Anoikis-resistant subpopulations of human osteosarcoma display significant chemoresistance and are sensitive to targeted epigenetic therapies predicted by expression profiling.

BACKGROUND: Osteosarcoma (OS) is the most common type of solid bone cancer, with latent metastasis being a typical mode of disease progression and a major contributor to poor prognosis. For this to occur, cells must resist anoikis and be able to recapitulate tumorigenesis in a foreign microenvironment. Finding novel approaches to treat osteosarcoma and target those cell subpopulations that possess the ability to resist anoikis and contribute to metastatic disease is imperative. Here we investigate anchorage-independent (AI) cell growth as a model to better characterize anoikis resistance in human osteosarcoma while using an expression profiling approach to identify and test targetable signaling pathways. METHODS: Established human OS cell lines and patient-derived human OS cell isolates were subjected to growth in either adherent or AI conditions using Ultra-Low Attachment plates in identical media conditions. Growth rate was assessed using cell doubling times and chemoresistance was assessed by determining cell viability in response to a serial dilution of either doxorubicin or cisplatin. Gene expression differences were examined using quantitative reverse-transcription PCR and microarray with principal component and pathway analysis. In-vivo OS xenografts were generated by either subcutaneous or intratibial injection of adherent or AI human OS cells into athymic nude mice. Statistical significance was determined using student's t-tests with significance set at α=0.05. RESULTS: We show that AI growth results in a global gene expression profile change accompanied by significant chemoresistance (up to 75 fold, p<0.05). AI cells demonstrate alteration of key mediators of mesenchymal differentiation (ß-catenin, Runx2), stemness (Sox2), proliferation (c-myc, Akt), and epigenetic regulation (HDAC class 1). AI cells were equally tumorigenic as their adherent counterparts, but showed a significantly decreased rate of growth in-vitro and in-vivo (p<0.05). Treatment with the pan-histone deacetylase inhibitor vorinostat and the DNA methyltransferase inhibitor 5-azacytidine mitigated AI growth, while 5-azacytidine sensitized anoikis-resistant cells to doxorubicin (p<0.05). CONCLUSIONS: These data demonstrate remarkable plasticity in anoikis-resistant human osteosarcoma subpopulations accompanied by a rapid development of chemoresistance and altered growth rates mirroring the early stages of latent metastasis. Targeting epigenetic regulation of this process may be a viable therapeutic strategy.

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.

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.

Patient-Derived Xenograft Models of Colorectal Cancer: Procedures for Engraftment and Propagation.

Preclinical compounds tested in animal models often demonstrate limited efficacy when transitioned into patients. As a result, individuals are assigned to treatment regimens that may be ineffective at treating their disease. The development of more clinically relevant models, such as patient-derived xenografts (PDXs), will (1) more completely mimic the human condition and (2) more accurately predict tumor responses to previously untested therapeutics.PDX models are clinically relevant as tumor tissue is implanted directly from human donor to the mouse recipient. Therefore, these models prevent cell population selection, intentional or unintentional, as the human tissue adapts to an in vitro, two-dimensional environment prior to implantation into a three-dimensional in vivo murine host. Often, cell heterogeneity and tumor architecture can be maintained from human to the PDX model in the mouse. This protocol describes the engraftment and propagation processes for establishing colorectal (CRC) PDX models in mice, using tumor tissue from human subjects.

Discovery of cancer biomarkers through the use of mouse models.

Although our understanding of the molecular pathogenesis of common types of cancer has improved considerably, the development of effective strategies for cancer diagnosis and treatment have lagged behind. Mouse models of cancer potentially represent an efficient means for uncovering diagnostic markers as genetic alterations associated with human tumors can be engineered in mice. In addition, defined stages of tumor development, breeding conditions, and blood sampling can all be controlled and standardized to limit heterogeneity. Alternatively human cancer cells can be injected into mice and tumor development monitored in xenotransplants. Mouse-based studies promise to elucidate a repertoire of protein changes that occur in blood and biological fluids during tumor development. This is illustrated in a study in which we have applied a three-dimensional intact protein analysis system (IPAS) to elucidate detectable protein changes in serum from immunodeficient mice with lung xenografts from orthotopically implanted human A549 lung adenocarcinoma cells. With sufficiently detailed protein sequence identifications, the observed protein changes can be attributed to either the host mouse or the human tumor cells. It is noteworthy that the majority of increases identified have corresponded to relatively abundant serum proteins, some of which have previously been reported as increased in the sera of cancer patients. Proteomic studies of mouse models of cancer allow assessment of the range of changes in plasma proteins that occur with tumor development and may lead to the identification of potential cancer markers applicable to humans.

Analysis of tumor-host interactions by gene expression profiling of lung adenocarcinoma xenografts identifies genes involved in tumor formation.

Tumor cell lines are relied on extensively for cancer investigations, yet cultured cells in an in vitro environment differ considerably in behavior compared with those of the same cancer cells that proliferate and form tumors in vivo. To uncover gene expression changes related to tumor formation, gene expression profiles of human lung adenocarcinoma (A549) cells grown as lung tumors in immune-compromised mice were compared with profiles of the same cells grown in vitro. Additionally, profiles of uninvolved adjacent mouse tissue were determined. A profound interplay between cancer cells and the host was shown that affected a complex protein interaction network involving processes of extracellular interaction, growth factor signaling, hemostasis, immune response, and transcriptional regulation. Growth in vivo of A549 cells, which carry an activating k-ras mutation, induced changes in gene expression that corresponded highly to a pattern characteristic of human lung tumors with k-ras mutation. Cytokines interleukin-4, interleukin-6, and IFN-gamma each induced distinct in vitro genomic responses in cancer cells that emulated many of the changes in gene expression observed in vivo. Genes that were both selectively induced in vivo and overexpressed in human lung adenocarcinoma tumors included CSPG2, which has not been associated previously with tumor formation. Knockdown in A549 of CSPG2 by RNA interference significantly inhibited tumor growth in vivo but not in vitro. Thus, analysis of tumor xenografts by gene expression profiling has the potential for identifying genes involved in tumor development that may not be expressed in cancer cells grown in vitro.

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.

Establishment of genetically diverse patient-derived xenografts of colorectal cancer.

Preclinical compounds tested in animal models often show limited efficacy when transitioned into human clinical trials. As a result, many patients are stratified into treatment regimens that have little impact on their disease. In order to create preclinical models that can more accurately predict tumor responses, we established patient-derived xenograft (PDX) models of colorectal cancer (CRC). Surgically resected tumor specimens from colorectal cancer patients were implanted subcutaneously into athymic nude mice. Following successful establishment, fourteen models underwent further evaluation to determine whether these models exhibit heterogeneity, both at the cellular and genetic level. Histological review revealed properties not found in CRC cell lines, most notably in overall architecture (predominantly columnar epithelium with evidence of gland formation) and the presence of mucin-producing cells. Custom CRC gene panels identified somatic driver mutations in each model, and therapeutic efficacy studies in tumor-bearing mice were designed to determine how models with known mutations respond to PI3K, mTOR, or MAPK inhibitors. Interestingly, MAPK pathway inhibition drove tumor responses across most models tested. Noteworthy, the MAPK inhibitor PD0325901 alone did not significantly mediate tumor response in the context of a KRAS(G12D) model, and improved tumor responses resulted when combined with mTOR inhibition. As a result, these genetically diverse models represent a valuable resource for preclinical efficacy and drug discovery studies.