Evidence map›Paper›PMID 41220734›Full record

ArticleJournal of gastrointestinal oncology2025

Comprehensive bioinformatic analysis reveals sorafenib response-related prognostic signature in hepatocellular carcinoma.

Yuanyu Zhao, Junfeng Dong, Hanxiang Zhong, Liangxi Peng, Liang Wu, Meicen Yu, Guoshan Ding, Wenyuan Guo

Abstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2025. 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

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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Yuanyu Zhao *Institute of Organ Transplantation, Changzheng Hospital, Navy Medical University, Shanghai, China.
Junfeng Dong *Department of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Hanxiang Zhong *Department of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Liangxi PengDepartment of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Liang WuDepartment of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Meicen YuDepartment of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Guoshan DingDepartment of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.
Wenyuan GuoDepartment of Liver Surgery, Shanghai Changzheng Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sorafenib is the first-line treatment agent for advanced hepatocellular carcinoma (HCC), but it is effective in very few patients. Thus, this study was intended to identify gene signatures associated with sorafenib response in HCC and construct a prognostic risk model based on these gene signatures. Methods: The gene expression level data of HCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, we evaluated the HCC sensitivity to sorafenib of the samples and investigated the correlation between HCC sensitivity to sorafenib and clinical prognosis. By Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm, the sorafenib resistance associated genes were obtained. Combined with the sorafenib resistance related data set, genes significantly associated sorafenib responses were screened. Then prognostic signature genes were screened to construct a risk prognosis model. The correlation of risk grouping with immune cells was explored. Results: A total of 399 significantly genes associated with sorafenib response were obtained, which were involved in metabolic and complement pathways. Finally, 5 signature genes ( Conclusions: Our study established a sorafenib response-related prognostic risk prediction model in HCC based on five signature genes (

Indexed as

Hepatocellular carcinoma (HCC)immunityprognostic modelsorafenib

Identifiers

PMID41220734
PMCPMC12598347

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.