Development of genomic instability-associated long non-coding RNA signature: A prognostic risk model of clear cell renal cell carcinoma

Dongfang Jiang; Tiange Wu; Naipeng Shi; Yong Shan; Jinfeng Wang; Hua Jiang; Yuqing Wu; Mengxue Wang; Jian Li; Hui Liu; Ming Chen

doi:10.3389/fonc.2022.1019011

Development of genomic instability-associated long non-coding RNA signature: A prognostic risk model of clear cell renal cell carcinoma

Front Oncol. 2022 Oct 19:12:1019011. doi: 10.3389/fonc.2022.1019011. eCollection 2022.

Authors

Dongfang Jiang¹, Tiange Wu^{2

3}, Naipeng Shi^{2

3}, Yong Shan⁴, Jinfeng Wang⁵, Hua Jiang^{2

3}, Yuqing Wu^{2

3}, Mengxue Wang², Jian Li⁶, Hui Liu⁷, Ming Chen³

Affiliations

¹ Department of Urology, Danyang People's Hospital, Danyang, China.
² Department of Clinical Medicine, Medical School of Southeast University, Nanjing, China.
³ Department of Urology, Zhongda Hospital Affiliated to Southeast University, Nanjing, China.
⁴ Department of Urology, The Second People's Hospital of Taizhou, Taizhou, China.
⁵ Department of Urology, Yancheng Third People's Hospital, Yancheng, China.
⁶ Department of Urology, Jinhu County People's Hospital, Huaian, China.
⁷ Department of Urology, Binhai County People's Hospital, Yancheng, China.

Abstract

Purpose: Renal clear cell carcinoma (ccRCC) is the most lethal of all pathological subtypes of renal cell carcinoma (RCC). Genomic instability was recently reported to be related to the occurrence and development of kidney cancer. The biological roles of long non-coding RNAs (lncRNAs) in tumorigenesis have been increasingly valued, and various lncRNAs were found to be oncogenes or cancer suppressors. Herein, we identified a novel genomic instability-associated lncRNA (GILncs) model for ccRCC patients to predict the overall survival (OS).

Methods: The Cancer Genome Atlas (TCGA) database was utilized to obtain full transcriptome data, somatic mutation profiles, and clinical characteristics. The differentially expressed lncRNAs between the genome-unstable-like group (GU) and the genome-stable-like group (GS) were defined as GILncs, with |logFC| > 1 and an adjusted p-value< 0.05 for a false discovery rate. All samples were allocated into GU-like or GS-like types based on the expression of GILncs observed using hierarchical cluster analyses. A genomic instability-associated lncRNA signature (GILncSig) was constructed using parameters of the included lncRNAs. Quantitative real-time PCR analysis was used to detect the in vitro expression of the included lncRNAs. Validation of the risk model was performed by the log-rank test, time-dependent receiver operating characteristic (ROC) curves analysis, and multivariate Cox regression analysis.

Results: Forty-six lncRNAs were identified as GILncs. LINC00460, AL139351.1, and AC156455.1 were employed for GILncSig calculation based on the results of Cox analysis. GILncSig was confirmed as an independent predictor for OS of ccRCC patients. Additionally, it presented a higher efficiency and accuracy than other RCC prognostic models reported before.

Conclusion: GILncSig score was qualified as a critical indicator, independent of other clinical factors, for prognostic prediction of ccRCC patients.

Keywords: TCGA; bioinformatics; cell renal cell carcinoma; long non-coding RNA; prognosis.