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Ren LK, Lu RS, Fei XB, Chen SJ, Liu P, Zhu CH, Wang X, Pan YZ. Unveiling the role of PYGB in pancreatic cancer: a novel diagnostic biomarker and gene therapy target. J Cancer Res Clin Oncol 2024; 150:127. [PMID: 38483604 PMCID: PMC10940407 DOI: 10.1007/s00432-024-05644-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/05/2024] [Indexed: 03/17/2024]
Abstract
PURPOSE Pancreatic cancer (PC) is a highly malignant tumor that poses a severe threat to human health. Brain glycogen phosphorylase (PYGB) breaks down glycogen and provides an energy source for tumor cells. Although PYGB has been reported in several tumors, its role in PC remains unclear. METHODS We constructed a risk diagnostic model of PC-related genes by WGCNA and LASSO regression and found PYGB, an essential gene in PC. Then, we explored the pro-carcinogenic role of PYGB in PC by in vivo and in vitro experiments. RESULTS We found that PYGB, SCL2A1, and SLC16A3 had a significant effect on the diagnosis and prognosis of PC, but PYGB had the most significant effect on the prognosis. Pan-cancer analysis showed that PYGB was highly expressed in most of the tumors but had the highest correlation with PC. In TCGA and GEO databases, we found that PYGB was highly expressed in PC tissues and correlated with PC's prognostic and pathological features. Through in vivo and in vitro experiments, we found that high expression of PYGB promoted the proliferation, invasion, and metastasis of PC cells. Through enrichment analysis, we found that PYGB is associated with several key cell biological processes and signaling pathways. In experiments, we validated that the MAPK/ERK pathway is involved in the pro-tumorigenic mechanism of PYGB in PC. CONCLUSION Our results suggest that PYGB promotes PC cell proliferation, invasion, and metastasis, leading to poor patient prognosis. PYGB gene may be a novel diagnostic biomarker and gene therapy target for PC.
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Affiliation(s)
- Li-Kun Ren
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
| | - Ri-Shang Lu
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
| | - Xiao-Bin Fei
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
| | - Shao-Jie Chen
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
- Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550000, China
| | - Peng Liu
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
- Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550000, China
| | - Chang-Hao Zhu
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China
- Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, 550000, China
| | - Xing Wang
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China.
- Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, 550000, China.
| | - Yao-Zhen Pan
- College of Clinical Medicine, Guizhou Medical University, Guiyang, 550000, Guizhou, China.
- Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, 550000, China.
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Yang J, Shay C, Saba NF, Teng Y. Cancer metabolism and carcinogenesis. Exp Hematol Oncol 2024; 13:10. [PMID: 38287402 PMCID: PMC10826200 DOI: 10.1186/s40164-024-00482-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/22/2024] [Indexed: 01/31/2024] Open
Abstract
Metabolic reprogramming is an emerging hallmark of cancer cells, enabling them to meet increased nutrient and energy demands while withstanding the challenging microenvironment. Cancer cells can switch their metabolic pathways, allowing them to adapt to different microenvironments and therapeutic interventions. This refers to metabolic heterogeneity, in which different cell populations use different metabolic pathways to sustain their survival and proliferation and impact their response to conventional cancer therapies. Thus, targeting cancer metabolic heterogeneity represents an innovative therapeutic avenue with the potential to overcome treatment resistance and improve therapeutic outcomes. This review discusses the metabolic patterns of different cancer cell populations and developmental stages, summarizes the molecular mechanisms involved in the intricate interactions within cancer metabolism, and highlights the clinical potential of targeting metabolic vulnerabilities as a promising therapeutic regimen. We aim to unravel the complex of metabolic characteristics and develop personalized treatment approaches to address distinct metabolic traits, ultimately enhancing patient outcomes.
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Affiliation(s)
- Jianqiang Yang
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, 201 Dowman Dr, Atlanta, GA, 30322, USA
| | - Chloe Shay
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30322, USA
| | - Nabil F Saba
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, 201 Dowman Dr, Atlanta, GA, 30322, USA
| | - Yong Teng
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, 201 Dowman Dr, Atlanta, GA, 30322, USA.
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30322, USA.
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Abecunas C, Fallahi-Sichani M. Multivariate modeling of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.28.569098. [PMID: 38076921 PMCID: PMC10705426 DOI: 10.1101/2023.11.28.569098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Targeting the distinct metabolic needs of tumor cells has recently emerged as a promising strategy for cancer therapy. The heterogeneous, context-dependent nature of cancer cell metabolism, however, poses challenges in identifying effective therapeutic interventions. Here, we utilize various unsupervised and supervised multivariate modeling approaches to systematically pinpoint recurrent metabolic states within hundreds of cancer cell lines, elucidate their association with tissue lineage and growth environments, and uncover vulnerabilities linked to their metabolic states across diverse genetic and tissue contexts. We validate key findings using data from an independent set of cell lines, pharmacological screens, and via single-cell analysis of patient-derived tumors. Our analysis uncovers new synthetically lethal associations between the tumor metabolic state (e.g., oxidative phosphorylation), driver mutations (e.g., loss of tumor suppressor PTEN), and actionable biological targets (e.g., mitochondrial electron transport chain). Investigating these relationships could inform the development of more precise and context-specific, metabolism-targeted cancer therapies.
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Affiliation(s)
- Cara Abecunas
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109
- Present address: Vindhya Data Science, 20 Bayless Ridge Court, Morrisville, NC 27560
| | - Mohammad Fallahi-Sichani
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908
- UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22908
- Lead contact
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Cherkaoui S, Durot S, Bradley J, Critchlow S, Dubuis S, Masiero MM, Wegmann R, Snijder B, Othman A, Bendtsen C, Zamboni N. A functional analysis of 180 cancer cell lines reveals conserved intrinsic metabolic programs. Mol Syst Biol 2022; 18:e11033. [PMID: 36321552 PMCID: PMC9627673 DOI: 10.15252/msb.202211033] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 10/03/2022] [Accepted: 10/07/2022] [Indexed: 11/30/2022] Open
Abstract
Cancer cells reprogram their metabolism to support growth and invasion. While previous work has highlighted how single altered reactions and pathways can drive tumorigenesis, it remains unclear how individual changes propagate at the network level and eventually determine global metabolic activity. To characterize the metabolic lifestyle of cancer cells across pathways and genotypes, we profiled the intracellular metabolome of 180 pan-cancer cell lines grown in identical conditions. For each cell line, we estimated activity for 49 pathways spanning the entirety of the metabolic network. Upon clustering, we discovered a convergence into only two major metabolic types. These were functionally confirmed by 13 C-flux analysis, lipidomics, and analysis of sensitivity to perturbations. They revealed that the major differences in cancers are associated with lipid, TCA cycle, and carbohydrate metabolism. Thorough integration of these types with multiomics highlighted little association with genetic alterations but a strong association with markers of epithelial-mesenchymal transition. Our analysis indicates that in absence of variations imposed by the microenvironment, cancer cells adopt distinct metabolic programs which serve as vulnerabilities for therapy.
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Affiliation(s)
- Sarah Cherkaoui
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PhD Program in Systems BiologyLife Science ZürichZürichSwitzerland
| | - Stephan Durot
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PhD Program in Systems BiologyLife Science ZürichZürichSwitzerland
| | | | | | - Sebastien Dubuis
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland
| | - Mauro Miguel Masiero
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PhD Program in Systems BiologyLife Science ZürichZürichSwitzerland
| | - Rebekka Wegmann
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PhD Program in Systems BiologyLife Science ZürichZürichSwitzerland
| | - Berend Snijder
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland
| | - Alaa Othman
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PHRT Swiss Multi‐OMICS Center / smoc.ethz.chZürichSwitzerland
| | | | - Nicola Zamboni
- Institute of Molecular Systems BiologyETH ZürichZürichSwitzerland,PHRT Swiss Multi‐OMICS Center / smoc.ethz.chZürichSwitzerland
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