ArticleOncotarget2017
Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Monoallelic mutations in MMD2 cause autosomal dominant aggressive periodontitis.The Journal of experimental medicine · 2025Article
- Differential gene expression analysis of HNSCC tumors deciphered tobacco dependent and independent molecular signatures.Oncotarget · 2019Article
- Differential Effect of Smoking on Gene Expression in Head and Neck Cancer Patients.International journal of environmental research and public health · 2018Article
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Authors and funding
3 authors.
Funding
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Abstract
In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets.
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