Gene expression differences between matched pairs of ovarian cancer patient tumors and patient-derived xenografts.
Yuanhang LiuPritha ChananaJaime I DavilaXiaonan HouValentina ZanfagninCordelia D McGeheeEllen L GoodeEric C PolleyPaul HaluskaS John WerohaChen WangPublished in: Scientific reports (2019)
As patient derived xenograft (PDX) models are increasingly used for preclinical drug development, strategies to account for the nonhuman component of PDX RNA expression data are critical to its interpretation. A bioinformatics pipeline to separate donor tumor and mouse stroma transcriptome profiles was devised and tested. To examine the molecular fidelity of PDX versus donor tumors, we compared mRNA differences between paired PDX-donor tumors from nine ovarian cancer patients. 1,935 differentially expressed genes were identified between PDX and donor tumors. Over 90% (n = 1767) of these genes were down-regulated in PDX models and enriched in stroma-specific functions. Several protein kinases were also differentially expressed in PDX tumors, e.g. PDGFRA, PDGFRB and CSF1R. Upon in silico removal of these PDX-donor tumor differentially expressed genes, a stronger transcriptional resemblance between PDX-donor tumor pairs was seen (average correlation coefficient increases from 0.91 to 0.95). We devised and validated an effective bioinformatics strategy to separate mouse stroma expression from human tumor expression for PDX RNAseq. In addition, we showed most of the PDX-donor differentially expressed genes were implicated in stromal components. The molecular similarities and differences between PDX and donor tumors have implications in future therapeutic trial designs and treatment response evaluations using PDX models.
Keyphrases
- gene expression
- genome wide
- poor prognosis
- binding protein
- endothelial cells
- machine learning
- dna methylation
- transcription factor
- clinical trial
- mesenchymal stem cells
- computed tomography
- genome wide identification
- bioinformatics analysis
- single cell
- current status
- heat shock protein
- induced pluripotent stem cells
- molecular dynamics simulations