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Reference

High-resolution mutational profiling suggests the genetic validity of glioblastoma patient-derived pre-clinical models.

Paper Id
COSP31176
Authors
Yost SE,Pastorino S,Rozenzhak S,Smith EN,Chao YS,Jiang P,Kesari S,Frazer KA and Harismendy O
Affiliation
Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America.
Journal
PloS one 2013;8(2):e56185
ISSN:1932-6203
PUBMED:23441165
Abstract
Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM) primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient's tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.
Paper Status
Curated
Genes Analysed
506
Mutated Samples
8
Total No. of Samples
8
This tab shows genes with mutations in the selected study/paper [more details]
Genes Samples CDS Mutation AA Mutation
This tab shows genes without mutations in the selected study/paper [more details]
Non-Mutant Genes Gene Id (COSG)
This tab shows samples without mutations in the selected study/paper [more details]
Non-Mutant Samples Sample Id (COSS)
This tab shows mutated samples in the selected study/paper [more details]
Sample Name Mutation Count
This tab shows non coding variant in the selected study/paper [more details]
Sample ID Sample Name ID NCV Annotation Zygosity Chromosome Genome start Genome stop Genome version Strand WT seq Mut seq
This tab shows the copy number variation data for this study. Only variants (classified as gain or loss) are listed. [more details]
CNV Gene Sample Position Minor Allele Copy Number Average Ploidy

1. N/A represents cases where average ploidy value is not available( mostly ICGC samples). For some TCGA samples where minor allele information is not available the average ploidy value could not be calculated.

2. For TCGA samples, Ascat algorithm is used to calculate the average ploidy.

3. For CGP samples, Picnic algorithm is used to calculate the average ploidy.

Type
This tab shows a table of count of samples having gain or loss for all genes [more details]
Gene Gain Samples Loss Samples Samples Tested
This tab shows the fusion mutations observed in this sample [more details]
Gene Sample Name Id Sample(COSS) CDS Mutation Somatic status Zygosity Validated Type