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Creating and Utilizing an Immune-Related Gene Prognosis Framework for Kidney Clear Cell Carcinoma

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DOI: 10.23977/medbm.2024.020113 | Downloads: 5 | Views: 122

Author(s)

Jiahui Luo 1, Qingbo Zhou 2

Affiliation(s)

1 The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
2 Department of Internal Medicine, Shaoxing Yuecheng People's Hospital, Shaoxing, China

Corresponding Author

Jiahui Luo

ABSTRACT

In this study, we initially classified renal cell carcinoma (ccRCC) samples into three distinct clusters based on immune expression patterns, utilizing an analysis of immunomodulatory genes. Through comprehensive examination of the differential genes across these clusters, a prognostic risk assessment framework was developed, aimed at determining risk levels to assist in prognostic evaluation and targeted therapy for ccRCC patients. Employing a consensus clustering method, 435 shared differential genes were pinpointed, predominantly associated with a range of immunomodulation pathways, through examining the immunomodulatory gene expressions in TCGA-KIRC patient samples. Furthermore, a univariate COX regression analysis allowed for the identification of 152 genes with significant prognostic associations, from which 11 pivotal genes were selected for the model through LASSO regression analysis. Utilizing these identified genes, a new prognostic risk assessment tool was crafted, and its predictive efficiency was confirmed via analysis of ROC curves. This newly developed prognostic tool, focusing on immunomodulatory genes, underwent thorough validation against external datasets, thereby enhancing the precision of clinical prognosis evaluations for ccRCC patients. 

KEYWORDS

Immunomodulatory Genes, Renal clear cell carcinoma, Prognostic model, Consensus clustering, Prognostic model

CITE THIS PAPER

Jiahui Luo, Qingbo Zhou, Creating and Utilizing an Immune-Related Gene Prognosis Framework for Kidney Clear Cell Carcinoma. MEDS Basic Medicine (2024) Vol. 2: 102-108. DOI: http://dx.doi.org/10.23977/medbm.2024.020113.

REFERENCES

[1] Melo, A.A.M., Gallegos, J.A.O., and Merchan, J.R. (2023). Abstract C121: Epidemiological characteristics and patterns of recurrence of renal cell carcinoma in Hispanics: A single US center cohort study. Cancer Epidemiology, Biomarkers & Prevention, 32, C121-C121. 10.1158/1538-7755.Disp22-c121.
[2] Schiavoni, V., Campagna, R., Pozzi, V., Cecati, M., Milanese, G., Sartini, D., Salvolini, E., Galosi, A.B., and Emanuelli, M. (2023). Recent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies. Cancers (Basel), 15. 10.3390/cancers15123207.
[3] Lebacle, C., Pooli, A., Bessede, T., Irani, J., Pantuck, A.J., and Drakaki, A. (2019). Epidemiology, biology and treatment of sarcomatoid RCC: current state of the art. World J Urol, 37, 115-123. 10.1007/s00345-018-2355-y.
[4] Liu, F., Davaro, F., Wong, R., Siddiqui, S., and Hamilton, Z. (2022). Young age is associated with decreased recurrence for renal cell carcinoma. Can J Urol, 29, 11142-11149.
[5] Correa, A.F., Jegede, O., Haas, N.B., Flaherty, K.T., Pins, M.R., Messing, E.M., Manola, J., Wood, C.G., Kane, C.J., Jewett, M.A.S., et al. (2019). Predicting Renal Cancer Recurrence: Defining Limitations of Existing Prognostic Models with Prospective Trial-Based Validation. J Clin Oncol, 37, 2062-2071. 10.1200/jco.19.00107.
[6] Choiniere, J., Wu, J., and Wang, L. (2017). Pyruvate Dehydrogenase Kinase 4 Deficiency Results in Expedited Cellular Proliferation through E2F1-Mediated Increase of Cyclins. Mol Pharmacol, 91, 189-196. 10.1124/mol. 116. 106757.
[7] Jiang, B., Chen, W., Qin, H., Diao, W., Li, B., Cao, W., Zhang, Z., Qi, W., Gao, J., Chen, M., et al. (2019). TOX3 inhibits cancer cell migration and invasion via transcriptional regulation of SNAI1 and SNAI2 in clear cell renal cell carcinoma. Cancer Lett, 449, 76-86. 10.1016/j.canlet.2019.02.020.
[8] Toledano, S., Nir-Zvi, I., Engelman, R., Kessler, O., and Neufeld, G. (2019). Class-3 Semaphorins and Their Receptors: Potent Multifunctional Modulators of Tumor Progression. Int J Mol Sci, 20. 10.3390/ijms20030556.
[9] Xiang, Y., Zhou, S., Hao, J., Zhong, C., Ma, Q., Sun, Z., and Wei, C. (2020). Development and validation of a prognostic model for kidney renal clear cell carcinoma based on RNA binding protein expression. Aging (Albany NY), 12, 25356-25372. 10.18632/aging.104137.
[10] Zhang, Y., Tang, M., Guo, Q., Xu, H., Yang, Z., and Li, D. (2022). The value of erlotinib related target molecules in kidney renal cell carcinoma via bioinformatics analysis. Gene, 816, 146173. 10.1016/j.gene.2021.146173.
[11] Li, M.K., Liu, L.X., Zhang, W.Y., Zhan, H.L., Chen, R.P., Feng, J.L., and Wu, L.F. (2020). Long non‑coding RNA MEG3 suppresses epithelial‑to‑mesenchymal transition by inhibiting the PSAT1‑dependent GSK‑3β/Snail signaling pathway in esophageal squamous cell carcinoma. Oncol Rep, 44, 2130-2142. 10.3892/or.2020.7754.

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