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    <responseDate>2026-10-15T23:11:13Z</responseDate>
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                <identifier>oai:data.mendeley.com/84kjtptmd8.1</identifier>
                <datestamp>2024-09-04T19:43:02Z</datestamp>
            </header>
            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator id="https://orcid.org/0000-0002-9768-7181">Behrouzfar, kiarash</dc:creator>
    <dc:title>Mesothelioma survival prediction based on a six-gene transcriptomic signature</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc: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: We performed RNAseq on a large tumor biobank (n=167) 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 this tumor phenotype to develop a 6-gene signature that could predict survival in four independent mesothelioma datasets (Bueno, NCI, TCGA and Creaney) and showed a potential to respond to cancer immunotherapy.
Here, the shared data include R markdown files to perform Gene set enrichment analysis (GSEA), CIBERSORT and WGCNA on RNAseq data from CCMT mouse model (CCMT data analysis_part 1 and 2).  Folder (Gene_signature_development_validation_part 3) include the R markdown file for developing and validating the 6-gene signature via interrogating five independent human mesothelioma datasets.</dc:description>
    <dc:subject>Genetics</dc:subject>
    <dc:subject>RNA Sequencing</dc:subject>
    <dc:subject>Mesothelioma</dc:subject>
    <dc:subject>Mouse Model of Cancer</dc:subject>
    <dc:contributor>Fisher, Scott</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/84kjtptmd8.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/84kjtptmd8.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/84kjtptmd8</dc:relation>
    <dc:date>2024-09-04T19:43:02Z</dc:date>
</oai_dc:dc></metadata>
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