| 1. |
- Couch, Fergus J., et al.
(författare)
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Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
- 2016
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
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| 2. |
- Ding, Yuan C, et al.
(författare)
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A nonsynonymous polymorphism in IRS1 modifies risk of developing breast and ovarian cancers in BRCA1 and ovarian cancer in BRCA2 mutation carriers
- 2012
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 21:8, s. 1362-1370
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: We previously reported significant associations between genetic variants in insulin receptor substrate 1 (IRS1) and breast cancer risk in women carrying BRCA1 mutations. The objectives of this study were to investigate whether the IRS1 variants modified ovarian cancer risk and were associated with breast cancer risk in a larger cohort of BRCA1 and BRCA2 mutation carriers.METHODS: IRS1 rs1801123, rs1330645, and rs1801278 were genotyped in samples from 36 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Data were analyzed by a retrospective cohort approach modeling the associations with breast and ovarian cancer risks simultaneously. Analyses were stratified by BRCA1 and BRCA2 status and mutation class in BRCA1 carriers.RESULTS: Rs1801278 (Gly972Arg) was associated with ovarian cancer risk for both BRCA1 (HR, 1.43; 95% confidence interval (CI), 1.06-1.92; P = 0.019) and BRCA2 mutation carriers (HR, 2.21; 95% CI, 1.39-3.52, P = 0.0008). For BRCA1 mutation carriers, the breast cancer risk was higher in carriers with class II mutations than class I mutations (class II HR, 1.86; 95% CI, 1.28-2.70; class I HR, 0.86; 95%CI, 0.69-1.09; P(difference), 0.0006). Rs13306465 was associated with ovarian cancer risk in BRCA1 class II mutation carriers (HR, 2.42; P = 0.03).CONCLUSION: The IRS1 Gly972Arg single-nucleotide polymorphism, which affects insulin-like growth factor and insulin signaling, modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers and breast cancer risk in BRCA1 class II mutation carriers.Impact: These findings may prove useful for risk prediction for breast and ovarian cancers in BRCA1 and BRCA2 mutation carriers.
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| 3. |
- Martrat, Griselda, et al.
(författare)
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Exploring the link between MORF4L1 and risk of breast cancer
- 2011
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Proteins encoded by Fanconi anemia (FA) and/or breast cancer (BrCa) susceptibility genes cooperate in a common DNA damage repair signaling pathway. To gain deeper insight into this pathway and its influence on cancer risk, we searched for novel components through protein physical interaction screens. Methods: Protein physical interactions were screened using the yeast two-hybrid system. Co-affinity purifications and endogenous co-immunoprecipitation assays were performed to corroborate interactions. Biochemical and functional assays in human, mouse and Caenorhabditis elegans models were carried out to characterize pathway components. Thirteen FANCD2-monoubiquitinylation-positive FA cell lines excluded for genetic defects in the downstream pathway components and 300 familial BrCa patients negative for BRCA1/2 mutations were analyzed for genetic mutations. Common genetic variants were genotyped in 9,573 BRCA1/2 mutation carriers for associations with BrCa risk. Results: A previously identified co-purifying protein with PALB2 was identified, MRG15 (MORF4L1 gene). Results in human, mouse and C. elegans models delineate molecular and functional relationships with BRCA2, PALB2, RAD51 and RPA1 that suggest a role for MRG15 in the repair of DNA double-strand breaks. Mrg15-deficient murine embryonic fibroblasts showed moderate sensitivity to g-irradiation relative to controls and reduced formation of Rad51 nuclear foci. Examination of mutants of MRG15 and BRCA2 C. elegans orthologs revealed phenocopy by accumulation of RPA-1 (human RPA1) nuclear foci and aberrant chromosomal compactions in meiotic cells. However, no alterations or mutations were identified for MRG15/MORF4L1 in unclassified FA patients and BrCa familial cases. Finally, no significant associations between common MORF4L1 variants and BrCa risk for BRCA1 or BRCA2 mutation carriers were identified: rs7164529, P-trend = 0.45 and 0.05, P-2df = 0.51 and 0.14, respectively; and rs10519219, P-trend = 0.92 and 0.72, P-2df = 0.76 and 0.07, respectively. Conclusions: While the present study expands on the role of MRG15 in the control of genomic stability, weak associations cannot be ruled out for potential low-penetrance variants at MORF4L1 and BrCa risk among BRCA2 mutation carriers.
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| 4. |
- Serra-Musach, Jordi, et al.
(författare)
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Cancer network activity associated with therapeutic response and synergism
- 2016
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Ingår i: Genome Medicine. - : BIOMED CENTRAL LTD. - 1756-994X. ; 8:88
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cancer patients often show no or only modest benefit from a given therapy. This major problem in oncology is generally attributed to the lack of specific predictive biomarkers, yet a global measure of cancer cell activity may support a comprehensive mechanistic understanding of therapy efficacy. We reasoned that network analysis of omic data could help to achieve this goal. Methods: A measure of "cancer network activity" (CNA) was implemented based on a previously defined network feature of communicability. The network nodes and edges corresponded to human proteins and experimentally identified interactions, respectively. The edges were weighted proportionally to the expression of the genes encoding for the corresponding proteins and relative to the number of direct interactors. The gene expression data corresponded to the basal conditions of 595 human cancer cell lines. Therapeutic responses corresponded to the impairment of cell viability measured by the half maximal inhibitory concentration (IC50) of 130 drugs approved or under clinical development. Gene ontology, signaling pathway, and transcription factor-binding annotations were taken from public repositories. Predicted synergies were assessed by determining the viability of four breast cancer cell lines and by applying two different analytical methods. Results: The effects of drug classes were associated with CNAs formed by different cell lines. CNAs also differentiate target families and effector pathways. Proteins that occupy a central position in the network largely contribute to CNA. Known key cancer-associated biological processes, signaling pathways, and master regulators also contribute to CNA. Moreover, the major cancer drivers frequently mediate CNA and therapeutic differences. Cell-based assays centered on these differences and using uncorrelated drug effects reveals novel synergistic combinations for the treatment of breast cancer dependent on PI3K-mTOR signaling. Conclusions: Cancer therapeutic responses can be predicted on the basis of a systems-level analysis of molecular interactions and gene expression. Fundamental cancer processes, pathways, and drivers contribute to this feature, which can also be exploited to predict precise synergistic drug combinations.
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