Machine learning-based analysis identifies glucose metabolism-related genes ADPGK as potential diagnostic biomarkers for clear cell renal cell carcinoma

Tie LiWang ShijinGuandu LiXiaochen Qi^*Guangzhen Wu^*Xiangyu Che^*

• Department of Urology, First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning Province, China

Abstract Introduction: Clear cell renal cell carcinoma, with its high morbidity and mortality, is one of the more difficult diseases in the world and still lacks an effective therapeutic target. The primary way they break down glucose is through aerobic glycolysis, which leads to energy acquisition and synthesis of the material base required for cell growth. Although targeting glucose metabolism has driven the development of a variety of tumour therapies, the specific regulatory mechanisms remain unclear. Therefore, based on machine learning analysis algorithms, we analysed the correlation between glycometabolic pathways and ccRCC in the REACTOME database and verified the impact of the key gene ADPGK on the prognosis of ccRCC. Methods: We utilised a total of 89 gene collections of glucose metabolism pathways from the REACTOME (https://reactome.org/) database as the data base for our study. To uncover potential therapeutic target genes, we adopt three machine learning algorithms (LASSO, RF, and Boruta). We reassigned the 7 screened genes based on gene expression differences between cancer and paracancerous tissues, and applied an unsupervised consensus clustering algorithm to establish a typology based on the expression of glucose metabolism-related genes (ADPGK). We then validated the link between ADPGK and cancer cell invasion and metastasis by in vitro experiments on ccRCC cell lines. Results: We identified ADPGK as a key gene for the glucose metabolism pathway and suggested that it may promote invasion and metastasis of ccRCC. In addition, based on the results of immune infiltration, ADPGK was observed to significantly affect the immune response in ccRCC. Our results suggest that the implementation of therapeutic strategies based on key genes of glucose metabolism may bring new hope for ccRCC patients. Discussion: Our results suggest that targeting the glucose metabolism pathway can kill ccRCC cells. ADPGK, a gene related to glucose metabolism, may be an important biomarker for the diagnosis and characterization of ccRCC. However, whether ADPGK affects glycolysis in ccRCC, and the mechanism by which glycolysis is regulated is not clear. This is the direction of further research in the future.