Prognostic Value and Immunological Function of Cuproptosis-related Genes in Lung Adenocarcinoma

Overview

Journal Heliyon

Specialty Social Sciences

Date 2024 May 2

PMID 38694039

Authors

Liming Zhang

Shaoqiang Wang

Lina Wang

Affiliations

Soon will be listed here.

Abstract

Background: Lung cancer is one of the malignant tumors with the highest morbidity and fatality rates worldwide. The overall survival (OS) of lung adenocarcinoma (LUAD) is poor. Cuproptosis is a copper-triggered modality of mitochondrial cell death, however, its contribution to the emergence of lung cancer is unknown. The clinical implication and immunological function of cuproptosis-related genes (CRGs) in LUAD has yet to be established.

Methods: TCGA, HPA, GEPIA, Kaplan-Meier, TIMER and CancerSEA database were used to explore the prognostic value and biological function of CRGs in LUAD.

Results: CRGs are primarily involved in copper ion transport, the citrate cycle (TCA cycle) and central carbon metabolism in LUAD. The mRNA expression of COA6, UBE2D1, DLAT, SLC25A3, and DBH was significantly increased. The expression of COA6, DLAT, SLC25A3, DBH, and LOXL2 were all strongly associated with the clinicopathological stages in LUAD. Moreover, high expression of COA6, UBE2D1, DLAT, SLC25A3 and LOXL2 was related to poor OS. The expression of SLC25A3 and LOXL2 showed different association with immune cell infiltration. The single cell sequencing demonstrated that CRGs play important roles in the regulation of DNA damage response, inflammation and metastasis in LUAD.

Conclusions: In summary, this study comprehensively uncovered that CRGs could be identified as potential prognostic and immunological biomarkers in LUAD. Our current research could provide a solid theoretical basis for LUAD survival research and clinical decision-making.

References

Jiang P, Du W, Mancuso A, Wellen K, Yang X . Reciprocal regulation of p53 and malic enzymes modulates metabolism and senescence. Nature. 2013; 493(7434):689-93. PMC: 3561500. DOI: 10.1038/nature11776. View

Li L, Yao W, Yan S, Dong X, Lv Z, Jing Q . Pan-Cancer Analysis of Prognostic and Immune Infiltrates for CXCs. Cancers (Basel). 2021; 13(16). PMC: 8392715. DOI: 10.3390/cancers13164153. View

Zhang C, Leighl N, Wu Y, Zhong W . Emerging therapies for non-small cell lung cancer. J Hematol Oncol. 2019; 12(1):45. PMC: 6482588. DOI: 10.1186/s13045-019-0731-8. View

Xie H, He Y, Wu Y, Lu Q . Silencing of UBE2D1 inhibited cell migration in gastric cancer, decreasing ubiquitination of SMAD4. Infect Agent Cancer. 2021; 16(1):63. PMC: 8574036. DOI: 10.1186/s13027-021-00402-2. View

Cattley S, Arthur J . BioManager: the use of a bioinformatics web application as a teaching tool in undergraduate bioinformatics training. Brief Bioinform. 2007; 8(6):457-65. DOI: 10.1093/bib/bbm039. View

Man S, Kanneganti T . Regulation of inflammasome activation. Immunol Rev. 2015; 265(1):6-21. PMC: 4400844. DOI: 10.1111/imr.12296. View

Lu X, Xin D, Du J, Zou Q, Wu Q, Zhang Y . Loss of LOXL2 Promotes Uterine Hypertrophy and Tumor Progression by Enhancing H3K36ac-Dependent Gene Expression. Cancer Res. 2022; 82(23):4400-4413. DOI: 10.1158/0008-5472.CAN-22-0848. View

He J, Ding H, Li H, Pan Z, Chen Q . Intra-Tumoral Expression of SLC7A11 Is Associated with Immune Microenvironment, Drug Resistance, and Prognosis in Cancers: A Pan-Cancer Analysis. Front Genet. 2021; 12:770857. PMC: 8687742. DOI: 10.3389/fgene.2021.770857. View

Dixon S, Lemberg K, Lamprecht M, Skouta R, Zaitsev E, Gleason C . Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell. 2012; 149(5):1060-72. PMC: 3367386. DOI: 10.1016/j.cell.2012.03.042. View

10.

Lanczky A, Gyorffy B . Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation. J Med Internet Res. 2021; 23(7):e27633. PMC: 8367126. DOI: 10.2196/27633. View

11.

Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z . GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017; 45(W1):W98-W102. PMC: 5570223. DOI: 10.1093/nar/gkx247. View

12.

Pavithra V, Sathisha T, Kasturi K, Mallika D, Amos S, Ragunatha S . Serum levels of metal ions in female patients with breast cancer. J Clin Diagn Res. 2015; 9(1):BC25-c27. PMC: 4347069. DOI: 10.7860/JCDR/2015/11627.5476. View

13.

Tsvetkov P, Detappe A, Cai K, Keys H, Brune Z, Ying W . Mitochondrial metabolism promotes adaptation to proteotoxic stress. Nat Chem Biol. 2019; 15(7):681-689. PMC: 8183600. DOI: 10.1038/s41589-019-0291-9. View

14.

Li T, Fan J, Wang B, Traugh N, Chen Q, Liu J . TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells. Cancer Res. 2017; 77(21):e108-e110. PMC: 6042652. DOI: 10.1158/0008-5472.CAN-17-0307. View

15.

Arbour K, Riely G . Systemic Therapy for Locally Advanced and Metastatic Non-Small Cell Lung Cancer: A Review. JAMA. 2019; 322(8):764-774. DOI: 10.1001/jama.2019.11058. View

16.

Mayakonda A, Lin D, Assenov Y, Plass C, Koeffler H . Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018; 28(11):1747-1756. PMC: 6211645. DOI: 10.1101/gr.239244.118. View

17.

Atakul T, Altinkaya S, Abas B, Yenisey C . Serum Copper and Zinc Levels in Patients with Endometrial Cancer. Biol Trace Elem Res. 2019; 195(1):46-54. DOI: 10.1007/s12011-019-01844-x. View

18.

Oliveri V . Selective Targeting of Cancer Cells by Copper Ionophores: An Overview. Front Mol Biosci. 2022; 9:841814. PMC: 8931543. DOI: 10.3389/fmolb.2022.841814. View

19.

Yu G, Wang L, Han Y, He Q . clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012; 16(5):284-7. PMC: 3339379. DOI: 10.1089/omi.2011.0118. View

20.

Yuan H, Yan M, Zhang G, Liu W, Deng C, Liao G . CancerSEA: a cancer single-cell state atlas. Nucleic Acids Res. 2018; 47(D1):D900-D908. PMC: 6324047. DOI: 10.1093/nar/gky939. View