Subtypes of HPV-positive head and neck cancers are associated with HPV characteristics, copy number variations, PIK3CA mutation, and pathway signatures.
Ontology highlight
ABSTRACT: This SuperSeries is composed of the SubSeries listed below.
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.
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.
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.
Project description:Subtypes of HPV-positive head and neck cancers are associated with HPV characteristics, copy number variations, PIK3CA mutation, and pathway signatures.
Project description:Until recently, research on the molecular signatures of Human papillomavirus (HPV)-associated head and neck cancers mainly focused on their differences with respect to HPV-negative head and neck squamous cell carcinomas (HNSCCs). However, given the continuing high incidence level of HPV-related HNSCC, the time is ripe to characterize the heterogeneity that exists within these cancers. Here, we review research thus far on HPV-positive HNSCC molecular subtypes, and their relationship with clinical characteristics and HPV integration into the host genome. Different omics data including host transcriptomics and epigenomics, as well as HPV characteristics, can provide complementary viewpoints. Keratinization, mesenchymal differentiation, immune signatures, stromal cells and oxidoreductive processes all play important roles.
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors.
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors. A total of 141 samples were considered. CEL files were subject to quality control (QC) procedures using the Affymetrix Genotyping Console, and arrays that produced contrast QC measurements above the default threshold of .4 were removed from subsequent analysis. The remaining 99 CEL files were processed with aroma, and log2 intensity ratios were produced using a pooled collection of normal samples as a reference. After segmenting the log2 ratios with DNAcopy, the resulting copy number profiles were subjected to manual review. Arrays that produced low quality copy number profiles were removed from subsequent analysis. Copy number values from chr1 - chr22 were considered.
Project description:We investigated the frequency and function of mutations and increased copy number of the PIK3CA gene in lung cancers. PIK3CA mutations are one of the most common gene changes present in human cancers. We analyzed the mutational status of exons 9 and 20 and gene copy number of PIK3CA using 86 non-small cell lung cancer (NSCLC) cell lines, 43 small cell lung cancer (SCLC) cell lines, 3 extrapulmonary small cell cancer (ExPuSC) cell lines, and 691 resected NSCLC tumors and studied the relationship between PIK3CA alterations and mutational status of epidermal growth factor receptor (EGFR) signaling pathway genes (EGFR, KRAS, HER2, and BRAF). We also determined PIK3CA expression and activity and correlated the findings with effects on cell growth. We identified mutations in 4.7% of NSCLC cell lines and 1.6% of tumors of all major histologic types. Mutations in cell lines of small cell origin were limited to two ExPuSC cell lines. PIK3CA copy number gains were more frequent in squamous cell carcinoma (33.1%) than in adenocarcinoma (6.2%) or SCLC lines (4.7%). Mutational status of PIK3CA was not mutually exclusive to EGFR or KRAS. PIK3CA alterations were associated with increased phosphatidylinositol 3-kinase activity and phosphorylated Akt expression. RNA interference-mediated knockdown of PIK3CA inhibited colony formation of cell lines with PIK3CA mutations or gains but was not effective in PIK3CA wild-type cells. PIK3CA mutations or gains are present in a subset of lung cancers and are of functional importance.
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.