Characterization of SNPs Associated with Prostate Cancer in Men of Ashkenazic Descent from the Set of GWAS Identified SNPs: Impact of Cancer Family History and Cumulative SNP Risk Prediction

Background

Genome-wide association studies (GWAS) have identified multiple SNPs associated with prostate cancer (PrCa). Population isolates may have different sets of risk alleles for PrCa constituting unique population and individual risk profiles.

Methods

To test this hypothesis, associations between 31 GWAS SNPs of PrCa were examined among 979 PrCa cases and 1,251 controls of Ashkenazic descent using logistic regression. We also investigated risks by age at diagnosis, pathological features of PrCa, and family history of cancer. Moreover, we examined associations between cumulative number of risk alleles and PrCa and assessed the utility of risk alleles in PrCa risk prediction by comparing the area under the curve (AUC) for different logistic models.

Results

Of the 31 genotyped SNPs, 8 were associated with PrCa at p≤0.002 (corrected p-value threshold) with odds ratios (ORs) ranging from 1.22 to 1.42 per risk allele. Four SNPs were associated with aggressive PrCa, while three other SNPs showed potential interactions for PrCa by family history of PrCa (rs8102476; 19q13), lung cancer (rs17021918; 4q22), and breast cancer (rs10896449; 11q13). Men in the highest vs. lowest quartile of cumulative number of risk alleles had ORs of 3.70 (95% CI 2.76–4.97); 3.76 (95% CI 2.57–5.50), and 5.20 (95% CI 2.94–9.19) for overall PrCa, aggressive cancer and younger age at diagnosis, respectively. The addition of cumulative risk alleles to the model containing age at diagnosis and family history of PrCa yielded a slightly higher AUC (0.69 vs. 0.64).

Conclusion

These data define a set of risk alleles associated with PrCa in men of Ashkenazic descent and indicate possible genetic differences for PrCa between populations of European and Ashkenazic ancestry. Use of genetic markers might provide an opportunity to identify men at highest risk for younger age of onset PrCa; however, their clinical utility in identifying men at highest risk for aggressive cancer remains limited.     

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, diagnosis, prognosis and treatment. In recent years, microRNAs (miRNAs) have emerged as promising alternate biomarkers for prostate cancer diagnosis and prognosis. However, the development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. miRNA analyses in prostate cancer clinical specimens is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The goal of this article is to describe a simplified workflow for miRNA analyses in archived FFPE or fresh frozen prostate cancer clinical specimens using a combination of quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH). Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues and expression analyses by Taqman-probe based miRNA RT-PCR. In addition, we describe an optimized method for ISH analyses formiRNA detection in prostate tissues using locked nucleic acid (LNA)- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA).     

In silico evidence of high frequency of miRNA-related SNPs in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is the dominant histological type of esophageal cancer significantly reported in developing nations. There is an increasing evidence suggesting that single nucleotide polymorphisms (SNPs) in the untranslated regions of genes (3′-UTRs) targeted by microRNAs (miRNAs) can change the target gene's expression and thereby affect the individual's cancer risk. Thus, in support of the role of SNPs occurring in miRNA target sites (miR-TS-SNPs) in the cancer, we analyzed the next generation sequencing data of 10 ESCC patients. In each patient, about 3,000 SNPs in 3′-UTRs were obtained in their whole-exome sequencing profiles. We applied two separate methods, manual and computational in silico approaches, to predict the miR-TS-SNPs with more effects on the miRNA–target interactions. dbSNP, 1000G, ExAC, Iranome, miRandb, miRCancer, TargetScan, Human, miRNASNP2 and miRBase databases were used for positive selection of miR-TS-SNPs and DIANA-miRPath v3.0 for pathway analysis. We identified six rare germline miR-TS-SNPs and two other ones with unknown miR-TS-SNPs. We interestingly observed all of these variants in only one patient, which can be evidence of the relationship between miR-TS-SNPs and cancer incidence. The study of cancer genetics including miR-TS-SNPs reveals miRNAs and their related pathways, which will be greatly useful in cancer research from noninvasive biomarkers to new treatments.     

Differential expression profile and genetic variants of microRNAs sequences in breast cancer patients

The technology available for cancer diagnosis and prognosis is not yet satisfactory at the molecular level, and requires further improvements. Micro RNAs (miRNAs) have been recently reported as useful biomarkers in diseases including cancer. We performed a miRNA expression profiling study using peripheral blood from breast cancer patients to detect and identify characteristic patterns. A total of 100 breast cancer patients and 89 healthy patients were recruited for miRNA genotyping and expression profiling. We found that hs-miR-196a2 in premenopausal patients, and hs-miR-499, hs-miR-146a and hs-miR-196a2 in postmenopausal patients, may discriminate breast cancer patients from healthy individuals. In addition, we found a significant association between two microRNA polymorphisms (hs-miR-196a2 and hs-miR-499) and breast cancer risk. However, no significant association between the hs-miR-146a gene and breast cancer risk was found. In summary, the study demonstrates that peripheral blood miRNAs and their expression and genotypic profiles can be developed as biomarkers for early diagnosis and prognosis of breast cancer.     

Fine-Mapping the HOXB Region Detects Common Variants Tagging a Rare Coding Allele: Evidence for Synthetic Association in Prostate Cancer

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10⁻¹⁴). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.     

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case–control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ≤ 1E ^?3) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.     

Mass spectrometry-based expression profiling of clinical prostate cancer

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.     

Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.     

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

ABSTRACT: BACKGROUND: The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment. RESULTS: Our findings demonstrate that a miRNA's functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set. CONCLUSIONS: We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment.     

There Is No Association between MicroRNA Gene Polymorphisms and Risk of Triple Negative Breast Cancer in a Chinese Han Population

Triple-negative breast cancer (TNBC) is defined by the lack of the expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). It is characterized by aggressive behavior, poor prognosis and lack of targeted therapies. MicroRNA (miRNA) as a novel modulator of gene expression has played an important regulatory role in the malignancy. Dysregulation and/or mutation of the miRNAs may also contribute to the TNBC susceptibility since it is associated with the expression of ER, PR and HER2. Single nucleotide polymorphisms (SNPs) in miRNAs may be extremely relevant for TNBC. We tried to validate the hypothesis that genetic variations in miRNA are associated with TNBC development, and identify candidate biomarkers for TNBC susceptibility and clinical treatment. We screened the genetic variants in all miRNA genes listed in the public database miRBase and NCBI. A total of 23 common SNPs in 22 miRNAs, which tagged the known common variants in the Chinese Han people with a minor allele frequency greater than 0.05, were genotyped. This case-control study involved 191 patients with TNBC and 192 healthy female controls. Frequencies of SNPs were compared between cases and controls to identify the SNPs associated with TNBC susceptibility. No significant association was found between TNBC risk and the SNPs in the miRNA genes in the Chinese Han people (P>0.05), but this warrants further studies.     

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P?=?3.9?×?10(-22)). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P?=?1.9?×?10(-34)). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.     

Spermine and Citrate as Metabolic Biomarkers for Assessing Prostate Cancer Aggressiveness

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10⁻⁴), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10⁻⁴). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.     

Protein network-based Lasso regression model for the construction of disease-miRNA functional interactions

BackgroundThere is a growing body of evidence associating microRNAs (miRNAs) with human diseases. MiRNAs are new key players in the disease paradigm demonstrating roles in several human diseases. The functional association between miRNAs and diseases remains largely unclear and far from complete. With the advent of high-throughput functional genomics techniques that infer genes and biological pathways dysregulted in diseases, it is now possible to infer functional association between diseases and biological molecules by integrating disparate biological information.ResultsHere, we first used Lasso regression model to identify miRNAs associated with disease signature as a proof of concept. Then we proposed an integrated approach that uses disease-gene associations from microarray experiments and text mining, and miRNA-gene association from computational predictions and protein networks to build functional associations network between miRNAs and diseases. The findings of the proposed model were validated against gold standard datasets using ROC analysis and results were promising (AUC=0.81). Our protein network-based approach discovered 19 new functional associations between prostate cancer and miRNAs. The new 19 associations were validated using miRNA expression data and clinical profiles and showed to act as diagnostic and prognostic prostate biomarkers. The proposed integrated approach allowed us to reconstruct functional associations between miRNAs and human diseases and uncovered functional roles of newly discovered miRNAs.ConclusionsLasso regression was used to find associations between diseases and miRNAs using their gene signature. Defining miRNA gene signature by integrating the downstream effect of miRNAs demonstrated better performance than the miRNA signature alone. Integrating biological networks and multiple data to define miRNA and disease gene signature demonstrated high performance to uncover new functional associations between miRNAs and diseases.     

Genetic variation in microRNA genes and prostate cancer risk in North Indian population

Recent evidence indicates the involvement of microRNAs (miRNAs), in cell growth control, differentiation, and apoptosis, thus playing a role in tumorigenesis. Single-nucleotide polymorphisms (SNPs) located at miRNA-binding sites (miRNA-binding SNPs) are likely to affect the expression of the miRNA target and may contribute to the susceptibility of humans to common diseases. We genotyped SNPs hsa-mir196a2 (rs11614913), hsa-mir146a (rs2910164), and hsa-mir499 (rs3746444) in a case–control study including 159 prostate cancer patients and 230 matched controls. Patients with heterozygous genotype in hsa-mir196a2 and hsa-mir499, showed significant risk for developing prostate cancer (P = 0.01; OR = 1.70 and P ≤ 0.001; OR = 2.27, respectively). Similarly, the variant allele carrier was also associated with prostate cancer, (P = 0.01; OR = 1.66 and P ≤ 0.001; OR = 1.97, respectively) whereas, hsa-mir146a revealed no association in prostate cancer. None of the miRNA polymorphisms were associated with Gleason grade and bone metastasis. This is the first study on Indian population substantially presenting that individual as well as combined genotypes of miRNA-related variants may be used to predict the risk of prostate cancer and may be useful for identifying patients at high risk.     

miR-888 is an expressed prostatic secretions-derived microRNA that promotes prostate cell growth and migration

microRNAs (miRNAs) are a growing class of small non-coding RNAs that exhibit widespread dysregulation in prostate cancer. We profiled miRNA expression in syngeneic human prostate cancer cell lines that differed in their metastatic potential in order to determine their role in aggressive prostate cancer. miR-888 was the most differentially expressed miRNA observed in human metastatic PC3-ML cells relative to non-invasive PC3-N cells, and its levels were higher in primary prostate tumors from cancer patients, particularly those with seminal vesicle invasion. We also examined a novel miRNA-based biomarker source called expressed prostatic secretions in urine (EPS urine) for miR-888 expression and found that its levels were preferentially elevated in prostate cancer patients with high-grade disease. These expression studies indicated a correlation for miR-888 in disease progression. We next tested how miR-888 regulated cancer-related pathways in vitro using human prostate cancer cell lines. Overexpression of miR-888 increased proliferation and migration, and conversely inhibition of miR-888 activity blocked these processes. miR-888 also increased colony formation in PC3-N and LNCaP cells, supporting an oncogenic role for this miRNA in the prostate. Our data indicates that miR-888 functions to promote prostate cancer progression and can suppress protein levels of the tumor suppressor genes RBL1 and SMAD4. This miRNA holds promise as a diagnostic tool using an innovative prostatic fluid source as well as a therapeutic target for aggressive prostate cancer.     

A common regulatory variant in SLC35B4 influences the recurrence and survival of prostate cancer

Single nucleotide polymorphisms (SNPs) within the regulatory elements of a gene can alter gene expression, making these SNPs of prime importance for candidate gene association studies. We aimed to determine whether such regulatory variants are associated with clinical outcomes in three cohorts of patients with prostate cancer. We used RegulomeDB to identify potential regulatory variants based on in silico predictions and reviewed genome‐wide experimental findings. Overall, 131 putative regulatory SNPs with the highest confidence score on predicted functionality were investigated in two independent localized prostate cancer cohorts totalling 458 patients who underwent radical prostatectomy. The statistically significant SNPs identified in these two cohorts were then tested in an additional cohort of 504 patients with advanced prostate cancer. We identified one regulatory SNPs, rs1646724, that are consistently associated with increased risk of recurrence in localized disease (P = .003) and mortality in patients with advanced prostate cancer (P = .032) after adjusting for known clinicopathological factors. Further investigation revealed that rs1646724 may affect expression of SLC35B4, which encodes a glycosyltransferase, and that down‐regulation of SLC35B4 by transfecting short hairpin RNA in DU145 human prostate cancer cell suppressed proliferation, migration and invasion. Furthermore, we found increased SLC35B4 expression correlated with more aggressive forms of prostate cancer and poor patient prognosis. Our study provides robust evidence that regulatory genetic variants can affect clinical outcomes.     

MicroRNA binding-site polymorphisms as potential biomarkers of cancer risk

Identification of people or populations at risk for developing cancer is a key to improved screening programs and earlier detection, with the hope of a commensurate reduction in cancer mortalities. Genetic alterations that change gene expression levels have long been investigated for association with development of cancer. Misregulation of genes through altered interactions is another potential mechanism of oncogenesis. Gene regulation by microRNAs (miRNAs) is a relatively new area of study, and a growing body of evidence suggests that alterations in this process may be associated with increased cancer risk. This can occur through alterations in miRNA levels, interactions with targets, or perhaps more complicated combinations of the two. Here we review the current data for association between single nucleotide polymorphisms (SNPs) in miRNA binding sites and specific cancers. This growing body of literature suggests that these SNPs have a potential role as biomarkers for cancer risk.     

Elevated Serum MicroRNA Levels Associate with Absence of High-Grade Prostate Cancer in a Retrospective Cohort

To reduce treatment of indolent prostate cancer (PCa), biomarkers are needed to improve identification of patients with a low-risk of having aggressive disease. Over-treatment of these patients occurs because of uncertainty in the aggressiveness of the entire tumor based on the biopsies, which do not accurately sample multifocal tumors. Circulating microRNAs (miRNAs) are stable serum markers and differential miRNA levels occur in men with PCa. The goal of this study was to identify circulating miRNAs that were associated with aggressive or indolent PCa. We measured circulating miRNAs in 150 patients prior to surgery and compared the miRNA levels to the pathology of the entire radical prostatectomy specimen. For this study we used an exceptionally well-characterized cohort of patients who had benign prostatic hyperplasia (BPH), low-grade or high-grade PCa. Low-grade was defined as patients with 100% Gleason grade 3 tumor as determined by step-wise sectioning. High-grade PCa patients had 30-90% Gleason grade 4+5 in the tumor. BPH patients had at least two biopsies negative for PCa. Twenty one miRNAs were selected for analysis. The miRNAs were quantified by RT-qPCR and analyzed by logistic regression. High levels of 14 miRNAs were exclusively present in the serum from patients with low-grade PCa or BPH, compared to men with high-grade PCa who had consistently low levels. The expression levels of the 14 miRNAs were combined into a “miR Score” which had a negative predictive value (NPV) of 0.939 to predict absence of high-grade PCa among PCa and BPH patients. Biochemical recurrence (BCR) was known for the PCa patients and a combined “miR Risk Score” accurately classified a subset of patients with low risk of BCR (NPV 0.941). In summary, measurement of serum miRNAs may have pre-surgical utility in combination with clinical risk calculators to identify patients with low risk of harboring aggressive PCa.     

Evaluation of polymorphisms in microRNA‐binding sites and pancreatic cancer risk in Chinese population

As promising biomarkers and therapy targets, microRNAs (miRNAs) are involved in various physiological and tumorigenic processes. Genetic variants in miRNA‐binding sites can lead to dysfunction of miRNAs and contribute to disease. However, systematic investigation of the miRNA‐related single nucleotide polymorphisms (SNPs) for pancreatic cancer (PC) risk remains elusive. We performed integrative bioinformatics analyses to select 31 SNPs located in miRNA‐target binding sites using the miRNASNP v2.0, a solid database providing miRNA‐related SNPs for genetic research, and investigated their associations with risk of PC in two large case‐control studies totally including 1847 cases and 5713 controls. We observed that the SNP rs3802266 is significantly associated with increased risk of PC (odds ratio (OR) = 1.21, 95% confidence intervals (CI) = 1.11‐1.31, P = 1.29E‐05). Following luciferase reporter gene assays show that rs3802266‐G creates a stronger binding site for miR‐181a‐2‐3p in 3′ untranslated region (3′UTR) of the gene ZHX2. Expression quantitative trait loci (eQTL) analysis suggests that ZHX2 expression is lower in individuals carrying rs3802266‐G with increased PC risk. In conclusion, our findings highlight the involvement of miRNA‐binding SNPs in PC susceptibility and provide new clues for PC carcinogenesis.     

Clinical implications of microRNAs in cancer

Abstract

MicroRNAs (miRNAs) are endogenously produced non-coding RNAs that serve as micromanagers by negatively regulating gene expression. MiRNAs are implicated in several biological pathways including development of neoplasia. Because altered miRNA expression is implicated in the pathobiology of various cancers, these molecules serve as potential therapeutic targets. Using miRNA mimics to restore levels of aberrantly down-regulated miRNAs or miRNA inhibitors to inactivate over-expressed miRNAs shows promise as the next generation of therapeutic strategies. Manipulation of miRNAs offers an alternative therapeutic approach for chemo- and radiation-resistant tumors. Similarly, miRNA expression patterns can be used for diagnosis and to predict prognosis and efficacy of therapy. We present here an overview of how miRNAs affect cancers, how they may be used as biomarkers, and the clinical implications of miRNAs in cancer.