A genome-wide association study of prognosis in breast cancer

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.

RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef

RNA sequencing (RNA-seq) has allowed for transcriptional profiling of biological systems through the identification of differentially expressed (DE) genes and pathways. A total of 80 steers with extreme phenotypes were selected from the University of Florida multibreed Angus-Brahman herd. The average slaughter age was 12.91±8.69 months. Tenderness, juiciness and connective tissue assessed by sensory panel, along with marbling, Warner-Bratzler Shear Force (WBSF) and cooking loss, were measured in longissimus dorsi muscle. Total RNA was extracted from muscle and one RNA-seq library per sample was constructed, multiplexed, and sequenced based on protocols by Illumina HiSeq-3000 platform to generate 2×101 bp paired-end reads. The overall read mapping rate using the Btau_4.6.1 reference genome was 63%. A total of 8,799 genes were analyzed using two different methodologies, an expression association and a DE analysis. A gene and exon expression association analysis was carried out using a meat quality index on all 80 samples as a continuous response variable. The expression of 208 genes and 3,280 exons from 1,565 genes was associated with the meat quality index (p-value ≤ 0.05). A gene and isoform DE evaluation was performed analyzing two groups with extreme WBSF, tenderness and marbling. A total of 676 (adjusted p-value≤0.05), 70 (adjusted p-value≤0.1) and 198 (adjusted p-value≤0.1) genes were DE for WBSF, tenderness and marbling, respectively. A total of 106 isoforms from 98 genes for WBSF, 13 isoforms from 13 genes for tenderness and 43 isoforms from 42 genes for marbling (FDR≤0.1) were DE. Cytoskeletal and transmembrane anchoring genes and pathways were identified in the expression association, DE and the gene enrichment analyses; these proteins can have a direct effect on meat quality. Cytoskeletal proteins and transmembrane anchoring molecules can influence meat quality by allowing cytoskeletal interaction with myocyte and organelle membranes, contributing to cytoskeletal structure and architecture maintenance postmortem.

Set-based genetic association and interaction tests for survival outcomes based on weighted V statistics

With advancements in high-throughout technologies, studies have been conducted to investigate the role of massive genetic variants in human diseases. While set-based tests have been developed for binary and continuous disease outcomes, there are few computationally efficient set-based tests available for time-to-event outcomes. To facilitate the genetic association and interaction analyses of time-to-event outcomes, We develop a suite of multivariant tests based on weighted V statistics with or without considering potential genetic heterogeneity. In addition to the computation efficiency and nice asymptotic properties, all the new tests can deal with left truncation and competing risks in the survival data, and adjust for covariates. Simulation studies show that the new tests run faster, are more accurate in small samples, and account for confounding effect better than the existing multivariant survival tests. When the genetic effect is heterogeneous across individuals/subpopulations, the association test considering genetic heterogeneity is more powerful than the existing tests that do not account for genetic heterogeneity. Using the new methods, we perform a genome-wide association analysis of the genotype and age-to-Alzheimer's data from the Rush Memory and Aging Project and the Religious Orders Study. The analysis identifies two genes, APOE and APOC1, associated with age to Alzheimer's disease onset.

A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank

With increasing biobanking efforts connecting electronic health records and national registries to germline genetics, the time-to-event data analysis has attracted increasing attention in the genetics studies of human diseases. In time-to-event data analysis, the Cox proportional hazards (PH) regression model is one of the most used approaches. However, existing methods and tools are not scalable when analyzing a large biobank with hundreds of thousands of samples and endpoints, and they are not accurate when testing low-frequency and rare variants. Here, we propose a scalable and accurate method, SPACox (a saddlepoint approximation implementation based on the Cox PH regression model), that is applicable for genome-wide scale time-to-event data analysis. SPACox requires fitting a Cox PH regression model only once across the genome-wide analysis and then uses a saddlepoint approximation (SPA) to calibrate the test statistics. Simulation studies show that SPACox is 76-252 times faster than other existing alternatives, such as gwasurvivr, 185-511 times faster than the standard Wald test, and more than 6,000 times faster than the Firth correction and can control type I error rates at the genome-wide significance level regardless of minor allele frequencies. Through the analysis of UK Biobank inpatient data of 282,871 white British European ancestry samples, we show that SPACox can efficiently analyze large sample sizes and accurately control type I error rates. We identified 611 loci associated with time-to-event phenotypes of 12 common diseases, of which 38 loci would be missed within a logistic regression framework with a binary phenotype defined as event occurrence status during the follow-up period.

Fine-mapping of a novel premenopausal breast cancer susceptibility locus at Chr4q31.22 in Caucasian women and validation in African and Chinese women

We previously identified a novel breast cancer susceptibility variant on chromosome 4q31.22 locus (rs1429142) conferring risk among women of European ancestry. Here, we report replication of findings, validation of the variant in diverse populations and fine-mapping of the associated locus in Caucasian population. The SNP rs1429142 (C/T, minor allele frequency 18%) showed association for the overall breast cancer risk in Stages 1-4 (n = 4,331 cases/4271 controls; p = 4.35 × 10-8 ; odds ratio, ORC-allele ,1.25), and an elevated risk among premenopausal women (n = 1,503 cases/4271 controls; p = 5.81 × 10-10 ; ORC-allele 1.40) in European populations. SNP rs1429142 was associated with premenopausal breast cancer risk in women of African (T/C; p-value 1.45 × 10-02 ; ORC-allele 1.2) but not from Chinese ancestry. Fine-mapping of the locus revealed several potential causal variants which are present within a single association signal, revealed from the conditional regression analysis. Functional annotation of the potential causal variants revealed three putative SNPs rs1366691, rs1429139 and rs7667633 with active enhancer functions inferred based on histone marks, DNase hypersensitive sites in breast cell line data. These putative variants were bound by transcription factors (C-FOS, STAT1/3 and POL2/3) with known roles in inflammatory pathways. Furthermore, Hi-C data revealed several short-range interactions in the fine-mapped locus harboring the putative variants. The fine mapped locus was predicted to be within a single topologically associated domain, potentially facilitating enhancer-promoter interactions possibly leading to the regulation of nearby genes.

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.

Downregulated expression of ARHGAP10 correlates with advanced stage and high Ki-67 index in breast cancer

Background

Rho GTPase-activating protein 10 (ARHGAP10), which catalyzes the conversion of active Rho GTPase to the inactive form, is downregulated in some cancers. However, little is known about ARHGAP10 in breast cancer.

Methods

The transcriptional expression level of ARHGAP10 in breast cancer was analyzed with the data downloaded from The Cancer Genome Atlas (TCGA) and Oncomine, then verified by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) in 30 pairs of breast cancer tissues and the corresponding adjacent normal tissues. ARHGAP10 protein expression was examined by immunohistochemistry (IHC) in 190 breast cancer and 30 corresponding adjacent normal breast tissue samples. The associations between ARHGAP10 expression and clinicopathological characteristics of patients were analyzed, and Kaplan-Meier Plotter was used to assess the relationship between ARHGAP10 and relapse-free survival (RFS). Different expression levels of ARHGAP10 in response to chemotherapy agents were determined by GEO2R online tool. The potential biological functions of ARHGAP10 were analyzed by Gene Set Enrichment Analysis (GSEA) using data downloaded from TCGA.

Results

ARHGAP10 mRNA and protein expression was lower in breast cancer tissues than in adjacent normal tissues. Low expression of ARHGAP10 was associated with advanced clinical TNM (cTNM) stage (p _b  = 0.001) and high Ki-67 index (p = 0.015). Low expression of ARHGAP10 indicated worse RFS (p = 0.0015) and a poor response to chemotherapy (p = 0.006). GSEA results showed that ARHGAP10 was involved in signaling pathways including protein export, nucleotide excision repair, base excision repair, focal adhesion, JAK-STAT pathway and the actin cytoskeleton.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

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.

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.

Germline copy number variations are associated with breast cancer risk and prognosis

Breast cancer is one of the most common cancers among women, and susceptibility is explained by genetic, lifestyle and environmental components. Copy Number Variants (CNVs) are structural DNA variations that contribute to diverse phenotypes via gene-dosage effects or cis-regulation. In this study, we aimed to identify germline CNVs associated with breast cancer susceptibility and their relevance to prognosis. We performed whole genome CNV genotyping in 422 cases and 348 controls using Human Affymetrix SNP 6 array. Principal component analysis for population stratification revealed 84 outliers leaving 366 cases and 320 controls of Caucasian ancestry for association analysis; CNVs with frequency > 10% and overlapping with protein coding genes were considered for breast cancer risk and prognostic relevance. Coding genes within the CNVs identified were interrogated for gene- dosage effects by correlating copy number status with gene expression profiles in breast tumor tissue. We identified 200 CNVs associated with breast cancer (q-value < 0.05). Of these, 21 CNV regions (overlapping with 22 genes) also showed association with prognosis. We validated representative CNVs overlapping with APOBEC3B and GSTM1 genes using the TaqMan assay. Germline CNVs conferred dosage effects on gene expression in breast tissue. The candidate CNVs identified in this study warrant independent replication.

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.

miR-3174 Contributes to Apoptosis and Autophagic Cell Death Defects in Gastric Cancer Cells by Targeting ARHGAP10

Gastric cancer (GC) is a major health problem worldwide because of its high morbidity and mortality. Considering the well-established roles of miRNA in the regulation of GC carcinogenesis and progression, we screened differentially expressed microRNAs (miRNAs) by using The Cancer Genome Atlas (TCGA) and the GEO databases. We found that miR-3174 was the most significantly differentially expressed miRNA in GC. Ectopic miR-3174 expression was also detected in clinical GC patient samples and cell lines and associated with poor patient prognosis. Apoptosis and autophagic cell death are two types of programmed cell death, whereas both are deficient in gastric cancer. Our functional analyses demonstrated that miR-3174 inhibited mitochondria-dependent apoptosis and autophagic cell death in GC. Moreover, high expression of miR-3174 also resulted in Cisplatin resistance in GC cells. Using bioinformatics analyses combined with in vitro and in vivo experiments, we determined that miR-3174 directly targets ARHGAP10. Notably, ARHGAP10 promoted mitochondria-dependent apoptosis by enhancing p53 expression, which was followed by Bax trans-activation and caspase cleavage. ARHGAP10 also facilitated autophagic cell death by suppressing mammalian target of rapamycin complex 1 (mTOC1) activity. Our results reveal a potential miRNA-based clinical therapeutic target that may also serve as a predictive marker for GC.

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.

The roles of ARHGAP10 in the proliferation, migration and invasion of lung cancer cells

Lung cancer is a leading cause of cancer-related mortalities worldwide. In the present study, a comparison of To determine the roles of ARHGAP10 in the proliferation, migration and invasion of lung cancer cells expression levels between normal lung tissues and lung cancer tissues were compared using immunoblotting, and CCK-8 and Transwell assays. Lung cancer tissues had a decreased ARHGAP10 mRNA expression level compared to the adjacent normal tissues. The ectopic expression of ARHGAP10 significantly suppressed the migration, invasion and proliferation of lung cancer cells. Gene set enrichment analysis revealed that metastasis and Wnt signaling pathways were negatively correlated with ARHGAP10 expression. Immunoblotting analysis revealed that ARHGAP10 overexpression inhibited metastasis [matrix metalloproteinase (MMP)-2, MMP-9 and VEGF] and the expression of Wnt pathway-related proteins (β-catenin and c-Myc). Moreover, the stimulation effects of lithium chloride, a GSK3β inhibitor, on the accumulation of β-catenin were notably suppressed by ARHGAP10 overexpression. Collectively, ARHGAP10 acts to suppress tumor within lung cancer by affecting metastasis and Wnt signaling pathways. The results therefore suggest that ARHGAP10 is a potentially attractive target for the treatment of lung cancer.

LincIN, a novel NF90-binding long non-coding RNA, is overexpressed in advanced breast tumors and involved in metastasis

BACKGROUND

Recent genome-wide profiling by sequencing and distinctive chromatin signatures has identified thousands of long non-coding RNA (lncRNA) species (>200 nt). LncRNAs have emerged as important regulators of gene expression, involving in both developmental and pathological processes. While altered expression of lncRNAs has been observed in breast cancer development, their roles in breast cancer progression and metastasis are still poorly understood.

METHODS

To identify novel breast cancer-associated lncRNA candidates, we employed a high-density SNP array-based approach to uncover intergenic lncRNA genes that are aberrantly expressed in breast cancer. We first evaluated the potential value as a breast cancer prognostic biomarker for one breast cancer-associated lncRNA, LincIN, using a breast cancer cohort retrieved from The Cancer Genome Atlas (TCGA) Data Portal. Then we characterized the role of LincIN in breast cancer progression and metastasis by in vitro invasion assay and a mouse tail vein injection metastasis model. To study the action of LincIN, we identified LincIN-interacting protein partner(s) by RNA pull-down experiments followed with protein identification by mass spectrometry.

RESULTS

High levels of LincIN expression are frequently observed in tumors compared to adjacent normal tissues, and are strongly associated with aggressive breast cancer. Importantly, analysis of TCGA data further suggest that high expression of LincIN is associated with poor overall survival in patients with breast cancer (P = 0.044 and P = 0.011 after adjustment for age). The functional experiments demonstrate that knockdown of LincIN inhibits tumor cell migration and invasion in vitro, which is supported by the results of transcriptome analysis in the LincIN-knockdown cells. Furthermore, knockdown of LincIN diminishes lung metastasis in a mouse tail vein injection model. We also identified a LincIN-binding protein, NF90, through which overexpression of LincIN may repress p21 protein expression by inhibiting its translation, and upregulation of p21 by LincIN knockdown may be associated with less aggressive metastasis phenotypes.

CONCLUSIONS

Our studies provide clear evidence to support LincIN as a new regulator of tumor progression-metastasis at both transcriptional and translational levels and as a promising prognostic biomarker for breast cancer.

ARHGAP10, downregulated in ovarian cancer, suppresses tumorigenicity of ovarian cancer cells

Rho GTPase-activating proteins (RhoGAPs) are implicated in the development and progression of ovarian cancer. ARHGAP10 is a member of RhoGAP proteins and inactivates Cdc42 by converting GTP-bound form to GDP-bound form. Here, we aimed to evaluate ARHGAP10 expression profile and functions in ovarian cancer. The decreased expression of ARHGAP10 was found in 77.3% (58/75) of ovarian cancer tissues, compared with their non-tumorous counterparts. Furthermore, overall survival in ovarian cancer patients with higher expression of ARHGAP10 was longer than those with lower expression. Ectopic expression of ARHGAP10 in two ovarian cancer cell lines with lower expression of ARHGAP10 (A2780 and HO-8910) dramatically suppressed cell proliferation in vitro. In nude mice, its stable overexpression significantly inhibited the tumorigenicity of A2780 cells. We further demonstrated that overexpression of ARHGAP10 significantly inhibited cell adhesion, migration and invasion, resulted in cell arrest in G1 phase of cell cycle and a significant increase of apoptosis. Moreover, ARHGAP10 interacted with Cdc42 and overexpression of ARHGAP10 inhibited the activity of Cdc42 in A2780 cells. Gene set enrichment analysis on The Cancer Genome Atlas dataset showed that KEGG cell cycle, replication and base excision repair (BER) pathways were correlatively with the ARHGAP10 expression, which was further confirmed in ovarian cancer cells by western blotting. Hence, ARHGAP10 may serve as a tumor suppressor through inactivating Cdc42, as well as inhibiting cell cycle, replication and BER pathways. Our data suggest an important role of ARHGAP10 in the molecular etiology of cancer and implicate the potential application of ARHGAP10 in cancer therapy.

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.

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.

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.

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.

A genome wide association study on Newfoundland colorectal cancer patients' survival outcomes

Background

In this study we performed genome-wide association studies to identify candidate SNPs that may predict the risk of disease outcome in colorectal cancer.

Methods

Patient cohort consisted of 505 unrelated patients with Caucasian ancestry. Germline DNA samples were genotyped using the Illumina® human Omni-1quad SNP chip. Associations of SNPs with overall and disease free survivals were examined primarily for 431 patients with microsatellite instability-low (MSI-L) or stable (MSS) colorectal tumors using Cox proportional hazards method adjusting for clinical covariates. Bootstrap method was applied for internal validation of results. As exploratory analyses, association analyses for the colon (n = 334) and rectal (n = 171) cancer patients were also performed.

Results

As a result, there was no SNP that reached the genomewide significance levels (p < 5x10⁻⁸) in any of the analyses. A small number of genetic markers (n = 10) showed nominal associations (p <10⁻⁶) for MSS/MSI-L, colon, or rectal cancer patient groups. These markers were located in two non-coding RNA genes or intergenic regions and none were amino acid substituting polymorphisms. Bootstrap analysis for the MSS/MSI-L cohort data suggested the robustness of the observed nominal associations.

Conclusions

Likely due to small number of patients, our study did not identify an acceptable level of association of SNPs with outcome in MSS/MSI-L, colon, or rectal cancer patients. A number of SNPs with sub-optimal p-values were, however, identified; these loci may be promising and examined in other larger-sized patient cohorts.

Electronic supplementary material

The online version of this article (doi:10.1186/s40364-015-0031-6) contains supplementary material, which is available to authorized users.

Therogenetics: transferring GWAS technology to the clinic

Molecular characteristics of breast tumours have been used for the last decades to guide clinicians in treating this devastating disease. More recent information has led to further refinement of molecular characteristics of breast tumours, and subsequent indications for specific treatments. However, evidence exists that factors independent of the primary tumour type, potentially germline genetics, may influence progression to metastasis. In this review, we expose some of this evidence, and propose tools needed to overcome current limitations to the identification of specific germline variants that influence risk of metastases in breast cancer patients.

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.

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.

A non-parametric approach for detecting gene-gene interactions associated with age-at-onset outcomes

Background

Cox-regression-based methods have been commonly used for the analyses of survival outcomes, such as age-at-disease-onset. These methods generally assume the hazard functions are proportional among various risk groups. However, such an assumption may not be valid in genetic association studies, especially when complex interactions are involved. In addition, genetic association studies commonly adopt case-control designs. Direct use of Cox regression to case-control data may yield biased estimators and incorrect statistical inference.

Results

We propose a non-parametric approach, the weighted Nelson-Aalen (WNA) approach, for detecting genetic variants that are associated with age-dependent outcomes. The proposed approach can be directly applied to prospective cohort studies, and can be easily extended for population-based case-control studies. Moreover, it does not rely on any assumptions of the disease inheritance models, and is able to capture high-order gene-gene interactions. Through simulations, we show the proposed approach outperforms Cox-regression-based methods in various scenarios. We also conduct an empirical study of progression of nicotine dependence by applying the WNA approach to three independent datasets from the Study of Addiction: Genetics and Environment. In the initial dataset, two SNPs, rs6570989 and rs2930357, located in genes GRIK2 and CSMD1, are found to be significantly associated with the progression of nicotine dependence (ND). The joint association is further replicated in two independent datasets. Further analysis suggests that these two genes may interact and be associated with the progression of ND.

Conclusions

As demonstrated by the simulation studies and real data analysis, the proposed approach provides an efficient tool for detecting genetic interactions associated with age-at-onset outcomes.

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.

Genetic variations associated with postoperative recurrence in stage I non-small cell lung cancer

PURPOSE

Postoperative recurrence in stage I non-small cell lung cancer (NSCLC) is the major cause of a poor prognosis. This study aims to identify genetic variants that are associated with the prognosis of early-stage NSCLCs.

EXPERIMENTAL DESIGN

A genome-wide association study (GWAS) was conducted in 250 patients in stage I NSCLCs and the results were replicated in additional 308 patients.

RESULTS

Results from an Affymetrix Genome-wide Human SNP array in 250 patients identified 94 SNPs with significant associations (P < 2 × 10(-4)), which were selected for replication in 308 additional patients. Pooled analysis of the 558 patients determined that rs1454694 in chromosome 4q34 was the most significant marker of lung cancer prognosis in the stage I patients (adjusted HR = 2.81; P = 5.91 × 10(-8)). After the candidate loci were mapped, an additional four markers at chromosome 4q34.3 were significantly associated with recurrence-free survival (RFS; P < 5 × 10(-5)). A haplotype of five SNPs in 4q34 also showed significant association with RFS (P = 4.29 × 10(-6)).

CONCLUSIONS

A genetic polymorphism rs1454694 was identified as a novel genetic risk factor for RFS of stage I NSCLCs. This genome-wide study suggests that genetic markers in 4q34.3 contribute to predict the prognosis of Korean patients with stage I NSCLCs.

A Single-Array-Based Method for Detecting Copy Number Variants Using Affymetrix High Density SNP Arrays and its Application to Breast Cancer

Cumulative evidence has shown that structural variations, due to insertions, deletions, and inversions of DNA, may contribute considerably to the development of complex human diseases, such as breast cancer. High-throughput genotyping technologies, such as Affymetrix high density single-nucleotide polymorphism (SNP) arrays, have produced large amounts of genetic data for genome-wide SNP genotype calling and copy number estimation. Meanwhile, there is a great need for accurate and efficient statistical methods to detect copy number variants. In this article, we introduce a hidden-Markov-model (HMM)-based method, referred to as the PICR-CNV, for copy number inference. The proposed method first estimates copy number abundance for each single SNP on a single array based on the raw fluorescence values, and then standardizes the estimated copy number abundance to achieve equal footing among multiple arrays. This method requires no between-array normalization, and thus, maintains data integrity and independence of samples among individual subjects. In addition to our efforts to apply new statistical technology to raw fluorescence values, the HMM has been applied to the standardized copy number abundance in order to reduce experimental noise. Through simulations, we show our refined method is able to infer copy number variants accurately. Application of the proposed method to a breast cancer dataset helps to identify genomic regions significantly associated with the disease.

Breast cancer susceptibility risk associations and heterogeneity by E-cadherin tumor tissue expression

E-cadherin is involved in cell-cell adhesion and epithelial-to-mesenchymal transitions. In cancers, loss or inactivation of E-cadherin is associated with epithelial cell proliferation and invasion. Here, we sought to determine, if risk associations for 18 breast cancer susceptibility single nucleotide polymorphisms (SNPs) differed by E-cadherin tumor tissue expression in the Polish Breast Cancer Study (PBCS), using data on 1,347 invasive breast cancer cases and 2,366 controls. E-cadherin expression (low/high) was assessed using immunohistochemical staining of tumor tissue microarrays. Replication data on 2,006 cases and 6,714 controls from the Study of Epidemiology and Risk Factors in Cancer Heredity was used to follow-up promising findings from PBCS. In PBCS, we found the rs11249433 SNP at the 1p11.2 locus to be more strongly associated with risk of E-cadherin low tumors (OR = 1.30, 95 % CI = 1.08-1.56) than with E-cadherin high tumors [OR = 1.06, 95 % CI = 0.95-1.18; case-only p-heterogeneity (p-het) = 0.05]. Findings in PBCS for rs11249433 were replicated in SEARCH. Combined analyses of the two datasets for SNP rs11249433 revealed significant heterogeneity by E-cadherin expression (combined case-only p-het = 0.004). Further, among carriers of rs11249433, the highest risk was seen for E-cadherin low tumors that were ER-positive and of lobular histology. Our results in two independent data sets suggest that rs11249433, which is located between the NOTCH2 and FCGR1B genes within the 1p11.2 locus, is more strongly associated with risk of breast tumors with low or absent E-cadherin expression, and suggest that evaluation of E-cadherin tumor tissue expression may be useful in clarifying breast cancer risk factor associations.

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.

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.

Germline variation in TP53 regulatory network genes associates with breast cancer survival and treatment outcome

Germline variation in the TP53 network genes PRKAG2, PPP2R2B, CCNG1, PIAS1 and YWHAQ was previously suggested to have an impact on drug response in vitro. Here, we investigated the effect on breast cancer survival of germline variation in these genes in 925 Finnish breast cancer patients and further analyzed five single nucleotide polymorphisms (SNPs) in PRKAG2 (rs1029946, rs4726050, rs6464153, rs7789699) and PPP2R2B (rs10477313) for 10-year survival in breast cancer patients, interaction with TP53 R72P and MDM2-SNP309, outcome after specific adjuvant therapy and correlation to tumor characteristics in 4,701 invasive cases from four data sets. We found evidence for carriers of PRKAG2-rs1029946 and PRKAG2-rs4726050 having improved survival in the pooled data (HR 0.53, 95% CI 0.3-0.9; p = 0.023 for homozygous carriers of the rare G-allele and HR 0.85, 95% CI 0.7-0.9; p = 0.049 for carriers of the rare G allele, respectively). PRKAG2-rs4726050 showed a significant interaction with MDM2-SNP309, with PRKAG2-rs4726050 rare G-allele having a dose-dependent effect for better breast cancer survival confined only to MDM2 SNP309 rare G-allele carriers (HR 0.45, 95% CI 0.2-0.7; p = 0.001). This interaction also emerged as an independent predictor of better survival (p = 0.047). PPP2R2B-rs10477313 rare A-allele was found to predict better survival (HR 0.82, 95% CI 0.6-0.9; p = 0.018), especially after hormonal therapy (HR 0.66, 95% CI 0.5-0.9; p = 0.048). These findings warrant further studies and suggest that genetic markers in TP53 network genes such as PRKAG2 and PPP2R2B might affect prognosis and treatment outcome in breast cancer patients.

The relationship between eight GWAS-identified single-nucleotide polymorphisms and primary breast cancer outcomes

BACKGROUND

Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies (GWAS). We investigated whether eight risk SNPs identified in GWAS were associated with breast cancer disease-free survival (DFS) and overall survival (OS) rates.

PATIENTS AND METHODS

A cohort of 739 white women with early-stage breast cancer was genotyped for eight GWAS-identified SNPs (rs2981582, rs1219648 [FGFR2], rs3803662, rs12443621, rs8051542 [TOX3], rs999737 [RAD51L1], rs6504950 [17q23], and rs4973768 [3p24]). Relationships between SNPs and breast cancer outcomes were evaluated using Cox proportional hazard regression models. The cumulative effects of SNPs on breast cancer outcomes were assessed by computing the number of at-risk genotypes.

RESULTS

At a median follow-up of 121 months (range: 188-231 months) for survivors, 237 deaths (32%) and 186 breast cancer events (25%) were identified among the 739 patients. After adjusting for age, clinical stage, and treatment, rs12443621 (16q12; p = .03) and rs6504950 (17q23; p = .008) were prognostic for OS but not DFS. A higher risk for death was also found in the multivariable analysis of patients harboring three or four at-risk genotypes of the GWAS SNPs compared to patients carrying two or less at-risk genotypes (hazard ratio: 1.60, 95% confidence interval: 1.23-2.24; p = .0008).

CONCLUSION

The study results suggest that previously identified breast cancer risk susceptibility loci, rs12443621 (16q12) and rs6504950 (17q23), may influence breast cancer prognosis or comorbid conditions associated with overall survival. The precise molecular mechanisms through which these risk SNPs, as well as others that were not included in the analysis, influence clinical outcomes remain to be determined.

Identification of inherited genetic variations influencing prognosis in early-onset breast cancer

Genome-Wide Association Studies (GWAS) have begun to investigate associations between inherited genetic variations and breast cancer prognosis. Here, we report our findings from a GWAS conducted in 536 patients with early-onset breast cancer aged 40 or less at diagnosis and with a mean follow-up period of 4.1 years (SD = 1.96). Patients were selected from the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer. A Bonferroni correction for multiple testing determined that a P value of 1.0 × 10(-7) was a statistically significant association signal. Following quality control, we identified 487,496 single nucleotide polymorphisms (SNP) for association tests in stage 1. In stage 2, 35 SNPs with the most significant associations were genotyped in 1,516 independent cases from the same early-onset cohort. In stage 2, 11 SNPs remained associated in the same direction (P ≤ 0.05). Fixed effects meta-analysis models identified one SNP associated at close to genome wide level of significance 556 kb upstream of the ARRDC3 locus [HR = 1.61; 95% confidence interval (CI), 1.33-1.96; P = 9.5 × 10(-7)]. Four further associations at or close to the PBX1, RORα, NTN1, and SYT6 loci also came close to genome-wide significance levels (P = 10(-6)). In the first ever GWAS for the identification of SNPs associated with prognosis in patients with early-onset breast cancer, we report a SNP upstream of the ARRDC3 locus as potentially associated with prognosis (median follow-up time for genotypes: CC = 4 years, CT = 3 years, and TT = 2.7 years; Wilcoxon rank-sum test CC vs. CT, P = 4 × 10(-4) and CT vs. TT, P = 0.76). Four further loci may also be associated with prognosis.

Polymorphisms in oxidative stress-related genes and mortality in breast cancer patients--potential differential effects by radiotherapy?

We assessed whether variants in 22 oxidative stress-related genes are associated with mortality of breast cancer patients and whether the associations differ according to radiotherapy. Using a prospective cohort of 1348 postmenopausal breast cancer patients, we estimated hazard ratios (HR) and 95% confidence intervals (CI) for 109 single nucleotide polymorphisms (SNPs) using Cox proportional hazards regression. Validation of results was attempted using two Scandinavian studies. Eleven SNPs in MT2A, NFE2L2, NQO1, PRDX1, and PRDX6 were significantly associated with overall mortality after a median follow-up of 5.7 years. Three SNPs in NQO1 (rs2917667) and in PRDX6 (rs7314, rs4916362) were consistently associated with increased risk of dying across all three study populations (pooled: HRNQO1_rs2917667 1.20, 95% CI 1.00-1.44, p = 0.051; HRPRDX6_rs7314 1.16, 95% CI 1.00-1.35, p = 0.056, HRPRDX6_rs4916362 1.14 95% CI 1.00-1.32, p = 0.062). Potential effect modification by radiotherapy was found for CAT_rs769218. In conclusion, genetic variants in NQO1 and PRDX6 may modify breast cancer prognosis.

Germline prognostic markers for urinary bladder cancer: obstacles and opportunities

Urinary bladder cancer is a heterogeneous disease with diverse genetic and environmental risk factors that can influence disease risk or clinical course for recurrence, progression, and survival. Therefore, identification of these factors is paramount for disease prevention and optimal clinical management of bladder cancer patients. Of particular interest is the need to identify molecular biomarkers that can give accurate assessment of tumor biological potential and to predict treatment response. Recent advances in molecular biology, cytogenetic, and genomic research have spurred discovery efforts for novel genetic, epigenetic, and proteomic biomarkers that are prognostic for cancer. This review focuses on some of the important germ line polymorphisms found to be correlated with clinical outcomes in bladder cancer. So far, most of the identified candidate loci were based on prior knowledge of pathogenesis and had not been validated for clinical applications. The future challenges are to analyze the wealth of information from whole-genome studies, to understand the underlying biological mechanisms of these associations, the network of gene-gene and gene-environment interactions, and to apply these markers for the identification of high-risk population for targeted, personalized therapy.

Technical reproducibility of genotyping SNP arrays used in genome-wide association studies

During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders' quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.

A multistage genetic association study identifies breast cancer risk loci at 10q25 and 16q24

BACKGROUND

Heritable risk for breast cancer includes an increasing number of common, low effect risk variants. We conducted a multistage genetic association study in a series of independent epidemiologic breast cancer study populations to identify novel breast cancer risk variants.

METHODS

We tested 1,162 SNPs of greatest nominal significance from stage I of the Cancer Genetic Markers of Susceptibility breast cancer study (CGEMS; 1,145 cases, 1,142 controls) for evidence of replicated association with breast cancer in the Nashville Breast Cohort (NBC; 599 cases, 1,161 controls), the Collaborative Breast Cancer Study (CBCS; 1,552 cases, 1,185 controls), and BioVU Breast Cancer Study (BioVU; 1,172 cases, 1,172 controls).

RESULTS

Among these SNPs, a series of validated breast cancer risk variants yielded expected associations in the study populations. In addition, we observed two previously unreported loci that were significantly associated with breast cancer risk in the CGEMS, NBC, and CBCS study populations and had a consistent, although not statistically significant, risk effect in the BioVU study population. These were rs1626678 at 10q25.3 near ENO4 and KIAA1598 (meta-analysis age-adjusted OR = 1.13 [1.07-1.20], P = 5.6 × 10(-5)), and rs8046508 at 16q23.1 in the eighth intron of WWOX (meta-analysis age-adjusted OR = 1.20 [1.10-1.31], P = 3.5 × 10(-5)).

CONCLUSIONS

Our data supports the association of two novel loci, at 10q25.3 and 16q23.1, with risk of breast cancer.

IMPACT

The expanding compendium of known breast cancer genetic risk variants holds increasing power for clinical risk prediction models of breast cancer, improving upon the Gail model.

Common genetic polymorphisms of microRNA biogenesis pathway genes and breast cancer survival

Background

Although the role of microRNA’s (miRNA’s) biogenesis pathway genes in cancer development and progression has been well established, the association between genetic variants of this pathway genes and breast cancer survival is still unknown.

Methods

We used genotype data available from a previously conducted case–control study to investigate association between common genetic variations in miRNA biogenesis pathway genes and breast cancer survival. We investigated the possible associations between 41 germ-line single-nucleotide polymorphisms (SNPs) and both disease free survival (DFS) and overall survival (OS) among 488 breast cancer patients. During the median follow-up of 6.24 years, 90 cases developed disease progression and 48 cases died.

Results

Seven SNPs were significantly associated with breast cancer survival. Two SNPs in AGO2 (rs11786030 and rs2292779) and DICER1 rs1057035 were associated with both DFS and OS. Two SNPs in HIWI (rs4759659 and rs11060845) and DGCR8 rs9606250 were associated with DFS, while DROSHA rs874332 and GEMIN4 rs4968104 were associated with only OS. The most significant association was observed in variant allele of AGO2 rs11786030 with 2.62-fold increased risk of disease progression (95% confidence interval (CI), 1.41-4.88) and in minor allele homozygote of AGO2 rs2292779 with 2.94-fold increased risk of death (95% CI, 1.52-5.69). We also found cumulative effects of SNPs on DFS and OS. Compared to the subjects carrying 0 to 2 high-risk genotypes, those carrying 3 or 4–6 high-risk genotypes had an increased risk of disease progression with a hazard ratio of 2.16 (95% CI, 1.18- 3.93) and 4.47 (95% CI, 2.45- 8.14), respectively (P for trend, 6.11E-07).

Conclusions

Our results suggest that genetic variants in miRNA biogenesis pathway genes may be associated with breast cancer survival. Further studies in larger sample size and functional characterizations are warranted to validate these results.

The role of genetic breast cancer susceptibility variants as prognostic factors

Recent genome-wide association studies identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. We investigated these and 62 other SNPs for their prognostic relevance. Confirmed BC risk SNPs rs17468277 (CASP8), rs1982073 (TGFB1), rs2981582 (FGFR2), rs13281615 (8q24), rs3817198 (LSP1), rs889312 (MAP3K1), rs3803662 (TOX3), rs13387042 (2q35), rs4973768 (SLC4A7), rs6504950 (COX11) and rs10941679 (5p12) were genotyped for 25 853 BC patients with the available follow-up; 62 other SNPs, which have been suggested as BC risk SNPs by a GWAS or as candidate SNPs from individual studies, were genotyped for replication purposes in subsets of these patients. Cox proportional hazard models were used to test the association of these SNPs with overall survival (OS) and BC-specific survival (BCS). For the confirmed loci, we performed an accessory analysis of publicly available gene expression data and the prognosis in a different patient group. One of the 11 SNPs, rs3803662 (TOX3) and none of the 62 candidate/GWAS SNPs were associated with OS and/or BCS at P<0.01. The genotypic-specific survival for rs3803662 suggested a recessive mode of action [hazard ratio (HR) of rare homozygous carriers=1.21; 95% CI: 1.09-1.35, P=0.0002 and HR=1.29; 95% CI: 1.12-1.47, P=0.0003 for OS and BCS, respectively]. This association was seen similarly in all analyzed tumor subgroups defined by nodal status, tumor size, grade and estrogen receptor. Breast tumor expression of these genes was not associated with prognosis. With the exception of rs3803662 (TOX3), there was no evidence that any of the SNPs associated with BC susceptibility were associated with the BC survival. Survival may be influenced by a distinct set of germline variants from those influencing susceptibility.

Inherited variants in the MC1R gene and survival from cutaneous melanoma: a BioGenoMEL study

Inherited MC1R variants modulate MITF transcription factor signaling, which in turn affects tumor cell proliferation, apoptosis, and DNA repair. The aim of this BioGenoMEL collaborative study in 10 melanoma cohorts was to test the hypothesis that inherited variants thereby moderate survival expectation. A survival analysis in the largest cohort (Leeds) was carried out adjusting for factors known to impact on survival. The results were then compared with data from nine smaller cohorts. The absence of any consensus MC1R alleles was associated with a significantly lower risk of death in the Leeds set (HR, 0.64; 95% CI, 0.46–0.89) and overall in the 10 data sets (HR, 0.78; 95% CI, 0.65–0.94) with some support from the nine smaller data sets considered together (HR, 0.83; 95% CI, 0.67–1.04). The data are suggestive of a survival benefit for inherited MC1R variants in melanoma patients.

Rac signaling in breast cancer: a tale of GEFs and GAPs

Rac GTPases, small G-proteins widely implicated in tumorigenesis and metastasis, transduce signals from tyrosine-kinase, G-protein-coupled receptors (GPCRs), and integrins, and control a number of essential cellular functions including motility, adhesion, and proliferation. Deregulation of Rac signaling in cancer is generally a consequence of enhanced upstream inputs from tyrosine-kinase receptors, PI3K or Guanine nucleotide Exchange Factors (GEFs), or reduced Rac inactivation by GTPase Activating Proteins (GAPs). In breast cancer cells Rac1 is a downstream effector of ErbB receptors and mediates migratory responses by ErbB1/EGFR ligands such as EGF or TGFα and ErbB3 ligands such as heregulins. Recent advances in the field led to the identification of the Rac-GEF P-Rex1 as an essential mediator of Rac1 responses in breast cancer cells. P-Rex1 is activated by the PI3K product PIP3 and Gβγ subunits, and integrates signals from ErbB receptors and GPCRs. Most notably, P-Rex1 is highly overexpressed in human luminal breast tumors, particularly those expressing ErbB2 and estrogen receptor (ER). The P-Rex1/Rac signaling pathway may represent an attractive target for breast cancer therapy.

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

Only two genome-wide association studies (GWAS) have been conducted to date to identify potential markers for total mortality after diagnosis of breast cancer. Here, we report the identification of two single-nucleotide polymorphisms (SNP) associated with total mortality from a two-stage GWAS conducted among 6,110 Shanghai-resident Chinese women with tumor-node-metastasis (TNM) stage I to IV breast cancer. The discovery stage included 1,950 patients and evaluated 613,031 common SNPs. The top 49 associations were evaluated in an independent replication stage of 4,160 Shanghai patients with breast cancer. A consistent and highly significant association with total mortality was documented for SNPs rs3784099 and rs9934948. SNP rs3784099, located in the RAD51L1 gene, was associated with total morality in both the discovery stage (P = 1.44 × 10(-8)) and replication stage (P = 0.06; P-combined = 1.17 × 10(-7)). Adjusted HRs for total mortality were 1.41 [95% confidence interval (CI), 1.18-1.68] for the AG genotype and 2.64 (95% CI, 1.74-4.03) for the AA genotype, when compared with the GG genotype. The variant C allele of rs9934948, located on chromosome 16, was associated with a similarly elevated risk of total mortality (P-combined = 5.75 × 10(-6)). We also observed this association among 1,145 patients with breast cancer of European ancestry from the Nurses' Health Study (NHS; P = 0.006); the association was highly significant in a combined analysis of NHS and Chinese data (P = 1.39 × 10(-7)). Similar associations were observed for these two SNPs with breast cancer-specific mortality. This study provides strong evidence suggesting that the RAD51L1 gene and a chromosome 16 locus influence breast cancer prognosis.