Eros Azzalini

Special Issue “Resistance to Therapy in Ovarian Cancers”

Epithelial ovarian cancers (EOCs) are a heterogenous group of neoplasms at the clinical, pathological, and molecular levels [...]

Comparative Analysis of Gene Expression Analysis Methods for RNA in Situ Hybridization Images

Gene expression analysis is pivotal in cancer research and clinical practice. Although traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, RNAscope score, RT-droplet digital PCR, and automated QuantISH and QuPath were used for quantifying RNA-ISH expression values from formalin-fixed, paraffin-embedded samples. The methods were compared using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. The findings demonstrate good concordance between automated methods and RNAscope, with RT-droplet digital PCR showing less concordance. Additionally, QuantISH exhibits robust performance, even for low-expressed genes like CCNE1, showcasing its modular design and enhancing accessibility as a viable alternative for gene expression analysis.

Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers

Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.

Nanomechanical Characterization of Ovarian Cancer Cell Lines as a Marker of Response to 2c Treatment

Epithelial ovarian cancers (EOCs) are a heterogeneous group of tumors with different molecular and clinical features. In past decades, few improvements have been achieved in terms of EOC management and treatment efficacy, such that the 5-year survival rate of patients remained almost unchanged. A better characterization of EOCs’ heterogeneity is needed to identify cancer vulnerabilities, stratify patients and adopt proper therapies. The mechanical features of malignant cells are emerging as new biomarkers of cancer invasiveness and drug resistance that can further improve our knowledge of EOC biology and allow the identification of new molecular targets. In this study, we determined the inter and intra-mechanical heterogeneity of eight ovarian cancer cell lines and their association with tumor invasiveness and resistance to an anti-tumoral drug with cytoskeleton depolymerization activity (2c).