Evidence map›Paper›PMID 39584133›Full record

ArticleFrontiers in pharmacology2024

Prognostic characteristics and drug sensitivity analysis of hepatocellular carcinoma based on histone modification-related genes: a multi-omics integrated study revealing potential therapeutic targets and individualized treatment strategies.

Ping Sun, Zheng Ding, Juan Chen, Kezhen Ou, Dianjie Zhou, Rui Li, Tianxiang Gu, He Sun, Ying Cheng

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Ping Sun *Department of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Zheng Ding *Department of Cardiac Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Juan Chen *Department of Medical Oncology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Kezhen OuDepartment of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Dianjie ZhouDepartment of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Rui LiDepartment of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Tianxiang GuDepartment of Cardiac Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
He SunDepartment of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Ying ChengDepartment of Organ transplantation and Hepatobiliary, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) ranks among the most prevalent and lethal malignancies worldwide. Histone modifications (HMs) play a pivotal role in the initiation and progression of HCC. However, our understanding of HMs in HCC remains limited due to the disease's heterogeneity and the complexity of HMs. Methods: We integrated multi-omics data from multiple cohorts, including single-cell RNA sequencing, bulk RNA sequencing, and clinical information. Weighted gene co-expression network analysis (WGCNA) and consensus clustering were employed to identify histone-related genes. We developed a histone modification-related signature (HMRS) using 117 machine learning methods. Comprehensive analyses of molecular characteristics, immune landscape, and drug sensitivity associated with the HMRS were performed. Results: Through integrative analysis, we defined 110 histone-related genes and identified 45 HCC-HM-related genes (HCC-HMRgenes). The HMRS demonstrated robust prognostic value across multiple cohorts. Patients with high HMRS scores exhibited distinct genomic alterations, including higher tumor heterogeneity and TP53 mutations. The high-risk group showed enrichment in cell cycle, DNA repair, and metabolic pathways. Immune landscape analysis revealed significant differences in immune cell infiltration and pathway activities between high- and low-risk groups. Drug sensitivity prediction suggested potential therapeutic strategies for different risk groups. Conclusion: Our study provides a comprehensive understanding of HMs in HCC and establishes a robust prognostic signature. The HMRS not only stratifies patients into distinct risk groups but also offers insights into underlying molecular mechanisms, immune characteristics, and potential therapeutic strategies, paving the way for personalized medicine in HCC.

Indexed as

drug sensitivityHCCHepatocellular carcinomahistone modificationmachine learningprognosis model

Identifiers

PMID39584133
PMCPMC11582355

What Socratic holds

Textmetadata
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 Socratic graph.