Effects of PKM2 on global metabolic changes and prognosis in hepatocellular carcinoma: from gene expression to drug discovery

Abstract

BackgroundHepatocellular carcinoma (HCC) is a malignant tumor that threatens global human health. High PKM2 expression is widely reported in multiple cancers, especially in HCC. This study aimed to explore the effects of PKM2 on global gene expression, metabolic damages, patient prognosis, and multiple transcriptional regulation relationships, as well as to identify several key metabolic genes and screen some small-molecule drugs.MethodsTranscriptome and clinical HCC data were downloaded from the NIH-GDC repository. Information regarding the metabolic genes and subsystems was collected from the Recon 2 human metabolic model. Drug-protein interaction data were obtained from the DrugBank and UniProt databases. We defined patients with PKM2 expression levels ≥11.25 as the high-PKM2 group, and those with low PKM2 expression (< 11.25) were defined as the low-PKM2 group.ResultsThe results showed that the global metabolic gene expression levels were obviously divided into the high- or low-PKM2 groups. In addition, a greater number of affected metabolic subsystems were observed in the high-PKM2 group. Furthermore, we identified 98 PKM2-correlated deregulated metabolic genes that were associated with poor overall patient survival. Together, these findings suggest more comprehensive influences of PKM2 on HCC. In addition, we screened several small-molecule drugs that target these metabolic enzymes, some of which have been used in antitumor clinical studies.ConclusionsHCC patients with high PKM2 expression showed more severe metabolic damage, transcriptional regulation imbalance and poor prognosis than low-PKM2 individuals. We believe that our study provides valuable information for pathology research and drug development for HCC.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-5023-0) contains supplementary material, which is available to authorized users.

Upregulated expression of pyruvate kinase M2 mRNA predicts poor prognosis in lung adenocarcinoma

“…According to the Warburg effect, most cancer cells produce energy by glycolysis, suggesting that targeting cancer metabolism might be a potential field in drug discovery (Liu et al, 2016;Lv et al, 2018;Yang et al, 2017). As a key regulator involving in Warburg effect, PKM2 is frequently expressed at high levels in numerous human tumors and play an important role in tumorigenesis, aerobic glycolysis and chemoresistance (Dayton, Jacks & Vander Heiden, 2016;Guo et al, 2019;Liu et al, 2016;Lv et al, 2018;Zhu et al, 2016). Recent evidents (Chu et al, 2015;Guo et al, 2019;Sun et al, 2015) have indicated that PKM2 is highly over-expressed in LUAC compared to normal lung tissues.…”

Peer Review #2 of "Upregulated expression of pyruvate kinase M2 mRNA predicts poor prognosis in lung adenocarcinoma (v0.1)"

“…According to the Warburg effect, most cancer cells produce energy by glycolysis, suggesting that targeting cancer metabolism might be a potential field in drug discovery (Liu et al 2016;Lv et al 2018;Yang et al 2017). As a key regulator involving in Warburg effect, PKM2 is frequently expressed at high levels in numerous human tumors, and play an important role in tumorigenesis, aerobic glycolysis and chemoresistance (Dayton et al 2016;Guo et al 2019;Liu et al 2016;Lv et al 2018;Zhu et al 2016). Recent evidents (Chu et al 2015;Guo et al 2019;Sun et al 2015) have indicated that PKM2 is highly over-expressed in LUAC compared to normal lung tissues.…”

“…Given that PKM2 is an important driver regulating energy metabolism of cancer cells, targeting PKM2 might be an promising therapeutic strategy. Recent studies have reported that high PKM2 expression is associated with an unfavorable prognosis in multiple human tumors including hepatocellular carcinoma (Lv et al 2018), breast cancer (Yang et al 2017) and osteosarcoma (Liu et al 2016), etc. Nevertheless, over-expression of PKM2 in gastric cancer and pancreatic cancer were not correlated with poor prognosis (Zhu et al 2017).…”

Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism—Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers?

“…These models are typically applied to individual pathways [68,69]. A global reconstruction model of human metabolism is publically available—Recon 2 [70]—this model can be combined with public clinical and experimental gene transcriptome data in order to identify potential metabolic characteristics and thus weaknesses of specific cancer types [71].…”