Evidence map›Paper›PMID 31789390›Full record

ArticleInternational journal of oncology2020

Identification of prognostic markers of lung cancer through bioinformatics analysis and in vitro experiments.

Bo Ling, Xianjiu Liao, Yuanhe Huang, Lingling Liang, Yan Jiang, Yaqin Pang, Guangzi Qi

Abstract read
In one paragraph

Article in International journal of oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
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  3. Functional significance of miR-218 in lung cancer.Journal of cancer metastasis and treatment · 2026
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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

7 authors.

Bo LingCollege of Pharmacy, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.
Xianjiu LiaoCollege of Pharmacy, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.
Yuanhe HuangCollege of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.
Lingling LiangCollege of Pharmacy, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.
Yan JiangMedical College, Guangxi University, Nanning, Guangxi 530004, P.R. China.
Yaqin PangCollege of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.
Guangzi QiCollege of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi 533000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most common types of cancer worldwide. Understanding the molecular mechanisms underlying the development and progression of lung cancer may improve early diagnosis, treatment and prognosis. The aim of the present study was to examine the pathogenesis of lung cancer and to identify potentially novel biomarkers. Gene expression datasets of patients with lung cancer were obtained from the Gene Expression Omnibus. Genes which were most closely associated with lung cancer (core genes) were screened by weighted gene co‑expression network analysis. In vitro cell based experiments were further utilized to verify the effects of the core genes on the proliferation of lung cancer cells, adhesion between cells and the matrix, and the associated metabolic pathways. Based on WGCNA screening, two gene modules and five core genes closely associated with lung cancer, including immunoglobulin superfamily member 10 (IGSF10) from the turquoise module, and ribonucleotide reductase regulatory subunit M2, protein regulator of cytokinesis 1, kinesin family member (KIF)14 and KIF2C from the brown module were identified as relevant. Survival analysis and differential gene expression analysis showed that there were significant differences in IGSF10 expression levels between the healthy controls and patients with lung cancer. In patients with lung cancer, IGSF10 expression was decreased, and the overall survival time of patients with lung cancer was significantly shortened. An MTT and colony formation assay showed that IGSF10‑knockout significantly increased proliferation of lung cancer cells, and Transwell assays and adhesion experiments further suggested that the adhesion between cells and the matrix was significantly increased in IGSF10‑knockout cells. Gene Set Enrichment Analysis showed that the expression level of IGSF10 was significantly associated with the activation of the integrin‑β1/focal adhesion kinase (FAK) pathway. Western blotting revealed that knockout of IGSF10 resulted in the activation of the integrin‑β1/FAK pathway, as the protein expression levels of integrin‑β1, phosphorylated (p)‑FAK and p‑AKT were significantly upregulated. Activation of the integrin‑β1/FAK pathway, following knockout of IGSF10, affected the proliferation and adhesion of lung cancer cells. Therefore, IGSF10 my serve as a potential prognostic marker of lung cancer.

Indexed as

Gene Expression ProfilingGene Regulatory NetworksApoptosisBiomarkers, TumorCell ProliferationComputational BiologyFemaleFollow-Up StudiesGene Expression Regulation, NeoplasticGene OntologyHumansIn Vitro TechniquesLung NeoplasmsMalePrognosisSurvival RateBiomarkers, Tumor

Identifiers

PMID31789390
PMCPMC6910184

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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.