{"title":"结直肠癌患者的自噬相关长非编码 RNA 特征。","authors":"Dongyan Zhao, Xizhen Sun, Sidan Long, Shukun Yao","doi":"10.1556/2060.2021.00125","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>Long non-coding RNAs (lncRNAs) have been identified to regulate cancers by controlling the process of autophagy and by mediating the post-transcriptional and transcriptional regulation of autophagy-related genes. This study aimed to investigate the potential prognostic role of autophagy-associated lncRNAs in colorectal cancer (CRC) patients.</p><p><strong>Methods: </strong>LncRNA expression profiles and the corresponding clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, autophagy-related lncRNAs were identified by Pearson correlation test. Univariate Cox regression analysis and the least absolute shrinkage and selection operator analysis (LASSO) Cox regression model were performed to construct the prognostic gene signature. Gene set enrichment analysis (GSEA) was used to further clarify the underlying molecular mechanisms.</p><p><strong>Results: </strong>We obtained 210 autophagy-related genes from the whole dataset and found 1187 lncRNAs that were correlated with the autophagy-related genes. Using Univariate and LASSO Cox regression analyses, eight lncRNAs were screened to establish an eight-lncRNA signature, based on which patients were divided into the low-risk and high-risk group. Patients' overall survival was found to be significantly worse in the high-risk group compared to that in the low-risk group (log-rank p = 2.731E-06). ROC analysis showed that this signature had better prognostic accuracy than TNM stage, as indicated by the area under the curve. Furthermore, GSEA demonstrated that this signature was involved in many cancer-related pathways, including TGF-β, p53, mTOR and WNT signaling pathway.</p><p><strong>Conclusions: </strong>Our study constructed a novel signature from eight autophagy-related lncRNAs to predict the overall survival of CRC, which could assistant clinicians in making individualized treatment.</p>","PeriodicalId":20058,"journal":{"name":"Physiology international","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An autophagy-related long non-coding RNA signature for patients with colorectal cancer.\",\"authors\":\"Dongyan Zhao, Xizhen Sun, Sidan Long, Shukun Yao\",\"doi\":\"10.1556/2060.2021.00125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>Long non-coding RNAs (lncRNAs) have been identified to regulate cancers by controlling the process of autophagy and by mediating the post-transcriptional and transcriptional regulation of autophagy-related genes. This study aimed to investigate the potential prognostic role of autophagy-associated lncRNAs in colorectal cancer (CRC) patients.</p><p><strong>Methods: </strong>LncRNA expression profiles and the corresponding clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, autophagy-related lncRNAs were identified by Pearson correlation test. Univariate Cox regression analysis and the least absolute shrinkage and selection operator analysis (LASSO) Cox regression model were performed to construct the prognostic gene signature. Gene set enrichment analysis (GSEA) was used to further clarify the underlying molecular mechanisms.</p><p><strong>Results: </strong>We obtained 210 autophagy-related genes from the whole dataset and found 1187 lncRNAs that were correlated with the autophagy-related genes. Using Univariate and LASSO Cox regression analyses, eight lncRNAs were screened to establish an eight-lncRNA signature, based on which patients were divided into the low-risk and high-risk group. Patients' overall survival was found to be significantly worse in the high-risk group compared to that in the low-risk group (log-rank p = 2.731E-06). ROC analysis showed that this signature had better prognostic accuracy than TNM stage, as indicated by the area under the curve. Furthermore, GSEA demonstrated that this signature was involved in many cancer-related pathways, including TGF-β, p53, mTOR and WNT signaling pathway.</p><p><strong>Conclusions: </strong>Our study constructed a novel signature from eight autophagy-related lncRNAs to predict the overall survival of CRC, which could assistant clinicians in making individualized treatment.</p>\",\"PeriodicalId\":20058,\"journal\":{\"name\":\"Physiology international\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2021-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physiology international\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1556/2060.2021.00125\",\"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":"Physiology international","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1556/2060.2021.00125","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
目的:已发现长非编码RNA(lncRNA)可通过控制自噬过程以及介导自噬相关基因的转录后和转录调控来调控癌症。本研究旨在探讨自噬相关lncRNAs在结直肠癌(CRC)患者中的潜在预后作用:方法:从癌症基因组图谱(TCGA)数据库中收集CRC患者的LncRNA表达谱和相应的临床信息。基于TCGA数据集,通过皮尔逊相关性检验确定了自噬相关的lncRNA。采用单变量Cox回归分析和最小绝对收缩与选择算子分析(LASSO)Cox回归模型构建预后基因特征。基因组富集分析(Gene set enrichment analysis,GSEA)用于进一步阐明潜在的分子机制:结果:我们从整个数据集中获得了210个自噬相关基因,并发现了1187个与自噬相关基因相关的lncRNA。通过单变量和LASSO Cox回归分析,筛选出8个lncRNA,建立了8个lncRNA特征,并据此将患者分为低危和高危组。结果发现,与低风险组相比,高风险组患者的总生存率明显降低(log-rank p = 2.731E-06)。ROC分析表明,从曲线下面积来看,该特征的预后准确性优于TNM分期。此外,GSEA显示,该特征参与了许多癌症相关通路,包括TGF-β、p53、mTOR和WNT信号通路:我们的研究从八个自噬相关的 lncRNA 中构建了一个新的特征来预测 CRC 的总生存率,这可以帮助临床医生进行个体化治疗。
An autophagy-related long non-coding RNA signature for patients with colorectal cancer.
Aim: Long non-coding RNAs (lncRNAs) have been identified to regulate cancers by controlling the process of autophagy and by mediating the post-transcriptional and transcriptional regulation of autophagy-related genes. This study aimed to investigate the potential prognostic role of autophagy-associated lncRNAs in colorectal cancer (CRC) patients.
Methods: LncRNA expression profiles and the corresponding clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, autophagy-related lncRNAs were identified by Pearson correlation test. Univariate Cox regression analysis and the least absolute shrinkage and selection operator analysis (LASSO) Cox regression model were performed to construct the prognostic gene signature. Gene set enrichment analysis (GSEA) was used to further clarify the underlying molecular mechanisms.
Results: We obtained 210 autophagy-related genes from the whole dataset and found 1187 lncRNAs that were correlated with the autophagy-related genes. Using Univariate and LASSO Cox regression analyses, eight lncRNAs were screened to establish an eight-lncRNA signature, based on which patients were divided into the low-risk and high-risk group. Patients' overall survival was found to be significantly worse in the high-risk group compared to that in the low-risk group (log-rank p = 2.731E-06). ROC analysis showed that this signature had better prognostic accuracy than TNM stage, as indicated by the area under the curve. Furthermore, GSEA demonstrated that this signature was involved in many cancer-related pathways, including TGF-β, p53, mTOR and WNT signaling pathway.
Conclusions: Our study constructed a novel signature from eight autophagy-related lncRNAs to predict the overall survival of CRC, which could assistant clinicians in making individualized treatment.
期刊介绍:
The journal provides a forum for important new research papers written by eminent scientists on experimental medical sciences. Papers reporting on both original work and review articles in the fields of basic and clinical physiology, pathophysiology (from the subcellular organization level up to the oranizmic one), as well as related disciplines, including history of physiological sciences, are accepted.