Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, with a high mortality and poor survival rate. Abnormal tumor metabolism is considered a hallmark of HCC and is a potential therapeutic target. This study aimed to identify metabolism-related biomarkers to evaluat...

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Autores principales: Li, Dongping, Lin, Xiahui, Li, Jiale, Liu, Xinyi, Zhang, Feng, Tang, Wenqing, Zhang, Si, Dong, Ling, Xue, Ruyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656919/
https://www.ncbi.nlm.nih.gov/pubmed/37978523
http://dx.doi.org/10.1186/s12935-023-03097-0
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author Li, Dongping
Lin, Xiahui
Li, Jiale
Liu, Xinyi
Zhang, Feng
Tang, Wenqing
Zhang, Si
Dong, Ling
Xue, Ruyi
author_facet Li, Dongping
Lin, Xiahui
Li, Jiale
Liu, Xinyi
Zhang, Feng
Tang, Wenqing
Zhang, Si
Dong, Ling
Xue, Ruyi
author_sort Li, Dongping
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, with a high mortality and poor survival rate. Abnormal tumor metabolism is considered a hallmark of HCC and is a potential therapeutic target. This study aimed to identify metabolism-related biomarkers to evaluate the prognosis of patients with HCC. METHOD: The Cancer Genome Atlas (TCGA) database was used to explore differential metabolic pathways based on high and low epithelial-mesenchymal transition (EMT) groupings. Genes in differential metabolic pathways were obtained for HCC metabolism-related molecular subtype analysis. Differentially expressed genes (DEGs) from the three subtypes were subjected to Lasso Cox regression analysis to construct prognostic risk models. Stard5 expression in HCC patients was detected by western blot and immunohistochemistry (IHC), and the role of Stard5 in the metastasis of HCC was investigated by cytological experiments. RESULTS: Unsupervised clustering analysis based on metabolism-related genes revealed three subtypes in HCC with differential prognosis. A risk prognostic model was constructed based on 11 genes (STARD5, FTCD, SCN4A, ADH4, CFHR3, CYP2C9, CCL14, GADD45G, SOX11, SCIN, and SLC2A1) obtained by LASSO Cox regression analysis of the three subtypes of DEGs. We validated that the model had a good predictive power. In addition, we found that the high-risk group had a poor prognosis, higher proportion of Tregs, and responded poorly to chemotherapy. We also found that Stard5 expression was markedly decreased in HCC tissues, which was associated with poor prognosis and EMT. Knockdown of Stard5 contributed to the invasion and migration of HCC cells. Overexpression of Stard5 inhibited EMT in HCC cells. CONCLUSION: We developed a new model based on 11 metabolism-related genes, which predicted the prognosis and response to chemotherapy or immunotherapy for HCC. Notably, we demonstrated for the first time that Stard5 acted as a tumor suppressor by inhibiting metastasis in HCC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-03097-0.
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spelling pubmed-106569192023-11-17 Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC Li, Dongping Lin, Xiahui Li, Jiale Liu, Xinyi Zhang, Feng Tang, Wenqing Zhang, Si Dong, Ling Xue, Ruyi Cancer Cell Int Research BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, with a high mortality and poor survival rate. Abnormal tumor metabolism is considered a hallmark of HCC and is a potential therapeutic target. This study aimed to identify metabolism-related biomarkers to evaluate the prognosis of patients with HCC. METHOD: The Cancer Genome Atlas (TCGA) database was used to explore differential metabolic pathways based on high and low epithelial-mesenchymal transition (EMT) groupings. Genes in differential metabolic pathways were obtained for HCC metabolism-related molecular subtype analysis. Differentially expressed genes (DEGs) from the three subtypes were subjected to Lasso Cox regression analysis to construct prognostic risk models. Stard5 expression in HCC patients was detected by western blot and immunohistochemistry (IHC), and the role of Stard5 in the metastasis of HCC was investigated by cytological experiments. RESULTS: Unsupervised clustering analysis based on metabolism-related genes revealed three subtypes in HCC with differential prognosis. A risk prognostic model was constructed based on 11 genes (STARD5, FTCD, SCN4A, ADH4, CFHR3, CYP2C9, CCL14, GADD45G, SOX11, SCIN, and SLC2A1) obtained by LASSO Cox regression analysis of the three subtypes of DEGs. We validated that the model had a good predictive power. In addition, we found that the high-risk group had a poor prognosis, higher proportion of Tregs, and responded poorly to chemotherapy. We also found that Stard5 expression was markedly decreased in HCC tissues, which was associated with poor prognosis and EMT. Knockdown of Stard5 contributed to the invasion and migration of HCC cells. Overexpression of Stard5 inhibited EMT in HCC cells. CONCLUSION: We developed a new model based on 11 metabolism-related genes, which predicted the prognosis and response to chemotherapy or immunotherapy for HCC. Notably, we demonstrated for the first time that Stard5 acted as a tumor suppressor by inhibiting metastasis in HCC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-03097-0. BioMed Central 2023-11-17 /pmc/articles/PMC10656919/ /pubmed/37978523 http://dx.doi.org/10.1186/s12935-023-03097-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Li, Dongping
Lin, Xiahui
Li, Jiale
Liu, Xinyi
Zhang, Feng
Tang, Wenqing
Zhang, Si
Dong, Ling
Xue, Ruyi
Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title_full Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title_fullStr Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title_full_unstemmed Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title_short Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC
title_sort eleven metabolism‑related genes composed of stard5 predict prognosis and contribute to emt phenotype in hcc
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656919/
https://www.ncbi.nlm.nih.gov/pubmed/37978523
http://dx.doi.org/10.1186/s12935-023-03097-0
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