Expression of stromal genes associated with the angiogenic response are not differentiated between human tumour xenografts with divergent vascular morphologies.

Human tumour xenografts have commonly been used to explore the mechanisms of tumour angiogenesis and the interaction of tumour cells with their microenvironment, as well as predict potential utility of anti-angiogenic inhibitors across different tumour types. To investigate how well human tumour xenografts can be used to differentiate the effects of stromal targeting agents we performed a comparative assessment of the murine angiogenic response across a panel of pre-clinical tumour xenografts. By analysing a panel of 22 tumour xenografts with a range of vascular morphologies, micro-vessel densities and levels of fibroblast and inflammatory infiltrate, we have examined the relationship between angiogenic stroma and human tumour models. These models were studied using a combination of immunohistochemistry and species specific mRNA profiling to differentiate the tumour and stromal transcript mRNA profiles. Principal Component Analysis (PCA) and regression analysis was used to investigate the transcriptional relationships between the individual models and the correlation with the stromal architecture. We found the human tumour cell expressed factors to be independent of the murine host responses such as microvessel density, and fibroblast or macrophage cellular infiltrate. Moreover mRNA profiling of the mouse stroma suggested that the host response to the different tumours was relatively uniform despite differences in stromal structures within the tumour. Supporting this, models with different stromal compositions responded similarly to cediranib, a small molecule inhibitor of VEGF signalling. The data indicate that although the angiogenic response to the tumour results in reproducible stromal architectures, these responses are not differentiated at the level of gene expression.

Plasma ctDNA Analysis for Detection of the EGFR T790M Mutation in Patients with Advanced Non-Small Cell Lung Cancer.

INTRODUCTION: Tumor biopsies for detecting EGFR mutations in advanced NSCLC are invasive, costly, and not always feasible for patients with late-stage disease. The clinical utility of the cobas EGFR Mutation Test v2 (Roche Molecular Systems, Inc., Pleasanton, CA) with plasma samples from patients with NSCLC at disease progression after previous EGFR tyrosine kinase inhibitor therapy was investigated to determine eligibility for osimertinib treatment. METHODS: Matched tumor tissue and plasma samples from patients screened for the AURA extension and AURA2 phase II studies were tested for EGFR mutations by using tissue- and plasma-based cobas EGFR mutation tests. Plasma test performance was assessed by using the cobas tissue test and a next-generation sequencing method (MiSeq [Illumina Inc., San Diego, CA]) as references. The objective response rate, measured by blinded independent central review, was assessed in patients receiving osimertinib with a plasma T790M mutation-positive status. RESULTS: During screening, 551 patients provided matched tumor tissue and plasma samples. Pooled analysis of the positive and negative percent agreements between the cobas plasma and tissue tests for detection of T790M mutation were 61% and 79%, respectively. Comparing cobas plasma test with next-generation sequencing demonstrated positive and negative percent agreements of 90% or higher. The objective response rate was 64% (95% confidence interval: 57-70) in T790M mutation-positive patients by both cobas tissue and plasma tests (evaluable for response). CONCLUSIONS: The cobas plasma test detected the T790M mutation in 61% of tumor tissue T790M mutation-positive patients. To mitigate the risk of false-negative plasma results, patients with a negative plasma result should undergo a tissue test where feasible.

EGFR Mutation Analysis for Prospective Patient Selection in Two Phase II Registration Studies of Osimertinib.

INTRODUCTION: Osimertinib is an oral, central nervous system-active, EGFR tyrosine kinase inhibitor (TKI) for the treatment of EGFR T790M-positive advanced NSCLC. Here we have evaluated EGFR mutation frequencies in two phase II studies of osimertinib (AURA extension and AURA2). METHODS: After progression while receiving their latest line of therapy, patients with EGFR mutation-positive advanced NSCLC provided tumor samples for mandatory central T790M testing for the study selection criteria. Tumor tissue mutation analysis for patient selection was performed with the Roche cobas EGFR Mutation Test (European Conformity-in vitro diagnostic, labeled investigational use only) (Roche Molecular Systems, Pleasanton, CA). Patients should not have been prescreened for T790M mutation status. The cobas test results were compared with those of the MiSeq next-generation sequencing system (Illumina, San Diego, CA), which was used as a reference method. RESULTS: Samples from 324 and 373 patients screened for AURA extension and AURA2, respectively, produced valid cobas test results. The T790M detection rates were similar between AURA extension and AURA2 (64% and 63%, respectively). The pooled T790M rate was 63%, with no difference by ethnicity (63% for Asian and non-Asian patients alike) or immediately prior treatment with an EGFR TKI (afatinib, 69%; erlotinib, 69%; and gefitinib, 63%). A higher proportion of patients had T790M detected against a background of exon 19 deletions versus L858R mutation (73% versus 58% [p = 0.0002]). In both trials the cobas test demonstrated high sensitivity (positive percent agreement) and specificity (negative percent agreement) for T790M detection when compared with the next-generation sequencing reference method: positive percent agreement of 91% versus 89% and negative percent agreement of 97% versus 98%. CONCLUSIONS: In both trials, the rate of detection of T790M mutation in patients with advanced NSCLC was approximately 63% and was unaffected by immediately prior treatment with an EGFR TKI or ethnicity.

RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib.

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers.

Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines.

BACKGROUND: Colorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment. METHODS: We applied a new unsupervised, iterative approach to stratify CRC tumor samples into subtypes based on genome-wide mRNA expression data. By applying this stratification to several CRC cell line panels and integrating pharmacological response data, we generated hypotheses regarding the targeted treatment of different subtypes. RESULTS: In agreement with earlier studies, the two dominant CRC subtypes are highly correlated with a gene expression signature of epithelial-mesenchymal-transition (EMT). Notably, further dividing these two subtypes using iNMF (iterative Non-negative Matrix Factorization) revealed five subtypes that exhibit activation of specific signaling pathways, and show significant differences in clinical and molecular characteristics. Importantly, we were able to validate the stratification on independent, published datasets comprising over 1600 samples. Application of this stratification to four CRC cell line panels comprising 74 different cell lines, showed that the tumor subtypes are well represented in available CRC cell line panels. Pharmacological response data for targeted inhibitors of SRC, WNT, GSK3b, aurora kinase, PI3 kinase, and mTOR, showed significant differences in sensitivity across cell lines assigned to different subtypes. Importantly, some of these differences in sensitivity were in concordance with high expression of the targets or activation of the corresponding pathways in primary tumor samples of the same subtype. CONCLUSIONS: The stratification presented here is robust, captures important features of CRC, and offers valuable insight into functional differences between CRC subtypes. By matching the identified subtypes to cell line panels that have been pharmacologically characterized, it opens up new possibilities for the development and application of targeted therapies for defined CRC patient sub-populations.