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Background: Ovarian cancer is a common gynecological tumor with high malignant potential and poor prognosis. TRIM8, is involved in the development of various tumors, but its precise regulatory role in ovarian cancer is still unknown. Aims: The aim of this study was to explore the specific mechanism by which TRIM8 regulates ovarian cancer. Materials and Methods: We used bioinformatics analysis to screen for high expression of TRIM8 in ovarian cancer. The expression of TRIM8 in healthy and cancerous ovarian tissues was assessed by immunofluorescence. TRIM8 was silenced or overexpressed in ovarian cancer cell lines, with cell proliferation and migration evaluated by CCK8, transwell and clonal formation assays. The effect of TRIM8 on ovarian cancer cells in vivo was assessed by subcutaneous tumor formation experiments in nude mice. The potential interacting protein VDAC2 was identified by mass spectrometry. The mechanism underlying TRIM8 regulation of VDAC2 was evaluated by co‐immunoprecipitation and western blotting. Results: TRIM8 was overexpressed in ovarian cancer. TRIM8 promoted the proliferation and migration of ovarian cancer cells in vitro and the growth of subcutaneous tumors in mice in vivo. TRIM8 interacted with VDAC2, weakened the stability of the protein, and promoted its polyubiquitination and subsequent degradation. Knockdown of VDAC2 increased the resistance of ovarian cancer cells to iron death, whereas overexpression of VDAC2 attenuated ovarian cancer progression induced by TRIM8 overexpression. Discussion: TRIM8 promotes ovarian cancer proliferation and migration by targeting VDAC2 for ubiquitination and degradation, these finding may provide new targets for the treatment of ovarian cancer. Conclusion: TRIM8 degraded VDAC2 through the ubiquitination pathway, increased the resistance of ovarian cancer cells to iron death, and promoted the proliferation and migration of ovarian cancer. [ABSTRACT FROM AUTHOR]

Abstract Purpose Accumulating evidence indicated that triple‐negative breast cancer (TNBC) can stimulate stronger immune responses than other subtypes of breast cancer. We hypothesized that integrating immune‐related genomic signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system. Methods Ten signatures that reflect specific immunogenic or immune microenvironmental features of TNBC were identified and re‐analyzed using bioinformatic methods. Then, clinically annotated TNBC (n = 711) with the corresponding expression profiles, which predicted a patient's probability of disease‐free survival (DFS) and overall survival (OS), was pooled to evaluate their prognostic values and establish a clinicopathologic‐genomic nomogram. Three and two immune features were, respectively, selected out of 10 immune features to construct nomogram for DFS and OS prediction based on multivariate backward stepwise Cox regression analyses. Results By integrating the above immune expression signatures with prognostic clinicopathologic features, clinicopathologic‐genomic nomograms were cautiously constructed, which showed reasonable prediction accuracies (DFS: HR, 1.79; 95% CI, 1.46‐2.18, P