Citation: | YANG Fan, WANG Nongyan, FANG Meng, ZHANG Yingjiao, HU Haiyan, FANG Peng. Construction and Validation of A Prognostic Model of Lung Adenocarcinoma Based on m5C Modification-Related Genes[J]. Cancer Research on Prevention and Treatment, 2025, 52(3): 208-216. DOI: 10.3971/j.issn.1000-8578.2025.24.0992 |
To construct a prognostic model of lung adenocarcinoma (LUAD) based on m5C modification-related genes and to explore its clinical value.
Based on the LUAD data in TCGA, GSE30219, GSE31210, and GSE50081 cohorts, prognosis-related m5C modification-related genes were screened, and the prognostic model was constructed by using univariate Cox, Lasso, and multivariate Cox regression analyses. Kaplan-Meier curve, ROC curve, and Cox regression were used to observe the robustness and prognostic performance of the model. The correlation between the prognostic model and clinicopathologic features was further explored.
A prognostic model consisting of eight m5C modification-related genes, including CDK1, CDKN1A, NOP2, RRM2, TCL6, TLR8, TRDMT1, and YTHDF2, was constructed. Risk score was an independent risk factor for the prognosis of patients with LUAD, and it is combined with age, T stage, and N stage to constitute a nomogram which can accurately predict the prognosis of patients. The infiltration of macrophages and CD4+/CD8+T cells was significantly reduced in high-risk patients. The risk score in LUAD tissues was significantly higher than that in normal tissues and was positively correlated with T stage and N stage. The risk score of smoking and EGFR wild-type patients was higher than that of non-smoking and EGFR-mutant patients.
The prognostic model constructed based on m5C modification-related genes has shown good accuracy and stability in predicting the prognosis of patients with LUAD, and it is closely related to clinical features, driver gene mutations, and immune infiltration, which can provide a potential basis for the treatment and prognostic assessment of LUAD.
Competing interests: The authors declare that they have no competing interests.
[1] |
Sung H, Ferlay J, Siegel R, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. doi: 10.3322/caac.21660
|
[2] |
国家卫生健康委办公厅. 原发性肺癌诊疗指南(2022年版)[J]. 协和医学杂志, 2022, 13(4): 549-570. [National Health Commission of the People’s Republic of China. Clinical Practice Guideline for Primary Lung Cancer (2022 Version)[J]. Xie He Yi Xue Za Zhi, 2022, 13(4): 549-570.]
National Health Commission of the People’s Republic of China. Clinical Practice Guideline for Primary Lung Cancer (2022 Version)[J]. Xie He Yi Xue Za Zhi, 2022, 13(4): 549-570.
|
[3] |
Pietro B, Filip S, Angana R, et al. MODOMICS: a database of RNA modification pathways. 2021 update[J]. Nucleic Acids Res, 2021, 50(D1): D231-D235.
|
[4] |
Song H, Zhang J, Liu B, et al. Biological roles of RNA m5C modification and its implications in Cancer immunotherapy[J]. Biomark Res, 2022, 10(1): 15. doi: 10.1186/s40364-022-00362-8
|
[5] |
Guo G, Wang H, Shi X, et al. Disease Activity-Associated Alteration of mRNA m5C Methylation in CD4+T Cells of Systemic Lupus Erythematosus[J]. Front Cell Dev Biol, 2020, 8: 430. doi: 10.3389/fcell.2020.00430
|
[6] |
Chen X, Li A, Sun BF, et al. 5-methylcytosine promotes pathogenesis of bladder cancer through stabilizing mRNAs[J]. Nat Cell Biol, 2019, 21(8): 978-990. doi: 10.1038/s41556-019-0361-y
|
[7] |
陈小梅, 王安奇, 杨积祯, 等. m1A/m5C/m6A/m7G调控基因预测胃癌预后及免疫关联性[J]. 实用医学杂志, 2024, 40(9): 1230-1237. [Chen XM, Wang AQ, Yang JZ, et al. Prognosis and immune correlation analysis of m1A/m5C/m6A/m7G regulated genes in gastric cancer[J]. Shi Yong Yi Xue Za Zhi, 2024, 40(9): 1230-1237.]
Chen XM, Wang AQ, Yang JZ, et al. Prognosis and immune correlation analysis of m1A/m5C/m6A/m7G regulated genes in gastric cancer[J]. Shi Yong Yi Xue Za Zhi, 2024, 40(9): 1230-1237.
|
[8] |
胡旭钢, 胡艳, 胡海燕, 等. 基于线粒体代谢相关基因构建和验证肺腺癌预后模型[J]. 浙江医学, 2024, 46(17): 1804-1811, 后插1. [Hu XG, Hu Y, Hu HY, et al. Construction and validation of a prognostic model for predicting lung adenocarcinoma based on mitochondrial metabolism related genes[J]. Zhejiang Yi Xue, 2024, 46(17): 1804-1811, insert 1.]
Hu XG, Hu Y, Hu HY, et al. Construction and validation of a prognostic model for predicting lung adenocarcinoma based on mitochondrial metabolism related genes[J]. Zhejiang Yi Xue, 2024, 46(17): 1804-1811, insert 1.
|
[9] |
李梦涵, 肖琼, 高鹏, 等. 基于TCGA数据库的消化道肿瘤LncRNA预后风险评分模型[J]. 肿瘤防治研究, 2022, 49(6): 606-611. [Li MH, Xiao Q, Gao P, et al. LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database[J]. Zhong Liu Fang Zhi Yan Jiu, 2022, 49(6): 606-611.]
Li MH, Xiao Q, Gao P, et al. LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database[J]. Zhong Liu Fang Zhi Yan Jiu, 2022, 49(6): 606-611.
|
[10] |
Chen X, Qin Z, Zhu X, et al. Identification and validation of telomerase related lncRNAs signature to predict prognosis and tumor immunotherapy response in bladder cancer[J]. Sci Rep, 2023, 13(1): 21816. doi: 10.1038/s41598-023-49167-1
|
[11] |
Xia C, Dong X, Li H, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants[J]. Chin Med J (Engl), 2022, 135(5): 584-590. doi: 10.1097/CM9.0000000000002108
|
[12] |
Wang Q, Bode AM, Zhang T. Targeting CDK1 in cancer: mechanisms and implications[J]. NPJ Precis Oncol, 2023, 7(1): 58. doi: 10.1038/s41698-023-00407-7
|
[13] |
Suski JM, Braun M, Strmiska V, et al. Targeting cell-cycle machinery in cancer[J]. Cancer Cell, 2021, 39(6): 759-778. doi: 10.1016/j.ccell.2021.03.010
|
[14] |
Manousakis E, Miralles CM, Esquerda MG, et al. CDKN1A/p21 in Breast Cancer: Part of the Problem, or Part of the Solution?[J]. Int J Mol Sci, 2023, 24(24): 17488. doi: 10.3390/ijms242417488
|
[15] |
Zuo Z, Zhou Z, Chang Y, et al. Ribonucleotide reductase M2 (RRM2): Regulation, function and targeting strategy in human cancer[J]. Genes Dis, 2022, 11(1): 218-233.
|
[16] |
Ke ZB, You Q, Sun JB, et al. A Novel Ferroptosis-Based Molecular Signature Associated with Biochemical Recurrence-Free Survival and Tumor Immune Microenvironment of Prostate Cancer[J]. Front Cell Dev Biol, 2022, 9: 774625. doi: 10.3389/fcell.2021.774625
|
[17] |
Tang B, Xu W, Wang Y, et al. Identification of critical ferroptosis regulators in lung adenocarcinoma that RRM2 facilitates tumor immune infiltration by inhibiting ferroptotic death[J]. Clin Immunol, 2021, 232: 108872. doi: 10.1016/j.clim.2021.108872
|
[18] |
Cuadros M, Andrades Á, Coira IF, et al. Expression of the long non-coding RNA TCL6 is associated with clinical outcome in pediatric B-cell acute lymphoblastic leukemia[J]. Blood Cancer J, 2019, 9(12): 93. doi: 10.1038/s41408-019-0258-9
|
[19] |
Ohto U, Tanji H, Shimizu T. Structure and function of toll-like receptor 8[J]. Microbes Infect, 2014, 16(4): 273-282. doi: 10.1016/j.micinf.2014.01.007
|
[20] |
Zhang R, Gan W, Zong J, et al. Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer[J]. Front Immunol, 2023, 14: 1054700. doi: 10.3389/fimmu.2023.1054700
|
[21] |
逯涛峰, 杨健, 赵调红, 等. YTHDF2与恶性肿瘤关系的研究进展[J]. 江苏医药, 2022, 48(8): 851-854. [Lu TF, Yang J, Zhao DH, et al. Advances in the study of the relationship between YTHDF2 and malignant tumors[J]. Jiangsu Yi Yao, 2022, 48(8): 851-854.]
Lu TF, Yang J, Zhao DH, et al. Advances in the study of the relationship between YTHDF2 and malignant tumors[J]. Jiangsu Yi Yao, 2022, 48(8): 851-854.
|