Signatures of mutational processes in human cancer.

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels

The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath’s pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications.publishedVersio

Breast cancer survival in Nordic BRCA2 mutation carriers-unconventional association with oestrogen receptor status.

To access publisher's full text version of this article click on the hyperlink belowBackground: The natural history of breast cancer among BRCA2 carriers has not been clearly established. In a previous study from Iceland, positive ER status was a negative prognostic factor. We sought to identify factors that predicted survival after invasive breast cancer in an expanded cohort of BRCA2 carriers. Methods: We studied 608 women with invasive breast cancer and a pathogenic BRCA2 mutation (variant) from four Nordic countries. Information on prognostic factors and treatment was retrieved from health records and by analysis of archived tissue specimens. Hazard ratios (HR) were estimated for breast cancer-specific survival using Cox regression. Results: About 77% of cancers were ER-positive, with the highest proportion (83%) in patients under 40 years. ER-positive breast cancers were more likely to be node-positive (59%) than ER-negative cancers (34%) (P < 0.001). The survival analysis included 584 patients. Positive ER status was protective in the first 5 years from diagnosis (multivariate HR = 0.49; 95% CI 0.26-0.93, P = 0.03); thereafter, the effect was adverse (HR = 1.91; 95% CI 1.07-3.39, P = 0.03). The adverse effect of positive ER status was limited to women who did not undergo endocrine treatment (HR = 2.36; 95% CI 1.26-4.44, P = 0.01) and patients with intact ovaries (HR = 1.99; 95% CI 1.11-3.59, P = 0.02). Conclusions: The adverse effect of a positive ER status in BRCA2 carriers with breast cancer may be contingent on exposure to ovarian hormones

A genomic map of a 6-Mb region at 13q21-q22 implicated in cancer development: identification and characterization of candidate genes

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldChromosomal region 13q21-q22 harbors a putative breast cancer susceptibility gene and has been implicated as a common site for somatic deletions in a variety of malignant tumors. We have built a complete physical clone contig for a region between D13S1308 and AFM220YE9 based on 18 yeast artificial chromosome and 81 bacterial artificial chromosome (BAC) clones linked together by 22 genetic markers and 61 other sequence tagged sites. Combining data from 47 sequenced BACs (as of June 2001), we have assembled in silico an integrated 5.7-Mb genomic map with 90% sequence coverage. This area contains eight known genes, two hypothetical proteins, 24 additional Unigene clusters, and approximately 100 predicted genes and exons. We have determined the cDNA and genomic sequence, and tissue expression profiles for the KIAA1008 protein (homologous to the yeast mitotic control protein dis3+), KLF12 (AP-2 repressor), progesterone induced blocking factor 1, zinc finger transcription factor KLF5, and LIM domain only-7, and for the hypothetical proteins FLJ22624 and FLJ21869. Mutation screening of the five known genes in 19 breast cancer families has revealed numerous polymorphisms, but no deleterious mutations. These data provide a basis and resources for further analyses of this chromosomal region in the development of cancer