Evidence map›Paper›PMID 37484410›Full record

ArticleHeliyon2023

A novel tumor 4-driver gene signature for the prognosis of hepatocellular carcinoma.

Houtian Guo, Fei Lu, Rongqi Lu, Meiqi Huang, Xuejing Li, Jianhui Yuan, Feng Wang

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

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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.

Houtian GuoFirst Clinical College of Guangxi Medical University, Nanning, China.
Fei LuFirst Clinical College of Guangxi Medical University, Nanning, China.
Rongqi LuFirst Clinical College of Guangxi Medical University, Nanning, China.
Meiqi HuangFirst Clinical College of Guangxi Medical University, Nanning, China.
Xuejing LiDepartment of Physiology, School of Basic Medical Sciences, Guangxi Medical University, Nanning, China.
Jianhui YuanDepartment of Physics, School of Basic Medical Sciences, Guangxi Medical University, Nanning, China.
Feng WangDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Guangxi Medical University, Nanning, China.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed. Methods: HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed. Result: A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups. Conclusion: The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients.

Indexed as

Driver genesHepatocellular carcinomaImmuneNomogramPrognosis

Identifiers

PMID37484410
PMCPMC10361245
OpenAlexW4379740979

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.