Evidence map›Paper›PMID 33226369›Full record

ArticleAging2020

The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction.

Zhen Tan, Yubin Lei, Jin Xu, Si Shi, Jie Hua, Bo Zhang, Qingcai Meng, Jiang Liu, Yiyin Zhang, Miaoyan Wei and 2 more

Open access · greenAbstract readValidation Study
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.5field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 45 citations in OpenAlex.

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  17. ENO3 Inhibits Growth and Metastasis of Hepatocellular CarcinomaFrontiers in cell and developmental biology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Zhen TanDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Yubin LeiDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Jin XuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Si ShiDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Jie HuaDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Bo ZhangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Qingcai MengDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Jiang LiuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Yiyin ZhangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Miaoyan WeiDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Xianjun YuDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Chen LiangDepartment of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Shanghai Cancer Institute · CNFudan University Shanghai Cancer Center · CNShanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.

Indexed as

Cellular ReprogrammingDecision Support TechniquesGene Expression ProfilingNomogramsTranscriptomeBiomarkers, TumorCarcinoma, Pancreatic DuctalDatabases, GeneticEnergy MetabolismFemaleGene Expression Regulation, NeoplasticGerm-Line MutationHumansMalePancreatic NeoplasmsPredictive Value of TestsBiomarkers, Tumormetabolic reprogrammingpancreatic adenocarcinoma

Identifiers

PMID33226369
PMCPMC7762467
OpenAlexW3110376673

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.