Genome and transcriptome analysis of patient-derived xenografts (PDXs)
The analysis of NGS-based genome and transcriptome data from PDXs represents a technical challenge due to the presence of mouse-derived surrounding tissues (stroma, endothelial cells, etc ). The sequencing reads generated from these models originate from the engrafted human tumor but they can also be mixed with those derived from the murine environment. The proportion of human versus murine reads can vary widely from sample to sample, thus potentially impacting on the sensitivity and specificity of the analysis. Alacris Theranostics has developed appropriate strategies for circumventing these problems in the analysis of PDXs.
The analysis of DNA and RNA-based NGS data require different computational methods. Alacris has developed an in silico workflow for DNA and RNA analysis of PDXs, that we have applied successfully to NGS data generated from more than 200 PDXs (colorectal cancer, leukemia, melanoma).
Range of analysis routinely performed
WES/WGS: germline variants, tumor-specific somatic alterations, single-nucleotide variants, small insertions/deletions, copy-number alterations
RNAseq: gene expression analysis distinguishing between the gene expression of the tumor and the contribution of the mouse stroma with high accuracy
We also offer advanced analysis of these data using statistical and machine learning approaches providing the possibility to link your NGS data with drug sensitivity measurements for biomarker identification.
Schütte et al.
Cancer Precision Medicine: Why More Is More and DNA Is Not Enough
Public Health Genomics, 2017 Jun 9. doi: 10.1159/000477157, PMID: 28595192 [Abstract]
Fischer et al.
Genomics and drug profiling of fatal TCF3-HLF−positive acute lymphoblastic leukemia identifies recurrent mutation patterns and therapeutic options.
Nature Genetics, 2015 Jul 27. doi: 10.1038/ng.3362 [Abstract]