Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model
IntroductionThe rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets,...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-12-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1296814/full |
| _version_ | 1827586389815853056 |
|---|---|
| author | Jie Hu Qilong Liu Bi Feng Yanling Lu Kai Chen |
| author_facet | Jie Hu Qilong Liu Bi Feng Yanling Lu Kai Chen |
| author_sort | Jie Hu |
| collection | DOAJ |
| description | IntroductionThe rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.MethodsTo bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.ResultsHypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.ConclusionOverall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice. |
| first_indexed | 2024-03-09T00:01:25Z |
| format | Article |
| id | doaj.art-e8362de868514d6183fbc77670da4fa5 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-09T00:01:25Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-e8362de868514d6183fbc77670da4fa52023-12-12T19:48:54ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-12-011310.3389/fonc.2023.12968141296814Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network modelJie Hu0Qilong Liu1Bi Feng2Yanling Lu3Kai Chen4Department of Medical Oncology of The Eastern Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, ChinaDepartment of Gastroenterology of The Eastern Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, ChinaDepartment of Medical Oncology of The Eastern Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, ChinaDepartment of Medical Oncology of The Eastern Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, ChinaDepartment of Medical Oncology of The Eastern Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, ChinaIntroductionThe rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.MethodsTo bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.ResultsHypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.ConclusionOverall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.https://www.frontiersin.org/articles/10.3389/fonc.2023.1296814/fullesophageal squamous cell carcinoma (ESCA)hypoxiaweighted gene co-expression network analysis (WGCNA)immune infiltrationprognostic biomarkers |
| spellingShingle | Jie Hu Qilong Liu Bi Feng Yanling Lu Kai Chen Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model Frontiers in Oncology esophageal squamous cell carcinoma (ESCA) hypoxia weighted gene co-expression network analysis (WGCNA) immune infiltration prognostic biomarkers |
| title | Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model |
| title_full | Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model |
| title_fullStr | Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model |
| title_full_unstemmed | Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model |
| title_short | Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model |
| title_sort | deciphering the hypoxia immune interface in esophageal squamous carcinoma a prognostic network model |
| topic | esophageal squamous cell carcinoma (ESCA) hypoxia weighted gene co-expression network analysis (WGCNA) immune infiltration prognostic biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1296814/full |
| work_keys_str_mv | AT jiehu decipheringthehypoxiaimmuneinterfaceinesophagealsquamouscarcinomaaprognosticnetworkmodel AT qilongliu decipheringthehypoxiaimmuneinterfaceinesophagealsquamouscarcinomaaprognosticnetworkmodel AT bifeng decipheringthehypoxiaimmuneinterfaceinesophagealsquamouscarcinomaaprognosticnetworkmodel AT yanlinglu decipheringthehypoxiaimmuneinterfaceinesophagealsquamouscarcinomaaprognosticnetworkmodel AT kaichen decipheringthehypoxiaimmuneinterfaceinesophagealsquamouscarcinomaaprognosticnetworkmodel |