2. Academic Validation
  3. Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

  • Discov Oncol. 2024 May 26;15(1):187. doi: 10.1007/s12672-024-01023-y.
Rui Feng # 1 2 3,  Haolin Li # 1 2 3,  Tong Meng 1 2 3,  Mingtian Fei 1 2 3,  Cheng Yang 4 5 6
Affiliations

Affiliations

  • 1 Department of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.
  • 2 Institute of Urology, Anhui Medical University, Hefei, Anhui, China.
  • 3 Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, Anhui, China.
  • 4 Department of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China. yang_cheng@ahmu.edu.cn.
  • 5 Institute of Urology, Anhui Medical University, Hefei, Anhui, China. yang_cheng@ahmu.edu.cn.
  • 6 Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, Anhui, China. yang_cheng@ahmu.edu.cn.
  • # Contributed equally.
PMID: 38797784 DOI: 10.1007/s12672-024-01023-y
Abstract

Purpose: This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.

Methods: First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and Cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan-Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and Cuproptosis, and may promote ccRCC progression.

Results: We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.

Conclusion: Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.

Keywords

Clear cell renal cell carcinoma; Cuproptosis; Long non-coding RNA; M6A; Prognostic mode.

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