Construction of a cuproptosis-tricarboxylic acid cycle-associated lncRNA model to predict the prognosis of non-small cell lung cancer

Xiang Li; Yunlong Zhao; Shengjie Wei; Yuqing Dai; Chun Yi

doi:10.21037/tcr-24-660

Construction of a cuproptosis-tricarboxylic acid cycle-associated lncRNA model to predict the prognosis of non-small cell lung cancer

Transl Cancer Res. 2024 Dec 31;13(12):6807-6824. doi: 10.21037/tcr-24-660. Epub 2024 Dec 27.

Authors

Xiang Li¹, Yunlong Zhao¹, Shengjie Wei¹, Yuqing Dai¹, Chun Yi²

Affiliations

¹ Faculty of Medicine, Hunan University of Chinese Medicine, Changsha, China.
² Department of Pathology, Faculty of Medicine, Hunan University of Chinese Medicine, Changsha, China.

Abstract

Background: In cuproptosis, excess copper ions induce cell death via fatty acylation in the tricarboxylic acid (TCA) cycle. However, the effects of cuproptosis-TCA-related long non-coding RNAs (lncRNAs) on the clinical prognosis of non-small cell lung cancer (NSCLC) and the associated tumor microenvironment remain unclear. The purpose of this study is to use cuproptosis-TCA related lncRNAs to predict the prognosis of NSCLC.

Methods: Molecular signature databases and cuproptosis-related publications were made use of identifying cuproptosis-TCA-related genes. They were identified based on Pearson correlation analysis. The prognostic features associated with these lncRNAs were evaluated using the absolute contraction and selection operator and a receiver operating characteristic curve analysis. Additionally, downstream functional enrichment and immunoinfiltration were analyzed to examine the immunotherapeutic responses of patients with NSCLC.

Results: Eleven cuproptosis-TCA-associated lncRNAs were identified. A high-risk group was compared with a low-risk group based on risk scores, and the high-risk group had a significantly lower overall survival (OS). We established a prognostic risk profile, and based on these characteristics and clinical staging, a nomogram was constructed. An analysis of functional enrichment revealed the involvement of pathways associated with cellular and humoral immunity and fatty acylation. Risk scores differed significantly based on immune cells and pathways (antigen-presenting cell co-stimulation). Moreover, TP53, TTN, and MUC16 mutation status were strongly associated with risk scores, with patients identified as having a higher risk of NSCLC being more responsive to immunotherapy.

Conclusions: Eleven cuproptosis-TCA-associated lncRNAs can be used to predict the prognosis of NSCLC patients, thereby providing a new theoretical basis for immunotherapy.

Keywords: Cuproptosis long non-coding RNAs (cuproptosis lncRNAs); non-small cell lung cancer (NSCLC); prognostic risk score; tricarboxylic acid cycle (TCA cycle).