Literature DB >> 31968179

Glycolysis-Based Genes Associated with the Clinical Outcome of Pancreatic Ductal Adenocarcinoma Identified by The Cancer Genome Atlas Data Analysis.

Guangwei Tian1, Guang Li1, Peipei Liu2, Zihui Wang3, Nan Li1.   

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadly tumors in digestive tract tumors. Although there has been advancement in PDAC treatment, its prognosis still remains unsatisfactory, mainly because of dismal diagnosis. This article aims to develop new prognostic factors related to energy metabolism in PDAC and to use these genes for novel risk stratification. Hundred fifty messenger RNA (mRNA) expression profiles and clinicopathological data of PDAC were downloaded from The Cancer Genome Atlas dataset. The glycolysis pathway was the significant pathway based on the gene set enrichment analysis. We chose the glycolysis pathway-related 176 genes for further analysis. Multivariate Cox regression analysis and forward stepwise Cox regression model established a novel three-gene glycolytic signature (including MET, B3GNT3, and SPAG4) for PDAC patients' prognosis prediction. All 150 patients were classified into two groups by the median risk score. High-risk group had a worse outcome compared to the low-risk group. The risk score was also significantly correlated with age and radiotherapy. A nomogram, including the glycolytic gene signature, has shown some clinical net benefit for overall survival prediction. We also validated the validity and reliability in the Puleo dataset. This novel gene expression signature may be involved in the pathophysiology and used for risk stratification and prognosis prediction in PDAC.

Entities:  

Keywords:  gene signature; glycolysis; pancreatic ductal adenocarcinoma; prognosis

Year:  2020        PMID: 31968179     DOI: 10.1089/dna.2019.5089

Source DB:  PubMed          Journal:  DNA Cell Biol        ISSN: 1044-5498            Impact factor:   3.311


  11 in total

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2.  Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells.

Authors:  Areej Abu Rmaileh; Balakrishnan Solaimuthu; Mayur Tanna; Anees Khatib; Michal Ben Yosef; Arata Hayashi; Michal Lichtenstein; Yoav D Shaul
Journal:  Biomolecules       Date:  2020-04-30

3.  Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer.

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Journal:  BMC Cancer       Date:  2020-11-23       Impact factor: 4.430

4.  A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer.

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5.  B3GNT3 acts as a carcinogenic factor in endometrial cancer via facilitating cell growth, invasion and migration through regulating RhoA/RAC1 pathway-associated markers.

Authors:  Ji-Shui Wang; Fang Ruan; Li-Zhu Guo; Feng-Ge Wang; Fu-Ling Wang; Hong-Min An
Journal:  Genes Genomics       Date:  2021-03-08       Impact factor: 1.839

6.  Glycolysis-Related Gene Expression Profiling Screen for Prognostic Risk Signature of Pancreatic Ductal Adenocarcinoma.

Authors:  Wenjing Song; Xin He; Pengju Gong; Yan Yang; Sirui Huang; Yifan Zeng; Lei Wei; Jingwei Zhang
Journal:  Front Genet       Date:  2021-06-23       Impact factor: 4.599

7.  A glycolysis-based 4-mRNA signature correlates with the prognosis and cell cycle process in patients with bladder cancer.

Authors:  Chen Zhang; Xin Gou; Weiyang He; Huaan Yang; Hubin Yin
Journal:  Cancer Cell Int       Date:  2020-05-20       Impact factor: 5.722

8.  Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma.

Authors:  Zengyu Feng; Minmin Shi; Kexian Li; Yang Ma; Lingxi Jiang; Hao Chen; Chenghong Peng
Journal:  J Transl Med       Date:  2020-09-21       Impact factor: 5.531

9.  A glycolysis-related two-gene risk model that can effectively predict the prognosis of patients with rectal cancer.

Authors:  Zhenzhen Liu; Zhentao Liu; Xin Zhou; Yongqu Lu; Yanhong Yao; Wendong Wang; Siyi Lu; Bingyan Wang; Fei Li; Wei Fu
Journal:  Hum Genomics       Date:  2022-02-02       Impact factor: 4.639

10.  Human sperm-associated antigen 4 as a potential prognostic biomarker of lung squamous cell carcinoma.

Authors:  Yongheng Wang; Yao Tang; Jianhui Li; Danfang Wang; Wenhan Li
Journal:  J Int Med Res       Date:  2021-07       Impact factor: 1.671

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