High grade serous ovarian carcinoma (HGSOC) is a systemic malignancy characterized by metastatic lesions that spread within the peritoneal cavity. Despite initial sensibility to platinum-based chemotherapy, more than 80% of patients experience a relapse and acquire chemoresistance. From a genomic point of view, HGSOC shows a high level of inter-and intra-tumor heterogeneity. A better understanding of molecular mechanisms of this disease and the identification of driving genetic alterations could provide relevant indications for diagnostic and prognostic evaluation. Here, we accomplished a double-tier omic-analysis by integrating copy number variation data with matched gene expression profiling of multiple lesions in a cohort of 7 patients. We identified potential driver genes contained in amplified regions whose behavior seem to impact on gene expression program. They represent a distinctive signature that can segregate biopsies of different patients. Moreover, a further analysis highlighted ZNF696, ASPSCR1 and RHPN1 as key drivers, whose regulatory program is confirmed in TCGA cohort. In conclusion, exploration of gene expression program in HSGOC by integrating copy number and transcriptomic data from spatially separated samples obtained from seven patients led to the identification of genes whose amplification is significantly correlated to specific gene expression modules and are related to survival.

Modulation of gene expression associated with copy number variation identifies key regulatory programs in high-grade serous ovarian carcinoma

Vescio M.;Pattini L.
2023-01-01

Abstract

High grade serous ovarian carcinoma (HGSOC) is a systemic malignancy characterized by metastatic lesions that spread within the peritoneal cavity. Despite initial sensibility to platinum-based chemotherapy, more than 80% of patients experience a relapse and acquire chemoresistance. From a genomic point of view, HGSOC shows a high level of inter-and intra-tumor heterogeneity. A better understanding of molecular mechanisms of this disease and the identification of driving genetic alterations could provide relevant indications for diagnostic and prognostic evaluation. Here, we accomplished a double-tier omic-analysis by integrating copy number variation data with matched gene expression profiling of multiple lesions in a cohort of 7 patients. We identified potential driver genes contained in amplified regions whose behavior seem to impact on gene expression program. They represent a distinctive signature that can segregate biopsies of different patients. Moreover, a further analysis highlighted ZNF696, ASPSCR1 and RHPN1 as key drivers, whose regulatory program is confirmed in TCGA cohort. In conclusion, exploration of gene expression program in HSGOC by integrating copy number and transcriptomic data from spatially separated samples obtained from seven patients led to the identification of genes whose amplification is significantly correlated to specific gene expression modules and are related to survival.
2023
High-grade serous ovarian carcinoma
Gene expression
Copy number variation
Systems biology
Cancer informatics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1260594
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