Genetic determinants of breast cancer

Breast cancer is the most common malignancy in women in the Western world and it is estimated that women who survive to the age of 85 years will have a 1 in 9 lifetime probability of developing this type of neoplasia (1, 2). The degree of risk is not spread homogeneously across the general population (2). The vast majority of risk factors associated to breast cancer susceptibility are related to hormonal exposure, either from endogenous sources such as early age at menarche, late age at menopause, late pregnancy or nullliparity, overweight and obesity, or exogenous sources such as the use of hormone replacement therapy (HRT) (3). Other risk factors include alcohol intake, radiation exposure, current age, past history of breast cancer and the history of a breast biopsy (2). Additionally, a recent study has shown that the risk of breast cancer is increased by 3% per pack/year of cigarette smoking when it is done between menarche and first childbirth (4)

Impact of TGF-ß1 -509C/T and 869T/C polymorphisms on glioma risk and patient prognosis

Transforming growth factor beta (TGF-ß) plays an important role in carcinogenesis. Two polymorphisms in the TGF-ß1 gene (-509C/T and 869T/C) were described to influence susceptibility to gastric and breast cancers. The 869T/C polymorphism was also associated with overall survival in breast cancer patients. In the present study, we investigated the relevance of these TGF-ß1 polymorphism in glioma risk and prognosis. A case-control study that included 114 glioma patients and 138 cancer-free controls was performed. Single nucleotide polymorphisms (SNPs) were evaluated by polymerase chain reaction followed by restriction fragment length polymorphism (PCR-RFLP). Univariate and multivariate logistic regression analyses were used to calculate odds ratio (OR) and 95 % confidence intervals (95 % CI). The influence of TGF-ß1 -509C/T and 869T/C polymorphisms on glioma patient survival was evaluated by a Cox regression model adjusted for patients' age and sex and represented in Kaplan-Meier curves. Our results demonstrated that TGF-ß1 gene polymorphisms -509C/T and 869T/C are not significantly associated with glioma risk. Survival analyses showed that the homozygous -509TT genotype associates with longer overall survival of glioblastoma (GBM) patients when compared with patients carrying CC + CT genotypes (OR, 2.41; 95 % CI, 1.06-5.50; p = 0.036). In addition, the homozygous 869CC genotype is associated with increased overall survival of GBM patients when compared with 869TT + TC genotypes (OR, 2.62; 95 % CI, 1.11-6.17; p = 0.027). In conclusion, this study suggests that TGF-ß1 -509C/T and 869T/C polymorphisms are not significantly associated with risk for developing gliomas but may be relevant prognostic biomarkers in GBM patients.This work was supported by Fundação para a Ciência e Tecnologia, Portugal (PTDC/SAU-GMG/113795/2009 and SFRH/BPD/33612/2009 to B.M.C.; SFRH/BD/88121/2012 to J.V.C.; SFRH/BD/92786/2013 to C.S.G.; PTDC/SAU-ONC/115513/2009 to R.R.)

TGF-β1 genotype and phenotype in breast cancer and their associations with IGFs and patient survival

Transforming growth factor-β (TGF-β)-mediated signals play complicated roles in the development and progression of breast tumour. The purposes of this study were to analyse the genotype of TGF-β1 at T29C and TGF-β1 phenotype in breast tumours, and to evaluate their associations with IGFs and clinical characteristics of breast cancer. Fresh tumour samples were collected from 348 breast cancer patients. TGF-β1 genotype and phenotype were analysed with TaqMan® and ELISA, respectively. Members of the IGF family in tumour tissue were measured with ELISA. Cox proportional hazards regression analysis was performed to assess the association of TGF-β1 and disease outcomes. Patients with the T/T (29%) genotype at T29C had the highest TGF-β1, 707.9 pg mg−1, followed by the T/C (49%), 657.8 pg mg−1, and C/C (22%) genotypes, 640.8 pg mg−1, (P=0.210, T/T vs C/C and C/T). TGF-β1 concentrations were positively correlated with levels of oestrogen receptor, IGF-I, IGF-II and IGFBP-3. Survival analysis showed TGF-β1 associated with disease progression, but the association differed by disease stage. For early-stage disease, patients with the T/T genotype or high TGF-β1 had shorter overall survival compared to those without T/T or with low TGF-β1; the hazard ratios (HR) were 3.54 (95% CI: 1.21–10.40) for genotype and 2.54 (95% CI: 1.10–5.89) for phenotype after adjusting for age, grade, histotype and receptor status. For late-stage disease, however, the association was different. The T/T genotype was associated with lower risk of disease recurrence (HR=0.13, 95% CI: 0.02–1.00), whereas no association was found between TGF-β1 phenotype and survival outcomes. The study suggests a complex role of TGF-β1 in breast cancer progression, which supports the finding of in vitro studies that TGF-β1 has conflicting effects on tumour growth and metastasis

Genetic variation in insulin-like growth factor signaling genes and breast cancer risk among BRCA1 and BRCA2 carriers

Abstract Introduction Women who carry mutations in BRCA1 and BRCA2 have a substantially increased risk of developing breast cancer as compared with the general population. However, risk estimates range from 20 to 80%, suggesting the presence of genetic and/or environmental risk modifiers. Based on extensive in vivo and in vitro studies, one important pathway for breast cancer pathogenesis may be the insulin-like growth factor (IGF) signaling pathway, which regulates both cellular proliferation and apoptosis. BRCA1 has been shown to directly interact with IGF signaling such that variants in this pathway may modify risk of cancer in women carrying BRCA mutations. In this study, we investigate the association of variants in genes involved in IGF signaling and risk of breast cancer in women who carry deleterious BRCA1 and BRCA2 mutations. Methods A cohort of 1,665 adult, female mutation carriers, including 1,122 BRCA1 carriers (433 cases) and 543 BRCA2 carriers (238 cases) were genotyped for SNPs in IGF1, IGF1 receptor (IGF1R), IGF1 binding protein (IGFBP1, IGFBP2, IGFBP5), and IGF receptor substrate 1 (IRS1). Cox proportional hazards regression was used to model time from birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD) blocks with multiple SNPs, an additive genetic model was assumed; and for single SNP analyses, no additivity assumptions were made. Results Among BRCA1 carriers, significant associations were found between risk of breast cancer and LD blocks in IGF1R (global P = 0.011 for LD block 2 and global P = 0.012 for LD block 11). Among BRCA2 carriers, an LD block in IGFBP2 (global P = 0.0145) was found to be associated with the time to breast cancer diagnosis. No significant LD block associations were found for the other investigated genes among BRCA1 and BRCA2 carriers. Conclusions This is the first study to investigate the role of genetic variation in IGF signaling and breast cancer risk in women carrying deleterious mutations in BRCA1 and BRCA2. We identified significant associations in variants in IGF1R and IRS1 in BRCA1 carriers and in IGFBP2 in BRCA2 carriers. Although there is known to be interaction of BRCA1 and IGF signaling, further replication and identification of causal mechanisms are needed to better understand these associations

An empirical comparison of meta-analyses of published gene-disease associations versus consortium analyses

Purpose: Consortia of investigators currently compile sufficiently large sample sizes to investigate the effects of low-risk susceptibility genetic variants. It is not clear how the results obtained by consortia compare-with those derived from meta-analyses of published studies. Methods: We performed meta-analyses of published data for 16 genetic polymorphisms investigated by the Breast Cancer Association Consortium, and compared sample sizes, heterogeneity, and effect sizes. PubMed, Web of Science, and Human Gerome Epidemiology Network databases were searched for breast cancer case-control association studies. Results: We found that theta-analyses of published data and consortium analyses were based on substantially different data. Published data by nonconsortium teams amounted on average to 26.9% of all available data (range 3.0 -50.0%). Both approaches showed statistically significant decreased breast cancer risks for CASP8 D302H. The mesa-analyses of published data demonstrated statistically significant results for five other genes and the consortium analyses for two other genes, but the strength of this evidence, evaluated on the basis of the Venice criteria, was not strong. Conclusions: Because both approaches identified the same gene out of 16 candidates, the methods can be complimentary. The expense and complexity of consortium-based studies should be considered vis-a-vis the potential methodological limitations of synthesis of published studies. Genet Med 2009:11(3):153-162

Meta-analyses of genetic studies on major depressive disorder

The genetic basis of major depressive disorder (MDD) has been investigated extensively, but the identification of MDD genes has been hampered by conflicting results from underpowered studies. We review all MDD case -control genetic association studies published before June 2007 and perform meta-analyses for polymorphisms that had been investigated in at least three studies. The study selection and data extraction were performed in duplicate by two independent investigators. The 183 papers that met our criteria studied 393 polymorphisms in 102 genes. Twenty-two polymorphisms (6%) were investigated in at least three studies. Seven polymorphisms had been evaluated in previous meta-analyses, 5 of these had new data available. Hence, we performed meta-analyses for 20 polymorphisms in 18 genes. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Statistically significant associations were found for the APOE epsilon 2 (OR, 0.51), GNB3 825T (OR, 1.38), MTHFR 677T (OR, 1.20), SLC6A4 44 bp Ins/Del S (OR, 1.11) alleles and the SLC6A3 40 bpVNTR 9/10 genotype (OR, 2.06). To date, there is statistically significant evidence for six MDD susceptibility genes (APOE, DRD4, GNB3, MTHFR, SLC6A3 and SLC6A4)