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Accession IconSRP066090

Subtypes of HPV-positive head and neck cancers are associated with HPV characteristics, copy number variations, PIK3CA mutation, and pathway signatures. [RNA-Seq]

Organism Icon Homo sapiens
Sample Icon 36 Downloadable Samples
Technology Badge IconIllumina HiSeq 2000

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Purpose: There is substantial heterogeneity within the human papillomavirus (HPV) positive head and neck cancer (HNC) tumors that predispose them to different outcomes, however this subgroup is poorly characterized due to various historical reasons. Experimental Design: we perform unsupervised gene expression clustering on well-annotated HPV(+) HNC samples from two cohorts ( 84 total primary tumors), as well as 18 HPV(-) HNCs, to discover subtypes, and begin to characterize the differences between the subtypes in terms of their HPV characteristics, pathway activity, whole-genome somatic copy number variations and mutation frequencies. Results: We identified two distinctive HPV(+) subtypes by unsupervised clustering. Membership in the HPV(+) subtypes correlates with genic viral integration status, E2/E4/E5 expression levels and the ratio of spliced to full length HPV oncogene E6. The subtypes also show differences in copy number alterations, in particular the loss of chr16q and gain of chr3q, PIK3CA mutation, and in the expression of genes involved in several biological processes related to cancer, including immune response, oxidation-reduction process, and keratinocyte and mesenchymal differentiation. Conclusion: Our characterization of two subtypes of HPV(+) tumors provides valuable molecular level information in relation to the alternative paths to tumor development and to that of HPV(-) HNCs. Together, these results will shed light on stratifications of the HPV(+) HNCs and will help to guide personalized care for HPV(+) HNC patients. Overall design: 36 head and neck primary tumors (18 HPV+ and 18 HPV-) and their matched blood samples were collected and genotyped by Illumina OmniExpress SNP array. RNA-seq was also performed on the same set of tumor samples.
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