Associations of breast cancer risk prediction tools with tumor characteristics and metastasis

Purpose: The association between established risk factors for breast cancer and subtypes or prognosis of the disease is not well known. We analyzed whether the Tyrer-Cuzick–predicted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide polymorphism polygenic risk score (PRS) were associated with breast cancer tumor prognosticators and risk of distant metastasis. Patients and Methods: We used a case-only design in a population-based cohort of 5,500 Swedish patients with breast cancer. Logistic and multinomial logistic regression of outcomes, estrogen receptor (ER) status, lymph node involvement, tumor size, and grade was performed with TCRS, PRS, and percent MD as exposures. Cox proportional hazard models were used to estimate hazard ratios (HRs) of distant metastasis. Results: Women at high risk for breast cancer based on PRS and/or TCRS were significantly more likely to be diagnosed with favorable prognosticators, such as ER-positive and low-grade tumors. In contrast, PRS weighted on ER-negative disease was associated with ER-negative tumors. When stratifying by age, the associations of TCRS with favorable prognosticators were restricted to women younger than age 50. Women scoring high in both TCRS and PRS had a lower risk of distant metastasis (HR, 0.69; 95% CI, 0.49 to 0.98). MD was not associated with any of the examined prognosticators. Conclusion: Women at high risk for breast cancer based on genetic and lifestyle factors were significantly more likely to be diagnosed with breast cancers with a favorable prognosis. Better knowledge of subtype- specific risk factors could be vital for the success of prevention programs aimed at lowering mortality.Swedish Research CouncilSwedish Cancer SocietyCancer Society in StockholmCancer Risk Prediction Center (CRisP)Linneus Centre - Swedish Research CouncilPublishe

Breast cancer genetic risk profile is differentially associated with interval and screen-detected breast cancers

Background: Polygenic risk profiles computed from multiple common susceptibility alleles for breast cancer have been shown to identify women at different levels of breast cancer risk. We evaluated whether this genetic risk stratification can also be applied to discriminate between screen-detected and interval cancers, which are usually associated with clinicopathological and survival differences. Patients and methods: A 77-SNP polygenic risk score (PRS) was constructed for breast cancer overall and by estrogen-receptor (ER) status. PRS was inspected as a continuous (per standard deviation increment) variable in a case-only design. Modification of the PRS by mammographic density was evaluated by fitting an additional interaction term. Results: PRS weighted by breast cancer overall estimates was found to be differentially associated with 1,865 screen-detected and 782 interval cancers in the LIBRO-1 study (age-adjusted ORperSD [95% confidence interval]=0.91 [0.83-0.99], p=0.023). The association was found to be more significant for PRS weighted by ER-positive breast cancer estimates (ORperSD=0.90 [0.82-0.98], p=0.011). This result was corroborated by two independent studies (combined ORperSD=0.87 [0.76-1.00], p=0.058) with no evidence of heterogeneity. When enriched for “true” interval cancers among nondense breasts, the difference in the association with PRS in screen-detected and interval cancers became more pronounced (ORperSD=0.74 [0.62-0.89], p=0.001), with a significant interaction effect between PRS and mammographic density (pinteraction=0.017). Conclusion: To our knowledge, this is the first report looking into the genetic differences between screendetected and interval cancers. It is an affirmation that the two types of breast cancer may have unique underlying biology.Swedish Research CouncilSwedish Cancer SocietyStockholm County CouncilBreast Cancer Theme Centre Consortium (BRECT)Accepte

Background risk of breast cancer and the association between physical activity and mammographic density

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A Common Variant at the 14q32 Endometrial Cancer Risk Locus Activates AKT1 through YY1 Binding.

A recent meta-analysis of multiple genome-wide association and follow-up endometrial cancer case-control datasets identified a novel genetic risk locus for this disease at chromosome 14q32.33. To prioritize the functional SNP(s) and target gene(s) at this locus, we employed an in silico fine-mapping approach using genotyped and imputed SNP data for 6,608 endometrial cancer cases and 37,925 controls of European ancestry. Association and functional analyses provide evidence that the best candidate causal SNP is rs2494737. Multiple experimental analyses show that SNP rs2494737 maps to a silencer element located within AKT1, a member of the PI3K/AKT/MTOR intracellular signaling pathway activated in endometrial tumors. The rs2494737 risk A allele creates a YY1 transcription factor-binding site and abrogates the silencer activity in luciferase assays, an effect mimicked by transfection of YY1 siRNA. Our findings suggest YY1 is a positive regulator of AKT1, mediating the stimulatory effects of rs2494737 increasing endometrial cancer risk. Identification of an endometrial cancer risk allele within a member of the PI3K/AKT signaling pathway, more commonly activated in tumors by somatic alterations, raises the possibility that well tolerated inhibitors targeting this pathway could be candidates for evaluation as chemopreventive agents in individuals at high risk of developing endometrial cancer.The QIMR Berghofer groups were supported by a Rio Tinto Ride to Conquer Cancer (RTCC)/Weekend to End Women's Cancers (WEWC) Grant and NHMRC project grants 1058415 to SLE and 1031333 to ABS. ABS is supported by an NHMRC Senior Research Fellowship (1061779). DFE is a Principal Research Fellow of CR-UK.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Cell Press

A comprehensive evaluation of the role of genetic variation in follicular lymphoma survival

Abstract Background: Survival in follicular lymphoma (FL) is highly variable, even within prognostic groups defined by tumor grade and the Follicular Lymphoma International Prognostic Index. Studies suggest that germline single nucleotide polymorphisms (SNPs) may hold prognostic information but further investigation is needed. Methods: We explored the association between SNPs and FL outcome using two approaches: 1) Two independent genome-wide association studies (GWAS) of~300.000 SNPs followed by a meta-analysis encompassing 586 FL patients diagnosed in Denmark/Sweden 1999-2002 and in the United States 2001-2006; and 2) Investigation of 22 candidate-gene variants previously associated with FL outcome in the Danish/Swedish cohort (N = 373). We estimated time to lymphoma-specific death (approach 1 and 2) and lymphoma progression (approach 2) with hazard ratios (HR) and 95% confidence intervals (CI) in a multivariable Cox regression model. Results: In the GWAS meta-analysis, using a random effects model, no variants were associated with lymphoma-specific death at a genome-wide significant level (p < 5.0 ×1

Multi-Variant Pathway Association Analysis Reveals the Importance of Genetic Determinants of Estrogen Metabolism in Breast and Endometrial Cancer Susceptibility

Peer reviewe

A genome-wide association scan on estrogen receptor-negative breast cancer.

INTRODUCTION: Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk. METHODS: We conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases. RESULTS: Association with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer shares a polygenic basis to disease with ER-positive breast cancer. CONCLUSIONS: ER-negative breast cancer is a distinct breast cancer subtype that merits independent analyses. Given the clinical importance of this phenotype and the likelihood that genetic effect sizes are small, greater sample sizes and further studies are required to understand the etiology of ER-negative breast cancers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer

Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86x10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76x10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types

Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation.

GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the 'iCOGS' genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against >100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84-0.87; P=1.7 × 10(-43)) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology