Evidence map›Paper›PMID 37004044›Full record

ArticleLipids in health and disease2023

A lipid metabolism-based prognostic risk model for HBV-related hepatocellular carcinoma.

Lili Zhou, Shaohuai Xia, Yaoyao Liu, Qiang Ji, Lifeng Li, Xuan Gao, Xiaodi Guo, Xin Yi, Feng Chen

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Lipids in health and disease, 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
1.2field-weighted citation impact, top 20% 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

9 authors at 4 institutions in 1 country.

Lili Zhou *Cancer Center, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nansihuan West Road, Fengtai District, Beijing, 100070, China.
Shaohuai Xia *Beijing Fuzheng Cancer Hospital, No. 20 Jinghai 3rd road, Yizhuang Economic and Technological Development Zone, Beijing, 100070, China.
Yaoyao Liu *Beijing GenePlus Genomics Institute, Beijing, 102205, China.
Qiang JiCancer Center, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nansihuan West Road, Fengtai District, Beijing, 100070, China.
Lifeng LiBeijing GenePlus Genomics Institute, Beijing, 102205, China.
Xuan GaoState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
Xiaodi GuoCancer Center, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nansihuan West Road, Fengtai District, Beijing, 100070, China.
Xin YiBeijing GenePlus Genomics Institute, Beijing, 102205, China.
Feng ChenCancer Center, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nansihuan West Road, Fengtai District, Beijing, 100070, China. chenfeng406@sina.com.ORCID https://orcid.org/0000-0003-4819-2518
Capital Medical University · CNBGI Group (China) · CNChinese Academy of Sciences · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUp to 85% of hepatocellular carcinoma (HCC) cases in China can be attributed to infection of hepatitis B virus (HBV). Lipid metabolism performs important function in hepatocarcinogenesis of HBV-related liver carcinoma. However, limited studies have explored the prognostic role of lipid metabolism in HBV-related HCC. This study established a prognostic model to stratify HBV-related HCC based on lipid metabolisms.

methodsBased on The Cancer Genome Atlas HBV-related HCC samples, this study selected prognosis-related lipid metabolism genes and established a prognosis risk model by performing uni- and multi-variate Cox regression methods. The final markers used to establish the model were selected through the least absolute shrinkage and selection operator method. Analysis of functional enrichment, immune landscape, and genomic alteration was utilized to investigate the inner molecular mechanism involved in prognosis.

resultsThe risk model independently stratified HBV-infected patients with liver cancer into two risk groups. The low-risk groups harbored longer survival times (with P < 0.05, log-rank test). TP53, LRP1B, TTN, and DNAH8 mutations and high genomic instability occurred in high-risk groups. Low-risk groups harbored higher CD8 T cell infiltration and BTLA expression. Lipid-metabolism (including "Fatty acid metabolism") and immune pathways were significantly enriched (P < 0.05) in the low-risk groups.

conclusionsThis study established a robust model to stratify HBV-related HCC effectively. Analysis results decode in part the heterogeneity of HBV-related liver cancer and highlight perturbation of lipid metabolism in HBV-related HCC. This study's findings could facilitate patients' clinical classification and give hints for treatment selection.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsHepatitis B virusHumansLipid MetabolismLipidsPrognosisRisk FactorsLipidsGenomic instabilityHBVHCCLipid metabolismPrognostic risk modelTME

Identifiers

PMID37004044
PMCPMC10067291
OpenAlexW4362466630

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.