Jingchao Liu1,2, Jinfu Wang1, Lanxin Zhang3, Jiawen Wang1,2, Zhengtong Lv1,2, Yaoguang Zhang1, Jianye Wang4,5. 1. Department of Urology, Institute of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, China. 2. Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 9 DongDan SANTIAO, Beijing, 100730, China. 3. Clinical Biobank, Institute of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, China. 4. Department of Urology, Institute of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, China. wjy08pro@126.com. 5. Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 9 DongDan SANTIAO, Beijing, 100730, China. wjy08pro@126.com.
Abstract
PURPOSE: This study aimed to investigate whether N6-methyladenosine (m6A)-related long non-coding RNAs (m6ARelncRNAs) could provide novel tools to predict overall survival of renal clear cell carcinoma. METHODS: The transcriptomic data and clinical information of patients with renal clear cell carcinoma from The Cancer Genome Atlas (TCGA) were analysed. Distinct m6A modification patterns were systemically analysed via consensus clustering analysis. An m6ARelncRNA signature was constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) analysis and validated in the test cohort. Potential predictive accuracy of the signature was further assessed via Kaplan-Meier survival, univariate and multivariate Cox regression and subgroup analyses. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the role of m6ARelncRNAs in guiding immunotherapy for patients with renal carcinoma. RESULTS: An m6ARelncRNA signature based on only six lncRNAs was successfully constructed. The high-risk group derived from this signature had significantly poorer overall survival in both training and test cohorts (p < 0.001). Independent prognostic analysis further revealed that m6ARelncRNA risk (p < 0.01) was an independent risk factor for survival outcomes of renal carcinoma. TIDE algorithm revealed that immunotherapy response was poorer in the high-risk group than in the low-risk group. Drug sensitivity analysis based on IC50 revealed that high-risk patients were potentially sensitive to various anti-tumour drugs, including bortezomib, cisplatin, docetaxel, etoposide and sunitinib. CONCLUSION: m6ARelncRNAs provide novel tools that can be used to predict overall survival and examine the immune microenvironment of renal clear cell carcinoma.
PURPOSE: This study aimed to investigate whether N6-methyladenosine (m6A)-related long non-coding RNAs (m6ARelncRNAs) could provide novel tools to predict overall survival of renal clear cell carcinoma. METHODS: The transcriptomic data and clinical information of patients with renal clear cell carcinoma from The Cancer Genome Atlas (TCGA) were analysed. Distinct m6A modification patterns were systemically analysed via consensus clustering analysis. An m6ARelncRNA signature was constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) analysis and validated in the test cohort. Potential predictive accuracy of the signature was further assessed via Kaplan-Meier survival, univariate and multivariate Cox regression and subgroup analyses. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the role of m6ARelncRNAs in guiding immunotherapy for patients with renal carcinoma. RESULTS: An m6ARelncRNA signature based on only six lncRNAs was successfully constructed. The high-risk group derived from this signature had significantly poorer overall survival in both training and test cohorts (p < 0.001). Independent prognostic analysis further revealed that m6ARelncRNA risk (p < 0.01) was an independent risk factor for survival outcomes of renal carcinoma. TIDE algorithm revealed that immunotherapy response was poorer in the high-risk group than in the low-risk group. Drug sensitivity analysis based on IC50 revealed that high-risk patients were potentially sensitive to various anti-tumour drugs, including bortezomib, cisplatin, docetaxel, etoposide and sunitinib. CONCLUSION: m6ARelncRNAs provide novel tools that can be used to predict overall survival and examine the immune microenvironment of renal clear cell carcinoma.
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