{"title":"凋亡相关的长链非编码RNA标记预测透明细胞肾癌的预后。","authors":"J W Liu, F Supandi, S K Dhillon","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Clear cell renal cell carcinoma (ccRCC) is very common and accounts for most kidney cancer deaths. While many studies are being conducted in finding the prognostic signatures of ccRCC, we believe that ferroptosis, which involves programmed cell death dependent on iron accumulation, has therapeutic potential in ccRCC. Recent research has shown that long noncoding RNAs (lncRNAs) are involved in ferroptosis-related tumour processes and are closely related to survival in patients with ccRCC. Hence, in this study we aim to further explore the role of ferroptosis-related lncRNAs (FRLs) in ccRCC, hoping to establish a signature to predict the survival outcome of ccRCC. We analysed transcriptome data from The Cancer Genome Atlas database (TCGA) and ferroptosis-related genes (FRGs) from FerrDb to identify FRLs using Pearson's correlation. Lasso Cox regression analysis and multivariate Cox proportional hazards models screened seventeen optimal FRLs for developing prognostic signatures. Kaplan-Meier survival curves and ROC curves were then plotted for validating the sensitivity, specificity, and accuracy of the identified signatures. Gene Set Enrichment Analysis and CIBERSORT algorithm were deployed to explore the role of these FRLs in the tumour microenvironment. It was concluded that these models demonstrate excellent performance in predicting prognosis among patients with ccRCC, also indicating association with the clinicopathologic parameters such as tumour grade, tumour stage and tumour immune infiltration. In conclusion, our findings provide novel insights into ferroptosis-related lncRNAs in ccRCC, which are important targets for investigating the tumorigenesis of ccRCC.</p>","PeriodicalId":12281,"journal":{"name":"Folia Biologica","volume":"68 1","pages":"1-15"},"PeriodicalIF":1.1000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ferroptosis-Related Long Noncoding RNA Signature Predicts Prognosis of Clear Cell Renal Carcinoma.\",\"authors\":\"J W Liu, F Supandi, S K Dhillon\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Clear cell renal cell carcinoma (ccRCC) is very common and accounts for most kidney cancer deaths. While many studies are being conducted in finding the prognostic signatures of ccRCC, we believe that ferroptosis, which involves programmed cell death dependent on iron accumulation, has therapeutic potential in ccRCC. Recent research has shown that long noncoding RNAs (lncRNAs) are involved in ferroptosis-related tumour processes and are closely related to survival in patients with ccRCC. Hence, in this study we aim to further explore the role of ferroptosis-related lncRNAs (FRLs) in ccRCC, hoping to establish a signature to predict the survival outcome of ccRCC. We analysed transcriptome data from The Cancer Genome Atlas database (TCGA) and ferroptosis-related genes (FRGs) from FerrDb to identify FRLs using Pearson's correlation. Lasso Cox regression analysis and multivariate Cox proportional hazards models screened seventeen optimal FRLs for developing prognostic signatures. Kaplan-Meier survival curves and ROC curves were then plotted for validating the sensitivity, specificity, and accuracy of the identified signatures. Gene Set Enrichment Analysis and CIBERSORT algorithm were deployed to explore the role of these FRLs in the tumour microenvironment. It was concluded that these models demonstrate excellent performance in predicting prognosis among patients with ccRCC, also indicating association with the clinicopathologic parameters such as tumour grade, tumour stage and tumour immune infiltration. In conclusion, our findings provide novel insights into ferroptosis-related lncRNAs in ccRCC, which are important targets for investigating the tumorigenesis of ccRCC.</p>\",\"PeriodicalId\":12281,\"journal\":{\"name\":\"Folia Biologica\",\"volume\":\"68 1\",\"pages\":\"1-15\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Folia Biologica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Folia Biologica","FirstCategoryId":"3","ListUrlMain":"","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOLOGY","Score":null,"Total":0}
Ferroptosis-Related Long Noncoding RNA Signature Predicts Prognosis of Clear Cell Renal Carcinoma.
Clear cell renal cell carcinoma (ccRCC) is very common and accounts for most kidney cancer deaths. While many studies are being conducted in finding the prognostic signatures of ccRCC, we believe that ferroptosis, which involves programmed cell death dependent on iron accumulation, has therapeutic potential in ccRCC. Recent research has shown that long noncoding RNAs (lncRNAs) are involved in ferroptosis-related tumour processes and are closely related to survival in patients with ccRCC. Hence, in this study we aim to further explore the role of ferroptosis-related lncRNAs (FRLs) in ccRCC, hoping to establish a signature to predict the survival outcome of ccRCC. We analysed transcriptome data from The Cancer Genome Atlas database (TCGA) and ferroptosis-related genes (FRGs) from FerrDb to identify FRLs using Pearson's correlation. Lasso Cox regression analysis and multivariate Cox proportional hazards models screened seventeen optimal FRLs for developing prognostic signatures. Kaplan-Meier survival curves and ROC curves were then plotted for validating the sensitivity, specificity, and accuracy of the identified signatures. Gene Set Enrichment Analysis and CIBERSORT algorithm were deployed to explore the role of these FRLs in the tumour microenvironment. It was concluded that these models demonstrate excellent performance in predicting prognosis among patients with ccRCC, also indicating association with the clinicopathologic parameters such as tumour grade, tumour stage and tumour immune infiltration. In conclusion, our findings provide novel insights into ferroptosis-related lncRNAs in ccRCC, which are important targets for investigating the tumorigenesis of ccRCC.
期刊介绍:
Journal of Cellular and Molecular Biology publishes articles describing original research aimed at the elucidation of a wide range of questions of biology and medicine at the cellular and molecular levels. Studies on all organisms as well as on human cells and tissues are welcome.