ArticleInternational journal of molecular medicine2018
A 16-gene expression signature to distinguish stage I from stage II lung squamous carcinoma.
Article in International journal of molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Article
- A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications.BMC bioinformatics · 2021Article
- Characteristic genes in THP‑1 derived macrophages infected with Mycobacterium tuberculosis H37Rv strain identified by integrating bioinformatics methods.International journal of molecular medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to perform screening of a gene signature for the discrimination and prognostic prediction of stage I and II lung squamous carcinoma. A microarray meta‑analysis was performed to identify differentially expressed genes (DEGs) between stage I and II lung squamous carcinoma samples in seven microarray datasets collected from the Gene Expression Omnibus database via the MetaQC and MetaDE package in R. The important DEGs were selected according to the betweenness centrality value of the protein‑protein interaction (PPI) network. Support vector machine (SVM) analysis was performed to screen the feature genes for discrimination and prognosis. One independent dataset downloaded from The Cancer Genome Atlas was used to validate the reliability. Pathway enrichment analysis was also performed for the feature genes. A total of 924 DEGs were identified to construct a PPI network consisting of 392 nodes and 686 edges. The top 100 of the 392 nodes were selected as crucial genes to construct an SVM classifier, and a 16‑gene signature (caveolin 1, eukaryotic translation elongation factor 1γ, casein kinase 2α1, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation η, tyrosine 3‑monooxygenase/tryptophan 5‑monooxygenase activation θ, pleiotrophin, insulin receptor, insulin receptor substrate 1, 3‑phosphoinositide‑dependent protein kinase‑1, specificity protein 1, COP9 signalosome subunit 6, N‑myc downstream regulated gene 1, retinoid X receptor α, heat shock protein 90α A1, karyopherin subunit β1 and erythrocyte membrane protein band 4.1) with high discrimination accuracy was identified. This 16‑gene signature had significant prognostic value, and patients with stage II lung squamous carcinoma exhibited shorter survival rates, compared with those with stage I disease. Seven DEGs of the 16-gene signature were significantly involved in the phosphoinositide 3‑kinase‑Akt signaling pathway. The 16‑gene signature identified in the present study may be useful for stratifying the patients with stage I or II lung squamous carcinoma and predicting prognosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.