Subtypes of HPV-positive head and neck cancers are associated with HPV characteristics, copy number variations, PIK3CA mutation, and pathway signatures.
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ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE74956
PROVIDER: PRJNA302001 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR2932820_1.fastq.gz | Fastqsanger.gz | |||
| SRR2932820_2.fastq.gz | Fastqsanger.gz | |||
| SRR2932830_1.fastq.gz | Fastqsanger.gz | |||
| SRR2932830_2.fastq.gz | Fastqsanger.gz | |||
| SRR2932840_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description: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.
2016-05-13 | GSE74949 | GEO
Project description: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. 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.
2016-05-13 | E-GEOD-74927 | biostudies-arrayexpress
Project description: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.
2016-05-13 | GSE74927 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-05-13 | GSE74956 | GEO
Project description:PurposeThere is substantial heterogeneity within human papillomavirus (HPV)-associated head and neck cancer (HNC) tumors that predispose them to different outcomes; however, the molecular heterogeneity in this subgroup is poorly characterized due to various historical reasons.Experimental designWe performed unsupervised gene expression clustering on deeply annotated (transcriptome and genome) HPV(+) HNC samples from two cohorts (84 total primary tumors), including 18 HPV(-) HNC samples, to discover subtypes and characterize the differences between subgroups in terms of their HPV characteristics, pathway activity, whole-genome somatic copy number alterations, and mutation frequencies.ResultsWe identified two distinct HPV(+) subtypes (namely HPV-KRT and HPV-IMU). HPV-KRT is characterized by elevated expression of genes in keratinocyte differentiation and oxidation-reduction process, whereas HPV-IMU has strong immune response and mesenchymal differentiation. The differences in expression are likely connected to the differences in HPV characteristics and genomic changes. HPV-KRT has more genic viral integration, lower E2/E4/E5 expression levels, and higher ratio of spliced to full-length HPV oncogene E6 than HPV-IMU; the subgroups also show differences in copy number alterations and mutations, in particular the loss of chr16q in HPV-IMU and gain of chr3q and PIK3CA mutation in HPV-KRT.ConclusionsOur characterization of two subtypes of HPV(+) HNC tumors provides valuable molecular level information that point to two main carcinogenic paths. Together, these results shed light on stratifications of the HPV(+) HNCs and will help to guide personalized care for HPV(+) HNC patients. Clin Cancer Res; 22(18); 4735-45. ©2016 AACR.
| S-EPMC5026546 | biostudies-literature
Project description:Profiling of mouse mammary tumours that have developed in a mouse model expressing mutant Pik3ca^H1047R at endogenous level under control of the MMTV promoter (Tikoo et al., PLoS one 2012). Copy number variations in tumours (compared to matching liver DNA) were detected using Agilent Sureprint microarrays.
2016-06-04 | GSE47635 | GEO
Project description:BackgroundCopy number variation (CNV) represents another important source of genetic variation complementary to single nucleotide polymorphism (SNP). High-density SNP array data have been routinely used to detect human CNVs, many of which have significant functional effects on gene expression and human diseases. In the dairy industry, a large quantity of SNP genotyping results are becoming available and can be used for CNV discovery to understand and accelerate genetic improvement for complex traits.ResultsWe performed a systematic analysis of CNV using the Bovine HapMap SNP genotyping data, including 539 animals of 21 modern cattle breeds and 6 outgroups. After correcting genomic waves and considering the pedigree information, we identified 682 candidate CNV regions, which represent 139.8 megabases (~4.60%) of the genome. Selected CNVs were further experimentally validated and we found that copy number "gain" CNVs were predominantly clustered in tandem rather than existing as interspersed duplications. Many CNV regions (~56%) overlap with cattle genes (1,263), which are significantly enriched for immunity, lactation, reproduction and rumination. The overlap of this new dataset and other published CNV studies was less than 40%; however, our discovery of large, high frequency (> 5% of animals surveyed) CNV regions showed 90% agreement with other studies. These results highlight the differences and commonalities between technical platforms.ConclusionsWe present a comprehensive genomic analysis of cattle CNVs derived from SNP data which will be a valuable genomic variation resource. Combined with SNP detection assays, gene-containing CNV regions may help identify genes undergoing artificial selection in domesticated animals.
| S-EPMC3053260 | biostudies-literature
Project description:We report the first RNA-Seq experiments profiling the effects of DEK loss in HNSCC. Our data also incorporates HPV+ and HPV- tumors to idenfity HPV-dependent and -independent gene signatures.
2016-02-05 | GSE70462 | GEO
Project description:Introduction: Human Papilloma Virus (HPV) is associated with a subset of head and neck squamous cell carcinoma (HNSCC), between 15% and 35% of HNSCC harboring HPV, almost exclusively of subtype 16. Demographic and exposure differences between HPV-positive (+) and negative (-) HNSCCs suggest that HPV(+) tumors may constitute a subclass with different biology, while clinical differences have also been observed. In this study, gene expression profiles of HPV(+) and (-) tumors were compared to further explore the biological effect of HPV in HNSCC. Methods: Thirty-six HNSCC tumors were analyzed for gene expression using Affymetrix Human 133U Plus 2.0 GeneChip and for HPV using consensus primers for HPV L1, E6 and E7 by PCR and RT-PCR. Results: Eight (22%) of 36 tumors were positive for HPV, all of the HPV 16 subtype, and the HPV positive samples also expressed viral HPV E6 mRNA determined by RT-PCR. Patients with HPV(+) HNSCCs were on average younger than those with HPV(-) tumors (mean age 50.2 vs. 58.7). Statistical analysis using Significance Analysis of Microarrays (SAM) based on HPV status as a supervising parameter resulted in a list of 91 genes that were differentially expressed with statistical significance. Results for a sub-set of these genes were verified by RT-PCR. Genes highly expressed in HPV(+) samples included cell cycle regulators (p16INK4A, p18 and CDK2) and transcription factors (TAF7L, RFC4, RPA2 and TFDP2). The microarray data were also investigated using DIGMap to map genes by chromosomal location. A large number of genes on chromosome 3q24-qter was found to be overrepresented in HPV(+) tumors. Conclusion: The gene expression profile associated with HPV reflects alterations in cell cycle and proliferation signals. Further investigation of differentially expressed genes may reveal the unique pathways in HPV(+) tumors that may explain the different natural history and biological properties of these tumors. These properties may be exploited as a target of novel therapeutic agents in HNSCC treatment. Keywords: HPV, HNSCC, head and neck cancer, human, human papilloma virus
2005-11-28 | GSE3292 | GEO
Project description:We report the first RNA-Seq experiments profiling the effects of DEK loss in HNSCC. Our data also incorporates HPV+ and HPV- tumors to idenfity HPV-dependent and -independent gene signatures. RNA-Seq of DEK-dependent gene signatures in HNSCC cell lines
2016-02-05 | E-GEOD-70462 | biostudies-arrayexpress