Evidence map›Paper›PMID 36564744›Full record

ArticleBMC pulmonary medicine2022

Characterization of the fatty acid metabolism-related genes in lung adenocarcinoma to guide clinical therapy.

Guichuan Huang, Jing Zhang, Ling Gong, Xiaowen Wang, Bangyan Zhang, Daishun Liu

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 45% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Identification of a novel ADCC-related gene signature for predicting the prognosis and therapy response in lung adenocarcinoma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2024
    Article
  4. Article
  5. 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

6 authors at 4 institutions in 1 country.

Guichuan HuangState Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Jing ZhangDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
Ling GongDepartment of Pulmonary and Critical Care Medicine, The First People's Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), No 98 Fenghuang Road, Huichuan District, Zunyi, 563000, China.
Xiaowen WangDepartment of Pulmonary and Critical Care Medicine, The First People's Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), No 98 Fenghuang Road, Huichuan District, Zunyi, 563000, China.
Bangyan ZhangDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, 550000, China.
Daishun LiuDepartment of Pulmonary and Critical Care Medicine, The First People's Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), No 98 Fenghuang Road, Huichuan District, Zunyi, 563000, China. ldslwtg@126.com.
First People’s Hospital of Zunyi · CNZunyi Medical University · CNGuizhou Provincial People's Hospital · CNState Key Laboratory of Respiratory Disease · CN

Funding

Guizhou Provincial Natural Science Foundation Project [2018]5623Guizhou Provincial Respiratory Critical Disease Clinical Research and Prevention and Treatment Talent Base Project [2020]8Guizhou Provincial Science and Technology Agency Project Qian Ke He Basic-ZK [2021] General 349Zunyi Respiratory Medicine Talent Base Project [2019]69
6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) is a common cancer with a bad prognosis. Numerous investigations have indicated that the metabolism of fatty acids plays an important role in the occurrence, progression, and treatment of cancer. Consequently, the objective of the current investigation was to elucidate the role and prognostic significance of genes associated with fatty acid metabolism in patients diagnosed with LUAD. MATERIALS AND

methodsThe data files were acquired from The Cancer Genome Atlas database and GSE31210 dataset. Univariate Cox and least absolute shrinkage and selection operator regression analyses were conducted to establish a prognostic risk scoring model depending on fatty acid metabolism-associated genes to predict the prognosis of patients with LUAD. pRRophetic algorithm was utilized to evaluate the potential therapeutic agents. Gene set variation analysis combined with cell-type identification based on the estimation of relative subsets of RNA transcript and single-sample gene set enrichment analysis was used to determine the association between immune cell infiltration and risk score. Tumor immune dysfunction and exclusion algorithm was employed to predict immunotherapeutic sensitivity.

resultsTo forecast the prognosis of patients with LUAD, a risk scoring model based on five genes associated with fatty acid metabolism was developed, including LDHA, ALDOA, CYP4B1, DPEP2, and HPGDS. Using the risk score algorithm, patients were divided into higher- and lower-risk categories. Patients classified as minimal risk showed superior prognosis than those with elevated risk. In addition, individuals in the higher-risk group had a proclivity toward chemoresistance and amenable to immunotherapy.

conclusionThe prognostic risk scoring model aids in estimating the prognosis of LUAD patients. It may also provide new insights into LUAD carcinogenesis and therapeutic strategies.

Indexed as

Adenocarcinoma of LungLung NeoplasmsHumansImmunotherapyLipid MetabolismPrognosisRisk FactorsFatty acid metabolismLung adenocarcinomaPrognosisRisk score model

Identifiers

PMID36564744
PMCPMC9784226
OpenAlexW4312179144

What OpenQuestion holds

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LicenceCC BY
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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.