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Overall survival remains very poor for patients diagnosed as having head and neck squamous cell carcinoma (HNSCC). Identification of additional biomarkers and novel therapeutic strategies are important for improving patient outcomes. Patient-derived xenografts (PDXs), generated by implanting fresh tumor tissue directly from patients into immunodeficient mice, recapitulate many of the features of their corresponding clinical cancers, including histopathological and molecular profiles. Using a large collection of PDX models of HNSCC, we demonstrate that rapid engraftment into immunocompromised mice is highly prognostic and show that genomic deregulation of the G1/S checkpoint pathway correlates with engraftment. Furthermore, CCND1 and CDKN2A genomic alterations are predictive of response to the CDK4and CDK6 inhibitor abemaciclib. Overall, our study supports the pursuit of CDK4 and CDK6 inhibitors as a therapeutic strategy for a substantial proportion of HNSCC patients and demonstrates the potential of using PDX models to identify targeted therapies that will benefit patients who have the poorest outcomes.
Pubmed ID: 30380421 RIS Download
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A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsNetwork of ftp and web servers around world that store identical, up to date, versions of code and documentation for R. Package archive network for R programming language.
View all literature mentionsSoftware package for copy number estimation from tumor genome sequencing data.Tools to analyze genomic sequencing data from paired normal-tumor samples, including cellularity and ploidy estimation; mutation and copy number (allele-specific and total copy number) detection, quantification and visualization.
View all literature mentionsThis monoclonal targets GAPDH
View all literature mentionsThis monoclonal targets Retinoblastoma Protein
View all literature mentionsThis polyclonal targets Phospho-Rb (Ser807/811)
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th,2023. Software package for genome analysis. Used for analysis of next generation genomic data in cancer.
View all literature mentionsSoftware for the reliable and accurate identification of somatic point mutations in next generation sequencing data of cancer genomes.
View all literature mentionsSoftware for somatic single nucleotide variant (SNV) and small indel detection from sequencing data of matched tumor-normal samples. The method employs a novel Bayesian approach which represents continuous allele frequencies for both tumor and normal samples, whilst leveraging the expected genotype structure of the normal. This is achieved by representing the normal sample as a mixture of germline variation with noise, and representing the tumor sample as a mixture of the normal sample with somatic variation. A natural consequence of the model structure is that sensitivity can be maintained at high tumor impurity without requiring purity estimates. The method has superior accuracy and sensitivity on impure samples compared to approaches based on either diploid genotype likelihoods or general allele-frequency tests.
View all literature mentionsA platform-independent, technology-independent software tool for identifying SNPs and indels in massively parallel sequencing of individual and pooled samples. Given data for a single sample, VarScan identifies and filters germline variants based on read counts, base quality, and allele frequency. Given data for a tumor-normal pair, VarScan also determines the somatic status of each variant (Germline, Somatic, or LOH) by comparing read counts between samples. (entry from Genetic Analysis Software)
View all literature mentionsSoftware to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth. By separating SCNA profiles into underlying arm-level and focal alterations, they improve the estimation of background rates for each category.
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th,2023. Software package for genome analysis. Used for analysis of next generation genomic data in cancer.
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