A Novel Prognostic Model Based on Autophagy-Related Long Non-Coding RNAs for Clear Cell Renal Cell Carcinoma
Authors:
Open Access
- 3 August 2021
- journal article
- research article
- Published by Frontiers Media SA in Frontiers in Oncology
- Vol. 11, 711736
Abstract
Background: Renal cell carcinoma (RCC) is one of the most common malignant tumors of the urinary system, of which the clear cell renal cell carcinoma (ccRCC) accounts for the most subtypes. The increasing discoveries of abundant autophagy-related long non-coding RNAs (ARLNRs) lead to a resurgent interest in evaluating their potential on prognosis prediction. Based on a large number of ccRCC gene samples from TCGA and clinics, ARLNRs analysis will provide a novel perspective into this field. Methods: We calculated the autophagy scores of each sample according to the expression levels of autophagy-related genes (ARGs) and screened the survival-related ARLNRs (sARLNRs) of ccRCC patients by Cox regression analysis. The high-risk group and the low-risk group were distinguished by the median score of the autophagy-related risk score (ARRS) model. The functional annotations were detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA). The expression levels of two kinds of sARLNRs in the renal tumor and adjacent normal tissues and cell lines were verified. Results: There were 146 ARLNRs selected by Pearson analysis. A total of 30 sARLNRs were remarkably correlated with the clinical outcomes of ccRCC patients. Eleven sARLNRs (AC002553.1, AC092611.2, AL360181.2, AP002807.1, AC098484.1, AL513218.1, AC008735.2, MHENCR, AC020907.4, AC011462.4, and AC008870.2) with the highest prognosis value were recruited to establish the ARRS in which the overall survival (OS) in the high-risk group was shorter than that in the low-risk group. ARRS could be treated as an independent prognostic factor and has significant correlations with OS. The distributions of autophagy genes were different between the high-risk group and the low-risk group. In addition, we also found that the expression levels of AC098484.1 in ccRCC cell lines and tumor tissues were lower than those in HK-2 and adjacent normal tissues, but AL513218.1 showed the inverse level. Furthermore, the AC098484.1 expressed decreasingly with the more advanced T-stages, but AL513218.1 gradually increased. Conclusion: Our study identified and verified some sARLNRs with clinical significances and revealed their potential values on predicting prognoses of ccRCC patients, which may provide a novel perspective for autophagy-related research and clinical decisions.Keywords
This publication has 29 references indexed in Scilit:
- Selective autophagy degrades nuclear pore complexesNature Cell Biology, 2020
- Methylomic Changes of Autophagy-Related Genes by Legionella Effector Lpg2936 in Infected MacrophagesFrontiers in Cell and Developmental Biology, 2020
- Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinomaJournal of Translational Medicine, 2019
- Integrated bioinformatics analysis revealing independent prognostic long non‑coding RNAs DNAH17‑AS1 and RP11‑400N13.2 and their potential oncogenic roles in colorectal cancerOncology Letters, 2019
- Updated European Association of Urology Guidelines on Renal Cell Carcinoma: Immune Checkpoint Inhibition Is the New Backbone in First-line Treatment of Metastatic Clear-cell Renal Cell CarcinomaEuropean Urology, 2019
- A 10-Long Non-Coding RNA-Based Expression Signature as a Potential Biomarker for Prognosis of Acute Myeloid LeukemiaMedical Science Monitor, 2019
- An autophagy‐related long non‐coding RNA signature for gliomaFEBS Open Bio, 2019
- WIPI1, BAG1, and PEX3 Autophagy‐Related Genes Are Relevant Melanoma MarkersOxidative Medicine and Cellular Longevity, 2018
- Autophagy‐related prognostic signature for breast cancerMolecular Carcinogenesis, 2015
- Non-coding landscapes of colorectal cancerWorld Journal of Gastroenterology, 2015