Ovarian cancer risk and common variation in the sex hormone-binding globulin gene: a population-based case-control study

BACKGROUND: The sex hormone-binding globulin (SHBG) is a carrier protein that modulates the bio-availability of serum sex steroid hormones, which may be involved in ovarian cancer. We evaluated whether common genetic variation in SHBG and its 3' neighbor ATP1B2, in linkage disequilibrium, is associated with the risk of epithelial ovarian cancer. METHODS: The study population included 264 women with ovarian carcinoma and 625 controls participating in a population-based case-control study in Poland. Five common single nucleotide polymorphisms (SNPs) in SHGB and five in ATP1B2 were selected to capture most common variation in this region. RESULTS: None of the SNPs evaluated was significantly associated with ovarian cancer risk, including the putative functional SNPs SHBG D356N (rs6259) and -67G>A 5'UTR (rs1799941). However, our data were consistent with a decreased ovarian cancer risk associated with the variant alleles for these two SNPs, which have been previously associated with increased circulating levels of SHBG. CONCLUSION: These data do not support a substantial association between common genetic variation in SHBG and ovarian cancer risk

Mutational processes molding the genomes of 21 breast cancers

All cancers carry somatic mutations. The patterns of mutation in cancer genomes reflect the DNA damage and repair processes to which cancer cells and their precursors have been exposed. To explore these mechanisms further, we generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes. Multiple distinct single- and double-nucleotide substitution signatures were discernible. Cancers with BRCA1 or BRCA2 mutations exhibited a characteristic combination of substitution mutation signatures and a distinctive profile of deletions. Complex relationships between somatic mutation prevalence and transcription were detected. A remarkable phenomenon of localized hypermutation, termed "kataegis," was observed. Regions of kataegis differed between cancers but usually colocalized with somatic rearrangements. Base substitutions in these regions were almost exclusively of cytosine at TpC dinucleotides. The mechanisms underlying most of these mutational signatures are unknown. However, a role for the APOBEC family of cytidine deaminases is proposed

Polymorphisms of TP53 codon 72 with breast carcinoma risk: evidence from 12226 cases and 10782 controls

<p>Abstract</p> <p>Background</p> <p>Previously, TP53 codon 72 polymorphisms have been implicated as risk factors for various cancers. A number of studies have conducted on the association of TP53 codon 72 polymorphisms with susceptibility to breast carcinoma and have yielded inconclusive results. The aim of the present study was to derive a more precise estimation of the relationship.</p> <p>Methods</p> <p>We conducted a search in the Medline, EMBASE, OVID, Sciencedirect, and Chinese National Knowledge Infrastructure (CNKI) without a language limitation, covering all papers published up to Jan 2009. The associated literature was acquired through deliberate searching and selected based on the established inclusion criteria for publications.</p> <p>Results</p> <p>A total of seventeen case-control studies, including 12226 cases and 10782 controls, met the included criteria and thus were selected. Ultimately, the relevant data were extracted and further analyzed using systematic meta-analyses. Overall, no associations of TP53 codon 72 polymorphisms with breast carcinoma were observed (for Arg/Arg vs Pro/Pro: OR = 1.20; 95%CI = 0.96–1.50; for dominant model: OR = 1.12; 95%CI = 0.96–1.32; for recessive model: OR = 1.13; 95%CI = 0.98–1.31). In the subgroup analysis by ethnicity, statistically similar results were obtained when the data were stratified as Asians, Caucasians and Africans.</p> <p>Conclusion</p> <p>Collectively, the results of the present study suggest that <it>TP53 codon 72 </it>polymorphisms might not be a low-penetrant risk factor for developing breast carcinoma.</p

EZH2 and BMI1 inversely correlate with prognosis and TP53 mutation in breast cancer

Introduction PolycombGroup (PcG) proteins maintain gene repression through histone modifications and have been implicated in stem cell regulation and cancer. EZH2 is part of Polycomb Repressive Complex 2 (PRC2) and trimethylates H3K27. This histone mark recruits the BMI1-containing PRC1 that silences the genes marked by PRC2. Based on their role in stem cells, EZH2 and BMI1 have been predicted to contribute to a poor outcome for cancer patients. Methods We have analysed the expression of EZH2 and BMI1 in a well-characterised dataset of 295 human breast cancer samples. Results Interestingly, although EZH2 overexpression correlates with a poor prognosis in breast cancer, BMI1 overexpression correlates with a good outcome. Although this may reflect transformation of different cell types, we also observed a functional difference. The PcG-target genes INK4A and ARF are not expressed in tumours with high BMI1, but they are expressed in tumours with EZH2 overexpression. ARF expression results in tumour protein P53 (TP53) activation, and we found a significantly higher proportion of TP53 mutations in tumours with high EZH2. This may explain why tumours with high EZH2 respond poorly to therapy, in contrast to tumours with high BMI1. Conclusions Overall, our data highlight that whereas EZH2 and BMI1 may function in a 'linear' pathway in normal development, their overexpression has different functional consequences for breast tumourigenesi

BRCA1-mutated and basal-like breast cancers have similar aCGH profiles and a high incidence of protein truncating TP53 mutations

<p>Abstract</p> <p>Background</p> <p>Basal-like breast cancers (BLBC) are aggressive breast cancers for which, so far, no targeted therapy is available because they typically lack expression of hormone receptors and HER2. Phenotypic features of BLBCs, such as clinical presentation and early age of onset, resemble those of breast tumors from <it>BRCA1</it>-mutation carriers. The genomic instability of <it>BRCA1</it>-mutated tumors can be effectively targeted with DNA-damaging agents and poly-(ADP-ribose) polymerase 1 (PARP1) inhibitors. Molecular similarities between BLBCs and <it>BRCA1</it>-mutated tumors may therefore provide predictive markers for therapeutic response of BLBCs.</p> <p>Methods</p> <p>There are several known molecular features characteristic for <it>BRCA1</it>-mutated breast tumors: 1) increased numbers of genomic aberrations, 2) a distinct pattern of genomic aberrations, 3) a high frequency of <it>TP53 </it>mutations and 4) a high incidence of complex, protein-truncating <it>TP53 </it>mutations. We compared the frequency of <it>TP53 </it>mutations and the pattern and amount of genomic aberrations between <it>BRCA1</it>-mutated breast tumors, BLBCs and luminal breast tumors by <it>TP53 </it>gene sequencing and array-based comparative genomics hybridization (aCGH) analysis.</p> <p>Results</p> <p>We found that the high incidence of protein truncating <it>TP53 </it>mutations and the pattern and amount of genomic aberrations specific for BRCA1-mutated breast tumors are also characteristic for BLBCs and different from luminal breast tumors.</p> <p>Conclusions</p> <p>Complex, protein truncating TP53 mutations in BRCA1-mutated tumors may be a direct consequence of genomic instability caused by BRCA1 loss, therefore, the presence of these types of TP53 mutations in sporadic BLBCs might be a hallmark of BRCAness and a potential biomarker for sensitivity to PARP inhibition. Also, our data suggest that a small subset of genomic regions may be used to identify BRCA1-like BLBCs. BLBCs share molecular features that were previously found to be specific for BRCA1-mutated breast tumors. These features might be useful for the identification of tumors with increased sensitivity to (high-dose or dose-dense) alkylating agents and PARP inhibitors.</p

Systematical Detection of Significant Genes in Microarray Data by Incorporating Gene Interaction Relationship in Biological Systems

Many methods, including parametric, nonparametric, and Bayesian methods, have been used for detecting differentially expressed genes based on the assumption that biological systems are linear, which ignores the nonlinear characteristics of most biological systems. More importantly, those methods do not simultaneously consider means, variances, and high moments, resulting in relatively high false positive rate. To overcome the limitations, the SWang test is proposed to determine differentially expressed genes according to the equality of distributions between case and control. Our method not only latently incorporates functional relationships among genes to consider nonlinear biological system but also considers the mean, variance, skewness, and kurtosis of expression profiles simultaneously. To illustrate biological significance of high moments, we construct a nonlinear gene interaction model, demonstrating that skewness and kurtosis could contain useful information of function association among genes in microarrays. Simulations and real microarray results show that false positive rate of SWang is lower than currently popular methods (T-test, F-test, SAM, and Fold-change) with much higher statistical power. Additionally, SWang can uniquely detect significant genes in real microarray data with imperceptible differential expression but higher variety in kurtosis and skewness. Those identified genes were confirmed with previous published literature or RT-PCR experiments performed in our lab

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

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.publishedVersio

Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters

Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR–validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control.National Institutes of Health (U.S.)National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (NIAMS) (K08-AR054615))National Cancer Institute (U.S.) (NIH/(NCI) (R01-CA118750))National Cancer Institute (U.S.) (NIH/(NCI) R01-CA130795))Juvenile Diabetes Research Foundation InternationalAmerican Cancer SocietyHoward Hughes Medical Institute (Early career scientist)Stanford University (Graduate Fellowship)National Science Foundation (U.S.) (Graduate Research Fellowship)United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship

The life history of 21 breast cancers.

Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer's life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer's lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer's development, triggering diagnosis

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome