The Significance of VSIG4 Expression in Ovarian Cancer

    loading  Checking for direct PDF access through Ovid

Abstract

Objectives

The protein V-set and Ig domain-containing 4 (VSIG4), a novel B7 family-related macrophage protein with the capacity to inhibit T-cell activation, has a potential role in cancer. Here we suggest its possibility as a therapeutic target and prognostic biomarker of ovarian cancer.

Methods

Between January 2011 and June 2015, tumor tissues and peripheral blood samples were obtained during surgery from 10 patients with benign ovarian tumors and 22 patients with ovarian cancers. Messenger RNA and protein expression levels of VSIG4 in benign tumor and cancer tissues were examined by the reverse transcription polymerase chain reaction and Western blot, respectively. Soluble VSIG4 concentrations were measured by an enzyme-linked immunosorbent assay. The correlation between VSIG4 expression and the prognosis of ovarian cancer was analyzed according to the patients' clinicopathologic characteristics.

Results

VSIG4 messenger RNA and protein expression levels in ovarian cancer tissues were higher than those in benign ovarian tumors (P = 0.0013 and 0.0001, respectively). Soluble VSIG4 concentrations were increased in patients with ovarian cancer compared with that in patients with benign ovarian tumors (P = 0.0452). Moreover, soluble VSIG4 levels were significantly increased in advanced-stage and recurrent ovarian cancer (P = 0.0244 and 0.0288, respectively). High VSIG4 expression of cancer tissue and low VSIG4 expression of plasma (soluble VSIG4) were associated with a longer disease-free interval (P = 0.0246 and 0.0398, respectively).

Conclusions

VSIG4 is overexpressed in ovarian cancers compared with that in benign tumors. This finding supports VSIG4 being used as a potential therapeutic target for ovarian cancer. Furthermore, soluble VSIG4 levels are associated with the progression and recurrence of ovarian cancer, indicating that soluble VSIG4 may be used as a potential biomarker for predicting tumor prognosis.

Related Topics

    loading  Loading Related Articles