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Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer
BACKGROUND: Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC). METHODS: In total, 162 genes involved in 203...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665511/ https://www.ncbi.nlm.nih.gov/pubmed/38022516 http://dx.doi.org/10.3389/fimmu.2023.1289700 |
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author | Li, Yiping Li, Xiaoqin Yang, Yufei Qiao, Xuehan Tao, Qing Peng, Chen Han, Miao Dong, Kebin Xu, Min Wang, Deqiang Han, Gaohua |
author_facet | Li, Yiping Li, Xiaoqin Yang, Yufei Qiao, Xuehan Tao, Qing Peng, Chen Han, Miao Dong, Kebin Xu, Min Wang, Deqiang Han, Gaohua |
author_sort | Li, Yiping |
collection | PubMed |
description | BACKGROUND: Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC). METHODS: In total, 162 genes involved in 203 hereditary metabolic diseases were identified in the Human Phenotype Ontology database. Clinical and multi-omic data were acquired from the GC cohort of the Affiliated Hospital of Jiangsu University and other published cohorts. A 4-gene and 32-gene signature was established for diagnosis and prognosis or therapeutic prediction, respectively, and corresponding abnormal metabolism scores (AMscores) were calculated. RESULTS: The diagnostic AMscore showed high sensitivity (0.88-1.00) and specificity (0.89-1.00) to distinguish between GC and paired normal tissues, with area under the receiver operating characteristic curve (AUC) ranging from 0.911 to 1.000 in four GC cohorts. The prognostic or predictive AMscore was an independent predictor of overall survival (OS) in five GC cohorts and a predictor of the OS and disease-free survival benefit of postoperative chemotherapy or chemoradiotherapy in one GC cohort with such data. The AMscore adversely impacts immune biomarkers, including tumor mutation burden, tumor neoantigen burden, microsatellite instability, programmed death-ligand 1 protein expression, tumor microenvironment score, T cell receptor clonality, and immune cell infiltration detected by multiplex immunofluorescence staining. The AUC of the AMscore for predicting immunotherapy response ranging from 0.780 to 0.964 in four cohorts involving GC, urothelial cancer, melanoma, and lung cancer. The objective response rates in the low and high AMscore subgroups were 78.6% and 3.2%, 40.4% and 7%, 52.6% and 0%, and 72.7% and 0%, respectively (all p<0.001). In cohorts with survival data, a high AMscore was hazardous for OS or progression-free survival, with hazard ratios ranged from 5.79 to 108.59 (all p<0.001). Importantly, the AMscore significantly improved the prediction of current immune biomarkers for both response and survival, thus redefining the advantaged and disadvantaged immunotherapy populations. CONCLUSIONS: Signatures based on genes associated with hereditary metabolic diseases and their corresponding scores could be used to guide the diagnosis and treatment of GC. Therefore, further validation is required. |
format | Online Article Text |
id | pubmed-10665511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106655112023-01-01 Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer Li, Yiping Li, Xiaoqin Yang, Yufei Qiao, Xuehan Tao, Qing Peng, Chen Han, Miao Dong, Kebin Xu, Min Wang, Deqiang Han, Gaohua Front Immunol Immunology BACKGROUND: Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC). METHODS: In total, 162 genes involved in 203 hereditary metabolic diseases were identified in the Human Phenotype Ontology database. Clinical and multi-omic data were acquired from the GC cohort of the Affiliated Hospital of Jiangsu University and other published cohorts. A 4-gene and 32-gene signature was established for diagnosis and prognosis or therapeutic prediction, respectively, and corresponding abnormal metabolism scores (AMscores) were calculated. RESULTS: The diagnostic AMscore showed high sensitivity (0.88-1.00) and specificity (0.89-1.00) to distinguish between GC and paired normal tissues, with area under the receiver operating characteristic curve (AUC) ranging from 0.911 to 1.000 in four GC cohorts. The prognostic or predictive AMscore was an independent predictor of overall survival (OS) in five GC cohorts and a predictor of the OS and disease-free survival benefit of postoperative chemotherapy or chemoradiotherapy in one GC cohort with such data. The AMscore adversely impacts immune biomarkers, including tumor mutation burden, tumor neoantigen burden, microsatellite instability, programmed death-ligand 1 protein expression, tumor microenvironment score, T cell receptor clonality, and immune cell infiltration detected by multiplex immunofluorescence staining. The AUC of the AMscore for predicting immunotherapy response ranging from 0.780 to 0.964 in four cohorts involving GC, urothelial cancer, melanoma, and lung cancer. The objective response rates in the low and high AMscore subgroups were 78.6% and 3.2%, 40.4% and 7%, 52.6% and 0%, and 72.7% and 0%, respectively (all p<0.001). In cohorts with survival data, a high AMscore was hazardous for OS or progression-free survival, with hazard ratios ranged from 5.79 to 108.59 (all p<0.001). Importantly, the AMscore significantly improved the prediction of current immune biomarkers for both response and survival, thus redefining the advantaged and disadvantaged immunotherapy populations. CONCLUSIONS: Signatures based on genes associated with hereditary metabolic diseases and their corresponding scores could be used to guide the diagnosis and treatment of GC. Therefore, further validation is required. Frontiers Media S.A. 2023-11-09 /pmc/articles/PMC10665511/ /pubmed/38022516 http://dx.doi.org/10.3389/fimmu.2023.1289700 Text en Copyright © 2023 Li, Li, Yang, Qiao, Tao, Peng, Han, Dong, Xu, Wang and Han https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Li, Yiping Li, Xiaoqin Yang, Yufei Qiao, Xuehan Tao, Qing Peng, Chen Han, Miao Dong, Kebin Xu, Min Wang, Deqiang Han, Gaohua Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title | Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title_full | Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title_fullStr | Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title_full_unstemmed | Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title_short | Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
title_sort | association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665511/ https://www.ncbi.nlm.nih.gov/pubmed/38022516 http://dx.doi.org/10.3389/fimmu.2023.1289700 |
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