Evidence map›Paper›PMID 39070142›Full record

ArticleFrontiers in oncology2024

A novel basement membrane-related gene signature predicts prognosis and immunotherapy response in hepatocellular carcinoma.

Bingyao Li, Yingkun Che, Puhua Zhu, Yuanpeng Xu, Haibo Yu, Deyu Li, Xiangming Ding

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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.

Bingyao Li *Henan Provincial People's Hospital, Xinxiang Medical University, Xinxiang, Henan, China.
Yingkun Che *Henan Provincial Key Medical Laboratory for Hepatobiliary and Pancreatic Diseases, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
Puhua ZhuHenan Provincial Key Medical Laboratory for Hepatobiliary and Pancreatic Diseases, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
Yuanpeng XuHenan Provincial Key Medical Laboratory for Hepatobiliary and Pancreatic Diseases, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
Haibo YuHenan Provincial People's Hospital, Xinxiang Medical University, Xinxiang, Henan, China.
Deyu LiHenan Provincial People's Hospital, Xinxiang Medical University, Xinxiang, Henan, China.
Xiangming DingHenan Provincial People's Hospital, Xinxiang Medical University, Xinxiang, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Basement membranes (BMs) have recently emerged as significant players in cancer progression and metastasis, rendering them promising targets for potential anti-cancer therapies. Here, we aimed to develop a novel signature of basement membrane-related genes (BMRGs) for the prediction of clinical prognosis and tumor microenvironment in hepatocellular carcinoma (HCC). Methods: The differentially expressed BMRGs were subjected to univariate Cox regression analysis to identify BMRGs with prognostic significance. A six-BMRGs risk score model was constructed using Least Absolute Shrinkage Selection Operator (LASSO) Cox regression. Furthermore, a nomogram incorporating the BMRGs score and other clinicopathological features was developed for accurate prediction of survival rate in patients with HCC. Results: A total of 121 differentially expressed BMRGs were screened from the TCGA HCC cohort. The functions of these BMRGs were significantly enriched in the extracellular matrix structure and signal transduction. The six-BMRGs risk score, comprising Conclusion: Our study suggests that the BMRGs score can serve as a robust biomarker for predicting clinical outcomes and evaluating the tumor microenvironment in patients with HCC, thereby facilitating more effective clinical implementation of immunotherapy.

Indexed as

basement membranehepatocellular carcinomaimmunotherapyprognosistumor microenvironment

Identifiers

PMID39070142
PMCPMC11272612

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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.