Evidence map›Paper›PMID 36544660›Full record

ArticleAnnals of translational medicine2022

Glycolysis-related gene dihydrolipoamide acetyltransferase promotes poor prognosis in hepatocellular carcinoma through the Wnt/β-catenin and PI3K/Akt signaling pathways.

Yuan Zhou, Haijuan Gu, Bingfeng Shao, Suqing Zhang, Harpreet Pall, Renata D'Alpino Peixoto, Shaffer R S Mok, Guodong Zhu

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Targeting cuproptosis in liver cancer: Molecular mechanisms and therapeutic implications.Apoptosis : an international journal on programmed cell death · 2025
    Review
  3. Article
  4. Review
  5. Article
  6. Oncology letters · 2025
    Article
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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 at 5 institutions in 3 countries.

Yuan Zhou *Department of Hepatobiliary Surgery, Tumor Hospital Affiliated to Nantong University, Nantong Tumor Hospital, Nantong, China.
Haijuan Gu *Department of Pharmacy, Tumor Hospital Affiliated to Nantong University, Nantong Tumor Hospital, Nantong, China.
Bingfeng ShaoDepartment of Hepatobiliary Surgery, Tumor Hospital Affiliated to Nantong University, Nantong Tumor Hospital, Nantong, China.
Suqing ZhangDepartment of Hepatobiliary Surgery, Tumor Hospital Affiliated to Nantong University, Nantong Tumor Hospital, Nantong, China.
Harpreet PallDepartment of Pediatrics, Hackensack Meridian School of Medicine, Hackensack Meridian K. Hovnanian Children's Hospital, Jersey Shore University Medical Center, Neptune, NJ, USA.
Renata D'Alpino PeixotoCentro Paulista de Oncologia (Grupo Oncoclínicas), São Paulo, Brazil.
Shaffer R S MokDepartment of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Guodong ZhuDepartment of Hepatobiliary Surgery, Affiliated Nantong Hospital 3 of Nantong University, Nantong, China.
Nantong Tumor Hospital · CNAffiliated Hospital of Nantong University · CNCentro Paulista de Investigação Clinica · BRJersey Shore University Medical Center · USMoffitt Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recent research suggests that dihydrolipoamide acetyltransferase (DLAT), which is a copper-induced cell death-related gene, is involved in multiple biological events in tumors. This study sought to investigate the relationship between DLAT and hepatocellular carcinoma (HCC). Methods: In the Cancer Genome Atlas (TCGA) database, we first identified the differentially expressed gene (i.e., DLAT), then confirmed DLAT expression, and found a link between it and the prognosis of HCC patients. An internal validation nomogram was built based on a multivariate Cox regression analysis. Data from the Tumor Immune Estimation Resource (TIMER) database was used to examine the association between DLT and immunological cells. A gene set enrichment analysis (GSEA) was conducted to investigate the probable mechanism of action. Finally, Results: The database screenings showed that DLAT was a differentially expressed molecule; that is, DLAT was more highly expressed in the cancer tissues than normal tissues. TCGA results and Kaplan-Meier-plotter data sets showed that HCC patients with reduced DLAT expression had greater disease-specific survival (DSS), overall survival (OS), and progression-free interval (PFI). The prediction model had a concordance index of 0.659 (0.614-0.704), which indicates high accuracy. According to the TIMER database, tumor cells in the HCC microenvironment may be able to bypass the immune system due to the expression of DLAT. The Conclusions: Decreased DLAT expression significantly prolongs the OS, PFI, and DSS of HCC patients. DLAT may be employed as a new predictive biomarker for HCC, and may be linked to the immune system in HCC patients. The tumor microenvironment (TME) may have a significant effect on the ability of tumor cells to evade the immune system. The PI3K/Akt and Wnt/β-catenin signaling pathways may affect the prognosis of HCC by interfering with DLAT. Given these findings, HCC may be an ideal target for the development of anti-cancer therapies.

Indexed as

bioinformatics analysisDihydrolipoamide acetyltransferase (DLAT)glycolysishepatocellular carcinoma (HCC)prognosis

Identifiers

PMID36544660
PMCPMC9761179
OpenAlexW4310811735

What OpenQuestion 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 OpenQuestion graph.