ArticleScientific reports2018
Distinct co-expression networks using multi-omic data reveal novel interventional targets in HPV-positive and negative head-and-neck squamous cell cancer.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 33 citations in OpenAlex.
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- Inference of epigenetic subnetworks by Bayesian regression with the incorporation of prior information.Scientific reports · 2022Article
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- A computational approach to generate highly conserved gene co-expression networks with RNA-seq data.STAR protocols · 2022Article
- Changes in gene-gene interactions associated with cancer onset and progression are largely independent of changes in gene expression.iScience · 2021Article
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- Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations.Journal of virology · 2021Article
- Multi-omics integration in biomedical research - A metabolomics-centric review.Analytica chimica acta · 2021Review
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- Current Insights and Advancements in Head and Neck Cancer: Emerging Biomarkers and Therapeutics with Cues from Single Cell and 3D Model Omics Profiling.Frontiers in oncology · 2021Review
- Integrated Multi-Omics Analyses in Oncology: A Review of Machine Learning Methods and Tools.Frontiers in oncology · 2020Review
- Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures.Cancers of the head & neck · 2020Review
- Systems Biology Approaches to Understanding the Human Immune System.Frontiers in immunology · 2020Article
- Discovering novel driver mutations from pan-cancer analysis of mutational and gene expression profiles.PloS one · 2020Article
- Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human papillomavirus (HPV) is present in a significant fraction of head-and-neck squamous cell cancer (HNSCC). The main goal of this study was to identify distinct co-expression patterns between HPV+ and HPV- HNSCC and to provide insights into potential regulatory mechanisms/effects within the analyzed networks. We selected cases deposited in The Cancer Genome Atlas database comprising data of gene expression, methylation profiles and mutational patterns, in addition to clinical information. The intersection among differentially expressed and differentially methylated genes showed the negative correlations between the levels of methylation and expression, suggesting that these genes have their expression levels regulated by methylation alteration patterns in their promoter. Weighted correlation network analysis was used to identify co-expression modules and a systematic approach was applied to refine them and identify key regulatory elements integrating results from the other omics. Three distinct co-expression modules were associated with HPV status and molecular signatures. Validation using independent studies reporting biological experimental data converged for the most significant genes in all modules. This study provides insights into complex genetic and epigenetic particularities in the development and progression of HNSCC according to HPV status, and contribute to unveiling specific genes/pathways as novel therapeutic targets in HNSCC.
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