Christine Ng

Clinical Utility of Patient-Derived Xenografts to Determine Biomarkers of Prognosis and Map Resistance Pathways in EGFR-Mutant Lung Adenocarcinoma

PURPOSE Although epidermal growth factor receptor (EGFR) -mutated adenocarcinomas initially have high response rates to EGFR tyrosine kinase inhibitors (TKIs), most patients eventually develop resistance. Patient-derived xenografts (PDXs) are considered preferred preclinical models to study the biology of patient tumors. EGFR-mutant PDX models may be valuable tools to study the biology of these tumors and to elucidate mechanisms of resistance to EGFR-targeted therapies. METHODS Surgically resected early-stage non-small-cell lung carcinoma (NSCLC) tumors were implanted into nonobese diabetic severe combined immune deficient (NOD-SCID) mice. EGFR TKI treatment was initiated at tumor volumes of 150 μL. Gene expression analysis was performed using a microarray platform. RESULTS Of 33 lung adenocarcinomas with EGFR activating mutations, only 6 (18%) engrafted and could be propagated beyond passage one. Engraftment was associated with upregulation of genes involved in mitotic checkpoint and cell proliferation. A differentially expressed gene set between engrafting and nonengrafting patients could identify patients harboring EGFR-mutant tumor with significantly different prognoses in The Cancer Genome Atlas Lung Adenocarcinoma datasets. The PDXs included models with variable sensitivity to first- and second-generation EGFR TKIs and the monoclonal antibody cetuximab. All EGFR-mutant NSCLC PDXs studied closely recapitulated their corresponding patient tumor phenotype and clinical course, including response pattern to EGFR TKIs. CONCLUSION PDX models closely recapitulate primary tumor biology and clinical outcome. They may serve as important laboratory models to investigate mechanisms of resistance to targeted therapies, and for preclinical testing of novel treatment strategies.

Integrin α11β1 regulates cancer stromal stiffness and promotes tumorigenicity and metastasis in non-small cell lung cancer

Integrin α11β1 is a stromal cell-specific receptor for fibrillar collagens and is overexpressed in carcinoma-associated fibroblasts (CAFs). We have investigated its direct role in cancer progression by generating severe combined immune deficient (SCID) mice deficient in integrin α11 (α11) expression. The growth of A549 lung adenocarcinoma cells and two patient-derived non-small cell lung carcinoma (NSCLC) xenografts in these α11 knockout (α11−/−) mice was significantly impeded, as compared with wild-type (α11+/+) SCID mice. Orthotopic implantation of a spontaneously metastatic NCI-H460SM cell line into the lungs of α11−/− and α11+/+ mice showed significant reduction in the metastatic potential of these cells in the α11−/− mice. We identified that collagen cross-linking is associated with stromal α11 expression, and the loss of tumor stromal α11 expression was correlated with decreased collagen reorganization and stiffness. This study shows the role of integrin α11β1, a receptor for fibrillar collagen in differentiation of fibroblasts into CAFs. Furthermore, our data support an important role for α11 signaling pathway in CAFs, promoting tumor growth and metastatic potential of NSCLC cells and being closely associated with collagen cross-linking and the organization and stiffness of fibrillar collagen matrices.

Novel combinations of PI3K-mTOR inhibitors with dacomitinib or chemotherapy in PTEN-deficient patient-derived tumor xenografts

PTEN inactivation occurs commonly in human cancers and putatively activates the PI3K/AKT/ mTOR pathway. Activation of this pathway has been involved in resistance to chemotherapy or anti-EGFR/HER2 therapies. We evaluated the combination of PI3K-mTOR inhibitors with chemotherapy or the pan-HER inhibitor dacomitinib in PTEN-deficient patient-derived tumor xenografts (PDX). Three PDXs were selected for their lack of PTEN expression by immunohistochemistry: a triple-negative breast cancer (TNBC), a KRAS G12R low-grade serous ovarian cancer (LGSOC), and KRAS G12C and TP53 R181P lung adenocarcinoma (LADC). Two dual PI3K-mTOR inhibitors were evaluated—PF-04691502 and PF-05212384—in combination with cisplatin, paclitaxel, or dacomitinib. The addition of PI3K-mTOR inhibitors to cisplatin or paclitaxel increased the activity of chemotherapy in the TNBC and LGSOC models; whereas no added activity was observed in the LADC model. Pharmacodynamic modulation of pS6 and pAKT was observed in the group treated with PI3K-mTOR inhibitor. Our research suggests that the addition of a PI3K-mTOR inhibitor may enhance tumor growth inhibition when compared to chemotherapy alone in certain PTEN-deficient PDXs. However, this benefit was absent in the KRAS and TP53 mutant LADC model. The role of PTEN deficiency in the antitumor activity of these combinations should be further investigated in the clinic.

Compendium of TCDD-mediated transcriptomic response datasets in mammalian model systems

Background2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptional effects of ligand-activated AHR.ResultsSpecifically, we have created a datasets package – TCDD.Transcriptomics – for the R statistical environment, consisting of 63 unique experiments comprising 377 samples, including various combinations of 3 species (human derived cell lines, mouse and rat), 4 tissue types (liver, kidney, white adipose tissue and hypothalamus) and a wide range of TCDD exposure times and doses. These datasets have been fully standardized using consistent preprocessing and annotation packages (available as of September 14, 2015). To demonstrate the utility of this R package, a subset of “AHR-core” genes were evaluated across the included datasets. Ahrr, Nqo1 and members of the Cyp family were significantly induced following exposure to TCDD across the studies as expected while Aldh3a1 was induced specifically in rat liver. Inmt was altered only in liver tissue and primarily by rat-AHR.ConclusionsAnalysis of the “AHR-core” genes demonstrates a continued need for studies surrounding the impact of AHR-activity on the transcriptome; genes believed to be consistently regulated by ligand-activated AHR show surprisingly little overlap across species and tissues. Until now, a comprehensive assessment of the transcriptome across these studies was challenging due to differences in array platforms, processing methods and annotation versions. We believe that this package, which is freely available for download (http://labs.oicr.on.ca/boutros-lab/tcdd-transcriptomics) will prove to be a highly beneficial resource to the scientific community evaluating the effects of TCDD exposure as well as the variety of functions of the AHR.

Valection: design optimization for validation and verification studies

BackgroundPlatform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile.ResultsTo determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets.ConclusionsValection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection