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Transcriptomic analysis of AGS treatment in human mesothelioma

ABSTRACT: Transcriptomic analysis of AGS treatment in human mesothelioma

PROVIDER: PRJNA858694 | ENA |

REPOSITORIES: ENA

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Transcriptomic analysis of AGS treatment in human mesothelioma

Project description:We analysed the molecular effects on gene modulation exerted by aglianico grape seed extract (AGS) in mesothelioma. Previous results allowed to demonstrate that AGS polar extracts determined apoptosis in three different mesothelioma cell lines including one resistant to conventional chemotherapeutic treatment. In addition this treatment affected tumorigenic and invasive properties of these cells We used microarrays to identify molecular pathway deregulated by AGS treatment and involved in apoptosis induction.

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Project description:KDM4B, an important epigenetic regulator of cell proliferation, metastasis and genome stability, is often overexpressed in gastric cancer. Notably, elevated expression of KDM4B is associated with a poor clinical outcome. A global transcriptomic analysis between KDM4B control and KDM4B-knockdown AGS cells without or with Helicobacter pylori challenge reveals differentially expressed genes involved in response to virus, multi-organism process, and response to stimulus, suggesting KDM4B as an inducible epigenetic factor under H. pylori challenge.

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Project description:Malignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no targeted therapies for PeM yet exist. This study performs comprehensive integrative analysis of genome, transcriptome, and proteome of treatment-naïve PeM tumors with the aim of identifying mesothelioma-related molecular alterations and potentially identifying novel treatment strategies.

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Project description:Background: Mesothelioma is an aggressive, fatal cancer that is inextricably linked to asbestos exposure. Recent trials using a combination of the immune checkpoint inhibitors ipilimumab and nivolumab has significantly improved treatment outcomes, however durable treatment responses remain restricted to a subset of patients (15-20%), highlighting the need to identify strategies that better predict treatment response. Method: Here, we performed RNAseq on a large tumor biobank from genetically diverse mouse model, CC-MexTAg model to compare gene expression profiles of tumors from mice with different overall survival to develop a prognostic gene signature. Results: while the variation in gene expression data of tumors did not associate with 3-fold variation in overall survival of CC-MexTAg mice, we identified two distinct tumor clusters characterized with immune and non-immune phenotypes, in which immune cluster tumours showed the better potential of response to cancer therapies. We used 20 hub genes associated with these tumor phenotypes to develop a 6-gene signature that could predict survival in four independent mesothelioma datasets and showed a potential to respond to cancer immunotherapy.

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