Evidence map›Paper›PMID 36860731›Full record

ArticleOxidative medicine and cellular longevity2023

Development of Prognostic Features of Hepatocellular Carcinoma Based on Metabolic Gene Classification and Immune and Oxidative Stress Characteristic Analysis.

Shimeng Cui, Minghao Zhang, Shanshan Bai, Yanfang Bi, Shan Cong, Shi Jin, Shuang Li, Hui He, Jian Zhang

Open access · hybridAbstract read
In one paragraph

Article in Oxidative medicine and cellular longevity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. New insights into T-cell exhaustion in liver cancer: from mechanism to therapy.Journal of cancer research and clinical oncology · 2023
    Review
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

9 authors at 2 institutions in 1 country.

Shimeng CuiDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.
Minghao ZhangDepartment of Vascular Interventional, Affiliated Hongqi Hospital of Mudanjiang Medical College, Mudanjiang 157011, China.
Shanshan BaiDepartment of Ultrasound, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.
Yanfang BiDepartment of Nursing, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.
Shan CongDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.
Shi JinDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.
Shuang LiBioinformatics R&D Department, Hangzhou Mugu Technology Co., Ltd., Hangzhou 310000, China.ORCID https://orcid.org/0000-0002-4479-483X
Hui HeDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.ORCID https://orcid.org/0000-0003-3348-3152
Jian ZhangDepartment of Interventional Therapy, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.ORCID https://orcid.org/0000-0001-6700-7256
Dalian Medical University · CNMudanjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The molecular classification of HCC premised on metabolic genes might give assistance for diagnosis, therapy, prognosis prediction, immune infiltration, and oxidative stress in addition to supplementing the limitations of the clinical staging system. This would help to better represent the deeper features of HCC. Methods: TCGA datasets combined with GSE14520 and HCCDB18 datasets were used to determine the metabolic subtype (MC) using ConsensusClusterPlus. ssGSEA method was used to calculate the IFN Results: Three MCs (MC1, MC2, and MC3) were identified and showed different prognoses (MC2-poor and MC1-better). Although MC2 had a high immune microenvironment infiltration, T cell exhaustion markers were expressed at a high level in MC2 in contrast with MC1. Most oxidative stress-related pathways are inhibited in the MC2 subtype and activated in the MC1 subtype. The immunophenotyping of pan-cancer showed that the C1 and C2 subtypes with poor prognosis accounted for significantly higher proportions of MC2 and MC3 subtypes than MC1, while the better prognostic C3 subtype accounted for significantly lower proportions of MC2 than MC1. As per the findings of the TIDE analysis, MC1 had a greater likelihood of benefiting from immunotherapeutic regimens. MC2 was found to have a greater sensitivity to traditional chemotherapy drugs. Finally, 7 potential gene markers indicate HCC prognosis. Conclusion: The difference (variation) in tumor microenvironment and oxidative stress among metabolic subtypes of HCC was compared from multiple angles and levels. A complete and thorough clarification of the molecular pathological properties of HCC, the exploration of reliable markers for diagnosis, the improvement of the cancer staging system, and the guiding of individualized treatment of HCC all gain benefit greatly from molecular classification associated with metabolism.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsCD3 ComplexHumansOxidative StressPrognosisTumor MicroenvironmentCD3 Complex

Identifiers

PMID36860731
PMCPMC9969974
OpenAlexW4321330686

What OpenQuestion holds

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LicenceCC BY
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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.