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Genome-Wide Gene Expression Analyses of BRCA1- and BRCA2-Associated Breast and Ovarian Tumours. Cancers (Basel) 2020; 12:cancers12103015. [PMID: 33081408 PMCID: PMC7603076 DOI: 10.3390/cancers12103015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 09/28/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022] Open
Abstract
Germline pathogenic variants in BRCA1 and BRCA2 increase cumulative lifetime risk up to 75% for breast cancer and 76% for ovarian cancer. Genetic testing for BRCA1 and BRCA2 pathogenic variants has become an important part of clinical practice for cancer risk assessment and for reducing individual risk of developing cancer. Genetic testing can produce three outcomes: positive (a pathogenic variant), uninformative (no pathogenic variant) and uncertain significance (a variant of unknown clinical significance). More than one third of BRCA1 and BRCA2 variants identified have been classified as variants of uncertain significance, presenting a challenge for clinicians. To address this important clinical challenge, a number of studies have been undertaken to establish a gene expression phenotype for pathogenic BRCA1 and BRCA2 variant carriers in several diseased and normal tissues. However, the consistency of gene expression phenotypes described in studies has been poor. To determine if gene expression analysis has been a successful approach for variant classification, we describe the design and comparability of 23 published gene expression studies that have profiled cells from BRCA1 and BRCA2 pathogenic variant carriers. We show the impact of advancements in expression-based technologies, the importance of developing larger study cohorts and the necessity to better understand variables affecting gene expression profiles across different tissue types.
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Masica DL, Karchin R. Towards Increasing the Clinical Relevance of In Silico Methods to Predict Pathogenic Missense Variants. PLoS Comput Biol 2016; 12:e1004725. [PMID: 27171182 PMCID: PMC4865359 DOI: 10.1371/journal.pcbi.1004725] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- David L. Masica
- Department of Biomedical Engineering and The Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Rachel Karchin
- Department of Biomedical Engineering and The Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- * E-mail:
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Piccolo SR, Hoffman LM, Conner T, Shrestha G, Cohen AL, Marks JR, Neumayer LA, Agarwal CA, Beckerle MC, Andrulis IL, Spira AE, Moos PJ, Buys SS, Johnson WE, Bild AH. Integrative analyses reveal signaling pathways underlying familial breast cancer susceptibility. Mol Syst Biol 2016; 12:860. [PMID: 26969729 PMCID: PMC4812528 DOI: 10.15252/msb.20156506] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 02/09/2016] [Accepted: 02/11/2016] [Indexed: 01/08/2023] Open
Abstract
The signaling events that drive familial breast cancer (FBC) risk remain poorly understood. While the majority of genomic studies have focused on genetic risk variants, known risk variants account for at most 30% of FBC cases. Considering that multiple genes may influence FBC risk, we hypothesized that a pathway-based strategy examining different data types from multiple tissues could elucidate the biological basis for FBC. In this study, we performed integrated analyses of gene expression and exome-sequencing data from peripheral blood mononuclear cells and showed that cell adhesion pathways are significantly and consistently dysregulated in women who develop FBC. The dysregulation of cell adhesion pathways in high-risk women was also identified by pathway-based profiling applied to normal breast tissue data from two independent cohorts. The results of our genomic analyses were validated in normal primary mammary epithelial cells from high-risk and control women, using cell-based functional assays, drug-response assays, fluorescence microscopy, and Western blotting assays. Both genomic and cell-based experiments indicate that cell-cell and cell-extracellular matrix adhesion processes seem to be disrupted in non-malignant cells of women at high risk for FBC and suggest a potential role for these processes in FBC development.
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Affiliation(s)
- Stephen R Piccolo
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA Department of Biology, Brigham Young University, Provo, UT, USA
| | - Laura M Hoffman
- Huntsman Cancer Institute, Salt Lake City, UT, USA Department of Biology, University of Utah, Salt Lake City, UT, USA
| | | | - Gajendra Shrestha
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA
| | - Adam L Cohen
- Huntsman Cancer Institute, Salt Lake City, UT, USA Department of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Jeffrey R Marks
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Leigh A Neumayer
- Department of Surgery, University of Utah, Salt Lake City, UT, USA
| | - Cori A Agarwal
- Department of Surgery, University of Utah, Salt Lake City, UT, USA
| | - Mary C Beckerle
- Huntsman Cancer Institute, Salt Lake City, UT, USA Department of Biology, University of Utah, Salt Lake City, UT, USA Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Avrum E Spira
- Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA
| | - Philip J Moos
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA
| | - Saundra S Buys
- Huntsman Cancer Institute, Salt Lake City, UT, USA Department of Medicine, University of Utah, Salt Lake City, UT, USA
| | - William Evan Johnson
- Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA
| | - Andrea H Bild
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA
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Piccolo SR, Andrulis IL, Cohen AL, Conner T, Moos PJ, Spira AE, Buys SS, Johnson WE, Bild AH. Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility. BMC Med Genomics 2015; 8:72. [PMID: 26538066 PMCID: PMC4634735 DOI: 10.1186/s12920-015-0145-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Accepted: 10/21/2015] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Women with a family history of breast cancer face considerable uncertainty about whether to pursue standard screening, intensive screening, or prophylactic surgery. Accurate and individualized risk-estimation approaches may help these women make more informed decisions. Although highly penetrant genetic variants have been associated with familial breast cancer (FBC) risk, many individuals do not carry these variants, and many carriers never develop breast cancer. Common risk variants have a relatively modest effect on risk and show limited potential for predicting FBC development. As an alternative, we hypothesized that additional genomic data types, such as gene-expression levels, which can reflect genetic and epigenetic variation, could contribute to classifying a person's risk status. Specifically, we aimed to identify common patterns in gene-expression levels across individuals who develop FBC. METHODS We profiled peripheral blood mononuclear cells from women with a family history of breast cancer (with or without a germline BRCA1/2 variant) and from controls. We used the support vector machines algorithm to differentiate between patients who developed FBC and those who did not. Our study used two independent datasets, a training set of 124 women from Utah (USA) and an external validation (test) set from Ontario (Canada) of 73 women (197 total). We controlled for expression variation associated with clinical, demographic, and treatment variables as well as lymphocyte markers. RESULTS Our multigene biomarker provided accurate, individual-level estimates of FBC occurrence for the Utah cohort (AUC = 0.76 [0.67-84]) . Even at their lower confidence bounds, these accuracy estimates meet or exceed estimates from alternative approaches. Our Ontario cohort resulted in similarly high levels of accuracy (AUC = 0.73 [0.59-0.86]), thus providing external validation of our findings. Individuals deemed to have "high" risk by our model would have an estimated 2.4 times greater odds of developing familial breast cancer than individuals deemed to have "low" risk. CONCLUSIONS Together, these findings suggest that gene-expression levels in peripheral blood cells reflect genomic variation associated with breast cancer risk and that such data have potential to be used as a non-invasive biomarker for familial breast cancer risk.
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Affiliation(s)
- Stephen R Piccolo
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
- Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
- Department of Biology, Brigham Young University, Provo, UT, USA.
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada.
| | - Adam L Cohen
- Huntsman Cancer Institute, Salt Lake City, UT, USA.
- Department of Medicine, University of Utah, Salt Lake City, UT, USA.
| | | | - Philip J Moos
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
| | - Avrum E Spira
- Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
| | - Saundra S Buys
- Huntsman Cancer Institute, Salt Lake City, UT, USA.
- Department of Medicine, University of Utah, Salt Lake City, UT, USA.
| | - W Evan Johnson
- Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
| | - Andrea H Bild
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
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DNA repair capacity is impaired in healthy BRCA1 heterozygous mutation carriers. Breast Cancer Res Treat 2015; 152:271-82. [PMID: 26071757 DOI: 10.1007/s10549-015-3459-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 06/05/2015] [Indexed: 01/12/2023]
Abstract
BRCA1 germline mutations increase the lifetime risk of developing breast and ovarian cancers. However, taking into account the differences in disease manifestation among mutation carriers, it is probable that different BRCA1 mutations have distinct haploinsufficiency effects and lead to the formation of different phenotypes. Using lymphoblastoid cell lines derived from heterozygous BRCA1 mutation carriers and non-carriers, we investigated the haploinsufficiency effects of various mutation types using qPCR, immunofluorescence, and microarray technology. Lymphoblastoid cell lines carrying a truncating mutation showed significantly lower BRCA1 mRNA and protein levels and higher levels of gamma-H2AX than control cells or those harboring a missense mutation, indicating greater spontaneous DNA damage. Cells carrying either BRCA1 mutation type showed impaired RAD51 foci formation, suggesting defective repair in mutated cells. Moreover, compared to controls, cell lines carrying missense mutations displayed a more distinct expression profile than cells with truncating mutations, which is consistent with different mutations giving rise to distinct phenotypes. Alterations in the immune response pathway in cells harboring missense mutations point to possible mechanisms of breast cancer initiation in carriers of these mutations. Our findings offer insight into how various heterozygous mutations in BRCA1 could lead to impairment of BRCA1 function and provide strong evidence of haploinsufficiency in BRCA1 mutation carriers.
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Song H, Cicek MS, Dicks E, Harrington P, Ramus SJ, Cunningham JM, Fridley BL, Tyrer JP, Alsop J, Jimenez-Linan M, Gayther SA, Goode EL, Pharoah PDP. The contribution of deleterious germline mutations in BRCA1, BRCA2 and the mismatch repair genes to ovarian cancer in the population. Hum Mol Genet 2014; 23:4703-9. [PMID: 24728189 PMCID: PMC4119409 DOI: 10.1093/hmg/ddu172] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2013] [Revised: 04/02/2014] [Accepted: 04/08/2014] [Indexed: 12/20/2022] Open
Abstract
The aim of this study was to estimate the contribution of deleterious mutations in BRCA1, BRCA2, MLH1, MSH2, MSH6 and PMS2 to invasive epithelial ovarian cancer (EOC) in the population. The coding sequence and splice site boundaries of all six genes were amplified in germline DNA from 2240 invasive EOC cases and 1535 controls. Barcoded fragment libraries were sequenced using the Illumina GAII or HiSeq and sequence data for each subject de-multiplexed prior to interpretation. GATK and Annovar were used for variant detection and annotation. After quality control 2222 cases (99.2%) and 1528 controls (99.5%) were included in the final analysis. We identified 193 EOC cases (8.7%) carrying a deleterious mutation in at least one gene compared with 10 controls (0.65%). Mutations were most frequent in BRCA1 and BRCA2, with 84 EOC cases (3.8%) carrying a BRCA1 mutation and 94 EOC cases (4.2%) carrying a BRCA2 mutation. The combined BRCA1 and BRCA2 mutation prevalence was 11% in high-grade serous disease. Seventeen EOC cases carried a mutation in a mismatch repair gene, including 10 MSH6 mutation carriers (0.45%) and 4 MSH2 mutation carriers (0.18%). At least 1 in 10 women with high-grade serous EOC has a BRCA1 or BRCA2 mutation. The development of next generation sequencing technologies enables rapid mutation screening for multiple susceptibility genes at once, suggesting that routine clinical testing of all incidence cases should be considered.
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Affiliation(s)
- Honglin Song
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK,
| | - Mine S Cicek
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Ed Dicks
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Patricia Harrington
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Susan J Ramus
- Department of Preventive Medicine, Keck School of Medicine, USC/Norris Comprehensive Cancer Center, University of Southern California, CA, USA
| | | | - Brooke L Fridley
- Department of Biostatistics, University of Kansas Medical Center, Kansas, USA and
| | - Jonathan P Tyrer
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Jennifer Alsop
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | | | - Simon A Gayther
- Department of Preventive Medicine, Keck School of Medicine, USC/Norris Comprehensive Cancer Center, University of Southern California, CA, USA
| | - Ellen L Goode
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Paul D P Pharoah
- CR-UK Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
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Guidugli L, Carreira A, Caputo SM, Ehlen A, Galli A, Monteiro ANA, Neuhausen SL, Hansen TVO, Couch FJ, Vreeswijk MPG. Functional assays for analysis of variants of uncertain significance in BRCA2. Hum Mutat 2013; 35:151-64. [PMID: 24323938 DOI: 10.1002/humu.22478] [Citation(s) in RCA: 92] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Accepted: 10/28/2013] [Indexed: 01/11/2023]
Abstract
Missense variants in the BRCA2 gene are routinely detected during clinical screening for pathogenic mutations in patients with a family history of breast and ovarian cancer. These subtle changes frequently remain of unknown clinical significance because of the lack of genetic information that may help establish a direct correlation with cancer predisposition. Therefore, alternative ways of predicting the pathogenicity of these variants are urgently needed. Since BRCA2 is a protein involved in important cellular mechanisms such as DNA repair, replication, and cell cycle control, functional assays have been developed that exploit these cellular activities to explore the impact of the variants on protein function. In this review, we summarize assays developed and currently utilized for studying missense variants in BRCA2. We specifically depict details of each assay, including variants of uncertain significance analyzed, and describe a validation set of (genetically) proven pathogenic and neutral missense variants to serve as a golden standard for the validation of each assay. Guidelines are proposed to enable implementation of laboratory-based methods to assess the impact of the variant on cancer risk.
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Affiliation(s)
- Lucia Guidugli
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
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Millot GA, Carvalho MA, Caputo SM, Vreeswijk MPG, Brown MA, Webb M, Rouleau E, Neuhausen SL, Hansen TVO, Galli A, Brandão RD, Blok MJ, Velkova A, Couch FJ, Monteiro ANA. A guide for functional analysis of BRCA1 variants of uncertain significance. Hum Mutat 2012; 33:1526-37. [PMID: 22753008 DOI: 10.1002/humu.22150] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2012] [Accepted: 05/29/2012] [Indexed: 12/12/2022]
Abstract
Germline mutations in the tumor suppressor gene BRCA1 confer an estimated lifetime risk of 56-80% for breast cancer and 15-60% for ovarian cancer. Since the mid 1990s when BRCA1 was identified, genetic testing has revealed over 1,500 unique germline variants. However, for a significant number of these variants, the effect on protein function is unknown making it difficult to infer the consequences on risks of breast and ovarian cancers. Thus, many individuals undergoing genetic testing for BRCA1 mutations receive test results reporting a variant of uncertain clinical significance (VUS), leading to issues in risk assessment, counseling, and preventive care. Here, we describe functional assays for BRCA1 to directly or indirectly assess the impact of a variant on protein conformation or function and how these results can be used to complement genetic data to classify a VUS as to its clinical significance. Importantly, these methods may provide a framework for genome-wide pathogenicity assignment.
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Affiliation(s)
- Gaël A Millot
- Institut Curie, CNRS, UMR 3244 Université Pierre et Marie Curie, Paris, France
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Flanagan JM, Cocciardi S, Waddell N, Johnstone CN, Marsh A, Henderson S, Simpson P, da Silva L, Khanna K, Lakhani S, Boshoff C, Chenevix-Trench G. DNA methylome of familial breast cancer identifies distinct profiles defined by mutation status. Am J Hum Genet 2010; 86:420-33. [PMID: 20206335 DOI: 10.1016/j.ajhg.2010.02.008] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2009] [Revised: 02/03/2010] [Accepted: 02/08/2010] [Indexed: 01/21/2023] Open
Abstract
It is now understood that epigenetic alterations occur frequently in sporadic breast carcinogenesis, but little is known about the epigenetic alterations associated with familial breast tumors. We performed genome-wide DNA-methylation profiling on familial breast cancers (n = 33) to identify patterns of methylation specific to the different mutation groups (BRCA1, BRCA2, and BRCAx) or intrinsic subtypes of breast cancer (basal, luminal A, luminal B, HER2-amplified, and normal-like). We used methylated DNA immunoprecipitation (MeDIP) on Affymetrix promoter chips to interrogate methylation profiles across 25,500 distinct transcripts. Using a support vector machine classification algorithm, we demonstrated that genome-wide methylation profiles predicted tumor mutation status with estimated error rates of 19% (BRCA1), 31% (BRCA2), and 36% (BRCAx) but did not accurately predict the intrinsic subtypes defined by gene expression. Furthermore, using unsupervised hierarchical clustering, we identified a distinct subgroup of BRCAx tumors defined by methylation profiles. We validated these findings in the 33 tumors in the test set, as well as in an independent validation set of 47 formalin-fixed, paraffin-embedded familial breast tumors, by pyrosequencing and Epityper. Finally, gene-expression profiling and SNP CGH array previously performed on the same samples allowed full integration of methylation, gene-expression, and copy-number data sets, revealing frequent hypermethylation of genes that also displayed loss of heterozygosity, as well as of genes that show copy-number gains, providing a potential mechanism for expression dosage compensation. Together, these data show that methylation profiles for familial breast cancers are defined by the mutation status and are distinct from the intrinsic subtypes.
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Affiliation(s)
- James M Flanagan
- CRUK Viral Oncology Group, UCL Cancer Institute, London WC1E 6BT, UK.
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Welsh M, Mangravite L, Medina MW, Tantisira K, Zhang W, Huang RS, McLeod H, Dolan ME. Pharmacogenomic discovery using cell-based models. Pharmacol Rev 2010; 61:413-29. [PMID: 20038569 DOI: 10.1124/pr.109.001461] [Citation(s) in RCA: 99] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.
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Affiliation(s)
- Marleen Welsh
- Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA
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Use of DNA-damaging agents and RNA pooling to assess expression profiles associated with BRCA1 and BRCA2 mutation status in familial breast cancer patients. PLoS Genet 2010; 6:e1000850. [PMID: 20174566 PMCID: PMC2824809 DOI: 10.1371/journal.pgen.1000850] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2009] [Accepted: 01/19/2010] [Indexed: 01/12/2023] Open
Abstract
A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory-based methods that can distinguish between carriers of pathogenic mutations and non-carriers are likely to have utility for the classification of these sequence variants. 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 was 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. 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. A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory methods to identify which of these variants are mutations would have utility for counseling and clinical decision making when identified in patients with a family history of breast cancer. We used DNA–damaging agents to disturb gene expression profiles of cell-lines derived from blood of patients, and we compared patterns from women with BRCA1 and BRCA2 mutations to women familial breast cancer families without such mutations. Using a pooling strategy, which allowed us to compare several treatments at one time, we identified which treatment caused the greatest difference in gene-expression changes between patient groups and used this treatment method for further study. We were able to accurately classify BRCA1 and BRCA2 samples, and our results supported other reported findings that suggested familial breast cancer patients without BRCA1/2 mutations are genetically heterogeneous. We demonstrate a useful strategy to identify treatments that induce gene expression differences associated with BRCA1/2 mutation status. This strategy may aid the development of a molecular-based tool to screen individuals from multi-case breast cancer families for the presence of pathogenic mutations.
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