Identification of a Candidate Gene Panel for the Early Diagnosis of Prostate Cancer

Validation of Novel Biomarkers for Prostate Cancer Progression by the Combination of Bioinformatics, Clinical and Functional Studies

The identification and validation of biomarkers for clinical applications remains an important issue for improving diagnostics and therapy in many diseases, including prostate cancer. Gene expression profiles are routinely applied to identify diagnostic and predictive biomarkers or novel targets for cancer. However, only few predictive markers identified in silico have also been validated for clinical, functional or mechanistic relevance in disease progression. In this study, we have used a broad, bioinformatics-based approach to identify such biomarkers across a spectrum of progression stages, including normal and tumor-adjacent, premalignant, primary and late stage lesions. Bioinformatics data mining combined with clinical validation of biomarkers by sensitive, quantitative reverse-transcription PCR (qRT-PCR), followed by functional evaluation of candidate genes in disease-relevant processes, such as cancer cell proliferation, motility and invasion. From 300 initial candidates, eight genes were selected for validation by several layers of data mining and filtering. For clinical validation, differential mRNA expression of selected genes was measured by qRT-PCR in 197 clinical prostate tissue samples including normal prostate, compared against histologically benign and cancerous tissues. Based on the qRT-PCR results, significantly different mRNA expression was confirmed in normal prostate versus malignant PCa samples (for all eight genes), but also in cancer-adjacent tissues, even in the absence of detectable cancer cells, thus pointing to the possibility of pronounced field effects in prostate lesions. For the validation of the functional properties of these genes, and to demonstrate their putative relevance for disease-relevant processes, siRNA knock-down studies were performed in both 2D and 3D organotypic cell culture models. Silencing of three genes (DLX1, PLA2G7 and RHOU) in the prostate cancer cell lines PC3 and VCaP by siRNA resulted in marked growth arrest and cytotoxicity, particularly in 3D organotypic cell culture conditions. In addition, silencing of PLA2G7, RHOU, ACSM1, LAMB1 and CACNA1D also resulted in reduced tumor cell invasion in PC3 organoid cultures. For PLA2G7 and RHOU, the effects of siRNA silencing on proliferation and cell-motility could also be confirmed in 2D monolayer cultures. In conclusion, DLX1 and RHOU showed the strongest potential as useful clinical biomarkers for PCa diagnosis, further validated by their functional roles in PCa progression. These candidates may be useful for more reliable identification of relapses or therapy failures prior to the recurrence local or distant metastases.

Non‑invasive prostate cancer detection by measuring miRNA variants (isomiRs) in urine extracellular vesicles

In many cancer types, the expression and function of ~22 nucleotide-long microRNAs (miRNA) is deregulated. Mature miRNAs can be stably detected in extracellular vesicles (EVs) in biofluids, therefore they are considered to have great potential as biomarkers. In the present study, we investigated whether miRNAs have a distinct expression pattern in urine-EVs of prostate cancer (PCa) patients compared to control males. By next generation sequencing, we determined the miRNA expression in a discovery cohort of 4 control men and 9 PCa patients. miRNAs were validated by using a stemloop RT-PCR in an independent cohort of 74 patients (26 control and 48 PCa-patients). Whereas standard mapping protocols identified > 10 PCa associated miRNAs in urinary EVs, miR-21, miR-375 and miR-204 failed to robustly discriminate for disease in a validation study with RT-PCR-detection of mature miRNA sequences. In contrast, we observed that miRNA isoforms (isomiRs) with 3' end modifications were highly discriminatory between samples from control men and PCa patients. Highly differentially expressed isomiRs of miR-21, miR-204 and miR-375 were subsequently validated in an independent group of 74 patients. Receiver-operating characteristic analysis was performed to evaluate the diagnostic performance of three isomiRs, resulting in a 72.9% sensitivity with a high (88%) specificity and an area under the curve (AUC) of 0.866. In comparison, prostate specific antigen had an AUC of 0.707 and measuring the mature form of these miRNAs yielded a lower 70.8% sensitivity and 72% specificity (AUC 0.766). We propose that isomiRs may carry discriminatory information which is useful to generate stronger biomarkers.

The role of HOXC6 in prostate cancer development

BACKGROUND

Homeobox (HOX) genes, which are involved in organ development and homeostasis, have been shown to be involved in normal prostate- and PCa development. In this study, we investigate the expression levels of the HOX A-D genes in PCa. The functional relevance and potential of HOX gene as biomarkers are explored.

METHODS

We evaluated HOX gene expression in prostate tissues of different grade and stage and related the outcome to clinical parameters. We analyzed AR regulation and function of HOXC6 in PCa cell lines. We developed a urine-based HOXC6 mRNA assay for diagnostic purposes.

RESULTS

HOXC6 was one of the most upregulated HOX genes in all primary, metastasized, and castration-resistant PCa. HOXC6 upregulation was specific to the epithelial component of PCa, and HOXC6 was shown to be involved in epithelial cell proliferation. HOXC6 expression was not influenced by androgens nor by treatments targeting the AR signaling pathway. HOXC6 expression was not related to a prognosis after radical prostatectomy, that is, biochemical or local recurrence. We successfully developed an assay for HOXC6 mRNA detection in urine and confirmed that HOXC6 levels are higher in PCa patients.

CONCLUSIONS

HOXC6 has a role in all PCa stages, particularly in PCa cell proliferation. Due to its stable expression, HOXC6 is a novel candidate biomarker for PCa not only in early detection but also for monitoring of progression or response to therapy.

Next-Generation Sequencing Approaches in Cancer: Where Have They Brought Us and Where Will They Take Us?

Next-generation sequencing (NGS) technologies and data have revolutionized cancer research and are increasingly being deployed to guide clinicians in treatment decision-making. NGS technologies have allowed us to take an “omics” approach to cancer in order to reveal genomic, transcriptomic, and epigenomic landscapes of individual malignancies. Integrative multi-platform analyses are increasingly used in large-scale projects that aim to fully characterize individual tumours as well as general cancer types and subtypes. In this review, we examine how NGS technologies in particular have contributed to “omics” approaches in cancer research, allowing for large-scale integrative analyses that consider hundreds of tumour samples. These types of studies have provided us with an unprecedented wealth of information, providing the background knowledge needed to make small-scale (including “N of 1”) studies informative and relevant. We also take a look at emerging opportunities provided by NGS and state-of-the-art third-generation sequencing technologies, particularly in the context of translational research. Cancer research and care are currently poised to experience significant progress catalyzed by accessible sequencing technologies that will benefit both clinical- and research-based efforts.