Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer

Background. Increasing evidence suggests that microRNAs (miRNAs) are involved in genome instability (GI) and drive the occurrence of tumors. However, the role of GI-related miRNAs in gastric cancer (GC) remains largely unknown. Herein, we developed a novel GI-related miRNA signature (GIMiSig) and fu...

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Autores principales:	Yaqiong Liu, Lin Cheng, Wei Huang, Xin Cheng, Weijun Peng, Dazun Shi
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Immunologic diseases. Allergy RC581-607
Acceso en línea:	https://doaj.org/article/7832671d59db4ca79ec36ae695967798
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spelling	oai:doaj.org-article:7832671d59db4ca79ec36ae6959677982021-11-15T01:19:22ZGenome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer2314-715610.1155/2021/2048833https://doaj.org/article/7832671d59db4ca79ec36ae6959677982021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2048833https://doaj.org/toc/2314-7156Background. Increasing evidence suggests that microRNAs (miRNAs) are involved in genome instability (GI) and drive the occurrence of tumors. However, the role of GI-related miRNAs in gastric cancer (GC) remains largely unknown. Herein, we developed a novel GI-related miRNA signature (GIMiSig) and further investigated its role in prognosis, the immune landscape, and immunotherapy responses in GC patients. Methods. An analysis of somatic mutation data on 434 gastric cancer cases from The Cancer Genome Atlas (TCGA) database was performed, thereby generating genome stability (GS) and GI groups. By detecting differentially expressed miRNAs between the GS and GI groups that were associated with overall survival, 8 miRNAs were identified and used to construct the GIMiSig. Results. The GIMiSig showed high accuracy in detecting GC patients. Using GIMiSig to stratify the patients into the high- and low-risk subgroups to predict survival outperformed the use of regular clinical features such as age, gender, or disease stage. Patients with low risk had a more favorable survival time than those with high risk. More importantly, the high-risk patients were associated with decreased UBQLN4 expression, higher accumulation of immune cells, lower Titin (TTN) mutation frequency, worse immunotherapy efficacy, and cancer-associated pathways. Conversely, the low-risk patients were characterized by UBQLN4 overexpression, lower fraction of immune cells, higher TTN mutation frequency, better response to immunotherapy, and GI-related pathways. Conclusion. In summary, we constructed a novel GIMiSig that could stratify GC patients into distinct risk groups that have different survival outcomes and immunotherapy efficacy. The results may provide new clues for improving GC outcomes.Yaqiong LiuLin ChengWei HuangXin ChengWeijun PengDazun ShiHindawi LimitedarticleImmunologic diseases. AllergyRC581-607ENJournal of Immunology Research, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Immunologic diseases. Allergy RC581-607
spellingShingle	Immunologic diseases. Allergy RC581-607 Yaqiong Liu Lin Cheng Wei Huang Xin Cheng Weijun Peng Dazun Shi Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
description	Background. Increasing evidence suggests that microRNAs (miRNAs) are involved in genome instability (GI) and drive the occurrence of tumors. However, the role of GI-related miRNAs in gastric cancer (GC) remains largely unknown. Herein, we developed a novel GI-related miRNA signature (GIMiSig) and further investigated its role in prognosis, the immune landscape, and immunotherapy responses in GC patients. Methods. An analysis of somatic mutation data on 434 gastric cancer cases from The Cancer Genome Atlas (TCGA) database was performed, thereby generating genome stability (GS) and GI groups. By detecting differentially expressed miRNAs between the GS and GI groups that were associated with overall survival, 8 miRNAs were identified and used to construct the GIMiSig. Results. The GIMiSig showed high accuracy in detecting GC patients. Using GIMiSig to stratify the patients into the high- and low-risk subgroups to predict survival outperformed the use of regular clinical features such as age, gender, or disease stage. Patients with low risk had a more favorable survival time than those with high risk. More importantly, the high-risk patients were associated with decreased UBQLN4 expression, higher accumulation of immune cells, lower Titin (TTN) mutation frequency, worse immunotherapy efficacy, and cancer-associated pathways. Conversely, the low-risk patients were characterized by UBQLN4 overexpression, lower fraction of immune cells, higher TTN mutation frequency, better response to immunotherapy, and GI-related pathways. Conclusion. In summary, we constructed a novel GIMiSig that could stratify GC patients into distinct risk groups that have different survival outcomes and immunotherapy efficacy. The results may provide new clues for improving GC outcomes.
format	article
author	Yaqiong Liu Lin Cheng Wei Huang Xin Cheng Weijun Peng Dazun Shi
author_facet	Yaqiong Liu Lin Cheng Wei Huang Xin Cheng Weijun Peng Dazun Shi
author_sort	Yaqiong Liu
title	Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
title_short	Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
title_full	Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
title_fullStr	Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
title_full_unstemmed	Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer
title_sort	genome instability-related mirnas predict survival, immune landscape, and immunotherapy responses in gastric cancer
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/7832671d59db4ca79ec36ae695967798
work_keys_str_mv	AT yaqiongliu genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer AT lincheng genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer AT weihuang genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer AT xincheng genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer AT weijunpeng genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer AT dazunshi genomeinstabilityrelatedmirnaspredictsurvivalimmunelandscapeandimmunotherapyresponsesingastriccancer
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Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer

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