Prognostic utility of the ovarian cancer secretome: a systematic investigation

Novel prognostic marker TGFBI affects the migration and invasion function of ovarian cancer cells and activates the integrin αvβ3-PI3K-Akt signaling pathway

BACKGROUND

Individual patients with ovarian cancer show remarkably different prognosis. Present prognostic models for ovarian cancer mainly focus on clinico-pathological parameters, so quantifiable prognostic markers at molecular level are urgently needed. Platelets contribute to ovarian cancer progression, but have not been considered as biomarkers likely due to their instability. Here, we aimed to search for a stable prognostic marker from platelet-treated ovarian cancer cells, and explore its functions and mechanisms.

METHODS

Microarrays analysis was done with platelet-treated SKOV-3 ovarian cancer cells. Relevant studies were searched in the Gene Expression Omnibus (GEO) database. The candidate genes were determined by differentially expressed genes (DEGs), Venn diagram drawing, protein-protein interaction (PPI) network, Cox proportional hazards model and Kaplan-Meier analysis. The expression of TGFBI in clinical samples was assessed by immunehistochemical staining (IHC), and the association of TGFBI levels with the clinic-pathological characteristics and prognosis in ovarian cancer patients was evaluated by univariate and multivariate analysis. The functions of TGFBI were predicted using data from TCGA, and validated by in vitro and in vivo experiments. The mechanism exploration was performed based on proteomic analysis, molecular docking and intervention study.

RESULTS

TGFBI was significantly higher expressed in the platelet-treated ovarian cancer cells. An analysis of bioinformatics data revealed that increased expression of TGFBI led to significant decrease of overall survival (OS), progression-free survival (PFS) and post-progression survival (PPS) in ovarian cancer patients. Tissue microarray results showed that TGFBI was an independent factor for ovarian cancer, and TGFBI expression predict poor prognosis. Functionally, TGFBI affected the migration and invasion of ovarian cancer cells by regulation of epithelial mesenchymal transition (EMT) markers (CDH1 and CDH2) and extracellular matrix (ECM) degradation proteins (MMP-2). Mechanistically, TGFBI phosphorylated PI3K and Akt by combining integrin αvβ3.

CONCLUSIONS

We found out TGFBI as a novel prognostic indicator for ovarian cancer patients. TGFBI could promote metastasis in ovarian cancer by EMT induction and ECM remodeling, which might be associated with the activation of integrin αvβ3-PI3K-Akt signaling pathway.

Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT

BACKGROUND

In ovarian cancer (OC) therapy, even initially responsive patients develop drug resistance.

METHODS

Here, we present an OC cell model composed of variants with differing degrees of acquired resistance to carboplatin (CBP), cross-resistance to paclitaxel, and CBP-induced metastatic properties (migration and invasion). Transcriptome data were analysed by two approaches identifying differentially expressed genes and CBP sensitivity-correlating genes. The impact of selected genes and signalling pathways on drug resistance and metastatic potential, along with their clinical relevance, was examined by in vitro and in silico approaches.

RESULTS

TMEM200A and PRKAR1B were recognised as potentially involved in both phenomena, also having high predictive and prognostic values for OC patients. CBP-resistant MES-OV CBP8 cells were more sensitive to PI3K/Akt/mTOR pathway inhibitors Rapamycin, Wortmannin, SB216763, and transcription inhibitor Triptolide compared with parental MES-OV cells. When combined with CBP, Rapamycin decreased the sensitivity of parental cells while Triptolide sensitised drug-resistant cells to CBP. Four PI3K/Akt/mTOR inhibitors reduced migration in both cell lines.

CONCLUSIONS

A newly established research model and two distinct transcriptome analysis approaches identified novel candidate genes enrolled in CBP resistance development and/or CBP-induced EMT and implied that one-gene targeting could be a better approach than signalling pathway inhibition for influencing both phenomena.