The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks.

Background: Prostate cancer (PCa) is the most common malignancy seen in men and the second leading cause of cancer-related death in males. The incidence and mortality associated with PCa has been rapidly increasing in China recently.

Methods: Multiple diagnostic models of human PCa were developed based on Taylor database by combining the artificial neural networks (ANNs) to enhance the ability of PCa diagnosis.

Increasing of FKBP9 can predict poor prognosis in patients with prostate cancer.

Background: FK506 binding protein 9 (FKBP9) has been reported and identified for a long time, but its relationship with cancer is rarely studied. For example, the role of FK506 binding protein 9 in prostate cancer (PCa) is still unclear. Therefore, we decided to detect the expression level of FKBP9 in PCa and explore its clinical significance.

miR‑30c suppresses prostate cancer survival by targeting the ASF/SF2 splicing factor oncoprotein.

Our previous study revealed that microRNA (miR) ‑30c represents a potential tumor suppressor gene, the expression of which is associated with decreased oncogenic potential in prostate cancer (PCa) cell lines. However, the functional role and underlying mechanisms of miR‑30c in PCa remain to be fully elucidated. Reverse transcription‑quantitative polymerase chain reaction and immunohistochemical analysis were used to detect the expression levels of alternative splicing factor/splicing factor 2 (ASF/SF2) in PCa tissues.

miR-195 Inhibits Tumor Progression by Targeting RPS6KB1 in Human Prostate Cancer.

Purpose: To investigate the involvement of hsa-miRNA-195-5p (miR-195) in progression and prognosis of human prostate cancer.

Experimental Design: qRT-PCR was performed to detect miR-195 expression in both prostate cancer cell lines and clinical tissue samples. Its clinical significance was statistically analyzed.

Down-regulation of dual-specificity phosphatase 5 predicts poor prognosis of patients with prostate cancer.

Dual-specificity phosphatase 5 (DUSP5), which specifically inactivates the extracellular signal-regulated kinase (ERK) 1/2 within the mitogen-activated protein kinase (MAPK) signaling, has recently been considered to be a tumor suppressor. However, its role in prostate cancer is still elusive. In this study, we performed immunohistochemistry analysis on human tissue microarray (TMA) to detect the DUSP5 protein expression pattern.

CC chemokine ligand 18 correlates with malignant progression of prostate cancer.

Background And Aim: CC chemokine ligand 18 (CCL18) promotes malignant behaviors of various human cancer types. However, its involvement in human prostate cancer has not been fully elucidated. The aim of this study was to investigate the role of CCL18 in PCa.

Combined overexpression of HIVEP3 and SOX9 predicts unfavorable biochemical recurrence-free survival in patients with prostate cancer.

Background: To clarify the involvement of HIVEP3 and SOX9 coexpression in prostate cancer (PCa).

Methods: A small interfering RNA was used to knockdown SOX9 expression in a PCa cell line and to analyze the effects of SOX9 inhibition on the expression of HIVEP3 in vitro. Then, HIVEP3 and SOX9 expression patterns in the human PCa tissues were detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry.

An integrative proteomics and interaction network-based classifier for prostate cancer diagnosis.

Aim: Early diagnosis of prostate cancer (PCa), which is a clinically heterogeneous-multifocal disease, is essential to improve the prognosis of patients. However, published PCa diagnostic markers share little overlap and are poorly validated using independent data. Therefore, we here developed an integrative proteomics and interaction network-based classifier by combining the differential protein expression with topological features of human protein interaction networks to enhance the ability of PCa diagnosis.

Expression of SOCSs in human prostate cancer and their association in prognosis.

Suppressors of cytokine signaling (SOCS) proteins have been identified as negative feedback regulators of cytokine-mediated signaling in various tissues, and demonstrated to play critical roles in tumorigenesis and tumor development of different cancers. The involvement of SOCSs in human prostate cancer (PCa) has not been fully elucidated. Thus, the aim of this study is to investigate the expression patterns and the clinical significance of SOCSs in PCa.