Mariana Nunes

Metformin Impairs Linsitinib Anti-Tumor Effect on Ovarian Cancer Cell Lines

Ovarian cancer (OC) remains one of the leading causes of cancer-related mortality among women. Targeting the insulin-like growth factor 1 (IGF-1) signaling pathway has emerged as a promising therapeutic strategy. Linsitinib, an IGF-1 receptor (IGF-1R) inhibitor, has shown potential in disrupting this pathway. Additionally, metformin, commonly used in the treatment of type 2 diabetes, has been studied for its anti-cancer properties due to its ability to inhibit metabolic pathways that intersect with IGF-1 signaling, making it a candidate for combination therapy in cancer treatments. This study explores the anti-cancer effects of linsitinib and metformin on OVCAR3 cells by the suppression of the IGF-1 signaling pathway by siRNA-mediated IGF-1 gene silencing. The goal is to evaluate their efficacy as therapeutic agents and to emphasize the critical role of this pathway in OC cell proliferation. Cellular viability was evaluated by resazurin-based assay, and apoptosis was assessed by flux cytometry. The results of this study indicate that the combination of linsitinib and metformin exhibits an antagonistic effect (obtained by SynergyFinder 2.0 Software), reducing their anti-neoplastic efficacy in OC cell lines. Statistical analyses were performed using ordinary one-way or two-way ANOVA, followed by Tukey’s or Šídák’s multiple comparison tests. While linsitinib shows promise as a therapeutic option for OC, further research is needed to identify agents that could synergize with it to enhance its therapeutic efficacy, like the combination with standard chemotherapy in OC (carboplatin and paclitaxel).

Deciphering the Molecular Mechanisms behind Drug Resistance in Ovarian Cancer to Unlock Efficient Treatment Options

Ovarian cancer is a highly lethal form of gynecological cancer. This disease often goes undetected until advanced stages, resulting in high morbidity and mortality rates. Unfortunately, many patients experience relapse and succumb to the disease due to the emergence of drug resistance that significantly limits the effectiveness of currently available oncological treatments. Here, we discuss the molecular mechanisms responsible for resistance to carboplatin, paclitaxel, polyadenosine diphosphate ribose polymerase inhibitors, and bevacizumab in ovarian cancer. We present a detailed analysis of the most extensively investigated resistance mechanisms, including drug inactivation, drug target alterations, enhanced drug efflux pumps, increased DNA damage repair capacity, and reduced drug absorption/accumulation. The in-depth understanding of the molecular mechanisms associated with drug resistance is crucial to unveil new biomarkers capable of predicting and monitoring the kinetics during disease progression and discovering new therapeutic targets.

Recycling the Purpose of Old Drugs to Treat Ovarian Cancer

The main challenge in ovarian cancer treatment is the management of recurrences. Facing this scenario, therapy selection is based on multiple factors to define the best treatment sequence. Target therapies, such as bevacizumab and polymerase (PARP) inhibitors, improved patient survival. However, despite their achievements, ovarian cancer survival remains poor; these therapeutic options are highly costly and can be associated with potential side effects. Recently, it has been shown that the combination of repurposed, conventional, chemotherapeutic drugs could be an alternative, presenting good patient outcomes with few side effects and low costs for healthcare institutions. The main aim of this review is to strengthen the importance of repurposed drugs as therapeutic alternatives, and to propose an in vitro model to assess the therapeutic value. Herein, we compiled the current knowledge on the most promising non-oncological drugs for ovarian cancer treatment, focusing on statins, metformin, bisphosphonates, ivermectin, itraconazole, and ritonavir. We discuss the primary drug use, anticancer mechanisms, and applicability in ovarian cancer. Finally, we propose the use of these therapies to perform drug efficacy tests in ovarian cancer ex vivo cultures. This personalized testing approach could be crucial to validate the existing evidences supporting the use of repurposed drugs for ovarian cancer treatment.

Mesothelin Expression Is Not Associated with the Presence of Cancer Stem Cell Markers SOX2 and ALDH1 in Ovarian Cancer

Mesothelin (MSLN) overexpression (OE) is a frequent finding in ovarian carcinomas and increases cell survival and tumor aggressiveness. Since cancer stem cells (CSCs) contribute to pathogenesis, chemoresistance and malignant behavior in ovarian cancer (OC), we hypothesized that MSLN expression could be creating a favorable environment that nurtures CSCs. In this study, we analyzed the expression of MSLN and CSC markers SOX2 and ALDH1 by immunohistochemistry (IHC) in different model systems: primary high-grade serous carcinomas (HGSCs) and OC cell lines, including cell lines that were genetically engineered for MSLN expression by either CRISPR-Cas9-mediated knockout (Δ) or lentivirus-mediated OE. Cell lines, wild type and genetically engineered, were evaluated in 2D and 3D culture conditions and xenografted in nude mice. We observed that MSLN was widely expressed in HGSC, and restricted expression was observed in OC cell lines. In contrast, SOX2 and ALDH1 expression was limited in all tissue and cell models. Most importantly, the expression of CSC markers was independent of MSLN expression, and manipulation of MSLN expression did not affect CSC markers. In conclusion, MSLN expression is not involved in driving the CSC phenotype.

Itraconazole in Advanced Ovarian Cancer

This is a randomized, placebo controlled; parallel study that will be conducted on 66 female patients with advanced epithelial ovarian carcinoma (stage III and stage IV) to compare effect of adding Itraconazole to paclitaxel and carboplatin versus placebo to paclitaxel and carboplatin as regard overall response rate (ORR) and Disease control rate (DCR) and Quality of life (QOL) and the change in the serum concentrations of the biological markers.