ArticleFrontiers in genetics2020
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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32 citing papers in PubMed, 1 synthesis or guideline pooled it, 67 citations in OpenAlex.
- Prognostic and Clinicopathological Value of ZWINT Expression Levels in Patients with Lung Adenocarcinoma: A Systematic Review and Meta-analysis.Clinics (Sao Paulo, Brazil) · 2021Pooled it
- Analysis and identification of mRNAsi‑related expression signatures via RNA sequencing in lung cancer.Oncology letters · 2024Article
- Identification of Potential Breast Cancer Stem Cell Biomarkers in the Secretome Using a Network Interaction Approach Analysis.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Identification of disulfidptosis-related subtypes and development of a prognosis model based on stacking framework in renal clear cell carcinoma.Journal of cancer research and clinical oncology · 2023Article
- Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment.Cancers · 2023Review
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- Identification of specific prognostic markers for lung squamous cell carcinoma based on tumor progression, immune infiltration, and stem index.Frontiers in immunology · 2023Article
- Study on the cytokines related to SARS-Cov-2 in testicular cells and the interaction network between cells based on scRNA-seq data.Open life sciences · 2023Article
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- BCSCdb: a database of biomarkers of cancer stem cells.Database : the journal of biological databases and curation · 2022Article
- Characterization of a prognostic model for lung squamous cell carcinoma based on eight stemness index-related genes.BMC pulmonary medicine · 2022Article
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- Article
- Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma.Animal cells and systems · 2022Article
- Development of a 5-Gene Signature to Evaluate Lung Adenocarcinoma Prognosis Based on the Features of Cancer Stem Cells.BioMed research international · 2022Article
- Identification and Validation of a Potential Stemness-Associated Biomarker in Hepatocellular Carcinoma.Stem cells international · 2022Article
- Evaluation of tumor microenvironmental immune regulation and prognostic in lung adenocarcinoma from the perspective of purinergic receptor P2Y13.Bioengineered · 2021Article
- A novel ferroptosis-related lncRNA signature for prognosis prediction in gastric cancer.BMC cancer · 2021Article
- Precise pathological classification of non-small cell lung adenocarcinoma and squamous carcinoma based on an integrated platform of targeted metabolome and lipidome.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- Novel VHL substrate targets SFMBT1 and ZHX2 may be important prognostic predictors in patients with ccRCC.Oncology letters · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.
methodsRNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.
resultsLUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein-protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.
conclusionmRNAsi-related hub genes could be a potential biomarker of LUSC.
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