[PMID: 29200198] [Nature Methods]
NetSig: network-based discovery from cancer genomes
“We developed a robust statistic (NetSig) that integrates protein interaction networks with data from 4,742 tumor exomes. NetSig can accurately classify known driver genes in 60% of tested tumor types and predicts 62 new driver candidates.” Work from Gaddy.
[PMID: 29179779] [Genome Biology]
Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines
“compared performance of 25 algorithms” on “14,819 benign or pathogenic missense variants from the ClinVar”
[PMID: 29109393] [Nature Communications]
Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors
“software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers.” Work from Gad Getz and Matthew Meyerson.
[PMID: 29093439] [Nature Communications]
Combating subclonal evolution of resistant cancer phenotypes
“track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment” “These findings highlight cancer’s ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves.”
[PMID: 29093438] [Nature Communications]
Mapping genomic and transcriptomic alterations spatially in epithelial cells adjacent to human breast carcinoma
“To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. “
[PMID: 29056344] [Cell]
Comprehensive Analysis of Hypermutation in Human Cancer
“an extensive assessment of mutation burden through sequencing analysis of >81,000 tumors from pediatric and adult patients” “Mutation burden analysis reveals new drivers of hypermutation in POLE and POLD1.” “Replication repair deficiency was a major contributing factor. ” “Unbiased clustering, based on mutational context, revealed clinically relevant subgroups regardless of the tumors’ tissue of origin, highlighting similarities in evolutionary dynamics leading to hypermutation.” “The order of mutational signatures identified previous treatment and germline replication repair deficiency”
[PMID: 29056346] [Cell]
Universal Patterns of Selection in Cancer and Somatic Tissues
“Nearly all (∼99%) coding mutations are tolerated and escape negative selection. Half of the coding driver mutations occur outside of known cancer genes.” Another great work from Sanger Institute.