Dataset Information

Profiling BRCA1, BRCA2 and non-BRCA1/2 LCLs post-Irradiation

ABSTRACT: The functional consequences of missense variants in disease genes are difficult to predict. We assessed if gene expression profiles could distinguish between BRCA1 or BRCA2 pathogenic truncating and missense mutation carriers and familial breast cancer cases whose disease was not attributable to BRCA1 or BRCA2 mutations (BRCAX cases). 72 cell lines from affected women in high-risk breast-ovarian families were assayed after exposure to ionising irradiation, including 23 BRCA1 carriers, 22 BRCA2 carriers, and 27 BRCAX individuals. A subset of 10 BRCAX individuals carried rare BRCA1/2 sequence variants considered to be of low clinical significance (LCS). BRCA1 and BRCA2 mutation carriers had similar expression profiles, with some subclustering of missense mutation carriers. The majority of BRCAX individuals formed a distinct cluster, but BRCAX individuals with LCS variants had expression profiles similar to BRCA1/2 mutation carriers. Gaussian Process Classifier predicted BRCA1, BRCA2 and BRCAX status with a maximum of 62% accuracy, and prediction accuracy decreased with inclusion of BRCAX samples carrying an LCS variant, and inclusion of pathogenic missense carriers. Similarly, prediction of mutation status with gene lists derived using Support Vector Machines was good for BRCAX samples without an LCS variant (82-94%), poor for BRCAX with an LCS (40-50%), and improved for pathogenic BRCA1/2 mutation carriers when the gene list used for prediction was appropriate to mutation effect being tested (71-100%). This study indicates that mutation effect, and presence of rare variants possibly associated with a low risk of cancer, must be considered in the development of array-based assays of variant pathogenicity. Keywords: cell type comparison, stress response

ORGANISM(S): Homo sapiens

PROVIDER: GSE10905 | GEO | 2008/03/21

SECONDARY ACCESSION(S): PRJNA107315

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Use of DNA damaging agents and RNA pooling to assess expression profiles associated with BRCA1 and BRCA2 mutation status in familial breast cancer patients Background: A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Determining the functional effect of these variants as well as their role in breast cancer susceptibility can be challenging using current classification methods. Methodology/Principal Findings: To identify predictors of pathogenic mutation status in familial breast cancer patients, we explored the use of gene expression arrays to assess the effect of two DNA damaging agents (irradiation and mitomycin C) on cellular response in relation to BRCA1 and BRCA2 mutation status. A range of regimes were used to treat 27 lymphoblastoid cell-lines (LCLs) derived from affected women in high-risk breast cancer families (nine BRCA1, nine BRCA2, and nine non-BRCA1/2 or BRCAX individuals) and nine LCLs from healthy individuals. Using an RNA pooling strategy, we found that treating LCLs with 1.2 μM mitomycin C and measuring the gene expression profiles 1 hour post-treatment had the greatest potential to discriminate BRCA1, BRCA2 and BRCAX mutation status. A classifier was built using the expression profile of nine QRT-PCR validated genes that were associated with BRCA1, BRCA2 and BRCAX status in RNA pools. These nine genes could distinguish BRCA1 from BRCA2 carriers with 83% accuracy in individual samples, but three-way analysis for BRCA1, BRCA2 and BRCAX had a maximum of 59% prediction accuracy. Conclusions/Significance: Our results suggest that, compared to BRCA1 and BRCA2 mutation carriers, non-BRCA1/2 (BRCAX) individuals are genetically heterogeneous. This study also demonstrates the effectiveness of RNA pools to compare the expression profiles of cell-lines from BRCA1, BRCA2 and BRCAX cases after treatment with irradiation and mitomycin C as a method to prioritize treatment regimes for detailed downstream expression analysis.

Project description:Approximately 25% of hereditary breast cancer cases associated with a strong familial history can be explained by mutations in BRCA1 or BRCA2 and other lower penetrance genes. The remaining high-risk families could be classified as BRCAX (non-BRCA1/2) families, in which no penetrant mutation has been found until now. Gene expression involving alternative splicing represents a well-known mechanism regulating the expression of multiple transcripts encoded by individual genes, which could be involved in cancer development. Thus using RNA-seq methodology, the analysis of transcriptome in immortalized lymphoblastoid cell lines of high-risk breast cancer individuals could reveal transcripts implicated in breast cancer susceptibility and development. RNA was extracted from immortalized lymphoblastoid cell lines of 117 women (affected and unaffected) coming from BRCA1, BRCA2 and BRCAX families. Anova analysis revealed a total of 95 transcripts corresponding to 85 different genes differentially expressed (Bonferroni corrected p-value <0.01) between those groups. Hierarchical clustering allowed distinctive subgrouping of BRCA1/2 subgroups from BRCAX individuals, without regard for the cancer status. We found enrichment for pathways in signaling cascades including mTOR and EIF2-related pathways. No transcripts were differentially expressed between BRCA1 and BRCA2 individuals, however out of 95 transcripts, 67 could discriminate BRCAX from combination of BRCA1 and BRCA2 individuals. On the other hand, 28 transcripts could discriminate affected from unaffected BRCAX individuals. These BRCAX-associated transcripts demonstrated enrichment in Telomere Extension by Telomerase and Double-Strand Break Repair by Non-Homologous End Joining mechanisms. To our knowledge, this represents the first study identifying transcripts differentially expressed in immortalized lymphoblastoid cell lines coming from the major classes of mutation-related breast cancer subgroups, namely BRCA1, BRCA2 and BRCAX. Moreover, some transcripts could discriminate affected from unaffected BRCAX individuals, which could represent potential therapeutic targets for breast cancer treatment.

Project description:Approximately 5% of all breast cancers can be attributed to an inherited mutation in one of two cancer susceptibility genes, BRCA1 and BRCA2. We searched for genes that have the potential to distinguish healthy BRCA1 and BRCA2 mutation carriers from non-carriers based on differences in expression profiling. Using expression microarrays we compared gene expression of irradiated lymphocytes from BRCA1 and BRCA2 mutation carriers versus control non-carriers. We identified 137 probe sets in BRCA1 carriers and 1345 in BRCA2 carriers with differential gene expression. Gene Ontology analysis revealed that most of these genes relate to regulation pathways of DNA repair processes, cell cycle regulation and apoptosis. Real-time PCR was performed on the 36 genes which were most prominently differentially expressed in the microarray assay; 21 genes were shown to be significantly differentially expressed in BRCA1 or BRCA2 mutation carriers as compared to controls (p<0.05). Based on a validation study with 40 mutation carriers and 17 non-carriers, a multiplex model that included six or more coincidental genes of 18 selected genes was constructed in order to predict the risk of carrying a mutation. The results using this model showed sensitivity 95% and specificity 88%. In summary, our study provides insight into the biological effect of heterozygous mutations in BRCA1 and BRCA2 genes in response to ionizing irradiation induced DNA damage. We also suggest a set of 18 genes that can be used as a prediction and screening tool for BRCA1 or BRCA2 mutational carriers by using easily obtained lymphocytes. Using expression microarrays we compared gene expression of irradiated lymphocytes from BRCA1 and BRCA2 mutation carriers versus control non-carriers Fresh blood samples were obtained from 9 BRCA1 and 8 BRCA2 mutation carriers and 9 mutation-negative women. Lymphocytes were collected from fresh blood samples, and RNA was extracted one hour after γ-irradiation

Project description:Pathogenic germline mutations in BRCA1 or BRCA2 are detected in less than one third of families with a strong history of breast cancer. It is therefore expected that mutations still remain undetected by currently used screening methods. In addition, a growing number of BRCA1/2 sequence variants of unclear pathogen significance are found in the families, constituting an increasing clinical challenge. New methods are therefore needed to improve the detection rate and aid the interpretation of the clinically uncertain variants. In this study we analyzed a series of 33 BRCA1, 22 BRCA2, and 128 sporadic tumors by RNA profiling to investigate the classification potential of RNA profiles to predict BRCA1/2 mutation status. We found that breast tumors from BRCA1 and BRCA2 mutation carriers display characteristic RNA expression patterns, allowing them to be distinguished from sporadic tumors. The majority of BRCA1 tumors were basal-like while BRCA2 tumors were mainly luminal B. Using RNA profiles, we were able to distinguish BRCA1 tumors from sporadic tumors among basal-like tumors with 83% accuracy and BRCA2 from sporadic tumors among luminal B tumors with 89% accuracy. Furthermore, subtype-specific BRCA1/2 gene signatures were successfully validated in two independent data sets with high accuracies. Although additional validation studies are required, indication of BRCA1/2 involvement (“BRCAness”) by RNA profiling could potentially be valuable as a tool for distinguishing pathogenic mutations from benign variants, for identification of undetected mutation carriers, and for selecting patients sensitive to new therapeutics such as PARP inhibitors. Gene expression profiling of 183 breast tumor samples. Breast tumors from hereditary breast cancer patients carrying a pathogenic BRCA1 (n=33) or BRCA2 (n=22) germ-line mutation were included in the study. Serving as a representative control group, primary breast tumor samples (n=128) were randomly selected. The study was conducted using Agilent-029949 Custom SurePrint G3 Human GE 8x60K Microarray platform. For cross-platform validation, a subset of the tumor samples (92 of the 183 samples) were analyzed by our in-house spotted microarray platform.

Dataset Information

Profiling BRCA1, BRCA2 and non-BRCA1/2 LCLs post-Irradiation

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure