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Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma

BACKGROUND: The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma...

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Detalles Bibliográficos
Autores principales: Wang, Yu, Xie, Yanting, Ma, Junyong, Wang, Yizhou, Gong, Renyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576066/
https://www.ncbi.nlm.nih.gov/pubmed/33241026
http://dx.doi.org/10.21037/atm-20-6112
Descripción
Sumario:BACKGROUND: The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma (HCC). METHODS: An IPM was constructed and validated based on immune-related genes. The influence of IPM on the HCC immune microenvironment, as well as the possible mechanism, was comprehensively analyzed. The value of the model in predicting the response of HCC patients to immunotherapy was also evaluated. RESULTS: A novel IPM based on eight genes was developed and validated to predict the prognosis of HCC patients. These genes are matrix metalloproteinase 12 (MMP12), heme oxygenase 1 (HMOX1), C-X-C motif chemokine receptor 6 (CXCR6), hepatoma-derived growth factor (HDGF), placental growth factor (PGF), tyrosine kinase 2 (TYK2), retinoid X receptor beta (RXRB), and cyclin-dependent kinase 4 (CDK4). High-risk patients showed significantly poorer survival than low-risk patients. A nomogram was also established based on the IPM and tumor, node, metastasis (TNM) classification, which showed some net clinical benefit. Gene set enrichment analysis (GSEA) revealed several significantly enriched oncological signatures and immunologic signatures. Furthermore, high-risk patients were characterized by severe clinicopathological characteristics and immune cell infiltration. Finally, we found the that the IPM showed a significant positive correlation with programmed cell death 1 (PDCD1), cluster of differentiation 274 (CD274), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression, suggesting a potentially enhanced effects of immunotherapy antibodies in HCC patients with a high risk score. CONCLUSIONS: A novel IPM that could predict clinical prognosis and immunotherapeutic response in HCC patients was developed. Our findings not only provide new insights into the identification of HCC patients with poor survival, but also deepen our understanding of the immune microenvironment, as well as the mechanism of immunotherapy, in HCC.