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:Clinical genetic testing for hereditary breast and ovarian cancer (HBOC) is becoming widespread. However, the interpretation of variants of unknown significance (VUS) in HBOC genes, such as the clinically actionable genes BRCA1 and BRCA2, remain a challenge. Among the variants that are frequently classified as VUS are those with unclear effects on splicing. In order to address this issue we developed a high-throughput RNA-massively parallel sequencing assay-CloneSeq-capable to perform quantitative and qualitative analysis of transcripts in cell lines and HBOC patients. This assay is based on cloning of RT-PCR products followed by massive parallel sequencing of the cloned transcripts. To validate this assay we compared it to the RNA splicing assays recommended by members of the ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium. This comparison was performed using well-characterized lymphoblastoid cell lines (LCLs) generated from carriers of the BRCA1 or BRCA2 germline variants that have been previously described to be associated with splicing defects. CloneSeq was able to replicate the ENIGMA results, in addition to providing quantitative characterization of BRCA1 and BRCA2 germline splicing alterations in a high-throughput fashion. Furthermore, CloneSeq was used to analyze blood samples obtained from carriers of BRCA1 or BRCA2 germline sequence variants, including the novel uncharacterized alteration BRCA1 c.5152+5G>T, which was identified in a HBOC family. CloneSeq provided a high-resolution picture of all the transcripts induced by BRCA1 c.5152+5G>T, indicating it results in significant levels of exon skipping. This analysis proved to be important for the classification of BRCA1 c.5152+5G>T as a clinically actionable likely pathogenic variant. Reclassifications such as these are fundamental in order to offer preventive measures, targeted treatment, and pre-symptomatic screening to the correct individuals.

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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