncover Cancer Driver Genes with Perturbed Interactions and Functionalities
AU - Kobren, Shilpa Nadimpalli
AU - Chazelle, Bernard
AU - Singh, Mona
PY - 2020/7/22
Y1 - 2020/7/22
N2 - A major challenge in cancer genomics is to identify genes with functional roles in cancer and uncover their mechanisms of action. We introduce an integrative framework that identifies cancer-relevant genes by pinpointing those whose interaction or other functional sites are enriched in somatic mutations across tumors. We derive analytical calculations that enable us to avoid time-prohibitive permutation-based significance tests, making it computationally feasible to simultaneously consider multiple measures of protein site functionality. Our accompanying software, PertInInt, combines knowledge about sites participating in interactions with DNA, RNA, peptides, ions, or small molecules with domain, evolutionary conservation, and gene-level mutation data. When applied to 10,037 tumor samples, PertInInt uncovers both known and newly predicted cancer genes, while additionally revealing what types of interactions or other functionalities are disrupted. PertInInt's analysis demonstrates that somatic mutations are frequently enriched in interaction sites and domains and implicates interaction perturbation as a pervasive cancer-driving event.
AB - A major challenge in cancer genomics is to identify genes with functional roles in cancer and uncover their mechanisms of action. We introduce an integrative framework that identifies cancer-relevant genes by pinpointing those whose interaction or other functional sites are enriched in somatic mutations across tumors. We derive analytical calculations that enable us to avoid time-prohibitive permutation-based significance tests, making it computationally feasible to simultaneously consider multiple measures of protein site functionality. Our accompanying software, PertInInt, combines knowledge about sites participating in interactions with DNA, RNA, peptides, ions, or small molecules with domain, evolutionary conservation, and gene-level mutation data. When applied to 10,037 tumor samples, PertInInt uncovers both known and newly predicted cancer genes, while additionally revealing what types of interactions or other functionalities are disrupted. PertInInt's analysis demonstrates that somatic mutations are frequently enriched in interaction sites and domains and implicates interaction perturbation as a pervasive cancer-driving event.
KW - bioinformatics
KW - cancer
KW - genome informatics
KW - software
UR - http://www.scopus.com/inward/record.url?scp=85088023059&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088023059&partnerID=8YFLogxK
U2 - 10.1016/j.cels.2020.06.005
DO - 10.1016/j.cels.2020.06.005
M3 - Article
C2 - 32711844
AN - SCOPUS:85088023059
VL - 11
SP - 63-74.e7
JO - Cell Systems
JF - Cell Systems
SN - 2405-4712
IS - 1
ER -