Leire Moya

MSR1 repeats modulate gene expression and affect risk of breast and prostate cancer

Background MSR1 repeats are a 36-38 bp minisatellite element that have recently been implicated in the regulation of gene expression, through copy number variation (CNV). Patients and methods Bioinformatic and experimental methods were used to assess the distribution of MSR1 across the genome, evaluate the regulatory potential of such elements and explore the role of MSR1 elements in cancer, particularly non-familial breast cancer and prostate cancer. Results MSR1s are predominately located at chromosome 19 and are functionally enriched in regulatory regions of the genome, particularly regions implicated in short-range regulatory activities (H3K27ac, H3K4me1 and H3K4me3). MSR1-regulated genes were found to have specific molecular roles, such as serine-protease activity (P = 4.80 × 10-7) and ion channel activity (P = 2.7 × 10-4). The kallikrein locus was found to contain a large number of MSR1 clusters, and at least six of these showed CNV. An MSR1 cluster was identified within KLK14, with 9 and 11 copies being normal variants. A significant association with the 9-copy allele and non-familial breast cancer was found in two independent populations (P = 0.004; P = 0.03). In the white British population, the minor allele conferred an increased risk of 1.21-3.51 times for all non-familial disease, or 1.7-5.3 times in early-onset disease. The 9-copy allele was also found to be associated with increased risk of prostate cancer in an independent population (odds ratio = 1.27-1.56; P =0.009). Conclusions MSR1 repeats act as molecular switches that modulate gene expression. It is likely that CNV of MSR1 will affect risk of development of various forms of cancer, including that of breast and prostate. The MSR1 cluster at KLK14 represents the strongest risk factor identified to date in non-familial breast cancer and a significant risk factor for prostate cancer. Analysis of MSR1 genotype will allow development of precise stratification of disease risk and provide a novel target for therapeutic agents.

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.

Erratum to: Fusion transcript loci share many genomic features with non-fusion loci

After publication of the original article [1], a reader noted that one reference cited in the main text had not been mentioned in the References section. The reference (Qin et al., [2]) was cited as Ref. 33 within the text, but mistakenly did not appear in the References. As such the total number of References was also incorrect – there should have been 36 in total. References 33 – 35 should have been numbered 34 – 36 in the main text and in the References section.

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.

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

Abstract 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.