Unravelling the Role of Iroquois Homeobox 4 and its Interplay with Androgen Receptor in Prostate Cancer.

Genome-wide association studies have linked Iroquois-Homeobox 4 (IRX4) as a robust expression quantitative-trait locus associated with prostate cancer (PCa) risk. However, the intricate mechanism and regulatory factors governing IRX4 expression in PCa remain poorly understood. Here, we unveil enrichment of androgen-responsive gene signatures in metastatic prostate tumors exhibiting heightened IRX4 expression. Furthermore, we uncover a novel interaction between IRX4 and the androgen receptor (AR) co-factor, FOXA1, suggesting that IRX4 modulates PCa cell behavior through AR cistrome alteration. Remarkably, we identified a distinctive short insertion-deletion polymorphism (INDEL), upstream of the IRX4 gene that differentially regulates IRX4 expression through the disruption of AR binding. This INDEL emerges as the most significant PCa risk-associated variant within the 5p15 locus, in a genetic analysis involving 82,591 PCa cases and 61,213 controls and was associated with PCa survival in patients undergoing androgen-deprivation therapy. These studies suggest the potential of this INDEL as a prognostic biomarker for androgen therapy in PCa and IRX4 as a potential therapeutic target in combination with current clinical management.

Characterisation of cell lines derived from prostate cancer patients with localised disease.

BACKGROUND: Prostate cancer is a broad-spectrum disease, spanning from indolent to a highly aggressive lethal malignancy. Prostate cancer cell lines are essential tools to understanding the basic features of this malignancy, as well as in identifying novel therapeutic strategies. However, most cell lines routinely used in prostate cancer research are derived from metastatic disease and may not fully elucidate the molecular events underlying the early stages of cancer development and progression. Thus, there is a need for new cell lines derived from localised disease to better span the disease spectrum. METHODS: Prostatic tissue from the primary site, and adjacent non-cancerous tissue was obtained from four patients with localised disease undergoing radical prostatectomy. Epithelial cell outgrowths were immortalised with human papillomavirus type 16 (HPV16) E6 and E7 to establish monoclonal cell lines. Chromosomal ploidy was imaged and STR profiles were determined. Cell morphology, colony formation and cell proliferation characteristics were assessed. Androgen receptor (AR) expression and AR-responsiveness to androgen treatment were analysed by immunofluorescence and RT-qPCR, respectively. RNA-seq analysis was performed to identify prostate lineage markers and expression of prostate cancer tumorigenesis-related genes. RESULTS: Two benign cell lines derived from non-cancer cells (AQ0420 and AQ0396) and two tumour tissue derived cancer cell lines (AQ0411 and AQ0415) were immortalised from four patients with localised prostatic adenocarcinoma. The cell lines presented an epithelial morphology and a slow to moderate proliferative rate. None of the cell lines formed anchorage independent colonies or displayed AR-responsiveness. Comparative RNA-seq expression analysis confirmed the prostatic lineage of the four cell lines, with a distinct gene expression profile from that of the metastatic prostate cancer cell lines, PC-3 and LNCaP. CONCLUSIONS: Comprehensive characterization of these cell lines may provide new in vitro tools that could bridge the current knowledge gap between benign, early-stage and metastatic disease.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer.

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

Severe COVID-19 May Impact Hepatic Fibrosis /Hepatic Stellate Cells Activation as Indicated by a Pathway and Population Genetic Study.

Coronavirus disease 19 (COVID-19) has affected over 112 million people and killed more than 2.5 million worldwide. When the pandemic was declared, Spain and Italy accounted for 29% of the total COVID-19 related deaths in Europe, while most infected patients did not present severe illness. We hypothesised that shared genomic characteristics, distinct from the rest of Europe, could be a contributor factor to a poor prognosis in these two populations. To identify pathways related to COVID-19 severity, we shortlisted 437 candidate genes associated with host viral intake and immune evasion from SARS-like viruses. From these, 21 were associated specifically with clinically aggressive COVID-19. To determine the potential mechanism of viral infections, we performed signalling pathway analysis with either the full list (n = 437) or the subset group (n = 21) of genes. Four pathways were significantly associated with the full gene list (Caveolar-mediated Endocytosis and the MSP-RON Signalling) or with the aggressive gene list (Hepatic Fibrosis/Hepatic Stellate Cell (HSC) Activation and the Communication between Innate and Adaptive Immune Cells). Single nucleotide polymorphisms (SNPs) from the ±1 Mb window of all genes related to these four pathways were retrieved from the dbSNP database. We then performed Principal Component analysis for these SNPs in individuals from the 1000 Genomes of European ancestry. Only the Hepatic Fibrosis/HSC Activation pathway showed population-specific segregation. The Spanish and Italian populations clustered together and away from the rest of the European ancestries, with the first segregating further from the rest. Additional in silico analysis identified potential genetic markers and clinically actionable therapeutic targets in this pathway, that may explain the severe disease.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Assessment of miR-98-5p, miR-152-3p, miR-326 and miR-4289 Expression as Biomarker for Prostate Cancer Diagnosis.

Prostate cancer (PCa) is one of the most commonly diagnosed cancers worldwide, accounting for almost 1 in 5 new cancer diagnoses in the US alone. The current non-invasive biomarker prostate specific antigen (PSA) has lately been presented with many limitations, such as low specificity and often associated with over-diagnosis. The dysregulation of miRNAs in cancer has been widely reported and it has often been shown to be specific, sensitive and stable, suggesting miRNAs could be a potential specific biomarker for the disease. Previously, we identified four miRNAs that are significantly upregulated in plasma from PCa patients when compared to healthy controls: miR-98-5p, miR-152-3p, miR-326 and miR-4289. This panel showed high specificity and sensitivity in detecting PCa (area under the curve (AUC) = 0.88). To investigate the specificity of these miRNAs as biomarkers for PCa, we undertook an in depth analysis on these miRNAs in cancer from the existing literature and data. Additionally, we explored their prognostic value found in the literature when available. Most studies showed these miRNAs are downregulated in cancer and this is often associated with cancer progression and poorer overall survival rate. These results suggest our four miRNA signatures could potentially become a specific PCa diagnostic tool of which prognostic potential should also be explored.

Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.

Association Analysis of a Microsatellite Repeat in the TRIB1 Gene With Prostate Cancer Risk, Aggressiveness and Survival.

With an estimated 1.1 million men worldwide diagnosed with prostate cancer yearly, effective and more specific biomarkers for early diagnosis could lead to better patient outcome. As such, novel genetic markers are sought for this purpose. The tribbles homologue 1 gene (TRIB1) has recently shown to have a role in prostate tumorigenesis and data-mining of prostate cancer expression data confirmed clinical significance of TRIB1 in prostate cancer. For the first time, a polymorphic microsatellite in this gene was studied for its potential association with prostate cancer risk and aggressiveness. Genomic DNA was extracted from a cohort of 1,152 prostate cancer patients and 1,196 cancer-free controls and the TTTTG-TRIB1 microsatellite was genotyped. The socio-demographic and clinical characteristics were analyzed using the non-parametric t-test and two-way ANOVA. Association of the TTTTG-TRIB1 microsatellite and prostate cancer risk and aggressiveness were analyzed by binary logistic regression and confirmed by bootstrapping. Total and prostate cancer mortality was analyzed using the Kaplan Meier test. Genotype and allele correlation with TRIB1 mRNA levels was analyzed using the non-parametric Kolmogorov-Smirnov test. To predict the effect that the TTTTG-TRIB1 polymorphisms had on the mRNA structure, the in silico RNA folding predictor tool, mfold, was used. By analyzing the publicly available data, we confirmed a significant over-expression of TRIB1 in prostate cancer compared to other cancer types, and an over-expression in prostate cancerous tissue compared to adjacent benign. Three alleles (three-five repeats) were observed for TTTTG-TRIB1. The three-repeat allele was associated with prostate cancer risk at the allele (OR = 1.16; P = 0.044) and genotypic levels (OR = 1.70; P = 0.006) and this association was age-independent. The four-repeat allele was inversely associated with prosatet cancer risk (OR = 0.57; P < 0.0001). TRIB1 expression was upregulated in tumors when compared to adjacent cancer-free tissue but was not allele specific. In silico analysis suggested that the TTTTG-TRIB1 alleles may alter TRIB1 mRNA structure. In summary, the three-repeat allele was significantly associated with prostate cancer risk, suggesting a biomarker potential for this microsatellite to predict prostate cancer. Further studies are needed to elucidate the functional role of this microsatellite in regulating TRIB1 expression, perhaps by affecting the TRIB1 mRNA structure and stability.

Mining human cancer datasets for kallikrein expression in cancer: the 'KLK-CANMAP' Shiny web tool.

The dysregulation of the serine-protease family kallikreins (KLKs), comprising 15 genes, has been reportedly associated with cancer. Their expression in several tissues and physiological fluids makes them potential candidates as biomarkers and therapeutic targets. There are several databases available to mine gene expression in cancer, which often include clinical and pathological data. However, these platforms present some limitations when comparing a specific set of genes and can generate considerable unwanted data. Here, several datasets that showed significant differential expression (p<0.01) in cancer vs. normal (n=118), metastasis vs. primary (n=15) and association with cancer survival (n=21) have been compiled in a user-friendly format from two open and/or publicly available databases Oncomine and OncoLnc for the 15 KLKs. The data have been included in a free web application tool: the KLK-CANMAP https://cancerbioinformatics.shinyapps.io/klk-canmap/. This tool integrates, analyses and visualises data and it was developed with the R Shiny framework. Using KLK-CANMAP box-plots, heatmaps and Kaplan-Meier graphs can be generated for the KLKs of interest. We believe this new cancer KLK focused web tool will benefit the KLK community by narrowing the data visualisation to only the genes of interest.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

A Plasma Biomarker Panel of Four MicroRNAs for the Diagnosis of Prostate Cancer.

Prostate cancer is diagnosed in over 1 million men every year globally, yet current diagnostic modalities are inadequate for identification of significant cancer and more reliable early diagnostic biomarkers are necessary for improved clinical management of prostate cancer patients. MicroRNAs (miRNAs) modulate important cellular processes/pathways contributing to cancer and are stably present in body fluids. In this study we profiled 372 cancer-associated miRNAs in plasma collected before (~60% patients) and after/during commencement of treatment (~40% patients), from age-matched prostate cancer patients and healthy controls, and observed elevated levels of 4 miRNAs - miR-4289, miR-326, miR-152-3p and miR-98-5p, which were validated in an independent cohort. The miRNA panel was able to differentiate between prostate cancer patients and controls (AUC = 0.88). Analysis of published miRNA transcriptomic data from clinical samples demonstrated low expression of miR-152-3p in tumour compared to adjacent non-malignant tissues. Overexpression of miR-152-3p increased proliferation and migration of prostate cancer cells, suggesting a role for this miRNA in prostate cancer pathogenesis, a concept that was supported by pathway analysis of predicted miR-152-3p target genes. In summary, a four miRNA panel, including miR-152-3p which likely targets genes with key roles in prostate cancer pathogenesis, has the potential to improve early prostate cancer diagnosis.

A microsatellite repeat in PCA3 long non-coding RNA is associated with prostate cancer risk and aggressiveness.

Short tandem repeats (STRs) are repetitive sequences of a polymorphic stretch of two to six nucleotides. We hypothesized that STRs are associated with prostate cancer development and/or progression. We undertook RNA sequencing analysis of prostate tumors and adjacent non-malignant cells to identify polymorphic STRs that are readily expressed in these cells. Most of the expressed STRs in the clinical samples mapped to intronic and intergenic DNA. Our analysis indicated that three of these STRs (TAAA-ACTG2, TTTTG-TRIB1, and TG-PCA3) are polymorphic and differentially expressed in prostate tumors compared to adjacent non-malignant cells. TG-PCA3 STR expression was repressed by the anti-androgen drug enzalutamide in prostate cancer cells. Genetic analysis of prostate cancer patients and healthy controls (N > 2,000) showed a significant association of the most common 11 repeat allele of TG-PCA3 STR with prostate cancer risk (OR = 1.49; 95% CI 1.11-1.99; P = 0.008). A significant association was also observed with aggressive disease (OR = 2.00; 95% CI 1.06-3.76; P = 0.031) and high mortality rates (HR = 3.0; 95% CI 1.03-8.77; P = 0.045). We propose that TG-PCA3 STR has both diagnostic and prognostic potential for prostate cancer. We provided a proof of concept to be applied to other RNA sequencing datasets to identify disease-associated STRs for future clinical exploratory studies.

Association mapping of starch chain length distribution and amylose content in pea (Pisum sativum L.) using carbohydrate metabolism candidate genes.

BACKGROUND: Although starch consists of large macromolecules composed of glucose units linked by α-1,4-glycosidic linkages with α-1,6-glycosidic branchpoints, variation in starch structural and functional properties is found both within and between species. Interest in starch genetics is based on the importance of starch in food and industrial processes, with the potential of genetics to provide novel starches. The starch metabolic pathway is complex but has been characterized in diverse plant species, including pea. RESULTS: To understand how allelic variation in the pea starch metabolic pathway affects starch structure and percent amylose, partial sequences of 25 candidate genes were characterized for polymorphisms using a panel of 92 diverse pea lines. Variation in the percent amylose composition of extracted seed starch and (amylopectin) chain length distribution, one measure of starch structure, were characterized for these lines. Association mapping was undertaken to identify polymorphisms associated with the variation in starch chain length distribution and percent amylose, using a mixed linear model that incorporated population structure and kinship. Associations were found for polymorphisms in seven candidate genes plus Mendel's r locus (which conditions the round versus wrinkled seed phenotype). The genes with associated polymorphisms are involved in the substrate supply, chain elongation and branching stages of the pea carbohydrate and starch metabolic pathways. CONCLUSIONS: The association of polymorphisms in carbohydrate and starch metabolic genes with variation in amylopectin chain length distribution and percent amylose may help to guide manipulation of pea seed starch structural and functional properties through plant breeding.

Ascochyta blight disease of pea (Pisum sativum L.): defence-related candidate genes associated with QTL regions and identification of epistatic QTL.

KEY MESSAGE: Advances have been made in our understanding of Ascochyta blight resistance genetics through mapping candidate genes associated with QTL regions and demonstrating the importance of epistatic interactions in determining resistance. Ascochyta blight disease of pea (Pisum sativum L.) is economically significant with worldwide distribution. The causal pathogens are Didymella pinodes, Phoma medicaginis var pinodella and, in South Australia, P. koolunga. This study aimed to identify candidate genes that map to quantitative trait loci (QTL) for Ascochyta blight field disease resistance and to explore the role of epistatic interactions. Candidate genes associated with QTL were identified beginning with 101 defence-related genes from the published literature. Synteny between pea and Medicago truncatula was used to narrow down the candidates for mapping. Fourteen pea candidate sequences were mapped in two QTL mapping populations, A26 × Rovar and A88 × Rovar. QTL peaks, or the intervals containing QTL peaks, for the Asc2.1, Asc4.2, Asc4.3 and Asc7.1 QTL were defined by four of these candidate genes, while another three candidate genes occurred within 1.0 LOD confidence intervals. Epistasis involving QTL × background marker and background marker × background marker interactions contributed to the disease response phenotypes observed in the two mapping populations. For each population, five pairwise interactions exceeded the 5% false discovery rate threshold. Two candidate genes were involved in significant pairwise interactions. Markers in three genomic regions were involved in two or more epistatic interactions. Therefore, this study has identified pea defence-related sequences that are candidates for resistance determination, and that may be useful for marker-assisted selection. The demonstration of epistasis informs breeders that the architecture of this complex quantitative resistance includes epistatic interactions with non-additive effects.

Fusion transcript loci share many genomic features with non-fusion loci.

BACKGROUND: Fusion transcripts are found in many tissues and have the potential to create novel functional products. Here, we investigate the genomic sequences around fusion junctions to better understand the transcriptional mechanisms mediating fusion transcription/splicing. We analyzed data from prostate (cancer) cells as previous studies have shown extensively that these cells readily undergo fusion transcription. RESULTS: We used the FusionMap program to identify high-confidence fusion transcripts from RNAseq data. The RNAseq datasets were from our (N = 8) and other (N = 14) clinical prostate tumors with adjacent non-cancer cells, and from the LNCaP prostate cancer cell line that were mock-, androgen- (DHT), and anti-androgen- (bicalutamide, enzalutamide) treated. In total, 185 fusion transcripts were identified from all RNAseq datasets. The majority (76%) of these fusion transcripts were 'read-through chimeras' derived from adjacent genes in the genome. Characterization of sequences at fusion loci were carried out using a combination of the FusionMap program, custom Perl scripts, and the RNAfold program. Our computational analysis indicated that most fusion junctions (76%) use the consensus GT-AG intron donor-acceptor splice site, and most fusion transcripts (85%) maintained the open reading frame. We assessed whether parental genes of fusion transcripts have the potential to form complementary base pairing between parental genes which might bring them into physical proximity. Our computational analysis of sequences flanking fusion junctions at parental loci indicate that these loci have a similar propensity as non-fusion loci to hybridize. The abundance of repetitive sequences at fusion and non-fusion loci was also investigated given that SINE repeats are involved in aberrant gene transcription. We found few instances of repetitive sequences at both fusion and non-fusion junctions. Finally, RT-qPCR was performed on RNA from both clinical prostate tumors and adjacent non-cancer cells (N = 7), and LNCaP cells treated as above to validate the expression of seven fusion transcripts and their respective parental genes. We reveal that fusion transcript expression is similar to the expression of parental genes. CONCLUSIONS: Fusion transcripts maintain the open reading frame, and likely use the same transcriptional machinery as non-fusion transcripts as they share many genomic features at splice/fusion junctions.

A genetic variant of MDM4 influences regulation by multiple microRNAs in prostate cancer.

The oncogene MDM4, also known as MDMX or HDMX, contributes to cancer susceptibility and progression through its capacity to negatively regulate a range of genes with tumour-suppressive functions. As part of a recent genome-wide association study it was determined that the A-allele of the rs4245739 SNP (A>C), located in the 3'-UTR of MDM4, is associated with an increased risk of prostate cancer. Computational predictions revealed that the rs4245739 SNP is located within a predicted binding site for three microRNAs (miRNAs): miR-191-5p, miR-887 and miR-3669. Herein, we show using reporter gene assays and endogenous MDM4 expression analyses that miR-191-5p and miR-887 have a specific affinity for the rs4245739 SNP C-allele in prostate cancer. These miRNAs do not affect MDM4 mRNA levels, rather they inhibit its translation in C-allele-containing PC3 cells but not in LNCaP cells homozygous for the A-allele. By analysing gene expression datasets from patient cohorts, we found that MDM4 is associated with metastasis and prostate cancer progression and that targeting this gene with miR-191-5p or miR-887 decreases in PC3 cell viability. This study is the first, to our knowledge, to demonstrate regulation of the MDM4 rs4245739 SNP C-allele by two miRNAs in prostate cancer, and thereby to identify a mechanism by which the MDM4 rs4245739 SNP A-allele may be associated with an increased risk for prostate cancer.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.