Metabolic genes in cancer: their roles in tumor progression and clinical implications

Abstract

Re-programming of metabolic pathways is a hallmark of physiological changes in cancer cells. The expression of certain genes that directly control the rate of key metabolic pathways including glycolysis, lipogenesis and nucleotide synthesis are drastically altered at different stages of tumor progression. These alterations are generally considered as an adaptation of tumor cells; however, they also contribute to the progression of tumor cells to become more aggressive phenotypes. This review summarizes the recent information about the mechanistic link of these genes to oncogenesis and their potential utility as diagnostic markers as well as for therapeutic targets. We particularly focus on three groups of genes; GLUT1, G6PD, TKTL1 and PGI/AMF in glycolytic pathway, ACLY, ACC1 and FAS in lipogenesis and RRM2, p53R2 and TYMS for nucleotide synthesis. All these genes are highly up-regulated in a variety of tumor cells in cancer patients, and they play active roles in tumor progression rather than expressing merely as a consequence of phenotypic change of the cancer cells. Molecular dissection of their orchestrated networks and understanding the exact mechanism of their expression will provide a window of opportunity to target these genes for specific cancer therapy. We also reviewed existing database of gene microarray to validate the utility of these genes for cancer diagnosis.

Fig. 1. Metabolic genes in cancer

GLUT1; glucose transporter 1, G6PD; Glucose-6-phosphate dehydrogenase, TKTL1; transketolase-like-1, RRM2; ribonucleotide reductase subunit M2, p53R2; p53-inducible ribonucleotide reductase small subunit 2 homolog, TYMS; thymidylate synthase, FH; fumarate hydratase, SDH; succinate dehydrogenase, IDH; isocitrate dehydrogenase, ACLY; ATP citrate lyase, ACC; acetyl-CoA carboxylase, and FAS; fatty acid synthase

Fig. 2. The expression profile of metabolic genes in clinical samples

The expressions of nine metabolic genes in four different types of cancers (breast, prostate, lung and colon) were examined using the GEO microarray database, and identity of each cohort was shown by GEO ID number. A closed box indicates significantly positive expression (p<0.05), and the number of normal and tumor samples in each cohort was also shown in the right column. N/A; Not Available.

Fig. 3. Kaplan-Meier analysis of metabolic genes for breast cancer patients

Microarray data of 663 breast cancer patients from four independent cohorts were normalized and examined by meta-analysis for PGI, ACLY, RRM2 and TYMS. P value was calculated by log-rank test.