Cargando…

Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer

BACKGROUND: Inflammation and immune cell dysfunction have been widely known as an essential role in the tumorigenesis of colorectal cancer (CRC). Yet, the role of tumor inflammation signature (TIS) associated with CRC prognosis, immune infiltration, and drug resistance remained unknown. METHOD: The...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yayun, Qiu, Zhengcai, Wang, Qipeng, Li, Shangshang, Zhang, Qiong, Han, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308547/
https://www.ncbi.nlm.nih.gov/pubmed/35880031
http://dx.doi.org/10.1155/2022/3465391
_version_ 1784753005320470528
author Li, Yayun
Qiu, Zhengcai
Wang, Qipeng
Li, Shangshang
Zhang, Qiong
Han, Jing
author_facet Li, Yayun
Qiu, Zhengcai
Wang, Qipeng
Li, Shangshang
Zhang, Qiong
Han, Jing
author_sort Li, Yayun
collection PubMed
description BACKGROUND: Inflammation and immune cell dysfunction have been widely known as an essential role in the tumorigenesis of colorectal cancer (CRC). Yet, the role of tumor inflammation signature (TIS) associated with CRC prognosis, immune infiltration, and drug resistance remained unknown. METHOD: The transcriptome sequencing data, as well as clinical data of CRC from the public dataset, were acquired for further investigation. Inflammation-related gene expression patterns were obtained and analyzed. Bioinformatics methods were used to build a prognostic TIS, and its prediction accuracy was verified by using ROC curve analyses. The independent prognostic factors in CRC were identified through multivariable Cox regression analysis. In addition, the specific features of the immunological landscape between low- and high-risk CRC cohorts were analyzed. RESULTS: We firstly screened the differentially expressed inflammation-related genes in CRC and constructed a prognostic TIS. We further classified CRC patients into high or low TIS score groups based on the optimal cutoff of prognostic TIS, and patients with high-risk scores had shorter overall survival (OS) than those in the low-risk cohort. The diagnostic accuracy of TIS was evaluated and confirmed with ROC analysis. The result of the univariate and multivariate analysis found that TIS was directly and independently linked to OS of CRC. Otherwise, an optimal nomogram model based on TIS exhibited a better prognostic accuracy in OS. Finally, the immunological status and immune cell infiltration were observed different in the two-risk cohorts. CONCLUSION: In summary, the risk model of the TIS in CRC was found to be useful for predicting patient prognosis and guiding individual treatment. This risk signature could also serve as potential biomarkers and immunotherapeutic targets and indicate immunotherapy response for patients with CRC.
format Online
Article
Text
id pubmed-9308547
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-93085472022-07-24 Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer Li, Yayun Qiu, Zhengcai Wang, Qipeng Li, Shangshang Zhang, Qiong Han, Jing Biomed Res Int Research Article BACKGROUND: Inflammation and immune cell dysfunction have been widely known as an essential role in the tumorigenesis of colorectal cancer (CRC). Yet, the role of tumor inflammation signature (TIS) associated with CRC prognosis, immune infiltration, and drug resistance remained unknown. METHOD: The transcriptome sequencing data, as well as clinical data of CRC from the public dataset, were acquired for further investigation. Inflammation-related gene expression patterns were obtained and analyzed. Bioinformatics methods were used to build a prognostic TIS, and its prediction accuracy was verified by using ROC curve analyses. The independent prognostic factors in CRC were identified through multivariable Cox regression analysis. In addition, the specific features of the immunological landscape between low- and high-risk CRC cohorts were analyzed. RESULTS: We firstly screened the differentially expressed inflammation-related genes in CRC and constructed a prognostic TIS. We further classified CRC patients into high or low TIS score groups based on the optimal cutoff of prognostic TIS, and patients with high-risk scores had shorter overall survival (OS) than those in the low-risk cohort. The diagnostic accuracy of TIS was evaluated and confirmed with ROC analysis. The result of the univariate and multivariate analysis found that TIS was directly and independently linked to OS of CRC. Otherwise, an optimal nomogram model based on TIS exhibited a better prognostic accuracy in OS. Finally, the immunological status and immune cell infiltration were observed different in the two-risk cohorts. CONCLUSION: In summary, the risk model of the TIS in CRC was found to be useful for predicting patient prognosis and guiding individual treatment. This risk signature could also serve as potential biomarkers and immunotherapeutic targets and indicate immunotherapy response for patients with CRC. Hindawi 2022-07-16 /pmc/articles/PMC9308547/ /pubmed/35880031 http://dx.doi.org/10.1155/2022/3465391 Text en Copyright © 2022 Yayun Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Yayun
Qiu, Zhengcai
Wang, Qipeng
Li, Shangshang
Zhang, Qiong
Han, Jing
Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title_full Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title_fullStr Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title_full_unstemmed Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title_short Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer
title_sort identification of a novel tumor inflammation signature for risk stratification, prognosis prediction, and immune status in colorectal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308547/
https://www.ncbi.nlm.nih.gov/pubmed/35880031
http://dx.doi.org/10.1155/2022/3465391
work_keys_str_mv AT liyayun identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer
AT qiuzhengcai identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer
AT wangqipeng identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer
AT lishangshang identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer
AT zhangqiong identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer
AT hanjing identificationofanoveltumorinflammationsignatureforriskstratificationprognosispredictionandimmunestatusincolorectalcancer