Evidence map›Paper›PMID 34257161›Full record

ArticleAging2021

Prognostic value of fatty acid metabolism-related genes in patients with hepatocellular carcinoma.

Dongsheng He, Lifang Cai, Weiming Huang, Qingqing Weng, Xi Lin, Mengxing You, Shengyin Liao

Open access · hybridAbstract read
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 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.6field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 38 citations in OpenAlex.

  1. Advances in Lipid Metabolism Reprogramming in Hepatocellular Carcinoma.Journal of clinical and translational hepatology · 2026
    Review
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  12. Computational and mathematical methods in medicine · 2023
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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

7 authors at 1 institution in 1 country.

Dongsheng HeDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Lifang CaiDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Weiming HuangDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Qingqing WengDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Xi LinDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Mengxing YouDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Shengyin LiaoDepartment of Medical Oncology, The First Hospital of Putian, Teaching Hospital, Fujian Medical University, Putian 351100, Fujian Province, China.
Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The deregulation of fatty acid metabolism plays a crucial role in cancer. However, the prognostic value of genes involved in the metabolism in hepatocellular carcinoma (HCC) remains largely unknown. We first constructed a multi-fatty acid metabolic gene prognostic model of HCC based on The Cancer Genome Atlas (TCGA) and further validated it using the International Cancer Genome Consortium (ICGC) database. The model was integrated with the clinical parameters, and a nomogram was built and weighted. Moreover, immune cell infiltration of the tumor microenvironment was investigated. A prognostic model was constructed using 6 selected fatty acid metabolism-related genes, and HCC patients were divided into high- and low-risk groups. Receiver operating characteristic curve (ROC) analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis showed the optimal performance of the model. The concordance index (C-index), ROC curve, calibration plot and decision curve analysis (DCA) all confirmed the satisfactory predictive capacity of the nomogram. The analysis of immune cell infiltration in HCC patients revealed a correlation with different risk levels. Our findings indicate that a prognostic model based on fatty acid metabolism-related genes has superior predictive capacities, which provides the possibility for further improving the individualized treatment of patients with HCC.

Indexed as

Carcinoma, HepatocellularFatty AcidsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLiver NeoplasmsModels, BiologicalNomogramsPredictive Value of TestsPrincipal Component AnalysisPrognosisReproducibility of ResultsROC CurveStochastic ProcessesSurvival AnalysisTumor MicroenvironmentFatty Acidsfatty acid metabolismhepatocellular carcinomaICGCprognosisTCGA

Identifiers

PMID34257161
PMCPMC8312438
OpenAlexW3180733422

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.