Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma

Esophageal carcinoma (ESCA) is one of the most frequent types of malignant tumor that has a dismal prognosis. This research applied datasets aimed from the GEO and TCGA to create a prognostic signature for forecasting the clinical outcome of ESCA patients on the basis of a circRNA-associated regulat...

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Autores principales:	Zhaonian Hu, Jun Xie, Xiaochun Chen, Jia Tang, Kaiguo Zhou, Song Han
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/39673172f78947abb8cff081eef89ea7
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spelling	oai:doaj.org-article:39673172f78947abb8cff081eef89ea72021-11-29T00:56:34ZIdentification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma1687-846910.1155/2021/1334571https://doaj.org/article/39673172f78947abb8cff081eef89ea72021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1334571https://doaj.org/toc/1687-8469Esophageal carcinoma (ESCA) is one of the most frequent types of malignant tumor that has a dismal prognosis. This research applied datasets aimed from the GEO and TCGA to create a prognostic signature for forecasting the clinical outcome of ESCA patients on the basis of a circRNA-associated regulatory network. Methods. A regulatory network associated with ESCA was established based on transcriptome data of circRNAs, miRNAs, and mRNAs. Functional annotations were implemented to further explore the mechanism of ESCA. Cox relative regression method was applied to create a risk signature. Besides, the immune microenvironment of the signature was investigated by utilizing the CIBERSORT algorithm. Results. Based on 27 DEcircRNAs, 65 DEmiRNAs, and 780 DEmRNAs, the circRNA-miRNA-mRNA network was finally set up. Functional enrichment unearthed that the regulatory network might participate in phosphorylation negative regulation, MAPK pathway, and PI3K/AKT pathway. This study established a risk scoring signature based on the seven immune-related genes (IRGs) (MARP14, RASGR1, PTK2, HMGB1, DKK1, RARB, and IGF1R), which was validated for its reliability. A stable and accurate nomogram combining immune-related risk scores with clinical features was constructed. Furthermore, we observed that the risk model was also related to the immunocyte infiltration. Conclusion. Our study successfully created a circRNA-associated regulatory network and further developed an immune-related model to forecast the clinical outcome of ESCA patients as well as to assess their immune status.Zhaonian HuJun XieXiaochun ChenJia TangKaiguo ZhouSong HanHindawi LimitedarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENJournal of Oncology, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Zhaonian Hu Jun Xie Xiaochun Chen Jia Tang Kaiguo Zhou Song Han Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
description	Esophageal carcinoma (ESCA) is one of the most frequent types of malignant tumor that has a dismal prognosis. This research applied datasets aimed from the GEO and TCGA to create a prognostic signature for forecasting the clinical outcome of ESCA patients on the basis of a circRNA-associated regulatory network. Methods. A regulatory network associated with ESCA was established based on transcriptome data of circRNAs, miRNAs, and mRNAs. Functional annotations were implemented to further explore the mechanism of ESCA. Cox relative regression method was applied to create a risk signature. Besides, the immune microenvironment of the signature was investigated by utilizing the CIBERSORT algorithm. Results. Based on 27 DEcircRNAs, 65 DEmiRNAs, and 780 DEmRNAs, the circRNA-miRNA-mRNA network was finally set up. Functional enrichment unearthed that the regulatory network might participate in phosphorylation negative regulation, MAPK pathway, and PI3K/AKT pathway. This study established a risk scoring signature based on the seven immune-related genes (IRGs) (MARP14, RASGR1, PTK2, HMGB1, DKK1, RARB, and IGF1R), which was validated for its reliability. A stable and accurate nomogram combining immune-related risk scores with clinical features was constructed. Furthermore, we observed that the risk model was also related to the immunocyte infiltration. Conclusion. Our study successfully created a circRNA-associated regulatory network and further developed an immune-related model to forecast the clinical outcome of ESCA patients as well as to assess their immune status.
format	article
author	Zhaonian Hu Jun Xie Xiaochun Chen Jia Tang Kaiguo Zhou Song Han
author_facet	Zhaonian Hu Jun Xie Xiaochun Chen Jia Tang Kaiguo Zhou Song Han
author_sort	Zhaonian Hu
title	Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
title_short	Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
title_full	Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
title_fullStr	Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
title_full_unstemmed	Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma
title_sort	identification of an immune-related biomarker model based on the circrna-associated regulatory network for esophageal carcinoma
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/39673172f78947abb8cff081eef89ea7
work_keys_str_mv	AT zhaonianhu identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma AT junxie identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma AT xiaochunchen identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma AT jiatang identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma AT kaiguozhou identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma AT songhan identificationofanimmunerelatedbiomarkermodelbasedonthecircrnaassociatedregulatorynetworkforesophagealcarcinoma
_version_	1718407697810849792

Identification of an Immune-Related Biomarker Model Based on the CircRNA-Associated Regulatory Network for Esophageal Carcinoma

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