Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer

BACKGROUND: Colon cancer is a common and highly malignant tumor. Its incidence is increasing rapidly with poor prognosis. At present, immunotherapy is a rapidly developing treatment for colon cancer. The aim of this study was to construct a prognostic risk model based on immune genes for early diagn...

Descripción completa

Detalles Bibliográficos
Autores principales: Hao, Mengdi, Li, Huimin, Yi, Meng, Zhu, Yubing, Wang, Kun, Liu, Yin, Liang, Xiaoqing, Ding, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996977/
https://www.ncbi.nlm.nih.gov/pubmed/36890467
http://dx.doi.org/10.1186/s12876-023-02679-6
_version_ 1784903163819589632
author Hao, Mengdi
Li, Huimin
Yi, Meng
Zhu, Yubing
Wang, Kun
Liu, Yin
Liang, Xiaoqing
Ding, Lei
author_facet Hao, Mengdi
Li, Huimin
Yi, Meng
Zhu, Yubing
Wang, Kun
Liu, Yin
Liang, Xiaoqing
Ding, Lei
author_sort Hao, Mengdi
collection PubMed
description BACKGROUND: Colon cancer is a common and highly malignant tumor. Its incidence is increasing rapidly with poor prognosis. At present, immunotherapy is a rapidly developing treatment for colon cancer. The aim of this study was to construct a prognostic risk model based on immune genes for early diagnosis and accurate prognostic prediction of colon cancer. METHODS: Transcriptome data and clinical data were downloaded from the cancer Genome Atlas database. Immunity genes were obtained from ImmPort database. The differentially expressed transcription factors (TFs) were obtained from Cistrome database. Differentially expressed (DE) immune genes were identified in 473 cases of colon cancer and 41 cases of normal adjacent tissues. An immune-related prognostic model of colon cancer was established and its clinical applicability was verified. Among 318 tumor-related transcription factors, differentially expressed transcription factors were finally obtained, and a regulatory network was constructed according to the up-down regulatory relationship. RESULTS: A total of 477 DE immune genes (180 up-regulated and 297 down-regulated) were detected. We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. The model was proved to be an independent prognostic variable with good prognostic ability. A total of 68 DE TFs (40 up-regulated and 23 down-regulated) were obtained. The regulation network between TF and immune genes was plotted by using TF as source node and immune genes as target node. In addition, Macrophage, Myeloid Dendritic cell and CD4(+) T cell increased with the increase of risk score. CONCLUSION: We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. This model can be used as a tool variable to predict the prognosis of colon cancer.
format Online
Article
Text
id pubmed-9996977
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-99969772023-03-10 Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer Hao, Mengdi Li, Huimin Yi, Meng Zhu, Yubing Wang, Kun Liu, Yin Liang, Xiaoqing Ding, Lei BMC Gastroenterol Research BACKGROUND: Colon cancer is a common and highly malignant tumor. Its incidence is increasing rapidly with poor prognosis. At present, immunotherapy is a rapidly developing treatment for colon cancer. The aim of this study was to construct a prognostic risk model based on immune genes for early diagnosis and accurate prognostic prediction of colon cancer. METHODS: Transcriptome data and clinical data were downloaded from the cancer Genome Atlas database. Immunity genes were obtained from ImmPort database. The differentially expressed transcription factors (TFs) were obtained from Cistrome database. Differentially expressed (DE) immune genes were identified in 473 cases of colon cancer and 41 cases of normal adjacent tissues. An immune-related prognostic model of colon cancer was established and its clinical applicability was verified. Among 318 tumor-related transcription factors, differentially expressed transcription factors were finally obtained, and a regulatory network was constructed according to the up-down regulatory relationship. RESULTS: A total of 477 DE immune genes (180 up-regulated and 297 down-regulated) were detected. We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. The model was proved to be an independent prognostic variable with good prognostic ability. A total of 68 DE TFs (40 up-regulated and 23 down-regulated) were obtained. The regulation network between TF and immune genes was plotted by using TF as source node and immune genes as target node. In addition, Macrophage, Myeloid Dendritic cell and CD4(+) T cell increased with the increase of risk score. CONCLUSION: We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. This model can be used as a tool variable to predict the prognosis of colon cancer. BioMed Central 2023-03-08 /pmc/articles/PMC9996977/ /pubmed/36890467 http://dx.doi.org/10.1186/s12876-023-02679-6 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/) . 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
Hao, Mengdi
Li, Huimin
Yi, Meng
Zhu, Yubing
Wang, Kun
Liu, Yin
Liang, Xiaoqing
Ding, Lei
Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title_full Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title_fullStr Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title_full_unstemmed Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title_short Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
title_sort development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996977/
https://www.ncbi.nlm.nih.gov/pubmed/36890467
http://dx.doi.org/10.1186/s12876-023-02679-6
work_keys_str_mv AT haomengdi developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT lihuimin developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT yimeng developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT zhuyubing developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT wangkun developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT liuyin developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT liangxiaoqing developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer
AT dinglei developmentofanimmunerelatedgeneprognosticriskmodelandidentificationofanimmuneinfiltrationsignatureinthetumormicroenvironmentofcoloncancer

Ejemplares similares