Phosphatase and tensin homolog (PTEN) expression on oncologic outcome in renal cell carcinoma: A systematic review and meta-analysis

<div><p>The phosphatase and tensin homolog (<i>PTEN</i>) gene is suggested to be a dormant tumor suppressor. However, the prognostic value of the loss of <i>PTEN</i> expression in renal cell carcinoma (RCC) remains controversial. Therefore, we conducted a meta-analysis to evaluate the association of <i>PTEN</i> expression with the clinicopathological presentations and outcomes of patients with RCC through immunohistochemistry staining analysis. We systematically searched for relevant studies in PubMed, Web of Science, and Embase until March 2016. Data regarding clinical stage, pathological type, Fuhrman grade, overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) was analyzed in the present study. In total, there were 12 studies with 2,368 patients included in this meta-analysis. The low <i>PTEN</i> expression in RCC was significantly associated with unfavorable DSS (HR = 1.568, 95% CI 1.015–2.242) in a random-effects model but not with OS (HR = 1.046, 95% CI 0.93–1.176) and PFS (HR = 1.244, 95% CI 0.907–1.704). Other results indicated that <i>PTEN</i> expression was not correlated with clinical stage, pathological type, and Fuhrman grade. This meta-analysis suggests that <i>PTEN</i> expression is of limited value in predicting the prognosis of patients with RCC for OS and PFS via immunohistochemistry staining analysis; and that for DSS, low <i>PTEN</i> expression is significantly associated with an unfavorable outcome.</p></div

Meta-analysis results of <i>PTEN</i> expression level and clinical features.

<p>Meta-analysis results of <i>PTEN</i> expression level and clinical features.</p

Meta-analysis results on <i>PTEN</i> expression and OS.

<p>Forest plot of the association between <i>PTEN</i> expression and overall survival of patients with RCC.</p

Results of meta-analysis on <i>PTEN</i> expression.

<p>Results of meta-analysis on <i>PTEN</i> expression.</p

Sensitivity analysis for OS, PFS and DSS.

<p>a. Sensitivity analysis for OS; b. Sensitivity analysis for PFS; c. Sensitivity analysis for DSS.</p

Begg's funnel plots of publication bias for OS, PFS and DSS.

<p>a. Begg's funnel plot for OS; b. Begg's funnel plot for PFS; c. Begg's funnel plot for DSS.</p

Flowchart of selection literature.

<p>Flowchart of selection literature.</p