TERT-locus single nucleotide polymorphisms (SNPs) and leucocyte telomere measures are reportedly associated with risks of multiple cancers. Using the iCOGs chip, we analysed ~480 TERT-locus SNPs in breast (n=103,991), ovarian (n=39,774) and BRCA1 mutation carrier (11,705) cancer cases and controls. 53,724 participants have leucocyte telomere measures. Most associations cluster into three independent peaks. Peak 1 SNP rs2736108 minor allele associates with longer telomeres (P=5.8×10 −7 ), reduced estrogen receptor negative (ER-negative) (P=1.0×10 −8 ) and BRCA1 mutation carrier (P=1.1×10 −5 ) breast cancer risks, and altered promoter-assay signal. Peak 2 SNP rs7705526 minor allele associates with longer telomeres (P=2.3×10 −14 ), increased low malignant potential ovarian cancer risk (P=1.3×10 −15 ) and increased promoter activity. Peak 3 SNPs rs10069690 and rs2242652 minor alleles increase ER-negative (P=1.2×10 −12 ) and BRCA1 mutation carrier (P=1.6×10 −14 ) breast and invasive ovarian (P=1.3×10 −11 ) cancer risks, but not via altered telomere length. The cancer-risk alleles of rs2242652 and rs10069690 respectively increase silencing and generate a truncated TERT splicevariant.

ABSTRACT:Recently, the SNPs rs11614913 in hsa-mir-196a2 and rs3746444 in hsa-mir-499 were reported to be associated with increased breast cancer risk, and the SNP rs2910164 in hsa-mir146a was shown to have an effect on age of breast cancer diagnosis. In order to further investigate the effect of these SNPs, we genotyped a total of 1894 breast cancer cases negative for diseasecausing mutations or unclassified variants in BRCA1 and BRCA2, and 2760 controls from Germany and Italy. We compared the genotype and allele frequencies of rs2910164, rs11614913 and rs3746444 in cases versus controls of the German and Italian series, and of the two series combined; we also investigated the effect of the three SNPs on age at breast cancer diagnosis. None of the performed analyses showed statistically significant results. In conclusion, our data suggested lack of association between SNPs rs2910164, rs11614913 and rs3746444 and breast cancer risk, or age at breast cancer onset.

Several unclassified variants (UVs) have been identified in splicing regions of disease-associated genes and their characterization as pathogenic mutations or benign polymorphisms is crucial for the understanding of their role in disease development. In this study, 24 UVs located at BRCA1 and BRCA2 splice sites were characterized by transcripts analysis. These results were used to evaluate the ability of nine bioinformatics programs in predicting genetic variants causing aberrant splicing (spliceogenic variants) and the nature of aberrant transcripts. Eleven variants in BRCA1 and 8 in BRCA2, including 8 not previously characterized at transcript level, were ascertained to affect mRNA splicing. Of these, 16 led to the synthesis of aberrant transcripts containing premature termination codons (PTCs), 2 to the up-regulation of naturally occurring alternative transcripts containing PTCs, and one to an in-frame deletion within the region coding for the DNA binding domain of BRCA2, causing the loss of the ability to bind the partner protein DSS1 and ssDNA. For each computational program, we evaluated the rate of non-informative analyses, i.e. those that did not recognize the natural splice sites in the wild-type sequence, and the rate of false positive predictions, i.e., variants incorrectly classified as spliceogenic, as a measure of their specificity, under conditions setting sensitivity of predictions to 100%. The programs that performed better were Human Splicing Finder and Automated Splice Site Analyses, both exhibiting 100% informativeness and specificity. For 10 mutations the activation of cryptic splice sites was observed, but we were unable to derive simple criteria to select, among the different cryptic sites predicted by the bioinformatics analyses, those actually used. Consistent with previous reports, our study provides evidences that in silico tools can be used for selecting splice site variants for in vitro analyses. However, the latter remain mandatory for the characterization of the nature of aberrant transcripts.

IntroductionPrevious studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium.MethodsA literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect.ResultsFifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease.ConclusionsAlthough no variants reached genome-wide significance (P <5 x 10−8), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0570-7) contains supplementary material, which is available to authorized users.

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