Dataset Information

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers.

ABSTRACT: BRCA1 encodes a tumour suppressor protein that plays pivotal roles in homologous recombination (HR) DNA repair, cell-cycle checkpoints, and transcriptional regulation. BRCA1 germline mutations confer a high risk of early-onset breast and ovarian cancer. In more than 80% of cases, tumours arising in BRCA1 germline mutation carriers are oestrogen receptor (ER)-negative; however, up to 15% are ER-positive. It has been suggested that BRCA1 ER-positive breast cancers constitute sporadic cancers arising in the context of a BRCA1 germline mutation rather than being causally related to BRCA1 loss-of-function. Whole-genome massively parallel sequencing of ER-positive and ER-negative BRCA1 breast cancers, and their respective germline DNAs, was used to characterize the genetic landscape of BRCA1 cancers at base-pair resolution. Only BRCA1 germline mutations, somatic loss of the wild-type allele, and TP53 somatic mutations were recurrently found in the index cases. BRCA1 breast cancers displayed a mutational signature consistent with that caused by lack of HR DNA repair in both ER-positive and ER-negative cases. Sequencing analysis of independent cohorts of hereditary BRCA1 and sporadic non-BRCA1 breast cancers for the presence of recurrent pathogenic mutations and/or homozygous deletions found in the index cases revealed that DAPK3, TMEM135, KIAA1797, PDE4D, and GATA4 are potential additional drivers of breast cancers. This study demonstrates that BRCA1 pathogenic germline mutations coupled with somatic loss of the wild-type allele are not sufficient for hereditary breast cancers to display an ER-negative phenotype, and has led to the identification of three potential novel breast cancer genes (ie DAPK3, TMEM135, and GATA4).

SUBMITTER: Natrajan R

PROVIDER: S-EPMC4976800 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers.

Natrajan Rachael R Mackay Alan A Lambros Maryou B MB Weigelt Britta B Wilkerson Paul M PM Manie Elodie E Grigoriadis Anita A A'Hern Roger R van der Groep Petra P Kozarewa Iwanka I Popova Tatiana T Mariani Odette O Turaljic Samra S Furney Simon J SJ Marais Richard R Rodruigues Daniel-Nava DN Flora Adriana C AC Wai Patty P Pawar Vidya V McDade Simon S Carroll Jason J Stoppa-Lyonnet Dominique D Green Andrew R AR Ellis Ian O IO Swanton Charles C van Diest Paul P Delattre Olivier O Lord Christopher J CJ Foulkes William D WD Vincent-Salomon Anne A Ashworth Alan A Stern Marc Henri MH Reis-Filho Jorge S JS

The Journal of pathology 20120223 1

BRCA1 encodes a tumour suppressor protein that plays pivotal roles in homologous recombination (HR) DNA repair, cell-cycle checkpoints, and transcriptional regulation. BRCA1 germline mutations confer a high risk of early-onset breast and ovarian cancer. In more than 80% of cases, tumours arising in BRCA1 germline mutation carriers are oestrogen receptor (ER)-negative; however, up to 15% are ER-positive. It has been suggested that BRCA1 ER-positive breast cancers constitute sporadic cancers arisi ...[more]

PMID: 22362584

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Project description:BackgroundVariation of microorganism communities in the rumen of cattle (Bos taurus) is of great interest because of possible links to economically or environmentally important traits, such as feed conversion efficiency or methane emission levels. The resolution of studies investigating this variation may be improved by utilizing untargeted massively parallel sequencing (MPS), that is, sequencing without targeted amplification of genes. The objective of this study was to develop a method which used MPS to generate "rumen metagenome profiles", and to investigate if these profiles were repeatable among samples taken from the same cow. Given faecal samples are much easier to obtain than rumen fluid samples; we also investigated whether rumen metagenome profiles were predictive of faecal metagenome profiles.ResultsRather than focusing on individual organisms within the rumen, our method used MPS data to generate quantitative rumen micro-biome profiles, regardless of taxonomic classifications. The method requires a previously assembled reference metagenome. A number of such reference metagenomes were considered, including two rumen derived metagenomes, a human faecal microflora metagenome and a reference metagenome made up of publically available prokaryote sequences. Sequence reads from each test sample were aligned to these references. The "rumen metagenome profile" was generated from the number of the reads that aligned to each contig in the database. We used this method to test the hypothesis that rumen fluid microbial community profiles vary more between cows than within multiple samples from the same cow. Rumen fluid samples were taken from three cows, at three locations within the rumen. DNA from the samples was sequenced on the Illumina GAIIx. When the reads were aligned to a rumen metagenome reference, the rumen metagenome profiles were repeatable (P?<?0.00001) by cow regardless of location of sampling rumen fluid. The repeatability was estimated at 9%, albeit with a high standard error, reflecting the small number of animals in the study. Finally, we compared rumen microbial profiles to faecal microbial profiles. Our hypothesis, that there would be a stronger correlation between faeces and rumen fluid from the same cow than between faeces and rumen fluid from different cows, was not supported by our data (with much greater significance of rumen versus faeces effect than animal effect in mixed linear model).ConclusionsWe have presented a simple and high throughput method of metagenome profiling to assess the similarity of whole metagenomes, and illustrated its use on two novel datasets. This method utilises widely used freeware. The method should be useful in the exploration and comparison of metagenomes.

Project description:Objective:The aim of this study was to compare the molecular profiling, including somatic mutation and somatic copy number variation (SCNV), between human epidermal growth factor receptor 2 (HER2)-positive (HER2+) and HER2-negative (HER2-) gastric cancer patients. Patients and methods:Tumor samples were collected from 15 gastric cancer patients, including 10 HER2+ samples and five HER2- samples, which were diagnosed by immunohistochemistry. Whole-genome sequencing was performed by Illumina HiSeq PE150 instrument, along with somatic single nucleotide variant (SNV), somatic structural variation (SV) and SCNV analyses. Results:The average number of somatic SNVs and mutation spectrum were similar between HER2+ and HER2- samples. Transition of C>T was the main type of mutation. For somatic SV, number of intrachromosomal translocation (2,850.3±1,260.4 vs 1,157±586.6, P=0.015) and insertion of large fragment (1,125.6±457.4 vs 500±138.9, P=0.002) in HER2+ samples were higher than those in HER2- samples. For all samples, lysine methyltransferase 2C (KMT2C), ZNF91, TAF1 and MAP4 genes were identified as new significant mutated driver genes. KMT2C gene mutations were mainly detected in HER2+ samples (7/10), which were correlated with the lysine degradation pathway. SERF2 gene mutations were more common in HER2- samples (3/5) than in HER2+ samples (1/10). Copy number gain was the major type of SCNV in both groups, and the average number of SCNVs was similar. In the HER2+ samples, by using the GISTIC algorithm, amplification of known driver genes cyclin-dependent kinase 12 (CDK12, 6/10) and RARA (5/10) was mainly observed, and other amplifications including JUP, GJD3, KRT39, CDC6, RAPGEFL1, WIPF2, FAM65C, KLF5, DACH1 and PIBF1 genes were also observed. Amplifications of solute carrier family 12 member 7 (SLC12A7, 5/5), TTC40 (4/5) and GALNT9 (4/5) genes were mainly detected in HER2- samples. Conclusion:Differences in genomic landscape between HER2+ and HER2- gastric cancer samples were revealed in this study. KMT2C mutation and CDK12 amplification were mainly detected in HER2+ gastric cancer, whereas SERF2 mutation and SLC12A7 amplification were detected in HER2- gastric cancer.

Dataset Information

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers.

Publications

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers.

Similar Datasets

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