Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma.

Fengdan Ye,Michael W Deem,Dongya Jia,Mingyang Lu,Herbert Levine

doi:10.18632/oncotarget.24551

Abstract

Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer prognosis. Among patients with recurred tumors, we found the correlation of higher modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients’ survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.

Highlights

Hepatocellular carcinoma (HCC) is a primary malignancy of the liver, with average survival time between 6 to 20 months without any intervention [1]
Yu et al developed the AMPK and HIF1 signatures to quantify the activities of metabolism phenotypes in hepatocellular carcinoma (HCC) [20]
The analyses of modularity in the glycolysis, hybrid and oxidative phosphorylation (OXPHOS) metabolism phenotypes; stage I and stage II–IV tumor stages; and varying tumor metastatic potentials and recurrence status consistently showed that a higher modularity of the AMPK and HIF-1 downstream gene network corresponded to worse overall survival results of HCC patients

Summary

Introduction

Hepatocellular carcinoma (HCC) is a primary malignancy of the liver, with average survival time between 6 to 20 months without any intervention [1]. It is the third leading cause of cancer mortality worldwide [2]. Diagnosis of HCC is usually based on biomarkers, such as AFP (alphafetoprotein) and miR-21 [4]. HCC can result from a variety of risk factors, such as hepatitis B/C virus or alcoholic liver disease [5], which makes it difficult to characterize HCC with single gene biomarkers. One key to a further breakthrough in HCC therapy lies in better understanding the underlying mechanism of HCC progression

Methods

Results

Conclusion