MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families

BackgroundHeritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS). The thus far identified Single Nucleotide Polymorphisms (SNPs) explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer.ResultsIn this study microRNA (miRNA) profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL) analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found.ConclusionBased on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening, together with Prostate Specific Antigene (PSA) testing, to identify men with an elevated PrCa risk.背景 遗传易感因素显然参与前列腺癌（prostate cancer, PrCa）的癌变进程，但目前遗传标志物尚未常规应用于该疾病的筛查与诊断。亟需更精准的信息以辅助治疗决策，区分侵袭性前列腺癌与惰性前列腺癌，而遗传易感因素在此方面可成为有效的辅助工具。直至近年，前列腺癌的遗传构成才通过大规模全基因组关联研究（genome-wide association studies, GWAS）逐步得以解析。但迄今已鉴定的单核苷酸多态性（Single Nucleotide Polymorphisms, SNPs）仅能解释部分家族聚集性病例。此外，已知的风险SNPs与该疾病的临床转归（如侵袭性或转移性前列腺癌）并无关联，因此无法用于预后预测。结合深度临床数据与微小RNA（microRNA, miRNA）表达谱对SNPs进行注释，有助于加深对前列腺癌不同表型潜在发病机制的理解。 结果 本研究以微小RNA（miRNA）表达谱作为潜在生物标志物，旨在预测前列腺癌的临床转归。研究对象来自芬兰高危前列腺癌家族队列。为筛选潜在生物标志物，本研究将一种新型非参数检验与随机森林分类器提供的重要性评分相结合。该分析策略筛选出一组共9种miRNA，可有效区分病例组与对照组样本。该检测得到的miRNA表达谱可在前列腺癌确诊前数年预测疾病发生风险，或可识别研究对象体内其他恶性肿瘤的存在。此外，通过表达数量性状位点（expression Quantitative Trait Loci, eQTL）分析，本研究发现了针对miR-483-3p的调控性SNPs，且这些SNPs本身亦与前列腺癌直接相关。 结论 基于本研究结果，我们认为基于血液的miRNA表达谱分析可应用于前列腺癌的诊断，甚至有望用于预后评估。未来，miRNA表达谱分析或可与前列腺特异性抗原（Prostate Specific Antigene, PSA）检测联合应用于针对性筛查，以识别前列腺癌风险升高的男性群体。