ArticleComputational and mathematical methods in medicine2021
Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.
Article in Computational and mathematical methods in medicine, 2021. 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 It has been retracted, and should not be counted.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.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
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- Gene Expression in Bronchial Epithelial Cell Responses to Vanadium Exposure.Biological trace element research · 2023Article
- Article
- Retracted: Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.Computational and mathematical methods in medicine · 2023Article
- Anti-POSTN and Anti-TIMP1 Autoantibodies as Diagnostic Markers in Esophageal Squamous Cell Carcinoma.Frontiers in genetics · 2022Article
Corrections and comments
- Retraction · 2023-12-06Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung squamous cell carcinoma (LUSC) is one of the most common types of lung carcinoma and has specific clinicopathologic characteristics. In this study, we screened novel molecular biomarkers relevant to the prognosis of LUSC to explore new diagnostic and treatment approaches for this disease.
methodsWe downloaded GSE73402 from the Gene Expression Omnibus (GEO) database. GSE73402 contains 62 samples, which could be classified as four subtypes according to their pathology and stages. Via weighted gene coexpression network analysis (WGCNA), the main module was identified and was further analyzed using differentially expressed genes (DEGs) analysis. Then, by protein-protein interaction (PPI) network and Gene Expression Profiling Interactive Analysis (GEPIA), hub genes were screened for potential biomarkers of LUSC.
resultsVia WGCNA, the yellow module containing 349 genes was identified, and it is strongly related to the subtype of CIS (carcinoma in situ). DEGs analysis detected 180 genes that expressed differentially between the subtype of CIS and subtype of early-stage carcinoma (Stage I and Stage II). A PPI network of DEGs was constructed, and the top 20 genes with the highest correlations were selected for GEPIA database to explore their effect on LUSC survival prognosis. Finally, ITGA5, TUBB3, SCNN1B, and SERPINE1 were screened as hub genes in LUSC.
conclusionsITGA5, TUBB3, SCNN1B, and SERPINE1 may have great diagnostic and prognostic significance for LUSC and have great potential to be new treatment targets for LUSC.
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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.