Evidence map›Paper›PMID 39279958›Full record

ArticleJournal of gastrointestinal oncology2024

Identification of a lactylation-related gene signature to characterize subtypes of hepatocellular carcinoma using bulk sequencing data.

Yan Chen, Li Chang, Ling Hu, Cuiping Yan, Liu Dai, Vishal G Shelat, Hooman Yarmohammadi, Jun Sun

Abstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  12. Journal of Cancer · 2025
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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

8 authors.

Yan ChenDepartment of Laboratory, Yangzhou Hongquan Hospital, Yangzhou, China.
Li ChangDepartment of Laboratory, Yangzhou Hongquan Hospital, Yangzhou, China.
Ling HuDepartment of Laboratory, Yangzhou Hongquan Hospital, Yangzhou, China.
Cuiping YanDepartment of Laboratory, Yangzhou Hongquan Hospital, Yangzhou, China.
Liu DaiDepartment of Laboratory, Yangzhou Second People's Hospital, Yangzhou, China.
Vishal G ShelatDepartment of General Surgery, Tan Tock Seng Hospital, Singapore, Singapore.
Hooman YarmohammadiDepartment of Interventional Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Jun SunDepartment of Oncology, Yangzhou Hongquan Hospital, Yangzhou, China.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Background: Prior studies indicate that lactylation regulates various biological mechanisms within cancer. However, lactylation-related genes (LRGs) have been found to have limited value in predicting the prognosis of hepatocellular carcinoma (HCC). The aim of this study was to review HCC LRGs using data from The Cancer Genome Atlas (TCGA). Methods: The RNA sequencing data and related clinical information of patients with HCC patients were collected from the TCGA database. A total of 20 LRGs were selected and bioinformatics analysis was performed. A consistency cluster analysis was conducted to classify the HCC tumors. Using a lactylation-related model of HCC, prognosis, immune cell infiltration, and immunotherapy was evaluated. Results: A total of 4,378 genes were associated with prognosis. Twenty LRGs (i.e., Conclusions: Strong correlation between LRGs and tumor classification as well as immunity in patients with HCC was identified. LRG signatures serve as reliable prognostic markers for HCC.

Indexed as

biomarkersHepatocellular carcinoma (HCC)lactylationlactylation-related gene signature (LRG signature)prognostic model

Identifiers

PMID39279958
PMCPMC11399878

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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.