Large‐scale transcriptome profiles reveal robust 20‐signatures metabolic prediction models and novel role of G6PC in clear cell renal cell carcinoma

Abstract

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.

Identification of Biomarkers for Prognosis and Immunotherapy in Clear Cell Renal Cell Carcinoma

“…After construction of protein-protein interaction network of DEGs, we used CytoHubba to identify the hub genes with degree > 10 and further screened the hub genes to obtain candidate genes related with the prognoses of ccRCC by synthesizing the results of UALCAN, GEPIA and HPA. The results showed that TIMP1, PCK1, HMGCS2, G6PC, FBP1, ACAA1, HADH, HAO2, TGFBI, RRM2 and SUCLG1 are of prognostic signi cance in ccRCC patients, which were consistent with results of previous researches [33][34][35][36][37]. Whereafter, we veri ed the mRNA and protein expression of these genes in different ways, thus obtained three target genes, namely PCK1, HMGCS2 and RRM2.…”

Hexokinase 3 dysfunction promotes tumorigenesis and immune escape by upregulating monocyte/macrophage infiltration into the clear cell renal cell carcinoma microenvironment

“…Instead, aerobic glycolysis provides up to 60% of ATP, which is identified as an important factor that leads to cancer growth promotion and metastasis 9 . Increasing evidence has shown that oncogene activation, tumor suppressor gene inactivation, and TME changes affect the abnormal expression of the glucose metabolism enzymes regulating the Warburg effect 14 . This remodeling of energy metabolism provides tumor cells with growth and proliferation advantages, helps tumor cells escape, and creates a microenvironment conducive to metastasis 15 , 16 .…”

Traditional Chinese medicine Bu-Shen-Jian-Pi-Fang attenuates glycolysis and immune escape in clear cell renal cell carcinoma: results based on network pharmacology

“…Importantly, this suggested that BSJPF could inhibit tumor proliferation by enhancing GLUT1-and LDHA-related glycolysis. The HIF-1 signaling pathway is regulated by Von Hippel-Lindau tumor suppressor protein and induces glucose metabolism, cell proliferation and angiogenesis, thereby playing a significant role in ccRCC progression [34][35][36]. This remodeling of energy metabolism provides tumor cells with growth and proliferation advantages, helps tumor cells escape apoptosis and creates a tumor microenvironment that is more conducive to metastasis [37].…”