Cyclin Dependent Kinase

The epithelial-mesenchymal transition (EMT) is a process through which epithelial cells trans-differentiate and acquire an aggressive mesenchymal phenotype. In tumor cells, EMT is a vital step of tumor progression and metastasis. Amid the increasing interest in tumor EMT, only a few studies focused on the soluble mediators secreted by tumor cells passing through this phenotypic switch. In this review, we focus on the essential role of interleukin-8 (IL-8) signaling for the acquisition and maintenance of tumor EMT via direct and indirect mechanisms. Besides the autocrine loop between IL-8 and tumor cells that have gone through EMT, IL-8 could potentiate adjacent epithelial tumor cells into a mesenchymal phenotype via a paracrine mode. Moreover, understanding the role of IL-8 in EMT will provide insight into the pathogenesis of tumor progression and may facilitate the development of an effective strategy for the prevention and treatment of metastatic cancer.

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IL-8, a novel messenger to cross-link inflammation and tumor EMT via autocrine and paracrine pathways (Review)

Summary Background Risk of relapse or progression remains high in the treatment of most patients with epithelial ovarian cancer, and development of a molecular predictor could be a valuable tool for stratification of patients by risk. We aimed to develop a microRNA (miRNA)-based molecular classifier that can predict risk of progression or relapse in patients with epithelial ovarian cancer. Methods We analysed miRNA expression profiles in three cohorts of samples collected at diagnosis. We used 179 samples from a Multicenter Italian Trial in Ovarian cancer trial (cohort OC179) to develop the model and 263 samples from two cancer centres (cohort OC263) and 452 samples from The Cancer Genome Atlas epithelial ovarian cancer series (cohort OC452) to validate the model. The primary clinical endpoint was progression-free survival, and we adapted a semi-supervised prediction method to the miRNA expression profile of OC179 to identify miRNAs that predict risk of progression. We assessed the independent prognostic role of the model using multivariable analysis with a Cox regression model. Findings We identified 35 miRNAs that predicted risk of progression or relapse and used them to create a prognostic model, the 35-miRNA-based predictor of Risk of Ovarian Cancer Relapse or progression (MiROvaR). MiROvaR was able to classify patients in OC179 into a high-risk group (89 patients; median progression-free survival 18 months [95% CI 15–22]) and a low-risk group (90 patients; median progression-free survival 38 months [24–not estimable]; hazard ratio [HR] 1·85 [1·29–2·64], p=0·00082). MiROvaR was a significant predictor of progression in the two validation sets (OC263 HR 3·16, 95% CI 2·33–4·29, p Interpretation MiROvaR is a potential predictor of epithelial ovarian cancer progression and has prognostic value independent of relevant clinical covariates. MiROvaR warrants further investigation for the development of a clinical-grade prognostic assay. Funding AIRC and CARIPLO Foundation.

Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study

Sialyltransferases transfer sialic acid to nascent oligosaccharides and are upregulated in cancer. The inhibition of sialyltransferases is emerging as a potential strategy to prevent metastasis in several cancers, including ovarian cancer. ST3GAL1 is a sialyltransferase that catalyzes the transfer of sialic acid from cytidine monophosphate-sialic acid to galactose-containing substrates and is associated with cancer progression and chemoresistance. However, the function of ST3GAL1 in ovarian cancer is uncertain. Herein, we use qRT-PCR, western blotting, and immunohistochemistry to assess the expression of ST3GAL1 in ovarian cancer tissue and cell lines and investigate whether it influences resistance to paclitaxel in vitro and in a mouse xenograft model. We found that ST3GAL1 is upregulated in ovarian cancer tissues and in the ovarian cancer cell lines SKOV-3 and OVCAR3 but downregulated in A2780 ovarian cancer cells. Overexpression of ST3GAL1 in A2780 cells increases cell growth, migration, and invasion whereas ST3GAL1 knockdown in SKOV-3 cells decreases cell growth, migration, and invasion. Furthermore, overexpression of ST3GAL1 increases resistance to paclitaxel while downregulation of ST3GAL1 decreases resistance to paclitaxel in vitro, and overexpression of ST3GAL1 increases tumorigenicity and resistance to paclitaxel in vivo. Transforming growth factor-β1 can increase ST3GAL1 expression and induce ovarian cell epithelial–mesenchymal transition (EMT). However, knockdown of ST3GAL1 inhibits EMT expression. Taken together, our findings have identified a regulatory mechanism involving ST3GAL1 in ovarian cancer. ST3GAL1 may be a promising target for overcoming paclitaxel resistance in ovarian carcinoma.

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Sialyltransferase ST3GAL1 promotes cell migration, invasion, and TGF-β1-induced EMT and confers paclitaxel resistance in ovarian cancer

Purpose Long-chain noncoding RNAs (lncRNAs) are involved in regulating the sensitivity of cancer cells to chemotherapeutic drugs, but the specific mechanism of action is not well understood. The aim of this study was to investigate the effect of lncRNA growth-stasis specific transcript 5 (GAS5) on triple-negative breast cancer (TNBC). Methods Quantitative real-time polymerase chain reaction and flow cytometry were used to screen lncRNA associated with tumor resistance. Double luciferase reporter gene assay, flow cytometry, and Western blot assay were used to determine whether miRNA 378a-5p and SUFU were involved in tumor cell apoptosis induced by lncRNA GAS5. A mouse model of subcutaneous xenografts was established to investigate the relationship between lncRNA GAS5 and tumor resistance in vivo. Results In this study, the expression of lncRNA GAS5 was significantly downregulated in cells treated with paclitaxel (PTX) or cisplatin (CIS). Furthermore, TNBC cells with low expression of lncRNA GAS5 had a lower percentage of apoptosis under stress conditions, especially in serum-free medium. More interestingly, the expression level of lncRNA GAS5 in TNBC patients was associated with tumor resistance to PTX and CIS. In addition, RNA immunoprecipitation experiments confirmed that lncRNA GAS5 and miR-378 could directly bind to each other. Moreover, the miR-378a-5p target of SUFU could promote lncRNA GAS5-induced apoptosis of TNBC cells. Finally, lncRNA GAS5 overexpressed MDA-231R could enhance the sensitivity of TNBC to PTX. Conclusion The above results confirmed that lncRNA GAS5 could induce apoptosis in TNBC cells by targeting miR-378a-5p/SUFU signaling.

lncRNA GAS5‐promoted apoptosis in triple‐negative breast cancer by targeting miR‐378a‐5p/SUFU signaling

Metastasis is the main cause of cancer mortality. One of the initiating events of cancer metastasis of epithelial tumors is epithelial-to-mesenchymal transition (EMT), during which cells dedifferentiate from a relatively rigid cell structure/morphology to a flexible and changeable structure/morphology often associated with mesenchymal cells. The presence of EMT in human epithelial tumors is reflected by the increased expression of genes and levels of proteins that are preferentially present in mesenchymal cells. The combined presence of these genes forms the basis of mesenchymal gene signatures, which are the foundation for classifying a mesenchymal subtype of tumors. Indeed, tumor classification schemes that use clustering analysis of large genomic characterizations, like The Cancer Genome Atlas (TCGA), have defined mesenchymal subtype in a number of cancer types, such as high-grade serous ovarian cancer and glioblastoma. However, recent analyses have shown that gene expression-based classifications of mesenchymal subtypes often do not associate with poor survival. This “paradox” can be ameliorated using integrated analysis that combines multiple data types. We recently found that integrating mRNA and microRNA (miRNA) data revealed an integrated mesenchymal subtype that is consistently associated with poor survival in multiple cohorts of patients with serous ovarian cancer. This network consists of 8 major miRNAs and 214 mRNAs. Among the 8 miRNAs, 4 are known to be regulators of EMT. This review provides a summary of these 8 miRNAs, which were associated with the integrated mesenchymal subtype of serous ovarian cancer.

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Feng Xia Xue

Papers

Key nodes of a microRNA network associated with the integrated mesenchymal subtype of high-grade serous ovarian cancer.