Evidence map›Paper›PMID 33686959›Full record

ArticleAging2021

Identification and validation of a glycolysis-associated multiomics prognostic model for hepatocellular carcinoma.

Tuo Deng, Qian Ye, Chen Jin, Mingliang Wu, Kaiyu Chen, Jinhuan Yang, Ziyan Chen, XiXiang Yu, Gang Chen, Yi Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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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

10 authors.

Tuo DengDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Qian YeDepartment of Clinical Laboratory, Wenzhou People's Hospital, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, China.
Chen JinDepartment of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Mingliang WuDepartment of Oncology, The First School of Clinical Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Kaiyu ChenDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Jinhuan YangDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Ziyan ChenDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
XiXiang YuDepartment of Oncology, The First School of Clinical Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Gang ChenDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Yi WangDepartment of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increased glycolysis has been reported as a major metabolic hallmark in many cancers, and is closely related to malignant behavior of tumors. However, the potential mechanism of glycolysis in hepatocellular carcinoma (HCC) and its prognostic value are not well understood. To address this, we investigated glycolysis-related gene expression data of patients with HCC from TCGA and ICGC. Patients were categorized into three different glycolysis-associated subgroups: Glycolysis-M, Glycolysis-H, and Glycolysis-L. We found that Glycolysis-H combined with Glycolysis-M (Glycolysis-H+M) subgroup was associated with poor overall survival and distinct cancer stem cell characteristics and immune infiltrate patterns. Additionally, multiomics-based analyses were conducted to evaluate genomic patterns of glycolysis subgroups, including their gene mutations, copy number variations, and RNA-sequencing data. Finally, a glycolysis-associated multiomics prognostic model (GMPM) consisting of 19 glycolysis-associated genes was developed. The capability of GMPM in categorizing patients with HCC into high- and low-risk groups was validated with independent HCC datasets. Finally, GMPM was confirmed as an independent risk factor for the prognosis of patients with HCC. We believe that our findings provide new insights into the mechanism of glycolysis and highlight the potential clinical value of GMPM in predicting the prognosis of patients with HCC.

Indexed as

GlycolysisAgedCarcinoma, HepatocellularFemaleHumansKaplan-Meier EstimateLiver NeoplasmsMaleMiddle AgedModels, StatisticalPrognosisRisk AssessmentSurvival AnalysisTranscriptomeglycolysishepatocellular carcinomamultiomic analysisprognostic signaturerisk stratification

Identifiers

PMID33686959
PMCPMC7993684

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Registered trials

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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.