Evidence map›Paper›PMID 39165997›Full record

ArticleHeliyon2024

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma.

Meng Sun, Jiangtao Bai, Haisong Wang, Mei Li, Long Zhou, Shanfeng Li

Abstract read
In one paragraph

Article in Heliyon, 2024. 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
–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

1 citing paper in PubMed.

  1. 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

6 authors.

Meng SunDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.
Jiangtao BaiDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.
Haisong WangDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.
Mei LiDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.
Long ZhouDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.
Shanfeng LiDepartment of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

Indexed as

AnoikisCancer-associated fibroblastsImmune cell infiltrationPrediction model

Identifiers

PMID39165997
PMCPMC11334810

What OpenQuestion holds

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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.