Genome and Transcriptome analysis of Patient-derived xenografts (PDXs)

The analysis of NGS-based genome and transcriptome data pertaining to 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 contain reads originating from the engrafted human tumour but with an admixture from the murine environment, whose proportion may 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 roughly 200 PDXs (colorectal cancer, leukemia, melanoma).

Range of analysis routinely performed:

WES/WGS: germline variants, tumour-specific somatic alterations, single-nucleotide variants, small insertions/deletions, copy-number alterations

RNAseq: gene expression analysis distinguishing between the gene expression of the tumour and the contribution of the mouse stroma with high accuracy; gene fusion detection

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.

Fischer et al., Genomics and drug profiling of fatal TCF3-HLF-positive acute lymphoblastic leukemia identifies recurrent mutation patterns and therapeutic options, Nat. Genet. 2015, PMID: 26214592 [Abstract]