Gene panel model predictive of outcome in patients with prostate cancer

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

Objectives

The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management.

Methods

We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included.

Results

Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies.

Conclusions

The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.

The association between histone 3 lysine 27 trimethylation (H3K27me3) and prostate cancer: relationship with clinicopathological parameters

BACKGROUND

It is well established that genetic and epigenetic alterations are common events in prostate cancer, which may lead to aberrant expression of critical genes. The importance of epigenetic mechanisms in prostate cancer carcinogenesis is increasingly evident. In this study, the focus will be on histone modifications and the primary objectives are to map H3K27me3 marks and quantify RAR beta 2, ER alpha, SRC3, RGMA, PGR, and EZH2 gene expressions in prostate cancer tissues compared to normal tissues. In addition, a data analysis was made in connection with the clinicopathological parameters.

METHODS

71 normal specimens and 66 cancer prostate tissues were randomly selected in order to assess the proportion of the repressive H3K27me3 mark and gene expression. H3K27me3 level was evaluated by ChIP-qPCR and mRNA expression using RT-qPCR between prostate cancer and normal tissues. Subsequently, western-blotting was performed for protein detection. The analysis of variance (ANOVA) was performed, and Tukey's test was used to correct for multiple comparisons (p-value threshold of 0.05). The principal component analysis (PCA) and discriminant factorial analysis (DFA) were used to explore the association between H3K27me3 level and clinicopathological parameters.

RESULTS

The study demonstrated that H3K27me3 level was significantly enriched at the RAR beta 2, ER alpha, PGR, and RGMA promoter regions in prostate cancer tissues compared to normal tissues. After stratification by clinicopathological parameters, the H3K27me3 level was positively correlated with Gleason score, PSA levels and clinical stages for RAR beta 2, ER alpha, PGR, and RGMA. High H3K27me3 mark was significantly associated with decreased RAR beta 2, ER alpha, PGR and RGMA gene expressions in prostate cancer sample compared to the normal one. Moreover, the results showed that mRNA level of EZH2, AR and SRC3 are upregulated in prostate cancer compared to normal prostate tissues and this correlates positively with Gleason score, PSA levels and clinical stages. Obviously, these observations were confirmed by protein level using western-blot.

CONCLUSIONS

This data clearly demonstrated that H3K27me3 level correlated with aggressive tumor features. Also this study revealed that reverse correlation of RAR beta 2, ER alpha, PGR, and RGMA expressions with EZH2, SRC3, and AR expressions in prostate cancer tissues suggests that these genes are the target of EZH2. Therefore, all therapeutic strategies leading to histone demethylation with epigenetic drugs such as histone methyltransferase inhibitor may be relevant treatments against prostate cancer.