Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers

Abstract

The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX).Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6. Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment.In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

Consensus Analysis of Whole Transcriptome Profiles from Two Breast Cancer Patient Cohorts Reveals Long Non-Coding RNAs Associated with Intrinsic Subtype and the Tumour Microenvironment

“…We next checked for evidence of expression in samples expected to consist of exclusively tumour cells, reasoning that lncRNAs expressed in clinical samples that typically contain a proportion of non-tumour cells (TCGA: mean tumour purity = 0.60±0.17, UBCS: 0.62±0.15), but with little or no expression in samples of high tumour cell purity, were likely stromal or immune cell specific. To do so, we calculated lncRNA expression levels across 41 breast cancer cell lines from the Cancer Cell Line Encyclopaedia [ 28 ] (CCLE; mean tumour purity = 0.99±0.01), and tumours from 10 breast cancer patient derived xenograft (PDX) models [ 29 ] (mean tumour purity = 0.99±0.01), in which tumour had been separated from stroma using an in silico species-specific mapping strategy [ 30 ]. For 5219 lncRNAs common to all three datasets, we then compared both median cell line and PDX expression to median expression across 47 UBCS samples achieving tumour purity>0.70.…”

Zebrafish Avatars towards Personalized Medicine—A Comparative Review between Avatar Models

“…These include endothelial cells to reconstruct blood and lymphatic systems, pericytes that cover endothelial cells, tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs) and other immune cells that constitute the complex TME [1,53,54]. These recruited cells can either be tissue-resident cells or cells that are summoned through systemic recruitment, many times coming from distant organs like the bone marrow [55,56].…”

An antibody-based approach for the in situ evaluation of mouse contribution in human stem cell-derived xenografts

“…Currently, many different approaches exist, which do not fullfill this set of criteria. The vast majority of them, including DNA 8,9 -and RNA [10][11][12][13] -based PCR and reverse transcription quantitative real-time PCR (RT-qPCR), species-specific transcriptome [14][15][16][17][18][19][20] and proteome 21,22 analyses as well as flow cytometry [23][24][25] , are molecular profiling approaches which require tissue dissociation or lysis and do not address host contribution in situ on a single cell level. To investigate the unperturbed interaction between the tumor and its microenvironment, the use of genetically modified cells or mouse models expressing fluorescent reporter proteins [26][27][28][29][30] might want to be avoided.…”