Identification of HGD and GSTZ1 as Biomarkers Involved Metabolic Reprogramming in Kidney Renal Clear Cell Carcinoma.
Ji-Yan WangHongkai ChangMeng SuYaya QiaoHuanran SunYongshan ZhaoShuai ZhangChangliang ShanPublished in: International journal of molecular sciences (2022)
Kidney renal clear cell carcinoma (KIRC) with poor prognosis is the main histological subtype of renal cell carcinoma, accounting for more than 80% of patients. Most patients are diagnosed at an advanced stage due to being asymptomatic early on. Advanced KIRC has an extremely poor prognosis due to its inherent resistance to radiotherapy and chemotherapy. Therefore, a comprehensive understanding of the molecular mechanisms of KIRC and the development of effective early diagnostic and therapeutic strategies is urgently needed. In this study, we aimed to identify the prognosis-related biomarker and analyzed its relationship with tumor progression. Metabolic changes are an important feature of kidney cancer, where the reduction of fumarate allows us to target the tyrosine metabolic pathway. The homogentisate 1,2-dioxygenase (HGD) and glutathione S-transferase zeta 1 (GSTZ1) related with prognosis of KIRC was identified through bioinformatics analysis based on The Cancer Genome Atlas (TCGA) databases. Mechanistically, we found that decreased HGD and GSTZ1 promote aerobic glycolysis in KIRC, coordinate the balance of amino acid metabolism and energy metabolism in tumor cells, and ultimately activate the tumor cell cycle and tumor progression. In summary, we identified the tyrosine metabolizing enzymes HGD and GSTZ1 as biomarkers of KIRC, which will further the understanding of the tumor metabolism profile, provide novel strategies and theoretical support for diagnosing and treating KIRC and as referential for future clinical research.
Keyphrases
- poor prognosis
- long non coding rna
- cell cycle
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- bioinformatics analysis
- cell proliferation
- amino acid
- renal cell carcinoma
- prognostic factors
- papillary thyroid
- locally advanced
- early stage
- machine learning
- gene expression
- squamous cell carcinoma
- dna methylation
- squamous cell
- genome wide
- high intensity
- single cell
- chemotherapy induced