The Efficacy and Safety of Sendai Viral Reprograming of Mouse Primary Cells Using Human Vectors.

Induced pluripotent stem cells (iPSCs) remain a promising approach to target diseases with a loss of functional parenchyma. This technology comes with a number of concerns for clinical applications, including teratogenic potential and genomic instability. Here we focused on evaluating the safety of cross-species Sendai viral reprogramming, as well as investigating the transcriptional dynamics during reprogramming and differentiation. We established that Sendai viral vectors carrying human Oct4, Sox2, Klf4, and c-Myc (OSKM) could produce mouse iPSCs free of transduced viral materials. Gene expression analysis revealed an efficient silencing of the virally-introduced human pluripotency factors and upregulation of the endogenous pluripotency network over time. In addition, single cell gene expression analysis of proof-of-principle-derived cardiomyocytes revealed distinct expression patterns indicative of subspecialized cardiac cell lineages. Moreover, our results demonstrate the importance of monitoring genomic aberrations before any clinical or preclinical applications, as we detected a high prevalence of chromosomal instability. Taken together, we demonstrated the successful use of a clinically germane method to reprogram terminally differentiated mouse cells and their potential to generate specialized cardiac cell types. Additionally, our results suggest a plasticity of OSKM to reprogram more divergent species and provide a new application of an established reprogramming approach.

Melanoma patient derived xenografts acquire distinct Vemurafenib resistance mechanisms.

Variable clinical responses, tumor heterogeneity, and drug resistance reduce long-term survival outcomes for metastatic melanoma patients. To guide and accelerate drug development, we characterized tumor responses for five melanoma patient derived xenograft models treated with Vemurafenib. Three BRAF(V600E) models showed acquired drug resistance, one BRAF(V600E) model had a complete and durable response, and a BRAF(V600V) model was expectedly unresponsive. In progressing tumors, a variety of resistance mechanisms to BRAF inhibition were uncovered, including mutant BRAF alternative splicing, NRAS mutation, COT (MAP3K8) overexpression, and increased mutant BRAF gene amplification and copy number. The resistance mechanisms among the patient derived xenograft models were similar to the resistance pathways identified in clinical specimens from patients progressing on BRAF inhibitor therapy. In addition, there was both inter- and intra-patient heterogeneity in resistance mechanisms, accompanied by heterogeneous pERK expression immunostaining profiles. MEK monotherapy of Vemurafenib-resistant tumors caused toxicity and acquired drug resistance. However, tumors were eradicated when Vemurafenib was combined the MEK inhibitor. The diversity of drug responses among the xenograft models; the distinct mechanisms of resistance; and the ability to overcome resistance by the addition of a MEK inhibitor provide a scheduling rationale for clinical trials of next-generation drug combinations.

Using a rhabdomyosarcoma patient-derived xenograft to examine precision medicine approaches and model acquired resistance.

BACKGROUND: Precision (Personalized) medicine has the potential to revolutionize patient health care especially for many cancers where the fundamental disease etiology remains either elusive or has no available therapy. Here we outline a study in alveolar rhabdomyosarcoma, in which we use gene expression profiling and a series of drug prediction algorithms combined with a matched patient-derived xenograft (PDX) model to test bioinformatically predicted therapies. PROCEDURE: A PDX model was developed from a patient biopsy and a number of drugs identified using gene expression analysis in combination with drug prediction algorithms. Drugs chosen from each of the predictive methodologies, along with the patient's standard-of-care therapy (ICE-T), were tested in vivo in the PDX tumor. A second study was initiated using the tumors that re-grew following the ICE-T treatment. Further expression analysis identified additional therapies with potential anti-tumor efficacy. RESULTS: A number of the predicted therapies were found to be active against the tumors in particular BGJ398 (FGFR2) and ICE-T. Re-transplanted ICE-T treated tumorgrafts demonstrated a decreased response to ICE-T recapitulating the patient's refractory disease. Gene expression profiling of the ICE-T treated tumorgrafts identified cytarabine (SLC29A1) as a potential therapy, which was shown, along with BGJ398, to be highly active in vivo. CONCLUSIONS: This study illustrates that PDX models are suitable surrogates for testing potential therapeutic strategies based on gene expression analysis, modeling clinical drug resistance and hold the potential to assist in guiding prospective patient care.

A multi-site feasibility study for personalized medicine in canines with osteosarcoma.

BACKGROUND: A successful therapeutic strategy, specifically tailored to the molecular constitution of an individual and their disease, is an ambitious objective of modern medicine. In this report, we highlight a feasibility study in canine osteosarcoma focused on refining the infrastructure and processes required for prospective clinical trials using a series of gene expression-based Personalized Medicine (PMed) algorithms to predict suitable therapies within 5 days of sample receipt. METHODS: Tumor tissue samples were collected immediately following limb amputation and shipped overnight from veterinary practices. Upon receipt (day 1), RNA was extracted from snap-frozen tissue, with an adjacent H&E section for pathological diagnosis. Samples passing RNA and pathology QC were shipped to a CLIA-certified laboratory for genomic profiling. After mapping of canine probe sets to human genes and normalization against a (normal) reference set, gene level Z-scores were submitted to the PMed algorithms. The resulting PMed report was immediately forwarded to the veterinarians. Upon receipt and review of the PMed report, feedback from the practicing veterinarians was captured. RESULTS: 20 subjects were enrolled over a 5 month period. Tissue from 13 subjects passed both histological and RNA QC and were submitted for genomic analysis and subsequent PMed analysis and report generation. 11 of the 13 samples for which PMed reports were produced were communicated to the veterinarian within the target 5 business days. Of the 7 samples that failed QC, 4 were due to poor RNA quality, whereas 2 were failed following pathological review. Comments from the practicing veterinarians were generally positive and constructive, highlighting a number of areas for improvement, including enhanced education regarding PMed report interpretation, drug availability, affordable pricing and suitable canine dosing. CONCLUSIONS: This feasibility trial demonstrated that with the appropriate infrastructure and processes it is possible to perform an in-depth molecular analysis of a patient's tumor in support of real time therapeutic decision making within 5 days of sample receipt. A number of areas for improvement have been identified that should reduce the level of sample attrition and support clinical decision making.

Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq)/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA) provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with literature describing successful use of drugs targeting this pathway in lymphomas.

Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue.

BACKGROUND: There is resurgence within drug and biomarker development communities for the use of primary tumorgraft models as improved predictors of patient tumor response to novel therapeutic strategies. Despite perceived advantages over cell line derived xenograft models, there is limited data comparing the genotype and phenotype of tumorgrafts to the donor patient tumor, limiting the determination of molecular relevance of the tumorgraft model. This report directly compares the genomic characteristics of patient tumors and the derived tumorgraft models, including gene expression, and oncogenic mutation status. METHODS: Fresh tumor tissues from 182 cancer patients were implanted subcutaneously into immune-compromised mice for the development of primary patient tumorgraft models. Histological assessment was performed on both patient tumors and the resulting tumorgraft models. Somatic mutations in key oncogenes and gene expression levels of resulting tumorgrafts were compared to the matched patient tumors using the OncoCarta (Sequenom, San Diego, CA) and human gene microarray (Affymetrix, Santa Clara, CA) platforms respectively. The genomic stability of the established tumorgrafts was assessed across serial in vivo generations in a representative subset of models. The genomes of patient tumors that formed tumorgrafts were compared to those that did not to identify the possible molecular basis to successful engraftment or rejection. RESULTS: Fresh tumor tissues from 182 cancer patients were implanted into immune-compromised mice with forty-nine tumorgraft models that have been successfully established, exhibiting strong histological and genomic fidelity to the originating patient tumors. Comparison of the transcriptomes and oncogenic mutations between the tumorgrafts and the matched patient tumors were found to be stable across four tumorgraft generations. Not only did the various tumors retain the differentiation pattern, but supporting stromal elements were preserved. Those genes down-regulated specifically in tumorgrafts were enriched in biological pathways involved in host immune response, consistent with the immune deficiency status of the host. Patient tumors that successfully formed tumorgrafts were enriched for cell signaling, cell cycle, and cytoskeleton pathways and exhibited evidence of reduced immunogenicity. CONCLUSIONS: The preservation of the patient's tumor genomic profile and tumor microenvironment supports the view that primary patient tumorgrafts provide a relevant model to support the translation of new therapeutic strategies and personalized medicine approaches in oncology.

Glycogene expression alterations associated with pancreatic cancer epithelial-mesenchymal transition in complementary model systems.

BACKGROUND: The ability to selectively detect and target cancer cells that have undergone an epithelial-mesenchymal transition (EMT) may lead to improved methods to treat cancers such as pancreatic cancer. The remodeling of cellular glycosylation previously has been associated with cell differentiation and may represent a valuable class of molecular targets for EMT. METHODOLOGY/PRINCIPAL FINDINGS: As a first step toward investigating the nature of glycosylation alterations in EMT, we characterized the expression of glycan-related genes in three in-vitro model systems that each represented a complementary aspect of pancreatic cancer EMT. These models included: 1) TGFß-induced EMT, which provided a look at the active transition between states; 2) a panel of 22 pancreatic cancer cell lines, which represented terminal differentiation states of either epithelial-like or mesenchymal-like; and 3) actively-migrating and stationary cells, which provided a look at the mechanism of migration. We analyzed expression data from a list of 587 genes involved in glycosylation (biosynthesis, sugar transport, glycan-binding, etc.) or EMT. Glycogenes were altered at a higher prevalence than all other genes in the first two models (p<0.05 and <0.005, respectively) but not in the migration model. Several functional themes were shared between the induced-EMT model and the cell line panel, including alterations to matrix components and proteoglycans, the sulfation of glycosaminoglycans; mannose receptor family members; initiation of O-glycosylation; and certain forms of sialylation. Protein-level changes were confirmed by Western blot for the mannose receptor MRC2 and the O-glycosylation enzyme GALNT3, and cell-surface sulfation changes were confirmed using Alcian Blue staining. CONCLUSIONS/SIGNIFICANCE: Alterations to glycogenes are a major component of cancer EMT and are characterized by changes to matrix components, the sulfation of GAGs, mannose receptors, O-glycosylation, and specific sialylated structures. These results provide leads for targeting aggressive and drug resistant forms of pancreatic cancer cells.