Novel genetic markers of breast cancer survival identified by a genome-wide association study

Machine learning reveals genetic modifiers of the immune microenvironment of cancer

Heritability in the immune tumor microenvironment (iTME) has been widely observed yet remains largely uncharacterized. Here, we developed a machine learning approach to map iTME modifiers within loci from genome-wide association studies (GWASs) for breast cancer (BrCa) incidence. A random forest model was trained on a positive set of immune-oncology (I-O) targets, and then used to assign I-O target probability scores to 1,362 candidate genes in linkage disequilibrium with 155 BrCa GWAS loci. Cluster analysis of the most probable candidates revealed two subfamilies of genes related to effector functions and adaptive immune responses, suggesting that iTME modifiers impact multiple aspects of anticancer immunity. Two of the top ranking BrCa candidates, LSP1 and TLR1, were orthogonally validated as iTME modifiers using BrCa patient biopsies and comparative mapping studies, respectively. Collectively, these data demonstrate a robust and flexible framework for functionally fine-mapping GWAS risk loci to identify translatable therapeutic targets.

A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study

Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mendelian randomization to examine associations between metabolic traits and breast cancer outcomes. In the Pathways Study of 3,902 patients and a median follow-up time of 10.5 years, we adapted a Mendelian randomization approach to calculate PGS for 55 metabolic traits and tested their associations with seven survival outcomes. Multivariable Cox proportional hazards models were used to derive HRs and 95% confidence intervals (CI) with adjustment for covariates. The highest tertile (T3) of PGS for cardiovascular disease was associated with shorter overall survival (HR = 1.34, 95% CI = 1.11-1.61) and second primary cancer-free survival (HR = 1.31, 95% CI = 1.12-1.53). PGS for hypertension (T3) was associated with shorter overall survival (HR = 1.20, 95% CI = 1.00-1.43), second primary cancer-free survival (HR = 1.24, 95% CI = 1.06-1.45), invasive disease-free survival (HR = 1.18, 95% CI = 1.01-1.38), and disease-free survival (HR = 1.21, 95% CI = 1.04-1.39). PGS for serum cystatin C levels (T3) was associated with longer disease-free survival (HR = 0.82, 95% CI = 0.71-0.95), breast event-free survival (HR = 0.74, 95% CI = 0.61-0.91), and breast cancer-specific survival (HR = 0.72, 95% CI = 0.54-0.95). The above associations were significant at a nominal P < 0.05 level but not after correcting for multiple testing (Bonferroni P < 0.0009). Our analyses revealed notable associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with breast cancer survival outcomes. These findings implicate metabolic traits in breast cancer prognosis.

Significance

To our knowledge, this is the largest study of PGS for metabolic traits with breast cancer prognosis. The findings revealed significant associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with several breast cancer survival outcomes. These findings implicate an underappreciated role of metabolic traits in breast cancer prognosis that would warrant further exploration.

Development and testing of a polygenic risk score for breast cancer aggressiveness

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

UACA locus is associated with breast cancer chemoresistance and survival

Few germline genetic variants have been robustly linked with breast cancer outcomes. We conducted trans-ethnic meta genome-wide association study (GWAS) of overall survival (OS) in 3973 breast cancer patients from the Pathways Study, one of the largest prospective breast cancer survivor cohorts. A locus spanning the UACA gene, a key regulator of tumor suppressor Par-4, was associated with OS in patients taking Par-4 dependent chemotherapies, including anthracyclines and anti-HER2 therapy, at a genome-wide significance level (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.27 \times 10^{ - 9}$$\end{document}P=1.27×10−9). This association was confirmed in meta-analysis across four independent prospective breast cancer cohorts (combined hazard ratio = 1.84, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.28 \times 10^{ - 11}$$\end{document}P=1.28×10−11). Transcriptome-wide association study revealed higher UACA gene expression was significantly associated with worse OS (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 4.68 \times 10^{ - 7}$$\end{document}P=4.68×10−7). Our study identified the UACA locus as a genetic predictor of patient outcome following treatment with anthracyclines and/or anti-HER2 therapy, which may have clinical utility in formulating appropriate treatment strategies for breast cancer patients based on their genetic makeup.

Using Linear Discriminant Analysis to Characterize Novel Single Nucleotide Polymorphisms and Expression Profile Changes in Genes of Three Breeds of Rabbit (Oryctolagus cuniculus)

The objectives of this study were to investigate polymorphisms and changes in expression patterns of the genes FGF5, PGAM2, TLR2 and IL10 in V-line, Baladi Black and Baladi Red rabbits. Blood samples were collected from 180 healthy rabbits (n = 60 for each breed) for DNA extraction and DNA sequencing. At 3 mo of age, 20 randomly selected females from each breed were euthanized for gene expression quantification in muscle and spleen samples. PCR-DNA sequencing revealed single nucleotide polymorphisms (SNPs) among the 3 breeds that provided a monomorphic pattern for 3 of the 4 genes analyzed. Linear discriminant analysis (LDA) was used to classify the SNPs of these genes in the 3 breeds. The overall percentage of correctly classified cases for the model was 75%, with percentages of 100% for FGF5, 63% for IL10, and 100% for TLR2. Breed was a significant predictor for gene classification with estimation (1.00). Expression profiles of the genes were higher in V-line as compared with Baladi Black or Baladi Red. The LDA discriminated the 3 breeds using results of the gene expression profile as predictors for classification. Overall, 73% of the cases were correctly classified by gene expression. The identified SNPs, along with changes in mRNA levels of FGF5, PGAM2, TLR2, and IL10, could provide a biomarker for efficient characterization of rabbit breeds and could thus help develop marker assisted selection for growth and immune traits in rabbits.

A Genome-Wide Association Study Identifying Genetic Variants Associated with Growth, Carcass and Meat Quality Traits in Rabbits

Simple Summary

Rabbit meat has been widely consumed in China and is considered as an ideal food source due to its high protein, low fat, low cholesterol and low sodium contents. The growth rate, carcass characteristics and meat quality are considered economically important traits in the rabbit industry. Genomic selection (GS) could facilitate genetic selection for important economic traits, however, the lack of molecular markers for these traits limits the application of GS in rabbits. Genome-wide association study (GWAS) has the potential to comprehensively identify trait-associated molecular markers and has been applied in animal and plant research. In this study, GWAS was used to examine growth, carcass and meat quality traits of meat rabbits based on specific-locus amplified fragment sequencing (SLAF-seq) technology to identify significantly associated SNPs and functional genes, to be used as a basis for prompting the application of GS in rabbits.

Abstract

Growth, carcass characteristics and meat quality are the most important traits used in the rabbit industry. Identification of the candidate markers and genes significantly associated with these traits will be beneficial in rabbit breeding. In this study, we enrolled 465 rabbits, including 16 male Californian rabbits and 17 female Kangda5 line rabbits as the parental generation, along with their offspring (232 male and 200 female), in a genome-wide association study (GWAS) based on SLAF-seq technology. Bodyweight at 35, 42, 49, 56, 63 and 70 d was recorded for growth traits; and slaughter liveweight (84 d) and dressing out percentage were measured as carcass traits; and cooking loss and drip loss were measured as meat quality traits. A total of 5,223,720 SLAF markers were obtained by digesting the rabbit genome using RsaI + EcoRV-HF^® restriction enzymes. After quality control, a subset of 317,503 annotated single-nucleotide polymorphisms (SNPs) was retained for subsequent analysis. A total of 28, 81 and 10 SNPs for growth, carcass and meat quality traits, respectively, were identified based on genome-wide significance (p < 3.16 × 10⁻⁷). Additionally, 16, 71 and 9 candidate genes were identified within 100 kb upstream or downstream of these SNPs. Further analysis is required to determine the biological roles of these candidate genes in determining rabbit growth, carcass traits and meat quality.

A functional variant near XCL1 gene improves breast cancer survival via promoting cancer immunity

Most genome-wide association studies (GWASs) identify genetic variants for breast cancer occurrence. In contrast, few are for recurrence and mortality. We conducted a GWAS on breast cancer survival after diagnosis in estrogen receptor-positive patients, including 953 Taiwanese patients with 159 events. Through Cox proportional hazard models estimation, we identified 24 risk SNPs with p < 1 × 10^-5 . Based on imputation and integrated analysis, one SNP, rs1024176 (located in 1q24.2, p = 2.43 × 10^-5 ) was found to be a functional variant associated with breast cancer survival and XCL1 gene expression. A series of experimental approaches, including cell-based analyses and CRISPR/Cas9 genome-editing system, were then used and identified the transcription factor MYBL2 was able to discriminately bind to the A allele of rs1024176, the protective variant for breast cancer survival, which promoted XCL1 expression, but not to the G allele of rs1024176. The chemokine XCL1 attracts type 1 dendritic cells (DC1s) to the tumor microenvironment. In breast cancer tissues, we applied a two-step Mendelian randomization analysis, using expression quantitative trait loci as instrumental variables, to confirm higher XCL1 expression was correlated with higher DC1 signatures and favorable disease progression, through the causal effect of rs1024176-A allele. Our study supports the genetic effect on preventing breast cancer survival through XCL1-induced DC1 recruitment in tumor microenvironment.

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) Gene Variants with Predisposition to Age-Related Macular Degeneration

Background

Age-related macular degeneration (AMD) is a progressive neurodegenerative disease of a central part of the neural retina (macula) and a leading cause of blindness in elderly people. While it is known that the AMD is a multifactorial disease, genetic factors involved in lipid metabolism, inflammation, and neovascularization are currently being widely studied in genome-wide association studies (GWAS). The aim of our study was to evaluate the impact of new single nucleotide polymorphisms (SNPs) in RAD51B, TRIB1, COL8A1, and COL10A1 genes on AMD development.

Methods

Case-control study involved 254 patients diagnosed with early AMD, 244 patients with exudative AMD, and 942 control subjects. The genotyping of RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) was carried out using TaqMan assays by a real-time polymerase chain reaction (RT-PCR) method.

Results

Statistically significant difference was found in genotype (TT, TC, and CC) distribution of COL8A1 rs13095226 between exudative AMD and control groups (60.2%, 33.6%, and 6.1% vs. 64.9%, 32.3%, and 2.9%, respectively, p = 0.036). Also, comparing with TT+TC, rs13095226 CC genotype was associated with 3.5-fold increased odds of exudative AMD development (OR = 3.540; 95% CI: 1.415-8.856; p = 0.007).

Conclusion

Our study revealed a strong association between a variant in COL8A1 (rs13095226) and exudative AMD development.

Genome-Wide Association Study Identifies a Genetic Prediction Model for Postoperative Survival in Patients with Hepatocellular Carcinoma

Background

As an important aspect of tumor heterogeneity, genetic variation may influence susceptibility and prognosis in different types of cancer. By exploring the prognostic value of genetic variation, this study aimed to establish a model for predicting postoperative survival and assessing the impact of variation on clinical outcomes in patients with hepatocellular carcinoma (HCC).

Material/Methods

A genome-wide association study of 367 patients with HCC was conducted to identify single nucleotide polymorphisms (SNPs) associated with prognosis. Identified predictors were further evaluated in 758 patients. Two prognostic models were established using Cox proportional hazards regression and Nomogram strategy, and validated in another 316 patients. The effect of the SNP rs2431 was analyzed in detail.

Results

A prognostic model including 5 SNPs (rs10893585, rs2431, rs34675408, rs6078460, and rs6766361) was established and exhibited high predictive accuracy for HCC prognosis. The panel combined with tumor node metastasis (TNM) stage resulted in a significantly higher c-index (0.723) than the individual c-index values. Stratified by the Nomogram prediction model, the median overall survival for the low-risk and high-risk groups were 100.1 versus 30.8 months (P<0.001) in the training set and 82.2 versus 22.5 months (P<0.001) in the validation set. A closer examination of rs2431 revealed that it may regulate the expression of FNDC3B by disrupting a microRNA-binding site.

Conclusions

This study established prediction models based on genetic factors alone or in combination with TNM stage for postoperative survival in patients with HCC, and identified FNDC3B as a potential therapeutic target for combating HCC metastasis.

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND

We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

METHODS

Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

RESULTS

We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

CONCLUSIONS

We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Polymorphisms in Survivin (BIRC5 Gene) Are Associated with Age of Onset in Breast Cancer Patients

Survivin, encoded by BIRC5 gene (baculoviral IAP repeat containing 5), belongs to the family of inhibitors of apoptosis proteins (IAPs). In mammalian cells it participates in the control of mitosis, apoptosis regulation, and cellular stress response. Its expression is increased in almost all types of cancers. The aim of this study was to investigate the role of BIRC5 polymorphisms in breast cancer (BC) and to connect survivin expression with various clinicopathological characteristics of BC patients. Blood and archival tumour tissue samples were collected from 26 BC patients from Croatia. Survivin expression was determined immunohistochemically. BIRC5 promoter, coding region, and 3'UTR were genotyped. DNA from 74 healthy women was used as control. BIRC5 polymorphisms and survivin expression were tested against age of onset, histological grade, tumour type and size, lymph node status, oestrogen, progesterone, Her2, and Ki67 status. Numbers of samples with weak, moderate, and strong survivin expression were 9 (33.3%), 11 (40.7%), and 7 (25.9%), respectively. Most patients had nuclear survivin staining (92.6%). High survivin expression was significantly associated with negative oestrogen receptor status (p=0.007) and positive Ki67 expression (p=0.032). Ki67 expression was also positively correlated with histological grade (p=0.0009). Fourteen polymorphisms were found in BC samples, located mostly in promoter and 3'UTR of BIRC5. There was no significant difference in the distribution of polymorphisms between BC and control samples. Among clinicopathological characteristics of BC patients, alleles of five BIRC5 polymorphisms were associated with younger age of onset: c.-644T>C (55.8 years [y] vs. 48.1 y; p=0.006), c.-241C>T (54.2 y vs. 45.0; p=0.029), c.9809T>C (55.8 y vs. 48.1 y; p=0.006), c.-1547C>T (58.3 y vs. 50.9 y; p=0.011), and c.9386T>C (50.8 y vs. 59.5 y; p=0.004). To assess the significance of BIRC5 polymorphisms and survivin expression as predictive and prognostic biomarkers for BC further research with a larger sample size is needed.

Bridging the gap by discerning SNPs in linkage disequilibrium and their role in breast cancer

Breast Cancer is the most common cancer among women with several genes involved in disease susceptibility. As majority of genome-wide significant variants fall outside the coding region, it is likely that some of them alter specific gene functions. GWAS database was used to interpret the regulatory functions of these genetic variants. A total of 320 SNPs for breast cancer were selected via GWAS, which were entered into the SNAP web portal tool, to determine the one's found to be in Linkage Disequilibrium (r² < 0.80). The resulting 2024 proxy SNP's were processed in RegulomeDB to predict their regulatory role. Of these, 1440 produced a score ranging from 1-6, whereas the remaining produced no data. Only the variants under score 4 (cut-off value) in RegulomeDB has been studied further. From these variants, 221 had scores of less than 4, indicating a high degree of potential regulatory role associated with them. Further study revealed that 61 of the 221 SNPs were reported to be genome-wide significant for breast cancer, 52 to be associated with other diseases, 99 as unconfirmed for association with breast cancer, leaving only 9 to be novel proxy SNPs linked to breast cancer. Therefore, the study further confirmed postulation of non-coding variants being linked to disease risk thereby, requiring additional validation through genome-wide association studies to substantiate their underlying mechanism.

Genome-wide association study identifies the GLDC/IL33 locus associated with survival of osteosarcoma patients

Survival rates for osteosarcoma, the most common primary bone cancer, have changed little over the past three decades and are particularly low for patients with metastatic disease. We conducted a multi-institutional genome-wide association study (GWAS) to identify germline genetic variants associated with overall survival in 632 patients with osteosarcoma, including 523 patients of European ancestry and 109 from Brazil. We conducted a time-to-event analysis and estimated hazard ratios (HR) and 95% confidence intervals (CI) using Cox proportional hazards models, with and without adjustment for metastatic disease. The results were combined across the European and Brazilian case sets using a random-effects meta-analysis. The strongest association after meta-analysis was for rs3765555 at 9p24.1, which was inversely associated with overall survival (HR = 1.76; 95% CI 1.41-2.18, p = 4.84 × 10-7 ). After imputation across this region, the combined analysis identified two SNPs that reached genome-wide significance. The strongest single association was with rs55933544 (HR = 1.9; 95% CI 1.5-2.4; p = 1.3 × 10-8 ), which localizes to the GLDC gene, adjacent to the IL33 gene and was consistent across both the European and Brazilian case sets. Using publicly available data, the risk allele was associated with lower expression of IL33 and low expression of IL33 was associated with poor survival in an independent set of patients with osteosarcoma. In conclusion, we have identified the GLDC/IL33 locus on chromosome 9p24.1 as associated with overall survival in patients with osteosarcoma. Further studies are needed to confirm this association and shed light on the biological underpinnings of this susceptibility locus.

PSMD7 downregulation induces apoptosis and suppresses tumorigenesis of esophageal squamous cell carcinoma via the mTOR/p70S6K pathway

PSMD7, a 19S proteasome subunit, is overexpressed in most carcinoma cells. It forms a dimer with PSMD14 that functions in the removal of attached ubiquitin chain. However, there is little knowledge about the cellular mechanism of PSMD7 and its exact biological function, especially in cancer cells. In this study, we explored the role of PSMD7 in proliferation, cell cycle, apoptosis, and proteasomal proteolysis in the esophageal squamous cell carcinoma (ESCC) cell line EC9706. Our results showed that PSMD7 was highly expressed in ESCC cells. Downregulation of PSMD7 by lentivirus‐mediated shRNA led to decreased proliferation, increased cell apoptosis, and reduced proteasomal function. Notably, lower expression level of mTOR and p70S6K and suppressed activity of mTOR/p70S6K pathway were detected after PSMD7 downregulation. By contrast, increased expression of p‐mTOR^Ser2448 and p‐p70S6K^{Thr421/Ser424} was discovered upon PSMD7 overexpression in Het‐1A cells. Furthermore, PSMD7 downregulation contributed to decelerated tumor growth, inhibition of proteasomal function, induced cell apoptosis and attenuated activity of mTOR/p70S6K pathway in vivo. These findings suggest that PSMD7 and the mTOR/p70S6K pathway may be a promising candidate for developing therapies for ESCC.

Association between 8q24 (rs13281615 and rs6983267) polymorphism and breast cancer susceptibility: a meta-analysis involving 117,355 subjects

Published data on the association between 8q24 polymorphism and breast cancer (BC) risk are inconclusive. Thus, we conducted a meta-analysis to evaluate the relationship between 8q24 (rs13281615 and rs6983267) polymorphism and BC risk. We searched PubMed, EMBASE, Web of Science and the Cochrane Library up to August 13, 2015 for relevant studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the strength of associations. Twenty-six studies published from 2008 to 2014, with a total of 52,683 cases and 64,672 controls, were included in this meta-analysis. The pooled results showed that there was significant association between 8q24 rs13281615 polymorphism and BC risk in any genetic model. In the subgroup analysis by ethnicity, the effects remained in Asians and Caucasians. However, no genetic models reached statistical association in Africans. There was no association in any genetic model in rs6983267. This meta-analysis suggests that 8q24 rs13281615 polymorphism is a risk factor for susceptibility to BC in Asians, Caucasians and in overall population, While, there was no association in Africans. The rs6983267 polymorphism has no association with BC risk in any genetic model. Further large scale multicenter epidemiological studies are warranted to confirm this finding.

OCA2 rs4778137 polymorphism predicts survival of breast cancer patients receiving neoadjuvant chemotherapy

BACKGROUND

Genome-wide association study (GWAS) studies have showed that single nucleotide polymorphisms (SNPs) in OCA2 gene were associated with the survival of breast cancer patients treated with adjuvant chemotherapy. To further explain the association between OCA2 SNPs and breast cancer survival, we investigated the predictive value of rs4778137 located in OCA2 in local advanced breast cancer patients receiving neoadjuvant chemotherapy.

PATIENTS AND METHODS

A case-cohort with 150 breast cancer patients was performed to evaluate the effects of the OCA2 rs4778137 on breast cancer survival. The association between rs4778137 genotypes and pathological complete response (pCR, defined that the postoperative pathology indicating no residual invasive breast cancer in the breast or the axillary lymph node) were analyzed. Logistic regression analysis was performed to identify the independent predictors of pCR. Survival was assessed by Kaplan-Meier method and Cox regression analysis according to the rs4778137 genotypes.

RESULTS

The differences between pCR and the rs4778137 genotypes were statistically significant (p < 0.05). The patients with genotype GG harbored a better disease-free survival (HR: 2.358, p = 0.000) and overall survival (HR: 1.578, p = 0.008) than the patients with genotype CC in rs4778137. The further Univariate and Multivariate survival analysis revealed that SNP rs4778137 was an independent predictive factor of disease-free survival (p = 0.000/p = 0.001) and overall survival (p = 0.006/p = 0.045).

CONCLUSION

The OCA2 rs4778137 may be a predictor for the clinical response and survival in local advanced breast cancer patients who received neoadjuvant chemotherapy.

Association of high-evidence gastric cancer susceptibility loci and somatic gene expression levels with survival

Eleven high-evidence single-nucleotide polymorphisms (SNPs) at nine loci for gastric cancer (GC) risk were reported, but their associations with survival remain unknown. In this study, we examined associations between SNP and GC survival by anatomic location and histology among 1147 incident cases from the Shanxi Upper Gastrointestinal Genetics Project. We further examined whether SNPs were expression quantitative trait loci in normal and tumor gastric tissues, and whether tumor versus normal somatic mRNA differences in 126 cases were associated with survival. No SNPs were associated with GC survival overall. However, subtype-specific associations were observed for gastric cardia adenocarcinomas at MUC1/TRIM46/1q22 rs2070803 [HRAA versus GA+GG = 2.16; 95% confidence interval (CI) = 1.24-3.78; P = 0.0068] and LTA/TNF/6p21.33 rs1799724 (HRTT+CT versus CC = 1.30; 95% CI = 1.07-1.57; P = 0.0077), and for diffuse-type GC at PSCA/8q24.3 rs2294008 (HRTT versus CT+CC = 1.99; 95% CI = 1.33-2.97; P = 7.8E-04). Rs2294008T was a cis-expression quantitative trait loci for PSCA, upregulating mRNA in normal gastric (β = 0.60; P = 5.7E-21) and GC (β = 0.30; P = 0.0089) tissues. Cases in the highest quartile (the smallest downregulation of tumor PSCA) had shortest survival than cases with the most downregulated PSCA (median survival of 0.47 years in the highest quartile versus 3.73 years in the lowest quartile; hazard ratio = 9.70; 95% CI = 2.46-38.4; P = 0.0012). Less striking effects for mRNA levels were observed for MTX1 at 1q22 in gastric cardia adenocarcinoma and for JRK at 8q24.3 in diffuse GC. Our results suggest three high-evidence GC risk loci have prognostic importance in GC subtypes. Future studies in well-characterized independent populations are warranted to validate our findings and further investigate the clinical utility of these variants in predicting GC prognosis.

Rethinking ovarian cancer genomics: where genome-wide association studies stand?

Genome-wide association studies (GWAS) allow the finding of genetic variants associated with several traits. Regarding ovarian cancer (OC), 15 GWAS have been conducted since 2009, with the discovery of 49 SNPs associated with disease susceptibility and 46 with impact in the clinical outcome of patients (p < 5.00 × 10-2). Among them, 14 variants reached the genome-wide significance (p < 5.00 × 10−8). Despite the results obtained, they should be validated in independent sets. So far, five validation studies have been conducted which could confirm the association of 12 OC susceptibility SNPs. Consequently, post-GWAS studies are crucial unravel the biological plausibility of GWAS’ findings and the allelic spectrum of OC.

Assessment of the prognostic role of a 94-single nucleotide polymorphisms risk score in early breast cancer in the SIGNAL/PHARE prospective cohort: no correlation with clinico-pathological characteristics and outcomes

Background

Genome-wide association studies (GWAS) have to date identified 94 genetic variants (single nucleotide polymorphisms (SNPs)) associated with risk of developing breast cancer. A score based on the combined effect of the 94 risk alleles can be calculated to measure the global risk of breast cancer. We aimed to test the hypothesis that the 94-SNP-based risk score is associated with clinico-pathological characteristics, breast cancer subtypes and outcomes in early breast cancer.

Methods

A 94-SNP risk score was calculated in 8703 patients in the PHARE and SIGNAL prospective case cohorts. This score is the total number of inherited risk alleles based on 94 selected SNPs. Clinical data and outcomes were prospectively registered. Genotyping was obtained from a GWAS.

Results

The median 94-SNP risk score in 8703 patients with early breast cancer was 77.5 (range: 58.1–97.6). The risk score was not associated with usual prognostic and predictive factors (age; tumor, node, metastasis (TNM) status; Scarff-Bloom-Richardson grade; inflammatory features; estrogen receptor status; progesterone receptor status; human epidermal growth factor receptor 2 (HER2) status) and did not correlate with breast cancer subtypes. The 94-SNP risk score did not predict outcomes represented by overall survival or disease-free survival.

Conclusions

In a prospective case cohort of 8703 patients, a risk score based on 94 SNPs was not associated with breast cancer characteristics, cancer subtypes, or patients’ outcomes. If we hypothesize that prognosis and subtypes of breast cancer are determined by constitutional genetic factors, our results suggest that a score based on breast cancer risk-associated SNPs is not associated with prognosis.

Trial registration

PHARE cohort: NCT00381901, Sept. 26, 2006 – SIGNAL cohort: INCa RECF1098, Jan. 28, 2009

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0888-4) contains supplementary material, which is available to authorized users.

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods

INTRODUCTION

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients.

METHODS

This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation.

RESULTS

The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics.

CONCLUSION

Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Association of gene coding variation and resting metabolic rate in a multi-ethnic sample of children and adults

Background

Resting metabolic rates (RMR) vary across individuals. Understanding the determinants of RMR could provide biological insight into obesity and its metabolic consequences such as type 2 diabetes and cardiovascular diseases.

Methods

The present study measured RMR using reference standard indirect calorimetry and evaluated genetic variations from an exome array in a sample of children and adults (N = 262) predominantly of African and European ancestry with a wide range of ages (10 – 67 years old) and body mass indices (BMI; 16.9 – 56.3 kg/m² for adults, 15.1 – 40.6 kg/m2 for children).

Results

Single variant analysis for RMR identified suggestive loci on chromosomes 15 (rs74010762, TRPM1, p-value = 2.7 × 10−6), 1 (rs2358728 and rs2358729, SH3D21, p-values < 5.8x10−5), 17 (AX-82990792, DHX33, 5.5 × 10−5) and 5 (rs115795863 and rs35433829, C5orf33 and RANBP3L, p-values < 8.2 × 10−5). To evaluate the effect of low frequency variations with RMR, we performed gene-based association tests. Our most significant locus was SH3D21 (p-value 2.01 × 10−4), which also contained suggestive results from single-variant analyses. A further investigation of all variants within the reported genes for all obesity-related loci from the GWAS catalog found nominal evidence for association of body mass index (BMI- kg/m²)-associated loci with RMR, with the most significant p-value at rs35433754 (TNKS, p-value = 0.0017).

Conclusions

These nominal associations were robust to adjustment for BMI. The most significant variants were also evaluated using phenome-wide association to evaluate pleiotropy, and genetically predicted gene expression using the summary statistics implicated loci related to in obesity and body composition. These results merit further examination in larger cohorts of children and adults.

Electronic supplementary material

The online version of this article (doi:10.1186/s40608-017-0145-5) contains supplementary material, which is available to authorized users.

A polygenic risk score for breast cancer risk in a Taiwanese population

BACKGROUND

Multiple common variants identified by genome-wide association studies showed limited evidence of the risk of breast cancer in Taiwan. In this study, we analyzed the breast cancer risk in relation to 13 individual single-nucleotide polymorphisms (SNPs) identified by a GWAS in an Asian population.

METHODS

In total, 446 breast cancer patients and 514 healthy controls were recruited for this case-control study. In addition, we developed a polygenic risk score (PRS) including those variants significantly associated with breast cancer risk, and also evaluated the contribution of PRS and clinical risk factors to breast cancer using receiver operating characteristic curve (AUC).

RESULTS

Logistic regression results showed that nine individual SNPs were significantly associated with breast cancer risk after multiple testing. Among all SNPs, six variants, namely FGFR2 (rs2981582), HCN1 (rs981782), MAP3K1 (rs889312), TOX3 (rs3803662), ZNF365 (rs10822013), and RAD51B (rs3784099), were selected to create PRS model. A dose-response association was observed between breast cancer risk and the PRS. Women in the highest quartile of PRS had a significantly increased risk compared to women in the lowest quartile (odds ratio 2.26; 95% confidence interval 1.51-3.38). The AUC for a model which contained the PRS in addition to clinical risk factors was 66.52%, whereas that for a model which with established risk factors only was 63.38%.

CONCLUSIONS

Our data identified a genetic risk predictor of breast cancer in Taiwanese population and suggest that risk models including PRS and clinical risk factors are useful in discriminating women at high risk of breast cancer from those at low risk.

The Circadian Rhythm Gene Arntl2 Is a Metastasis Susceptibility Gene for Estrogen Receptor-Negative Breast Cancer

Breast cancer mortality is primarily due to metastasis rather than primary tumors, yet relatively little is understood regarding the etiology of metastatic breast cancer. Previously, using a mouse genetics approach, we demonstrated that inherited germline polymorphisms contribute to metastatic disease, and that these single nucleotide polymorphisms (SNPs) could be used to predict outcome in breast cancer patients. In this study, a backcross between a highly metastatic (FVB/NJ) and low metastatic (MOLF/EiJ) mouse strain identified Arntl2, a gene encoding a circadian rhythm transcription factor, as a metastasis susceptibility gene associated with progression, specifically in estrogen receptor-negative breast cancer patients. Integrated whole genome sequence analysis with DNase hypersensitivity sites reveals SNPs in the predicted promoter of Arntl2. Using CRISPR/Cas9-mediated substitution of the MOLF promoter, we demonstrate that the SNPs regulate Arntl2 transcription and affect metastatic burden. Finally, analysis of SNPs associated with ARNTL2 expression in human breast cancer patients revealed reproducible associations of ARNTL2 expression quantitative trait loci (eQTL) SNPs with disease-free survival, consistent with the mouse studies.

Estrogen receptor-negative (ER-) breast cancer is a highly malignant form of breast cancer with poor prognosis. Like most solid tumors, the mortality associated with ER- breast cancer is due to the development of secondary tumors, or metastases, in vital organs distant from the original breast tumor. ER- breast tumors, particularly those also lacking HER (human epidermal growth factor receptor) expression, are particularly deadly because unlike ER+ or HER+ breast cancers, targeted therapies have not yet been developed that can effectively reduce or eliminate tumor cells that have disseminated throughout the patient. Therefore, better understanding of the etiology of metastasis in ER- patients would potentially have a large clinical benefit by providing new targets to eradicate single tumor cells before they develop into metastases. A better understanding of metastasis etiology may also provide methods to prevent the conversion of these disseminated cells into life-threatening lesions. In this study, we demonstrate that a commonly used model of metastatic breast cancer is capable of identifying genes that play a role in the metastatic progression of ER- breast cancers. Furthermore, we identify the circadian rhythm gene, Arntl2, as a gene associated with inherited susceptibility for the development of metastatic lesions. These studies provide additional information regarding the mechanisms associated with metastasis in ER- breast cancers.

Single nucleotide variants in metastasis-related genes are associated with breast cancer risk, by lymph node involvement and estrogen receptor status, in women with European and African ancestry

Single nucleotide polymorphisms (SNPs) in pathways influencing lymph node (LN) metastasis and estrogen receptor (ER) status in breast cancer may partially explain inter-patient variability in prognosis. We examined 154 SNPs in 12 metastasis-related genes for associations with breast cancer risk, stratified by LN and ER status, in European-American (EA) and African-American (AA) women. Two-thousand six hundred and seventy-one women enrolled in the Women's Circle of Health Study were genotyped. Pathway analyses were conducted using the adaptive rank truncated product (ARTP) method, with p_ARTP  ≤ 0.10 as significant. Multi-allelic risk scores were created for the ARTP-significant gene(s). Single-SNP and risk score associations were modeled using logistic regression, with false discovery rate (FDR) P-value adjustment. Although single-SNP associations were not significant at p_FDR  < 0.05, several genes were significant in the ARTP analyses. In AA women, significant ARTP gene-level associations included CDH1 with LN+ (p_ARTP  = 0.10; multi-allelic OR = 1.13, 95%CI 1.07-1.19, p_FDR  = 0.0003) and SIPA1 with ER- breast cancer (p_ARTP  = 0.10; multi-allelic OR = 1.16, 95%CI 1.02-1.31, p_FDR  = 0.03). In EA women, MTA2 was associated with overall breast cancer risk (p_ARTP  = 0.004), regardless of ER status, and with LN- disease (p_ARTP  = 0.01). Also significant were SATB1 in ER- (p_ARTP  = 0.03; multi-allelic OR = 1.12, 95%CI 1.05-1.20, p_FDR  = 0.003) and KISS1 in LN- (p_ARTP  = 0.10; multi-allelic OR = 1.18, 95%CI 1.08-1.29, p_FDR  = 0.002) analyses. Among LN+ cases, significant ARTP associations were observed for SNAI1, CD82, NME1, and CTNNB1 (multi-allelic OR = 1.09, 95%CI 1.04-1.14, p_FDR  = 0.001). Our findings suggest that variants in several metastasis genes may affect breast cancer risk by LN or ER status, although verification in larger studies is required. © 2016 Wiley Periodicals, Inc.

Cytochrome P450 Allele CYP3A7*1C Associates with Adverse Outcomes in Chronic Lymphocytic Leukemia, Breast, and Lung Cancer

CYP3A enzymes metabolize endogenous hormones and chemotherapeutic agents used to treat cancer, thereby potentially affecting drug effectiveness. Here, we refined the genetic basis underlying the functional effects of a CYP3A haplotype on urinary estrone glucuronide (E1G) levels and tested for an association between CYP3A genotype and outcome in patients with chronic lymphocytic leukemia (CLL), breast, or lung cancers. The most significantly associated SNP was rs45446698, an SNP that tags the CYP3A7*1C allele; this SNP was associated with a 54% decrease in urinary E1G levels. Genotyping this SNP in 1,008 breast cancer, 1,128 lung cancer, and 347 CLL patients, we found that rs45446698 was associated with breast cancer mortality (HR, 1.74; P = 0.03), all-cause mortality in lung cancer patients (HR, 1.43; P = 0.009), and CLL progression (HR, 1.62; P = 0.03). We also found borderline evidence of a statistical interaction between the CYP3A7*1C allele, treatment of patients with a cytotoxic agent that is a CYP3A substrate, and clinical outcome (Pinteraction = 0.06). The CYP3A7*1C allele, which results in adult expression of the fetal CYP3A7 gene, is likely to be the functional allele influencing levels of circulating endogenous sex hormones and outcome in these various malignancies. Further studies confirming these associations and determining the mechanism by which CYP3A7*1C influences outcome are required. One possibility is that standard chemotherapy regimens that include CYP3A substrates may not be optimal for the approximately 8% of cancer patients who are CYP3A7*1C carriers.

Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.

A pilot genome-wide association study of breast cancer susceptibility loci in Indonesia

Genome-wide association studies (GWASs) of the entire genome provide a systematic approach for revealing novel genetic susceptibility loci for breast cancer. However, genetic association studies have hitherto been primarily conducted in women of European ancestry. Therefofre we here performed a pilot GWAS with a single nucleotide polymorphism (SNP) array 5.0 platform from Affymetrix® that contains 443,813 SNPs to search for new genetic risk factors in 89 breast cancer cases and 46 healthy women of Indonesian ancestry. The case-control association of the GWAS finding set was evaluated using PLINK. The strengths of allelic and genotypic associations were assessed using logistic regression analysis and reported as odds ratios (ORs) and P values; P values less than 1.00x10(-8) and 5.00x10(-5) were required for significant association and suggestive association, respectively. After analyzing 292,887 SNPs, we recognized 11 chromosome loci that possessed suggestive associations with breast cancer risk. Of these, however, there were only four chromosome loci with identified genes: chromosome 2p.12 with the CTNNA2 gene [Odds ratio (OR)=1.20, 95% confidence interval (CI)=1.13-1.33, P=1.08x10(-7)]; chromosome 18p11.2 with the SOGA2 gene (OR=1.32, 95%CI=1.17-1.44, P=6.88x10(-6)); chromosome 5q14.1 with the SSBP2 gene (OR=1.22, 95%CI=1.11-1.34, P=4.00x10(-5)); and chromosome 9q31.1 with the TEX10 gene (OR=1.24, 95%CI=1.12-1.35, P=4.68x10(-5)). This study identified 11 chromosome loci which exhibited suggestive associations with the risk of breast cancer among Indonesian women.

Inbreeding and homozygosity in breast cancer survival

Genome-wide association studies (GWASs) help to understand the effects of single nucleotide polymorphisms (SNPs) on breast cancer (BC) progression and survival. We performed multiple analyses on data from a previously conducted GWAS for the influence of individual SNPs, runs of homozygosity (ROHs) and inbreeding on BC survival. (I.) The association of individual SNPs indicated no differences in the proportions of homozygous individuals among short-time survivors (STSs) and long-time survivors (LTSs). (II.) The analysis revealed differences among the populations for the number of ROHs per person and the total and average length of ROHs per person and among LTSs and STSs for the number of ROHs per person. (III.) Common ROHs at particular genomic positions were nominally more frequent among LTSs than in STSs. Common ROHs showed significant evidence for natural selection (iHS, Tajima's D, Fay-Wu's H). Most regions could be linked to genes related to BC progression or treatment. (IV.) Results were supported by a higher level of inbreeding among LTSs. Our results showed that an increased level of homozygosity may result in a preference of individuals during BC treatment. Although common ROHs were short, variants within ROHs might favor survival of BC and may function in a recessive manner.

"Liquid biopsy"-ctDNA detection with great potential and challenges

Circulating tumor DNA (ctDNA) is now being extensively studied as it is a noninvasive "real-time" biomarker that can provide diagnostic and prognostic information before, during treatment and at progression. These include DNA mutations, epigenetic alterations and other forms of tumor-specific abnormalities such as microsatellite instability (MSI) and loss of heterozygosity (LOH). ctDNA is of great value in the process of cancer treatment. However, up to date, there is no strict standard considering the exact biomarker because the development and progression of cancer is extremely complicated. Also, results of the studies evaluating ctDNA are not consistent due to the different detection methods and processing. The major challenge is still assay sensitivity and specificity for analysis of ctDNA. This review mainly focuses on the tumor specific DNA mutations, epigenetic alterations as well as detecting methods of ctDNA. The advantages and disadvantages will also be discussed.

Polymorphism at 19q13.41 Predicts Breast Cancer Survival Specifically after Endocrine Therapy

PURPOSE

Although most patients with estrogen receptor (ER)-positive breast cancer benefit from endocrine therapies, a significant proportion do not. Our aim was to identify inherited genetic variations that might predict survival among patients receiving adjuvant endocrine therapies.

EXPERIMENTAL DESIGN

We performed a meta-analysis of two genome-wide studies; Helsinki Breast Cancer Study, 805 patients, with 240 receiving endocrine therapy and Prospective study of Outcomes in Sporadic versus Hereditary breast cancer, 536 patients, with 155 endocrine therapy patients, evaluating 486,478 single-nucleotide polymorphisms (SNP). The top four associations from the endocrine treatment subgroup were further investigated in two independent datasets totaling 5,011 patients, with 3,485 receiving endocrine therapy.

RESULTS

A meta-analysis identified a common SNP rs8113308, mapped to 19q13.41, associating with reduced survival among endocrine-treated patients [hazard ratio (HR), 1.69; 95% confidence interval (CI), 1.37-2.07; P = 6.34 × 10(-7)] and improved survival among ER-negative patients, with a similar trend in ER-positive cases not receiving endocrine therapy. In a multivariate analysis adjusted for conventional prognostic factors, we found a significant interaction between the rs8113308 and endocrine treatment, indicating a predictive, treatment-specific effect of the SNP rs8113308 on breast cancer survival, with the per-allele HR for interaction 2.16 (95% CI, 1.30-3.60; Pinteraction = 0.003) and HR = 7.77 (95% CI, 0.93-64.71) for the homozygous genotype carriers. A biologic rationale is suggested by in silico functional analyses.

CONCLUSIONS

Our findings suggest carrying the rs8113308 rare allele may identify patients who will not benefit from adjuvant endocrine treatment.

Polymorphisms of homologous recombination RAD51, RAD51B, XRCC2, and XRCC3 genes and the risk of prostate cancer

Genetic polymorphisms in DNA repair genes may induce individual variations in DNA repair capacity, which may in turn contribute to the risk of cancer developing. Homologous recombination repair (HRR) plays a critical role in maintaining chromosomal integrity and protecting against carcinogenic factors. The aim of the present study was to evaluate the relationship between prostate cancer risk and the presence of single nucleotide polymorphisms (SNPs) in the genes involved in HRR, that is, RAD51 (rs1801320 and rs1801321), RAD51B (rs10483813 and rs3784099), XRCC2 (rs3218536), and XRCC3 (rs861539). Polymorphisms were analyzed by PCR-RFLP and Real-Time PCR in 101 patients with prostate adenocarcinoma and 216 age- and sex-matched controls. A significant relationship was detected between the RAD51 gene rs1801320 polymorphism and increased prostate cancer risk. Our results indicate that the RAD51 gene rs1801320 polymorphism may contribute to prostate cancer susceptibility in Poland.

Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients

Here we perform the first genome-wide association study (GWAS) of multiple myeloma (MM) survival. In a meta-analysis of 306 MM patients treated at UCSF and 239 patients treated at the Mayo clinic, we find a significant association between SNPs near the gene FOPNL on chromosome 16p13 and survival (rs72773978; P=6 × 10(-10)). Patients with the minor allele are at increased risk for mortality (HR: 2.65; 95% CI: 1.94-3.58) relative to patients homozygous for the major allele. We replicate the association in the IMMEnSE cohort including 772 patients, and a University of Utah cohort including 318 patients (rs72773978 P=0.044). Using publicly available data, we find that the minor allele was associated with increased expression of FOPNL and increased expression of FOPNL was associated with higher expression of centrosomal genes and with shorter survival. Polymorphisms at the FOPNL locus are associated with survival among MM patients.

Identification of novel genetic markers of breast cancer survival

BACKGROUND

Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival.

METHODS

We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided.

RESULTS

We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust.

CONCLUSIONS

This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.

Common germline polymorphisms associated with breast cancer-specific survival

INTRODUCTION

Previous 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.

METHODS

A 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.

RESULTS

Fifty-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.

CONCLUSIONS

Although 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.

Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes

PURPOSE

To identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients.

METHODS

From the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell's C.

RESULTS

In the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (Prs166870 = 2.88 × 10(-7) and Prs10825036 = 3.54 × 10(-7) in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P discovery=1.18 × 10(-8) and P replication = 2.08 × 10(-5)) and HR- HRE2- subtypes (P discovery = 2.35 × 10(-4) and P replication = 2.60 × 10(-2)). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status.

CONCLUSION

Combined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

INTRODUCTION

Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy).

METHODS

We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast cancer-specific survival (BCSS). Heterogeneity according to chemotherapy or ER status was evaluated with the log-likelihood ratio test.

RESULTS

Three independent SNPs in TGFBR2 and IL12B were associated with OS (P <10⁻³) solely in ER-negative patients after chemotherapy (267 events). Poorer OS associated with TGFBR2 rs1367610 (G > C) (per allele hazard ratio (HR) 1.54 (95% confidence interval (CI) 1.22 to 1.95), P = 3.08 × 10⁻⁴) was not found in ER-negative patients without chemotherapy or ER-positive patients with chemotherapy (P for interaction <10-3). Two SNPs in IL12B (r² = 0.20) showed different associations with ER-negative disease after chemotherapy: rs2546892 (G > A) with poorer OS (HR 1.50 (95% CI 1.21 to 1.86), P = 1.81 × 10⁻⁴), and rs2853694 (A > C) with improved OS (HR 0.73 (95% CI 0.61 to 0.87), P = 3.67 × 10⁻⁴). Similar associations were observed with BCSS. Association with TGFBR2 rs1367610 but not IL12B variants replicated using BCAC Asian samples and the independent Prospective Study of Outcomes in Sporadic versus Hereditary Breast Cancer Study and yielded a combined HR of 1.57 ((95% CI 1.28 to 1.94), P = 2.05 × 10⁻⁵) without study heterogeneity.

CONCLUSIONS

TGFBR2 variants may have prognostic and predictive value in ER-negative breast cancer patients treated with adjuvant chemotherapy. Our findings provide further insights into the development of immunotherapeutic targets for ER-negative breast cancer.

Addressing population-specific multiple testing burdens in genetic association studies

The number of effectively independent tests performed in genome-wide association studies (GWAS) varies by population, making a universal P-value threshold inappropriate. We estimated the number of independent SNPs in Phase 3 HapMap samples by: (1) the LD-pruning function in PLINK, and (2) an autocorrelation-based approach. Autocorrelation was also used to estimate the number of independent SNPs in whole genome sequences from 1000 Genomes. Both approaches yielded consistent estimates of numbers of independent SNPs, which were used to calculate new population-specific thresholds for genome-wide significance. African populations had the most stringent thresholds (1.49 × 10(-7) for YRI at r(2) = 0.3), East Asian populations the least (3.75 × 10(-7) for JPT at r(2) = 0.3). We also assessed how using population-specific significance thresholds compared to using a single multiple testing threshold at the conventional 5 × 10(-8) cutoff. Applied to a previously published GWAS of melanoma in Caucasians, our approach identified two additional genes, both previously associated with the phenotype. In a Chinese breast cancer GWAS, our approach identified 48 additional genes, 19 of which were in or near genes previously associated with the phenotype. We conclude that the conventional genome-wide significance threshold generates an excess of Type 2 errors, particularly in GWAS performed on more recently founded populations.

A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis

OBJECTIVE

Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset.

METHODS

To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10(-8) was used to determine significance. Replication was performed in 1523 additional patients from the POSH study.

RESULTS

Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10(-6). These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27-1.75, P = 1.1×10(-6)), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67-0.85, P = 1.8×10(-6)), and rs1728400 which is between LINC00917 and FOXF1.

CONCLUSIONS

In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.

Germline DNA variations in breast cancer predisposition and prognosis: a systematic review of the literature

Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented.

CXM: a new tool for mapping breast cancer risk in the tumor microenvironment

The majority of causative variants in familial breast cancer remain unknown. Of the known risk variants, most are tumor cell autonomous, and little attention has been paid yet to germline variants that may affect the tumor microenvironment. In this study, we developed a system called the Consomic Xenograft Model (CXM) to map germline variants that affect only the tumor microenvironment. In CXM, human breast cancer cells are orthotopically implanted into immunodeficient consomic strains and tumor metrics are quantified (e.g., growth, vasculogenesis, and metastasis). Because the strain backgrounds vary, whereas the malignant tumor cells do not, any observed changes in tumor progression are due to genetic differences in the nonmalignant microenvironment. Using CXM, we defined genetic variants on rat chromosome 3 that reduced relative tumor growth and hematogenous metastasis in the SS.BN3(IL2Rγ) consomic model compared with the SS(IL2Rγ) parental strain. Paradoxically, these effects occurred despite an increase in the density of tumor-associated blood vessels. In contrast, lymphatic vasculature and lymphogenous metastasis were unaffected by the SS.BN3(IL2Rγ) background. Through comparative mapping and whole-genome sequence analysis, we narrowed candidate variants on rat chromosome 3 to six genes with a priority for future analysis. Collectively, our results establish the utility of CXM to localize genetic variants affecting the tumor microenvironment that underlie differences in breast cancer risk.

2q36.3 is associated with prognosis for oestrogen receptor-negative breast cancer patients treated with chemotherapy

Large population-based registry studies have shown that breast cancer prognosis is inherited. Here we analyse single-nucleotide polymorphisms (SNPs) of genes implicated in human immunology and inflammation as candidates for prognostic markers of breast cancer survival involving 1,804 oestrogen receptor (ER)-negative patients treated with chemotherapy (279 events) from 14 European studies in a prior large-scale genotyping experiment, which is part of the Collaborative Oncological Gene-environment Study (COGS) initiative. We carry out replication using Asian COGS samples (n=522, 53 events) and the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) study (n=315, 108 events). Rs4458204_A near CCL20 (2q36.3) is found to be associated with breast cancer-specific death at a genome-wide significant level (n=2,641, 440 events, combined allelic hazard ratio (HR)=1.81 (1.49-2.19); P for trend=1.90 × 10(-9)). Such survival-associated variants can represent ideal targets for tailored therapeutics, and may also enhance our current prognostic prediction capabilities.

Systematic pathway enrichment analysis of a genome-wide association study on breast cancer survival reveals an influence of genes involved in cell adhesion and calcium signaling on the patients' clinical outcome

Genome-wide association studies (GWASs) may help to understand the effects of genetic polymorphisms on breast cancer (BC) progression and survival. However, they give only a focused view, which cannot capture the tremendous complexity of this disease. Therefore, we investigated data from a previously conducted GWAS on BC survival for enriched pathways by different enrichment analysis tools using the two main annotation databases Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The goal was to identify the functional categories (GO terms and KEGG pathways) that are consistently overrepresented in a statistically significant way in the list of genes generated from the single nucleotide polymorphism (SNP) data. The SNPs with allelic p-value cut-offs 0.005 and 0.01 were annotated to the genes by excluding or including a 20 kb up-and down-stream sequence of the genes and analyzed by six different tools. We identified eleven consistently enriched categories, the most significant ones relating to cell adhesion and calcium ion binding. Moreover, we investigated the similarity between our GWAS and the enrichment analyses of twelve published gene expression signatures for breast cancer prognosis. Five of them were commonly used and commercially available, five were based on different aspects of metastasis formation and two were developed from meta-analyses of published prognostic signatures. This comparison revealed similarities between our GWAS data and the general and the specific brain metastasis gene signatures as well as the Oncotype DX signature. As metastasis formation is a strong indicator of a patient’s prognosis, this result reflects the survival aspect of the conducted GWAS and supports cell adhesion and calcium signaling as important pathways in cancer progression.

Cancer biomarker discovery: current status and future perspectives

PURPOSE

Cancer is a multigene disease which arises as a result of mutational and epigenetic changes coupled with activation of complex signaling networks. The use of biomarkers for early cancer detection, staging and individualization of therapy might improve patient care. A few fundamental issues such as tumor heterogeneity, a highly dynamic nature of the intrinsic and extrinsic determinants of radio- and chemoresistance, along with the plasticity and diversity of cancer stem cells (CSC) make biomarker development a challenging task. In this review we outline the preclinical strategies of cancer biomarker discovery including genomic, proteomic, metabolomic and microRNomic profiling, comparative genome hybridization (CGH), single nucleotide polymorphism (SNP) analysis, high throughput screening (HTS) and next generation sequencing (NGS). Other promising approaches such as assessment of circulating tumor cells (CTC), analysis of CSC-specific markers and cell-free circulating tumor DNA (ctDNA) are also discussed.

CONCLUSIONS

The emergence of powerful proteomic and genomic technologies in conjunction with advanced bioinformatic tools allows the simultaneous analysis of thousands of biological molecules. These techniques yield the discovery of new tumor signatures, which are sensitive and specific enough for early cancer detection, for monitoring disease progression and for proper treatment selection, paving the way to individualized cancer treatment.

Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data

BACKGROUND

Next-generation sequencing (NGS) technologies have resulted in petabytes of scattered data, decentralized in archives, databases and sometimes in isolated hard-disks which are inaccessible for browsing and analysis. It is expected that curated secondary databases will help organize some of this Big Data thereby allowing users better navigate, search and compute on it.

RESULTS

To address the above challenge, we have implemented a NGS biocuration workflow and are analyzing short read sequences and associated metadata from cancer patients to better understand the human variome. Curation of variation and other related information from control (normal tissue) and case (tumor) samples will provide comprehensive background information that can be used in genomic medicine research and application studies. Our approach includes a CloudBioLinux Virtual Machine which is used upstream of an integrated High-performance Integrated Virtual Environment (HIVE) that encapsulates Curated Short Read archive (CSR) and a proteome-wide variation effect analysis tool (SNVDis). As a proof-of-concept, we have curated and analyzed control and case breast cancer datasets from the NCI cancer genomics program - The Cancer Genome Atlas (TCGA). Our efforts include reviewing and recording in CSR available clinical information on patients, mapping of the reads to the reference followed by identification of non-synonymous Single Nucleotide Variations (nsSNVs) and integrating the data with tools that allow analysis of effect nsSNVs on the human proteome. Furthermore, we have also developed a novel phylogenetic analysis algorithm that uses SNV positions and can be used to classify the patient population. The workflow described here lays the foundation for analysis of short read sequence data to identify rare and novel SNVs that are not present in dbSNP and therefore provides a more comprehensive understanding of the human variome. Variation results for single genes as well as the entire study are available from the CSR website (http://hive.biochemistry.gwu.edu/dna.cgi?cmd=csr).

CONCLUSIONS

Availability of thousands of sequenced samples from patients provides a rich repository of sequence information that can be utilized to identify individual level SNVs and their effect on the human proteome beyond what the dbSNP database provides.

Correlates of 25-hydroxyvitamin D among Chinese breast cancer patients

Background

Few studies have investigated vitamin D status in association with modifiable lifestyle factors and clinical characteristics among breast cancer patients, with no studies among Chinese women, who may be at higher risk of vitamin D deficiency. We aimed to evaluate circulating 25-hydroxyvitamin D (25(OH)D) levels in association with clinical and lifestyle factors among 1,940 Chinese breast cancer patients.

Methods

Participants included breast cancer cases aged 22–77 from a population-based case-control study conducted in Shanghai, China during 1996–1998 (n = 1,044) and 2002–2005 (n = 896). Circulating 25(OH)D levels were measured in plasma samples (95% collected ≤6 months post-diagnosis). Prevalence ORs and 95% CIs were derived from multinomial logistic regression models, adjusting for age, season, and other factors.

Results

About 23% and 48% of women were vitamin D deficient (<30 nmol/L) or insufficient (30–50 nmol/L), respectively. Tumor characteristics were not associated with vitamin D status. Higher BMI was associated with increased odds of vitamin D deficiency (ORs (95% CIs): 1 (reference), 1.12 (0.85,1.47), and 1.57 (1.02,2.42), for <23, 23–<27.5, and ≥27.5 kg/m², respectively, P_trend <0.06). Total physical activity was associated with reduced odds of vitamin D deficiency (ORs (95% CIs):1 (reference), 0.84 (0.59,1.20), 0.65 (0.45,0.93), and 0.69 (0.48,1.00), for <7.65, 7.65–<10.6, 10.6–<13.5, ≥13.5 MET-hours/day, respectively, P_trend <0.02). Smoking was associated with vitamin D insufficiency and deficiency (ORs (95% CIs): 2.50 (1.07,5.84) and 2.78 (1.11,6.95), respectively).

Conclusions

In the largest study to date, the prevalence of low vitamin D status was high among Chinese breast cancer patients and associated with higher BMI, smoking, and lower physical activity. Our findings support careful monitoring of vitamin D status and recommendations for supplementation and other lifestyle modifications that may improve vitamin D status in breast cancer patients.

Genetic ancestry and risk of mortality among U.S. Latinas with breast cancer

Multiple studies have reported that Latina women in the United States are diagnosed with breast cancer at more advanced stages and have poorer survival than non-Latina White women. However, Latinas are a heterogeneous group with individuals having different proportions of European, Indigenous American, and African genetic ancestry. In this study, we evaluated the association between genetic ancestry and survival after breast cancer diagnosis among 899 Latina women from the San Francisco Bay area. Genetic ancestry was estimated from single-nucleotide polymorphisms from an Affymetrix 6.0 array and we used Cox proportional hazards models to evaluate the association between genetic ancestry and breast cancer-specific mortality (tests were two-sided). Women were followed for an average of 9 years during which 75 died from breast cancer. Our results showed that Individuals with higher Indigenous American ancestry had increased risk of breast cancer-specific mortality [HR: 1.57 per 25% increase in Indigenous American ancestry; 95% confidence interval (CI): 1.08-2.29]. Adjustment for demographic factors, tumor characteristics, and some treatment information did not explain the observed association (HR: 1.75; 95%CI, 1.12-2.74). In an analysis in which ancestry was dichotomized, the hazard of mortality showed a two-fold increase when comparing women with less than 50% Indigenous American ancestry to women with 50% or more [HR, 1.89, 95%CI, 1.10-3.24]. This was also reflected by Kaplan-Meier survival estimates (P for log-rank test of 0.003). Overall, results suggest that genetic factors and/or unmeasured differences in treatment or access to care should be further explored to understand and reduce ethnic disparities in breast cancer outcomes.

DNA double-strand break repair genotype and phenotype and breast cancer risk within sisters from the New York site of the Breast Cancer Family Registry (BCFR)

PURPOSE

We previously observed that poor DNA repair phenotype is associated with increased breast cancer (BC) risk within families. Here, we examined whether genetic variation in double-strand break repair (DSBR) genes is associated with BC risk and if genotypes are related to phenotype in unaffected women.

METHODS

Using data from the New York site of the Breast Cancer Family Registry, we investigated 25 single-nucleotide polymorphism (SNPs) involved in DSBR using biospecimens from 337 BC cases and 410 unaffected sister controls.

RESULTS

Genotypes in XRCC4 were associated with BC risk, with ORs of 1.67 (95 % CI 1.01-2.76) for the combined GA/AA of rs1805377 and 1.69 (95 % CI 1.03-2.77) for rs1056503 TG/GG; these associations were no longer statistically significant in multivariable conditional logistic regression models. When examining the association of SNPs with phenotype, we found that genotypes of XRCC5 rs3834 and rs1051685, which were highly correlated with each other, were associated with end-joining (EJ) capacity; women with the XRCC5 rs3834 GA genotype had better DNA repair as measured by higher levels of EJ capacity (37.8 ± 14.1 % for GA vs. 27.9 ± 11.8 % for GG carriers p = 0.0006). Women with the AA genotype of BRCA1 rs799917 also had higher EJ capacity (35.1 ± 9.2 %) than those with GG (26.4 ± 10.1 %, p = 0.02).

CONCLUSIONS

Overall, we found that selected DSBR genotypes were associated with phenotype, although they were not associated with BC risk itself, suggesting that phenotypic measures are influenced by endogenous and exogenous factors across the life course and may be better markers than genotypic measures for ascertaining BC risk.

The seed and soil hypothesis revisited: current state of knowledge of inherited genes on prognosis in breast cancer

The crucial event in the course of malignancies such as breast cancer is its metastatic spread from the primary tumor of origin to distant organs. The natural history of a tumor is determined by the expression of its genes, and in this sense, knowledge has advanced dramatically in recent decades. However, much less is known about the role that the patient plays in the behavior of a tumor. In this article, we review the evidence regarding the genetic background of the host in metastatic tumor dissemination, providing information from epidemiological studies as well as from animal models and human studies. Undoubtedly, the elucidation of possible interpersonal variability in susceptibility to developing metastases would significantly contribute to improve management of cancer patients.

Genome-wide association study identifies common variants in SLC39A6 associated with length of survival in esophageal squamous-cell carcinoma

We conducted a genome-wide scan of SNPs to identify variants associated with length of survival in 1,331 individuals with esophageal squamous-cell carcinoma (ESCC), with associations validated in 2 independent sets including 1,962 individuals with this cancer. We identified rs1050631 in SLC39A6 as associated with the survival times of affected individuals, with the hazard ratio for death from ESCC in the combined sample being 1.30 (95% confidence interval (CI) = 1.19-1.43; P = 3.77 × 10(-8)). rs7242481, located in the 5' UTR of SLC39A6, disturbs a transcriptional repressor binding site and results in upregulation of SLC39A6 expression. Immunohistochemical staining of ESCC tissues showed that higher expression of SLC39A6 protein was correlated with shorter length of survival in individuals with advanced ESCC (P = 0.013). Knockdown of SLC39A6 expression suppressed proliferation and invasion in ESCC cells. These results suggest that SLC39A6 has an important role in the prognosis of ESCC and may be a potential therapeutic target.