{"title":"构建自噬相关的11长链非编码RNA标记以预测胃癌患者的预后、免疫细胞浸润和免疫治疗反应","authors":"G C Mu, Y J Luo, J Q Chen","doi":"10.26402/jpp.2023.3.05","DOIUrl":null,"url":null,"abstract":"<p><p>Long noncoding RNAs (LncRNAs) may be involved in the occurrence, development, and drug resistance of gastric cancer (GC) by regulating autophagy. This study aims to establish an autophagy-related LncRNA (ARL) signature (ARLSig) and explore its immunogenomic implications in patients with GC. The RNA sequencing and clinical data of patients with GC from The Cancer Genome Atlas database, and autophagy genes from the Human Autophagy Database were extracted. The co-expression and Cox regression analyses were performed to establish a prognostic ARLSig. Further, the differences in clinicopathology, immune microenvironment, immune function, and response to immunotherapy between the risk groups were explored by several algorithms. A prognostic risk model consisting of 11 ARLs was constructed. The clinical correlation analysis between the ARLSig and clinicopathological factors indicated that the ARLSig was correlated with the comprehensive, T, and N stages (all P<0.05). Further, a nomogram including the ARLSig and clinical factors suggested it had a powerful predictive value for survival, with a higher prediction efficiency for 1-, 3-, and 5-year survival than other clinicopathological factors. Finally, the immune-related analysis between the two risk groups showed that the high-risk group had significantly higher infiltration proportions of natural killer cells resting, monocytes, M2 macrophages, and dendritic cells resting, as well as higher expression of 25 immune checkpoint genes. In addition, the immunotherapy response prediction by the tracking of indels by decomposition algorithm showed the low-risk group was more sensitive to immune checkpoint inhibitor therapy. The ARLSig consisting of 11 ARLs in GC showed highly efficient predictive value for survival of patients with GC and might provide novel targets for their individualized immunotherapy.</p>","PeriodicalId":50089,"journal":{"name":"Journal of Physiology and Pharmacology","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction of an autophagy-related eleven long noncoding RNA signature to predict the outcomes, immune cell infiltration, and immunotherapy response in patients with gastric cancer.\",\"authors\":\"G C Mu, Y J Luo, J Q Chen\",\"doi\":\"10.26402/jpp.2023.3.05\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Long noncoding RNAs (LncRNAs) may be involved in the occurrence, development, and drug resistance of gastric cancer (GC) by regulating autophagy. This study aims to establish an autophagy-related LncRNA (ARL) signature (ARLSig) and explore its immunogenomic implications in patients with GC. The RNA sequencing and clinical data of patients with GC from The Cancer Genome Atlas database, and autophagy genes from the Human Autophagy Database were extracted. The co-expression and Cox regression analyses were performed to establish a prognostic ARLSig. Further, the differences in clinicopathology, immune microenvironment, immune function, and response to immunotherapy between the risk groups were explored by several algorithms. A prognostic risk model consisting of 11 ARLs was constructed. The clinical correlation analysis between the ARLSig and clinicopathological factors indicated that the ARLSig was correlated with the comprehensive, T, and N stages (all P<0.05). Further, a nomogram including the ARLSig and clinical factors suggested it had a powerful predictive value for survival, with a higher prediction efficiency for 1-, 3-, and 5-year survival than other clinicopathological factors. Finally, the immune-related analysis between the two risk groups showed that the high-risk group had significantly higher infiltration proportions of natural killer cells resting, monocytes, M2 macrophages, and dendritic cells resting, as well as higher expression of 25 immune checkpoint genes. In addition, the immunotherapy response prediction by the tracking of indels by decomposition algorithm showed the low-risk group was more sensitive to immune checkpoint inhibitor therapy. The ARLSig consisting of 11 ARLs in GC showed highly efficient predictive value for survival of patients with GC and might provide novel targets for their individualized immunotherapy.</p>\",\"PeriodicalId\":50089,\"journal\":{\"name\":\"Journal of Physiology and Pharmacology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physiology and Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.26402/jpp.2023.3.05\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PHYSIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physiology and Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.26402/jpp.2023.3.05","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
长链非编码rna (LncRNAs)可能通过调控自噬参与胃癌(GC)的发生、发展和耐药过程。本研究旨在建立自噬相关LncRNA (ARL)特征(ARLSig),并探讨其在胃癌患者中的免疫基因组意义。从The Cancer Genome Atlas数据库中提取GC患者的RNA测序和临床数据,从Human autophagy database中提取自噬基因。采用共表达和Cox回归分析建立预后ARLSig。此外,通过几种算法探讨了危险组之间在临床病理、免疫微环境、免疫功能和免疫治疗反应方面的差异。构建由11个arl组成的预后风险模型。ARLSig与临床病理因素的临床相关性分析显示,ARLSig与综合分期、T分期、N分期均有相关性(P < 0.05)
Construction of an autophagy-related eleven long noncoding RNA signature to predict the outcomes, immune cell infiltration, and immunotherapy response in patients with gastric cancer.
Long noncoding RNAs (LncRNAs) may be involved in the occurrence, development, and drug resistance of gastric cancer (GC) by regulating autophagy. This study aims to establish an autophagy-related LncRNA (ARL) signature (ARLSig) and explore its immunogenomic implications in patients with GC. The RNA sequencing and clinical data of patients with GC from The Cancer Genome Atlas database, and autophagy genes from the Human Autophagy Database were extracted. The co-expression and Cox regression analyses were performed to establish a prognostic ARLSig. Further, the differences in clinicopathology, immune microenvironment, immune function, and response to immunotherapy between the risk groups were explored by several algorithms. A prognostic risk model consisting of 11 ARLs was constructed. The clinical correlation analysis between the ARLSig and clinicopathological factors indicated that the ARLSig was correlated with the comprehensive, T, and N stages (all P<0.05). Further, a nomogram including the ARLSig and clinical factors suggested it had a powerful predictive value for survival, with a higher prediction efficiency for 1-, 3-, and 5-year survival than other clinicopathological factors. Finally, the immune-related analysis between the two risk groups showed that the high-risk group had significantly higher infiltration proportions of natural killer cells resting, monocytes, M2 macrophages, and dendritic cells resting, as well as higher expression of 25 immune checkpoint genes. In addition, the immunotherapy response prediction by the tracking of indels by decomposition algorithm showed the low-risk group was more sensitive to immune checkpoint inhibitor therapy. The ARLSig consisting of 11 ARLs in GC showed highly efficient predictive value for survival of patients with GC and might provide novel targets for their individualized immunotherapy.
期刊介绍:
Journal of Physiology and Pharmacology publishes papers which fall within the range of basic and applied physiology, pathophysiology and pharmacology. The papers should illustrate new physiological or pharmacological mechanisms at the level of the cell membrane, single cells, tissues or organs. Clinical studies, that are of fundamental importance and have a direct bearing on the pathophysiology will also be considered. Letters related to articles published in The Journal with topics of general professional interest are welcome.