title: Whole-genome analysis of papillary kidney cancer finds significant noncoding alterations.
abstract: To date, studies on papillary renal-cell carcinoma (pRCC) have largely focused on coding alterations in traditional drivers, particularly the tyrosine-kinase, Met. However, for a significant fraction of tumors, researchers have been unable to determine a clear molecular etiology. To address this, we perform the first whole-genome analysis of pRCC. Elaborating on previous results on MET, we find a germline SNP (rs11762213) in this gene predicting prognosis. Surprisingly, we detect no enrichment for small structural variants disrupting MET. Next, we scrutinize noncoding mutations, discovering potentially impactful ones associated with MET. Many of these are in an intron connected to a known, oncogenic alternative-splicing event; moreover, we find methylation dysregulation nearby, leading to a cryptic promoter activation. We also notice an elevation of mutations in the long noncoding RNA NEAT1, and these mutations are associated with increased expression and unfavorable outcome. Finally, to address the origin of pRCC heterogeneity, we carry out whole-genome analyses of mutational processes. First, we investigate genome-wide mutational patterns, finding they are governed mostly by methylation-associated C-to-T transitions. We also observe significantly more mutations in open chromatin and early-replicating regions in tumors with chromatin-modifier alterations. Finally, we reconstruct cancer-evolutionary trees, which have markedly different topologies and suggested evolutionary trajectories for the different subtypes of pRCC.
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.
authors.forename: Shantao
authors.identifier: 0000-0002-5440-2780
authors.initials: S
authors.lastname: Li
authors.affiliation: Department of Urology, Yale School of Medicine, New Haven, Connecticut, United States of America.
authors.forename: Brian M
authors.initials: BM
authors.lastname: Shuch
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Computer Science, Yale University, New Haven, Connecticut, United States of America.
authors.forename: Mark B
authors.identifier: 0000-0002-9746-3719
authors.initials: MB
authors.lastname: Gerstein
mesh_terms: D002292:Carcinoma, Renal Cell / Q000235:genetics* / Q000473:pathology; D002843:Chromatin / Q000235:genetics; D019175:DNA Methylation / Q000235:genetics; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D015894:Genome, Human; D006801:Humans; D007438:Introns / Q000235:genetics; D007680:Kidney Neoplasms / Q000235:genetics* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D009154:Mutation; D020641:Polymorphism, Single Nucleotide; D019859:Proto-Oncogene Proteins c-met / Q000235:genetics*; D062085:RNA, Long Noncoding / Q000235:genetics*
chemical_list: D002843:Chromatin; C577276:NEAT1 long non-coding RNA, human; D062085:RNA, Long Noncoding; C491743:MET protein, human; D019859:Proto-Oncogene Proteins c-met