Tag: WGS

Multi-region Omics in Ovarian Cancer

[PMID: 29754820] [Cell]

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer

“Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. “

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Childhood Cancer Genomes

[PMID: 29489754] [Nature]

The landscape of genomic alterations across childhood cancers

“a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer.”

[PMID: 29489755] [Nature]

Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours

“a pan-cancer study of somatic alterations, including single nucleotide variants, small insertions or deletions, structural variations, copy number alterations, gene fusions and internal tandem duplications in 1,699 paediatric leukaemias and solid tumours across six histotypes, with whole-genome, whole-exome and transcriptome sequencing data processed under a uniform analytical framework. We report 142 driver genes in paediatric cancers, of which only 45% match those found in adult pan-cancer studies; copy number alterations and structural variants constituted the majority (62%) of events.”

Accurity

[PMID: 29385401] [Bioinformatics]

Accurity: Accurate tumor purity and ploidy inference from tumor-normal WGS data by jointly modelling somatic copy number alterations and heterozygous germline single-nucleotide-variants

“infers tumor purity, tumor cell ploidy, and absolute allelic copy numbers for somatic copy number alterations (SCNAs) from tumor-normal WGS data by jointly modelling SCNAs and heterozygous germline single-nucleotide-variants (HGSNVs).”

Subclonal Evolution of Resistant Cancer Phenotypes

[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.”

Evolution of Breast Cancer Mets

[PMID: 28810143] [Cell]

Genomic Evolution of Breast Cancer Metastasis and Relapse

“We sequenced whole genomes or a panel of 365 genes on 299 samples from 170 patients with locally relapsed or metastatic breast cancer. Several lines of analysis indicate that clones seeding metastasis or relapse disseminate late from primary tumors, but continue to acquire mutations, mostly accessing the same mutational processes active in the primary tumor. Most distant metastases acquired driver mutations not seen in the primary tumor, drawing from a wider repertoire of cancer genes than early drivers. ” “In primary breast cancer, ER-positive and triple-negative tumors show rather distinct combinations of driver mutations, with PIK3CA, GATA3, and MAPK-pathway mutations characterizing the former and TP53 and copy number alterations the latter. When studying relapse and metastasis samples, however, we found that the genomic differences between triple-negative and ER-positive cancers became more blurred: TP53 mutations were seen in 40%–50% of relapsed ER-positive cases; and PIK3CA, GATA3, CDH1, and MAP3K1 all increased several-fold in relapsed ER-negative cancers.” Work from Peter Campbell.