ArticleBMC cancer2019
Distinct signatures of lung cancer types: aberrant mucin O-glycosylation and compromised immune response.
Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- GALNT7-induced O-glycosylation of NUP50 activates fatty acid β-oxidation to promote lung adenocarcinoma metastasis.The Journal of biological chemistry · 2026Article
- Integrative Analysis of Glycosylation-Related Genes Reveals Prognostic Subtypes, Immune Evasion, and Therapeutic Vulnerabilities in Lung Adenocarcinoma.Oncology research · 2026Article
- A Pilot Study: Contrasting Genomic Profiles of Lung Adenocarcinoma Between Patients of European and Latin American Ancestry.International journal of molecular sciences · 2025Article
- Post-translational modifications of protein and lung cancer.Frontiers in oncology · 2025Review
- Identification and validation of a glycosyltransferase gene signature as a novel prognostic model for lung adenocarcinoma.Heliyon · 2024Article
- Data mining-based identification of epigenetic signatures with discrimination potential of lung adenocarcinoma and squamous cell carcinoma.Molecular biology reports · 2024Article
- MUC21: a new target for tumor treatment.Frontiers in oncology · 2024Review
- A workflow to study mechanistic indicators for driver gene prediction with Moonlight.Briefings in bioinformatics · 2023Article
- Identification of Altered Primary Immunodeficiency-Associated Genes and Their Implications in Pediatric Cancers.Cancers · 2022Article
- Lung Tumor Cells with Different Tn Antigen Expression Present Distinctive Immunomodulatory Properties.International journal of molecular sciences · 2022Article
- Smoking-associated Downregulation of FILIP1L Enhances Lung Adenocarcinoma Progression Through Mucin Production, Inflammation, and Fibrosis.Cancer research communications · 2022Article
- Analysis of Exosomal Cargo Provides Accurate Clinical, Histologic and Mutational Information in Non-Small Cell Lung Cancer.Cancers · 2022Article
- Multi-omics analyses provide novel biological insights to distinguish lobular ductal types of invasive breast cancers.Breast cancer research and treatment · 2022Article
- Identification of condition-specific regulatory mechanisms in normal and cancerous human lung tissue.BMC genomics · 2022Article
- Article
- Diagnostic value of periostin in lung cancer-related malignant pleural effusion.Journal of clinical laboratory analysis · 2022Article
- A novel glycosyltransferase-related lncRNA signature correlates with lung adenocarcinoma prognosis.Frontiers in oncology · 2022Article
- Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods.Scientific reports · 2021Article
- ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages.Bioinformatics (Oxford, England) · 2021Article
- DifferentialOncology reports · 2021Observational
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundGenomic initiatives such as The Cancer Genome Atlas (TCGA) contain data from -omics profiling of thousands of tumor samples, which may be used to decipher cancer signaling, and related alterations. Managing and analyzing data from large-scale projects, such as TCGA, is a demanding task. It is difficult to dissect the high complexity hidden in genomic data and to account for inter-tumor heterogeneity adequately.
methodsIn this study, we used a robust statistical framework along with the integration of diverse bioinformatic tools to analyze next-generation sequencing data from more than 1000 patients from two different lung cancer subtypes, i.e., the lung adenocarcinoma (LUAD) and the squamous cell carcinoma (LUSC).
resultsWe used the gene expression data to identify co-expression modules and differentially expressed genes to discriminate between LUAD and LUSC. We identified a group of genes which could act as specific oncogenes or tumor suppressor genes in one of the two lung cancer types, along with two dual role genes. Our results have been validated against other transcriptomics data of lung cancer patients.
conclusionsOur integrative approach allowed us to identify two key features: a substantial up-regulation of genes involved in O-glycosylation of mucins in LUAD, and a compromised immune response in LUSC. The immune-profile associated with LUSC might be linked to the activation of three oncogenic pathways, which promote the evasion of the antitumor immune response. Collectively, our results provide new future directions for the design of target therapies in lung cancer.
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