Daniela Gallo

The interaction of β-arrestin1 with talin1 driven by endothelin A receptor as a feature of α5β1 integrin activation in high-grade serous ovarian cancer

AbstractDissemination of high-grade serous ovarian cancer (HG-SOC) in the omentum and intercalation into a mesothelial cell (MC) monolayer depends on functional α5β1 integrin (Intα5β1) activity. Although the binding of Intα5β1 to fibronectin drives these processes, other molecular mechanisms linked to integrin inside-out signaling might support metastatic dissemination. Here, we report a novel interactive signaling that contributes to Intα5β1 activation and accelerates tumor cells toward invasive disease, involving the protein β-arrestin1 (β-arr1) and the activation of the endothelin A receptor (ETAR) by endothelin-1 (ET-1). As demonstrated in primary HG-SOC cells and SOC cell lines, ET-1 increased Intβ1 and downstream FAK/paxillin activation. Mechanistically, β-arr1 directly interacts with talin1 and Intβ1, promoting talin1 phosphorylation and its recruitment to Intβ1, thus fueling integrin inside-out activation. In 3D spheroids and organotypic models mimicking the omentum, ETAR/β-arr1-driven Intα5β1 signaling promotes the survival of cell clusters, with mesothelium-intercalation capacity and invasive behavior. The treatment with the antagonist of ETAR, Ambrisentan (AMB), and of Intα5β1, ATN161, inhibits ET-1-driven Intα5β1 activity in vitro, and tumor cell adhesion and spreading to intraperitoneal organs and Intβ1 activity in vivo. As a prognostic factor, high EDNRA/ITGB1 expression correlates with poor HG-SOC clinical outcomes. These findings highlight a new role of ETAR/β-arr1 operating an inside-out integrin activation to modulate the metastatic process and suggest that in the new integrin-targeting programs might be considered that ETAR/β-arr1 regulates Intα5β1 functional pathway.

KLF7: a new candidate biomarker and therapeutic target for high-grade serous ovarian cancer

Abstract Background In spite of great progress in the surgical and clinical management, until now no significant improvement in overall survival of High-Grade Serous Ovarian Cancer (HGSOC) patients has been achieved. Important aspects for disease control remain unresolved, including unclear pathogenesis, high heterogeneity and relapse resistance after chemotherapy. Therefore, further research on molecular mechanisms involved in cancer progression are needed to find new targets for disease management. The Krüppel-like factors (KLFs) are a family of transcriptional regulators controlling several basic cellular processes, including proliferation, differentiation and migration. They have been shown to play a role in various cancer-relevant processes, in a context-dependent way. Methods To investigate a possible role of KLF family members as prognostic biomarkers, we carried out a bioinformatic meta-analysis of ovarian transcriptome datasets in different cohorts of late-stage HGSOC patients. In vitro cellular models of HGSOC were used for functional studies exploring the role of KLF7 in disease development and progression. Finally, molecular modelling and virtual screening were performed to identify putative KLF7 inhibitors. Results Bioinformatic analysis highlighted KLF7 as the most significant prognostic gene, among the 17 family members. Univariate and multivariate analyses identified KLF7 as an unfavourable prognostic marker for overall survival in late-stage TCGA-OV and GSE26712 HGSOC cohorts. Functional in vitro studies demonstrated that KLF7 can play a role as oncogene, driving tumour growth and dissemination. Mechanistic targets of KLF7 included genes involved in epithelial to mesenchymal transition, and in maintaining pluripotency and self-renewal characteristics of cancer stem cells. Finally, in silico analysis provided reliable information for drug-target interaction prediction. Conclusions Results from the present study provide the first evidence for an oncogenic role of KLF7 in HGSOC, suggesting it as a promising prognostic marker and therapeutic target.

Preclinical models of epithelial ovarian cancer: practical considerations and challenges for a meaningful application

AbstractDespite many improvements in ovarian cancer diagnosis and treatment, until now, conventional chemotherapy and new biological drugs have not been shown to cure the disease, and the overall prognosis remains poor. Over 90% of ovarian malignancies are categorized as epithelial ovarian cancers (EOC), a collection of different types of neoplasms with distinctive disease biology, response to chemotherapy, and outcome. Advances in our understanding of the histopathology and molecular features of EOC subtypes, as well as the cellular origins of these cancers, have given a boost to the development of clinically relevant experimental models. The overall goal of this review is to provide a comprehensive description of the available preclinical investigational approaches aimed at better characterizing disease development and progression and at identifying new therapeutic strategies. Systems discussed comprise monolayer (2D) and three-dimensional (3D) cultures of established and primary cancer cell lines, organoids and patient-derived explants, animal models, including carcinogen-induced, syngeneic, genetically engineered mouse, xenografts, patient-derived xenografts (PDX), humanized PDX, and the zebrafish and the laying hen models. Recent advances in tumour-on-a-chip platforms are also detailed. The critical analysis of strengths and weaknesses of each experimental model will aid in identifying opportunities to optimize their translational value.

Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients

AbstractBackgroundHigh-grade serous ovarian cancer (HGSOC) has poor survival rates due to a combination of diagnosis at advanced stage and disease recurrence as a result of chemotherapy resistance. In BRCA1 (Breast Cancer gene 1) - or BRCA2-wild type (BRCAwt) HGSOC patients, resistance and progressive disease occur earlier and more often than in mutated BRCA. Identification of biomarkers helpful in predicting response to first-line chemotherapy is a challenge to improve BRCAwt HGSOC management.MethodsTo identify a gene signature that can predict response to first-line chemotherapy, pre-treatment tumor biopsies from a restricted cohort of BRCAwt HGSOC patients were profiled by RNA sequencing (RNA-Seq) technology. Patients were sub-grouped according to platinum-free interval (PFI), into sensitive (PFI > 12 months) and resistant (PFI < 6 months). The gene panel identified by RNA-seq analysis was then tested by high-throughput quantitative real-time PCR (HT RT-qPCR) in a validation cohort, and statistical/bioinformatic methods were used to identify eligible markers and to explore the relevant pathway/gene network enrichments of the identified gene set. Finally, a panel of primary HGSOC cell lines was exploited to uncover cell-autonomous mechanisms of resistance.ResultsRNA-seq identified a 42-gene panel discriminating sensitive and resistant BRCAwt HGSOC patients and pathway analysis pointed to the immune system as a possible driver of chemotherapy response. From the extended cohort analysis of the 42 DEGs (differentially expressed genes), a statistical approach combined with the random forest classifier model generated a ten-gene signature predictive of response to first-line chemotherapy. The ten-gene signature included: CKB (Creatine kinase B), CTNNBL1 (Catenin, beta like 1), GNG11 (G protein subunit gamma 11), IGFBP7 (Insulin-like growth factor-binding protein 7), PLCG2 (Phospholipase C, gamma 2), RNF24 (Ring finger protein 24), SLC15A3 (Solute carrier family 15 member 3), TSPAN31 (Tetraspanin 31), TTI1 (TELO2 interacting protein 1) and UQCC1 (Ubiquinol-cytochrome c reductase complex assembly factor). Cytotoxicity assays, combined with gene-expression analysis in primary HGSOC cell lines, allowed to define CTNNBL1, RNF24, and TTI1 as cell-autonomous contributors to tumor resistance.ConclusionsUsing machine-learning techniques we have identified a gene signature that could predict response to first-line chemotherapy in BRCAwt HGSOC patients, providing a useful tool towards personalized treatment modalities.

Stat1 confers sensitivity to radiation in cervical cancer cells by controlling Parp1 levels: a new perspective for Parp1 inhibition

AbstractCervical cancer (CC) is the fourth most common cause of cancer-related death in women. According to international guidelines, a standard treatment for locally advanced cervical cancer (LACC) consists of exclusive concurrent chemoradiation treatment (CRT). However, chemoradioresistance and subsequent relapse and metastasis of cancer occur in many patients, and survival for these women has generally remained poor. Therefore, strategies to overcome resistance are urgently needed. We have recently reported a radiosensitizing effect of the signal transducer and activator of transcription 1 (STAT1) in CC, associated with the control of [Poly(ADP-ribose) polymerase −1] PARP1 levels, a key factor in cell response to DNA damage induced by radiation. Here, we sought to decipher the underlying mechanism of STAT1-mediated control of PARP1, elucidating its role as a radiosensitizer in CC. Functional and molecular biology studies demonstrated that STAT1 may act at both transcriptional and posttranscriptional levels to modulate PARP1 expression in CC cells. In light of these results, we tested the effect of Olaparib in sensitizing CC cells to radiation and investigated signaling pathways involved in the activity observed. Results showed that PARP1 inhibition, at clinically achievable doses, may indeed selectively improve the sensitivity of resistant CC cells to DNA-damaging treatment. The translational relevance of our findings was supported by preliminary results in a limited patient cohort, confirming that higher PARP1 levels are significantly associated with a radioresistant phenotype. Finally, bioinformatics analysis of GEPIA and TCGA databases, demonstrated that PARP1 mRNA is higher in CC than in normal tissues and that increased PARP1 mRNA expression levels are associated with poor prognosis of LACC patients. Overall, our data open new opportunities for the development of personalized treatments in women diagnosed with CC.