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Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database

BACKGROUND: Researches have manifested that the disorder of iron metabolism is participated in Gastric cancer (GC), but whether iron metabolism-relevant genes (IMRGs) is related to the survival outcome of GC remain unknown. METHODS: Eleven tumor as well as nine adjacent normal tissues from GC patien...

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Autores principales: Liu, Xihong, Ren, Junyu, Zhou, Ruize, Wen, Zhengqi, Wen, Zhengwei, Chen, Zihao, He, Shanshan, Zhang, Hongbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644585/
https://www.ncbi.nlm.nih.gov/pubmed/37957566
http://dx.doi.org/10.1186/s12885-023-11569-9
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author Liu, Xihong
Ren, Junyu
Zhou, Ruize
Wen, Zhengqi
Wen, Zhengwei
Chen, Zihao
He, Shanshan
Zhang, Hongbin
author_facet Liu, Xihong
Ren, Junyu
Zhou, Ruize
Wen, Zhengqi
Wen, Zhengwei
Chen, Zihao
He, Shanshan
Zhang, Hongbin
author_sort Liu, Xihong
collection PubMed
description BACKGROUND: Researches have manifested that the disorder of iron metabolism is participated in Gastric cancer (GC), but whether iron metabolism-relevant genes (IMRGs) is related to the survival outcome of GC remain unknown. METHODS: Eleven tumor as well as nine adjacent normal tissues from GC patients were underwent mRNA sequencing, and the The Cancer Genome Atlas Stomach Cancer (TCGA-STAD) datasets were acquired from the TCGA database. Cox analyses and least absolute shrinkage and selection operator (LASSO) regression were applied to build a IMRGs signature. The relationship between signature genes and the infiltration profiling of 24 immune cells were investigated using single-sample GSEA (ssGSEA). Meanwhile, the potential biological significance, genes that act synergistically with signature genes, and the upstream regulatory targets were predicted. Finally, the abundance of the signature genes were measured via the quantitative real-time PCR (qRT-PCR). RESULTS: A IMRGs signature was constructed according to the expression and corresponding coefficient of DOHH, P4HA3 and MMP1 (The Schoenfeld individual test showed risk score was not significant with P values = 0.83). The prognostic outcome of patients in the high-risk group was terrible (p < 0.05). Receiver operating characteristic (ROC) curves confirmed that the IMRGs signature presented good efficiency for predicting GC prognosis (AUC > 0.6). The nomogram was performed well for clinical utilize (C-index = 0.60), and the MMP1 expression significantly increased in the cohorts at age > 60 and Stage II-IV (p < 0.05). The positive correlation of P4HA3 and MMP1 expression as well as the negative correlation of DOHH expression with risk score (p < 0.0001) and worse prognosis (p < 0.05) were detected as well. Furthermore, 11 differential immune cells were associated with these signature genes (most p < 0.01). Finally, qRT-PCR revealed that the abundance of DOHH, P4HA3 and MMP1 were high in tumor cases, indicating the complex mechanism between the high expression of DOHH as a protective factor and the high expression of P4HA3 and MMP1 as the risk factors in the development of GC. CONCLUSION: An iron metabolism-related signature was constructed and has significant values for foretelling the OS of GC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11569-9.
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spelling pubmed-106445852023-11-13 Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database Liu, Xihong Ren, Junyu Zhou, Ruize Wen, Zhengqi Wen, Zhengwei Chen, Zihao He, Shanshan Zhang, Hongbin BMC Cancer Research BACKGROUND: Researches have manifested that the disorder of iron metabolism is participated in Gastric cancer (GC), but whether iron metabolism-relevant genes (IMRGs) is related to the survival outcome of GC remain unknown. METHODS: Eleven tumor as well as nine adjacent normal tissues from GC patients were underwent mRNA sequencing, and the The Cancer Genome Atlas Stomach Cancer (TCGA-STAD) datasets were acquired from the TCGA database. Cox analyses and least absolute shrinkage and selection operator (LASSO) regression were applied to build a IMRGs signature. The relationship between signature genes and the infiltration profiling of 24 immune cells were investigated using single-sample GSEA (ssGSEA). Meanwhile, the potential biological significance, genes that act synergistically with signature genes, and the upstream regulatory targets were predicted. Finally, the abundance of the signature genes were measured via the quantitative real-time PCR (qRT-PCR). RESULTS: A IMRGs signature was constructed according to the expression and corresponding coefficient of DOHH, P4HA3 and MMP1 (The Schoenfeld individual test showed risk score was not significant with P values = 0.83). The prognostic outcome of patients in the high-risk group was terrible (p < 0.05). Receiver operating characteristic (ROC) curves confirmed that the IMRGs signature presented good efficiency for predicting GC prognosis (AUC > 0.6). The nomogram was performed well for clinical utilize (C-index = 0.60), and the MMP1 expression significantly increased in the cohorts at age > 60 and Stage II-IV (p < 0.05). The positive correlation of P4HA3 and MMP1 expression as well as the negative correlation of DOHH expression with risk score (p < 0.0001) and worse prognosis (p < 0.05) were detected as well. Furthermore, 11 differential immune cells were associated with these signature genes (most p < 0.01). Finally, qRT-PCR revealed that the abundance of DOHH, P4HA3 and MMP1 were high in tumor cases, indicating the complex mechanism between the high expression of DOHH as a protective factor and the high expression of P4HA3 and MMP1 as the risk factors in the development of GC. CONCLUSION: An iron metabolism-related signature was constructed and has significant values for foretelling the OS of GC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11569-9. BioMed Central 2023-11-13 /pmc/articles/PMC10644585/ /pubmed/37957566 http://dx.doi.org/10.1186/s12885-023-11569-9 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
Liu, Xihong
Ren, Junyu
Zhou, Ruize
Wen, Zhengqi
Wen, Zhengwei
Chen, Zihao
He, Shanshan
Zhang, Hongbin
Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title_full Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title_fullStr Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title_full_unstemmed Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title_short Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database
title_sort construction of iron metabolism-related prognostic features of gastric cancer based on rna sequencing and tcga database
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644585/
https://www.ncbi.nlm.nih.gov/pubmed/37957566
http://dx.doi.org/10.1186/s12885-023-11569-9
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