Cuproptosis-related gene biomarkers to predict overall survival outcomes in cervical cancer

Background: Cervical carcinoma (CC) remains a prevailing gynecologic malignancy. Cuproptosis is a recently identified and extensively researched type of cellular death. However, the understanding of cuproptosis-associated genes in CC and their correlation with prognosis is still uncertain. Methods: We identified 6 genes related to cuproptosis that were differentially expressed between normal cervical tissue and CC from 18 cuproptosis-related genes. We obtained prognostic information, along with associated clinical information, in normal cervical tissue and CCs from TCGA (The Cancer Genome Atlas). Results: Six differentially expressed cuproptosis-associated genes were utilized to develop a prognostic pattern and categorize the overall CC patients in the TCGA cohort into low- or high-cohort groups. Gene Expression Omnibus (GEO) database data were employed to certify the model of prognosis. There was a significantly higher survival rate for CC patients in low-risk than in high-risk group (p = 0.001) for the TCGA cohort. Both univariate (p = 0.0012) and multivariate Cox regression analyses (p < 0.001) illustrated that the risk score was obviously linked to poor survival. The outside validation was carried out by data in GEO database. There also existed an exceedingly obvious distinction in the survival rate between the two groups (p = 0.0239). There were also evident differences between poor survival and risk score in univariate (p = 0.0242) as well as multivariate Cox regression analysis (p = 0.0279). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) were utilized. The results forecasted that extracellular matrix organization, signaling receptor activator activity, receptor ligand activity, neuroactive ligand-receptor interplay, and cytokine-cytokine receptor interplay were closely associated with CC cuproptosis. Conclusions: The risk prediction model based on genes related to cuproptosis could excellently predict CC prognosis. The prognostic model can offer a vital reference for future biomarkers and therapeutic targets for the sake of precise therapy of cervical carcinoma.

Cervical cancer; Cuproptosis; Risk model; Prognosis; Overall survival

[1] Arbyn M, Weiderpass E, Bruni L, de Sanjosé S, Saraiya M, Ferlay J, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. The Lancet Global Health. 2020; 8: e191–e203.

[2] Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA: A Cancer Journal for Clinicians. 2021; 71: 7–33.

[3] Jin J. HPV infection and cancer. JAMA. 2018; 319: 1058.

[4] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians. 2021; 71: 209–249.

[5] Bjurberg M, Beskow C, Kannisto P, Lindahl G. Cervical cancer is a clinical challenge. Läkartidningen. 2015; 112: DIUS. (In Swedish)

[6] Pimple SA, Mishra GA. Global strategies for cervical cancer prevention and screening. Minerva Ginecologica. 2019; 71: 313–320.

[7] Tsvetkov P, Coy S, Petrova B, Dreishpoon M, Verma A, Abdusamad M, et al. Copper induces cell death by targeting lipoylated TCA cycle proteins. Science. 2022; 375: 1254–1261.

[8] Ou R, Lu S, Wang L, Wang Y, Lv M, Li T, et al. Circular RNA circLMO1 suppresses cervical cancer growth and metastasis by triggering miR-4291/ACSL4-mediated ferroptosis. Frontiers in Oncology. 2022; 12: 858598.

[9] Ye Y, Dai Q, Qi H. A novel defined pyroptosis-related gene signature for predicting the prognosis of ovarian cancer. Cell Death Discovery. 2021; 7: 71.

[10] Song H, Li T, Sheng J, Li D, Liu X, Xiao H, et al. Necroptosis-related miRNA biomarkers for predicting overall survival outcomes for endometrial cancer. Frontiers in Genetics. 2022; 13: 828456.

[11] Dixon SJ, Lemberg KM, Lamprecht MR, Skouta R, Zaitsev EM, Gleason CE, et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell. 2012; 149: 1060–1072.

[12] Tsvetkov P, Detappe A, Cai K, Keys HR, Brune Z, Ying W, et al. Mitochondrial metabolism promotes adaptation to proteotoxic stress. Nature Chemical Biology. 2019; 15: 681–689.

[13] Wang Y, Zhang L, Zhou F. Cuproptosis: a new form of programmed cell death. Cellular & Molecular Immunology. 2022; 19: 867–868.

[14] Tang D, Chen X, Kroemer G. Cuproptosis: a copper-triggered modality of mitochondrial cell death. Cell Research. 2022; 32: 417–418.

[15] Jiang Y, Huo Z, Qi X, Zuo T, Wu Z. Copper-induced tumor cell death mechanisms and antitumor theragnostic applications of copper complexes. Nanomedicine. 2022; 17: 303–324.

[16] Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS: a Journal of Integrative Biology. 2012; 16: 284–287.

[17] Liang B, Li Y, Wang T. A three miRNAs signature predicts survival in cervical cancer using bioinformatics analysis. Scientific Reports. 2017; 7: 5624.

[18] Dai F, Chen G, Wang Y, Zhang L, Long Y, Yuan M, et al. Identification of candidate biomarkers correlated with the diagnosis and prognosis of cervical cancer via integrated bioinformatics analysis. OncoTargets and Therapy. 2019; 12: 4517–4532.

[19] Ma X, Liu J, Wang H, Jiang Y, Wan Y, Xia Y, et al. Identification of crucial aberrantly methylated and differentially expressed genes related to cervical cancer using an integrated bioinformatics analysis. Bioscience Reports. 2020; 40: BSR20194365.

[20] Liu X, Zhou L, Gao M, Dong S, Hu Y, Hu C. Signature of seven cuproptosis-related lncRNAs as a novel biomarker to predict prognosis and therapeutic response in cervical cancer. Frontiers in Genetics. 2022; 13: 989646.

[21] Kong X, Xiong Y, Xue M, He J, Lu Q, Chen M, et al. Identification of cuproptosis-related lncRNA for predicting prognosis and immunotherapeutic response in cervical cancer. Scientific Reports. 2023; 13: 10697.

[22] Wang Q, Xu Y. Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer. Frontiers in Pharmacology. 2022; 13: 1065701.

[23] Liu L, Zheng J, Xia H, Wu Q, Cai X, Ji L, et al. Construction and comprehensive analysis of a curoptosis-related lncRNA signature for predicting prognosis and immune response in cervical cancer. Frontiers in Genetics. 2023; 14: 1023613.

[24] Zhou J, Xu L, Zhou H, Wang J, Xing X. Prediction of prognosis and chemotherapeutic sensitivity based on cuproptosis-associated lncRNAs in cervical squamous cell carcinoma and endocervical adenocarcinoma. Genes. 2023; 14: 1381.

[25] Liu Y, Fan Y, Wang X, Huang Z, Shi K, Zhou B. Musashi-2 is a prognostic marker for the survival of patients with cervical cancer. Oncology Letters. 2018; 15: 5425–5432.

[26] Monk BJ, Kauderer JT, Moxley KM, Bonebrake AJ, Dewdney SB, Secord AA, et al. A phase II evaluation of elesclomol sodium and weekly paclitaxel in the treatment of recurrent or persistent platinum-resistant ovarian, fallopian tube or primary peritoneal cancer: an NRG oncology/gynecologic oncology group study. Gynecologic Oncology. 2018; 151: 422–427.

[27] O’Day SJ, Eggermont AM, Chiarion-Sileni V, Kefford R, Grob JJ, Mortier L, et al. Final results of phase III SYMMETRY study: randomized, double-blind trial of Elesclomol plus paclitaxel versus paclitaxel alone as treatment for chemotherapy-naive patients with advanced melanoma. Journal of Clinical Oncology. 2013; 31: 1211–1218.

[28] Adamus A, Müller P, Nissen B, Kasten A, Timm S, Bauwe H, et al. GCSH antisense regulation determines breast cancer cells’ viability. Scientific Reports. 2018; 8: 15399.

[29] Chen Y, Xu T, Xie F, Wang L, Liang Z, Li D, et al. Evaluating the biological functions of the prognostic genes identified by the pathology atlas in bladder cancer. Oncology Reports. 2021; 45: 191–201.

[30] Li H, Hardin H, Zaeem M, Huang W, Hu R, Lloyd RV. LncRNA expression and SDHB mutations in pheochromocytomas and paragangliomas. Annals of Diagnostic Pathology. 2021; 55: 151801.

[31] Buffet A, Burnichon N, Favier J, Gimenez-Roqueplo A. An overview of 20 years of genetic studies in pheochromocytoma and paraganglioma. Best Practice & Research Clinical Endocrinology & Metabolism. 2020; 34: 101416.

[32] Jochmanova I, Wolf KI, King KS, Nambuba J, Wesley R, Martucci V, et al. SDHB-related pheochromocytoma and paraganglioma penetrance and genotype-phenotype correlations. Journal of Cancer Research and Clinical Oncology. 2017; 143: 1421–1435.

[33] Jochmanova I, Abcede AMT, Guerrero RJS, Malong CLP, Wesley R, Huynh T, et al. Clinical characteristics and outcomes of SDHB-related pheochromocytoma and paraganglioma in children and adolescents. Journal of Cancer Research and Clinical Oncology. 2020; 146: 1051–1063.

[34] Liu S, Xiao Z, Ai F, Liu F, Chen X, Cao K, et al. miR-142-5p promotes development of colorectal cancer through targeting SDHB and facilitating generation of aerobic glycolysis. Biomedicine & Pharmacotherapy. 2017; 92: 1119–1127.

[35] Chung IC, Chen LC, Tsang NM, Chuang WY, Liao TC, Yuan SN, et al. Mitochondrial oxidative phosphorylation complex regulates NLRP3 inflammasome activation and predicts patient survival in nasopharyngeal carcinoma. Molecular & Cellular Proteomics. 2020; 19: 142–154.

[36] Wang H, Luo J, Tian W, Yan W, Ge S, Zhang Y, et al. γ-Tocotrienol inhibits oxidative phosphorylation and triggers apoptosis by inhibiting mitochondrial complex I subunit NDUFB8 and complex II subunit SDHB. Toxicology. 2019; 417: 42–53.

[37] Zhuang L, Zhang B, Liu X, Lin L, Wang L, Hong Z, et al. Exosomal miR-21-5p derived from cisplatin-resistant SKOV3 ovarian cancer cells promotes glycolysis and inhibits chemosensitivity of its progenitor SKOV3 cells by targeting PDHA1. Cell Biology International. 2021; 45: 2140–2149.

[38] Liu Z, Yu M, Fei B, Fang X, Ma T, Wang D. miR-21-5p targets PDHA1 to regulate glycolysis and cancer progression in gastric cancer. Oncology Reports. 2018; 40: 2955–2963.

[39] Roche ME, Lin Z, Whitaker-Menezes D, Zhan T, Szuhai K, Bovee JVMG, et al. Translocase of the outer mitochondrial membrane complex subunit 20 (TOMM20) facilitates cancer aggressiveness and therapeutic resistance in chondrosarcoma. Biochimica Et Biophysica Acta (BBA)—Molecular Basis of Disease. 2020; 1866: 165962.

[40] Yang X, Song D, Zhang J, Yang X, Feng H, Guo J. PRR34-AS1 sponges miR-498 to facilitate TOMM20 and ITGA6 mediated tumor progression in HCC. Experimental and Molecular Pathology. 2021; 120: 104620.