Analysis and interpretation of transcriptomic data obtained from extended Warburg effect genes in patients with clear cell renal cell carcinoma

Abstract

BackgroundMany cancers adopt a metabolism that is characterized by the well-known Warburg effect (aerobic glycolysis). Recently, numerous attempts have been made to treat cancer by targeting one or more gene products involved in this pathway without notable success. This work outlines a transcriptomic approach to identify genes that are highly perturbed in clear cell renal cell carcinoma (CCRCC).MethodsWe developed a model of the extended Warburg effect and outlined the model using Cytoscape. Following this, gene expression fold changes (FCs) for tumor and adjacent normal tissue from patients with CCRCC (GSE6344) were mapped on to the network. Gene expression values with FCs of greater than two were considered as potential targets for treatment of CCRCC.ResultsThe Cytoscape network includes glycolysis, gluconeogenesis, the pentose phosphate pathway (PPP), the TCA cycle, the serine/glycine pathway, and partial glutaminolysis and fatty acid synthesis pathways. Gene expression FCs for nine of the 10 CCRCC patients in the GSE6344 data set were consistent with a shift to aerobic glycolysis. Genes involved in glycolysis and the synthesis and transport of lactate were over-expressed, as was the gene that codes for the kinase that inhibits the conversion of pyruvate to acetyl-CoA. Interestingly, genes that code for unique proteins involved in gluconeogenesis were strongly under-expressed as was also the case for the serine/glycine pathway. These latter two results suggest that the role attributed to the M2 isoform of pyruvate kinase (PKM2), frequently the principal isoform of PK present in cancer: i.e. causing a buildup of glucose metabolites that are shunted into branch pathways for synthesis of key biomolecules, may not be operative in CCRCC. The fact that there was no increase in the expression FC of any gene in the PPP is consistent with this hypothesis. Literature protein data generally support the transcriptomic findings.ConclusionsA number of key genes have been identified that could serve as valid targets for anti-cancer pharmaceutical agents. Genes that are highly over-expressed include ENO2, HK2, PFKP, SLC2A3, PDK1, and SLC16A1. Genes that are highly under-expressed include ALDOB, PKLR, PFKFB2, G6PC, PCK1, FBP1, PC, and SUCLG1.

Metabolic Heterogeneity of Cancer Cells: An Interplay between HIF-1, GLUTs, and AMPK

“…Indeed, analysis and interpretation of transcriptomic data with the use of Cytoscape network showed highly over-expressed glycolytic genes including HK2, PFKP, ENO2, SLC2A3, SLC16A1, and PDK1 in patients with clear cell renal carcinoma [102]. However, according to this study, some other glycolytic enzymes such as ALDOB, PKLR, PFKFB2, G6PC, PCK1, FBP1, and SUCLG1 were highly down-regulated.…”

Downregulation of ALDOB is associated with poor prognosis of patients with gastric cancer

“… 12 In previous studies, a remarkable decrease in ALDOB was detected in GC, HCC, and clear cell renal cell carcinoma. 11 , 32 , 33 Peng et al identified that the downregulation of ALDOB positively correlated with aggressive features of tumors, such as poor differentiation, a higher grade of TNM stage, earlier tumor recurrence, and shorter 5-year survival. 17 Another study confirmed that lower ALDOB expression in patients was correlated with poor prognosis, and revealed the possible mechanism of ALDOB: ALDOB inhibited HCC metastasis by elevating the expression level of TET1 , a gene acting as a tumor suppressor with the function of promoting DNA demethylation.…”

Targeting cancer cell metabolism in pancreatic adenocarcinoma

“…The glycolytic switch is an early phenomenon characterized by increased expression of lactate dehydrogenase (LDH, that converts pyruvate into lactate) and inactivation of pyruvate dehydrogenase (PDH, that converts pyruvate into acetyl-CoA for the TCA cycle) [ 40 – 46 ]. The glycolytic switch is thought to be driven by the hypoxic tumor microenvironment through HIF-1α activation, aberrant signaling due to oncogene activation ( e.g ., Ras, PI3K/mTOR, c-Myc), tumor suppressor gene inactivation ( e.g ., p53), or by mutations in the OXPHOS pathway [ 47 , 48 ].…”