Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network

BackgroundHepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. Non-coding RNAs play an important role in HCC. This study aims to identify a senescence-related non-coding RNA network-based prognostic model for individualized therapies for HCC.MethodsHCC su...

Full description

Bibliographic Details
Main Authors: Yanan Jiang, Kunpeng Luo, Jincheng Xu, Xiuyun Shen, Yang Gao, Wenqi Fu, Xuesong Zhang, Hongguang Wang, Bing Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.912537/full
_version_ 1811329423755968512
author Yanan Jiang
Yanan Jiang
Kunpeng Luo
Jincheng Xu
Xiuyun Shen
Yang Gao
Wenqi Fu
Xuesong Zhang
Hongguang Wang
Bing Liu
author_facet Yanan Jiang
Yanan Jiang
Kunpeng Luo
Jincheng Xu
Xiuyun Shen
Yang Gao
Wenqi Fu
Xuesong Zhang
Hongguang Wang
Bing Liu
author_sort Yanan Jiang
collection DOAJ
description BackgroundHepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. Non-coding RNAs play an important role in HCC. This study aims to identify a senescence-related non-coding RNA network-based prognostic model for individualized therapies for HCC.MethodsHCC subtypes with senescence status were identified on the basis of the senescence-related genes. Immune status of the subtypes was analyzed by CIBERSORT and ESTIMATE algorithm. The differentially expressed mRNAs, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) were identified between the two HCC subtypes. A senescence-based competing endogenous RNA (ceRNA) co-expression network in HCC was constructed. On the basis of the ceRNA network, Lasso Cox regression was used to construct the senescence-related prognostic model (S score). The prognosis potential of the S score was evaluated in the training dataset and four external validation datasets. Finally, the potential of the prognostic model in predicting immune features and response to immunotherapy was evaluated.ResultsThe HCC samples were classified into senescence active and inactivate subtypes. The senescence active group showed an immune suppressive microenvironment compared to the senescence inactive group. A total of 2,902 mRNAs, 19 miRNAs, and 308 lncRNAs were identified between the two subtypes. A ceRNA network was constructed using these differentially expressed genes. On the basis of the ceRNA network, S score was constructed to predict the prognosis of patients with HCC. The S score was correlated with immune features and can predict response to immunotherapy of cancer.ConclusionThe present study analyzed the biological heterogeneity across senescence-related subtypes and constructed a senescence-related ceRNA-network-based prognostic model for predicting prognosis and immunotherapy responsiveness.
first_indexed 2024-04-13T15:43:37Z
format Article
id doaj.art-eeb03bb1f5cb4412b300f0f0908e1f37
institution Directory Open Access Journal
issn 2234-943X
language English
last_indexed 2024-04-13T15:43:37Z
publishDate 2022-06-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Oncology
spelling doaj.art-eeb03bb1f5cb4412b300f0f0908e1f372022-12-22T02:41:03ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.912537912537Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA NetworkYanan Jiang0Yanan Jiang1Kunpeng Luo2Jincheng Xu3Xiuyun Shen4Yang Gao5Wenqi Fu6Xuesong Zhang7Hongguang Wang8Bing Liu9Department of Pharmacology (State-Province Key Laboratories of Biomedicine- Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, ChinaTranslational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin, ChinaDepartment of Gastroenterology and Hepatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, ChinaDepartment of Pharmacology (State-Province Key Laboratories of Biomedicine- Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, ChinaDepartment of Pharmacology (State-Province Key Laboratories of Biomedicine- Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, ChinaDepartment of Gastroenterology and Hepatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, ChinaDepartment of Pharmacology (State-Province Key Laboratories of Biomedicine- Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, ChinaDepartment of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, ChinaSchool of Civil Engineering, Northeast Forestry University, Harbin, ChinaDepartment of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, ChinaBackgroundHepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. Non-coding RNAs play an important role in HCC. This study aims to identify a senescence-related non-coding RNA network-based prognostic model for individualized therapies for HCC.MethodsHCC subtypes with senescence status were identified on the basis of the senescence-related genes. Immune status of the subtypes was analyzed by CIBERSORT and ESTIMATE algorithm. The differentially expressed mRNAs, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) were identified between the two HCC subtypes. A senescence-based competing endogenous RNA (ceRNA) co-expression network in HCC was constructed. On the basis of the ceRNA network, Lasso Cox regression was used to construct the senescence-related prognostic model (S score). The prognosis potential of the S score was evaluated in the training dataset and four external validation datasets. Finally, the potential of the prognostic model in predicting immune features and response to immunotherapy was evaluated.ResultsThe HCC samples were classified into senescence active and inactivate subtypes. The senescence active group showed an immune suppressive microenvironment compared to the senescence inactive group. A total of 2,902 mRNAs, 19 miRNAs, and 308 lncRNAs were identified between the two subtypes. A ceRNA network was constructed using these differentially expressed genes. On the basis of the ceRNA network, S score was constructed to predict the prognosis of patients with HCC. The S score was correlated with immune features and can predict response to immunotherapy of cancer.ConclusionThe present study analyzed the biological heterogeneity across senescence-related subtypes and constructed a senescence-related ceRNA-network-based prognostic model for predicting prognosis and immunotherapy responsiveness.https://www.frontiersin.org/articles/10.3389/fonc.2022.912537/fullhepatocellular carcinoma (HCC)senescencenon-coding RNA (ncRNA)prognosisregulatory network
spellingShingle Yanan Jiang
Yanan Jiang
Kunpeng Luo
Jincheng Xu
Xiuyun Shen
Yang Gao
Wenqi Fu
Xuesong Zhang
Hongguang Wang
Bing Liu
Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
Frontiers in Oncology
hepatocellular carcinoma (HCC)
senescence
non-coding RNA (ncRNA)
prognosis
regulatory network
title Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
title_full Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
title_fullStr Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
title_full_unstemmed Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
title_short Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network
title_sort integrated analysis revealing the senescence mediated immune heterogeneity of hcc and construction of a prognostic model based on senescence related non coding rna network
topic hepatocellular carcinoma (HCC)
senescence
non-coding RNA (ncRNA)
prognosis
regulatory network
url https://www.frontiersin.org/articles/10.3389/fonc.2022.912537/full
work_keys_str_mv AT yananjiang integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT yananjiang integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT kunpengluo integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT jinchengxu integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT xiuyunshen integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT yanggao integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT wenqifu integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT xuesongzhang integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT hongguangwang integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork
AT bingliu integratedanalysisrevealingthesenescencemediatedimmuneheterogeneityofhccandconstructionofaprognosticmodelbasedonsenescencerelatednoncodingrnanetwork