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Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients
Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expressi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518294/ https://www.ncbi.nlm.nih.gov/pubmed/36790659 http://dx.doi.org/10.1007/s12033-023-00671-9 |
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author | Shang, Fanjing Wang, Yafei Shi, Zixu Deng, Zhidong Ma, Jianwen |
author_facet | Shang, Fanjing Wang, Yafei Shi, Zixu Deng, Zhidong Ma, Jianwen |
author_sort | Shang, Fanjing |
collection | PubMed |
description | Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune–stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12033-023-00671-9. |
format | Online Article Text |
id | pubmed-10518294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-105182942023-09-26 Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients Shang, Fanjing Wang, Yafei Shi, Zixu Deng, Zhidong Ma, Jianwen Mol Biotechnol Original Paper Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune–stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12033-023-00671-9. Springer US 2023-02-15 2023 /pmc/articles/PMC10518294/ /pubmed/36790659 http://dx.doi.org/10.1007/s12033-023-00671-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . |
spellingShingle | Original Paper Shang, Fanjing Wang, Yafei Shi, Zixu Deng, Zhidong Ma, Jianwen Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title | Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title_full | Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title_fullStr | Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title_full_unstemmed | Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title_short | Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients |
title_sort | development of a signature based on eight metastatic-related genes for prognosis of gc patients |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518294/ https://www.ncbi.nlm.nih.gov/pubmed/36790659 http://dx.doi.org/10.1007/s12033-023-00671-9 |
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