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...
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Frontiers Media S.A.
2022-06-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.912537/full |
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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. |
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publishDate | 2022-06-01 |
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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 |
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