Purpose: This study aimed to identify the potential prognostic role of HK3 and provide clues about glycolysis and the microenvironmental characteristics of ccRCC. Methods: Based on the Cancer Genome Atlas (TCGA, n = 533) and Gene expression omnibus (GEO) (n = 127) databases, real-world (n = 377) ccRCC cohorts, and approximately 15,000 cancer samples, the prognostic value and immune implications of HK3 were identified. The functional effects of HK3 in ccRCC were analyzed in silico and in vitro . Results: The large-scale findings suggested a significantly higher HK3 expression in ccRCC tissues and the predictive efficacy of HK3 for tumor progression and a poor prognosis. Next, the subgroup survival and Cox regression analyses showed that HK3 serves as a promising and independent predictive marker for the prognosis and survival of patients with ccRCC from bioinformatic databases and real-world cohorts. Subsequently, we found that HK3 could be used to modulate glycolysis and the malignant behaviors of ccRCC cells. The comprehensive results suggested that HK3 is highly correlated with the abundance of immune cells, and specifically stimulates the infiltration of monocytes/macrophages presenting surface markers, regulates the immune checkpoint molecules PD-1 and CTLA-4 of exhaustive T cells, restrains the immune escape of tumor cells, and prompts the immune-rejection microenvironment of ccRCC. Conclusion: In conclusion, the large-scale data first revealed that HK3 could affect glycolysis, promote malignant biologic processes, and predict the aggressive progression of ccRCC. HK3 may stimulate the abundance of infiltrating monocytes/macrophages presenting surface markers and regulate the key molecular subgroups of immune checkpoint molecules of exhaustive T cells, thus inducing the microenvironmental characteristics of active anti-tumor immune responses.
BackgroundProstate cancer is characterized by aberrant lipid metabolism, including elevated fatty acid oxidation. Carnitine palmitoyltransferase 1B (CPT1B) catalyzes the rate‐limiting step of fatty acid oxidation. This study aimed to determine if CPT1B has a critical role in prostate cancer progression and to identify its regulatory mechanism.MethodsCPT1B expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases was compared with patient survival data. A tissue microarray was constructed with 60 samples of prostate cancer and immunohistochemically stained for CPT1B. Castration‐resistant prostate cancer (CRPC) cell lines 22RV1 and C4‐2 in which CPT1B expression had been stably knocked down were established; and cell proliferation, cell cycle distribution, and invasion were investigated by Cell Counting Kit‐8 (CCK‐8) and colony formation assays, flow cytometry, and Transwell assays, respectively. To examine the impact of androgen receptor (AR) inhibition on CPT1B expression, JASPAR CORE was searched to identify AR‐binding sites in CPT1B. Dual luciferase and ChIP assays were performed to confirm CPT1B activity and AR binding, respectively. Differentially expressed genes (DEGs) in prostate cancer underwent gene set enrichment analysis (GSEA). Enzalutamide‐resistant C4‐2 cells were generated and the mechanism of enzalutamide resistance and downstream signaling pathway changes of CPT1B to C4‐2 was explored through CCK‐8 test.ResultsCPT1B expression was upregulated in human prostate cancer compared with normal prostate tissue and was associated with poor disease‐free survival and overall survival. Silencing of CPT1B resulted in downregulated cell proliferation, reduced S‐phase distribution, and lower invasive ability, whereas the opposite was observed in CRPC cells overexpressing CPTB1. DEGS in prostate cancer were correlated with G‐protein–coupled receptor signaling, molecular transducer activity, and calcium ion binding. AR may regulate CPT1B expression and activity via specific binding sites, as confirmed by dual luciferase and ChIP assays. The CCK‐8 experiment demonstrated that CPT1B overexpression in C4‐2 cells did not significantly increase the ability of enzalutamide resistance. However, overexpression of CPT1B in C4‐2R cells significantly increased the enzalutamide resistance. Upregulation of CPT1B expression increased AKT expression and phosphorylation.ConclusionsCPT1B is upregulated in prostate cancer and is correlated with poor prognosis, indicating its potential as a biomarker. AR inhibits the transcription of CPT1B. In the CRPC cell line, overexpression of CPT1B alone cannot promote enzalutamide resistance, but in the drug‐resistant line C4‐2R, overexpression of CPT1B can promote the resistance of C4‐2R to enzalutamide.
Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post‐operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20‐mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA ( P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts ( P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC , a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis ( P < 0.0001, HR = 0.316) and aggressive progression ( P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check‐point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large‐scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.
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