Evidence map›Paper›PMID 37708874›Full record

ArticleMedical principles and practice : international journal of the Kuwait University, Health Science Centre2023

Bioinformatics Analysis and Screening of Potential Target Genes Related to the Lung Cancer Prognosis.

Ping Huang, Yinfang Gu, Longhua Guo, Xiaofang Zou, Lilan Yi, Guowu Wu

RetractedAbstract readRetracted Publication
In one paragraph

Article in Medical principles and practice : international journal of the Kuwait University, Health Science Centre, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Research progress of kinesin family in neurological diseases.Frontiers in cellular neuroscience · 2025
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ping Huang
Yinfang Gu
Longhua Guo
Xiaofang Zou
Lilan Yi
Guowu Wu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSeveral genes have been validated as molecular targets for gene therapy in lung cancer. We screened target genes that affect survival of patients with lung cancer.

methodsData on gene expression in normal lung tissues/lung adenocarcinoma (LUAD) samples were acquired from Genotype-Tissue Expression (GTEx)/The Cancer Genome Atlas (TCGA) databases and merged to expand the sample size, followed by differential analysis of the merged expression data and acquisition of differentially expressed genes. Survival and simple Cox analyses were used to screen for genes affecting LUAD survival. Protein-protein interaction/multivariable Cox analyses were utilized, and a risk model was established. Candidate genes expression levels in cancer/paracancerous tissues of lung cancer patients, and BEAS-2B/A549/HCC95 cells were measured by RT-qPCR/Western blot. Survival analysis of candidate genes was conducted in LUAD samples collected from TCGA.

resultsAmong 947 genes differentially expressed in LUAD, 151 were correlated with patient survival, and 116 might act as risk factors for LUAD. The 7 identified candidate genes (TOP2A, TK1, KIF4A, ANLN, KIF2C, ASF1B, CCNB1) were high-risk genes playing possible roles in LUAD. These genes were differentially expressed in lung cancer and were associated with TNM stages (III - IV)/differentiation grade/lymph node metastasis/distant metastasis, which affected lung cancer patient survival.

conclusionP2A, TK1, KIF4A, ANLN, KIF2C, ASF1B and CCNB1 were highly-expressed in LUAD/lung squamous cell carcinoma (LUSC) and correlated with LUAD patient survival. This study contributes to better understanding of the prognostic regulation mechanism in LUAD and the screening of target genes for clinical treatment.

Identifiers

PMID37708874
PMCPMC12065997

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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.