Animal models and their role in imaging-assisted co-clinical trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients\u27 tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials

Elevated Tumor Lactate and Efflux in High-grade Prostate Cancer demonstrated by Hyperpolarized 13C Magnetic Resonance Spectroscopy of Prostate Tissue Slice Cultures.

Non-invasive assessment of the biological aggressiveness of prostate cancer (PCa) is needed for men with localized disease. Hyperpolarized (HP) 13C magnetic resonance (MR) spectroscopy is a powerful approach to image metabolism, specifically the conversion of HP [1-13C]pyruvate to [1-13C]lactate, catalyzed by lactate dehydrogenase (LDH). Significant increase in tumor lactate was measured in high-grade PCa relative to benign and low-grade cancer, suggesting that HP 13C MR could distinguish low-risk (Gleason score ≤3 + 4) from high-risk (Gleason score ≥4 + 3) PCa. To test this and the ability of HP 13C MR to detect these metabolic changes, we cultured prostate tissues in an MR-compatible bioreactor under continuous perfusion. 31P spectra demonstrated good viability and dynamic HP 13C-pyruvate MR demonstrated that high-grade PCa had significantly increased lactate efflux compared to low-grade PCa and benign prostate tissue. These metabolic differences are attributed to significantly increased LDHA expression and LDH activity, as well as significantly increased monocarboxylate transporter 4 (MCT4) expression in high- versus low- grade PCa. Moreover, lactate efflux, LDH activity, and MCT4 expression were not different between low-grade PCa and benign prostate tissues, indicating that these metabolic alterations are specific for high-grade disease. These distinctive metabolic alterations can be used to differentiate high-grade PCa from low-grade PCa and benign prostate tissues using clinically translatable HP [1-13C]pyruvate MR

A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity

Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue–ECM boundary, rather than by differential homo- and heterotypic energies of cell–cell interaction. Surprisingly, interactions with the tissue–ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell–cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell–cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell–ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer

Comprehensive Drug Testing of Patient-derived Conditionally Reprogrammed Cells from Castration-resistant Prostate Cancer

AbstractBackgroundTechnology development to enable the culture of human prostate cancer (PCa) progenitor cells is required for the identification of new, potentially curative therapies for PCa.ObjectiveWe established and characterized patient-derived conditionally reprogrammed cells (CRCs) to assess their biological properties and to apply these to test the efficacies of drugs.Design, setting, and participantsCRCs were established from seven patient samples with disease ranging from primary PCa to advanced castration-resistant PCa (CRPC). The CRCs were characterized by genomic, transcriptomic, protein expression, and drug profiling.Outcome measurements and statistical analysisThe phenotypic quantification of the CRCs was done based on immunostaining followed by image analysis with Advanced Cell Classifier using Random Forest supervised machine learning. Copy number aberrations (CNAs) were called from whole-exome sequencing and transcriptomics using in-house pipelines. Dose-response measurements were used to generate multiparameter drug sensitivity scores using R-statistical language.Results and limitationsWe generated six benign CRC cultures which all had an androgen receptor-negative, basal/transit-amplifying phenotype with few CNAs. In three-dimensional cell culture, these cells could re-express the androgen receptor. The CRCs from a CRPC patient (HUB.5) displayed multiple CNAs, many of which were shared with the parental tumor. We carried out high-throughput drug-response studies with 306 emerging and clinical cancer drugs. Using the benign CRCs as controls, we identified the Bcl-2 family inhibitor navitoclax as the most potent cancer-specific drug for the CRCs from a CRPC patient. Other drug efficacies included taxanes, mepacrine, and retinoids.ConclusionsComprehensive cancer pharmacopeia-wide drug testing of CRCs from a CRPC patient highlighted both known and novel drug sensitivities in PCa, including navitoclax, which is currently being tested in clinical trials of CRPC.Patient summaryWe describe an approach to generate patient-derived cancer cells from advanced prostate cancer and apply such cells to discover drugs that could be applied in clinical trials for castration-resistant prostate cancer

Anti-oncogenic and pro-differentiation effects of clorgyline, a monoamine oxidase A inhibitor, on high grade prostate cancer cells

<p>Abstract</p> <p>Background</p> <p>Monoamine oxidase A (MAO-A), a mitochondrial enzyme that degrades monoamines including neurotransmitters, is highly expressed in basal cells of the normal human prostatic epithelium and in poorly differentiated (Gleason grades 4 and 5), aggressive prostate cancer (PCa). Clorgyline, an MAO-A inhibitor, induces secretory differentiation of normal prostate cells. We examined the effects of clorgyline on the transcriptional program of epithelial cells cultured from high grade PCa (E-CA).</p> <p>Methods</p> <p>We systematically assessed gene expression changes induced by clorgyline in E-CA cells using high-density oligonucleotide microarrays. Genes differentially expressed in treated and control cells were identified by Significance Analysis of Microarrays. Expression of genes of interest was validated by quantitative real-time polymerase chain reaction.</p> <p>Results</p> <p>The expression of 156 genes was significantly increased by clorgyline at all time points over the time course of 6 – 96 hr identified by Significance Analysis of Microarrays (SAM). The list is enriched with genes repressed in 7 of 12 oncogenic pathway signatures compiled from the literature. In addition, genes downregulated ≥ 2-fold by clorgyline were significantly enriched with those upregulated by key oncogenes including beta-catenin and ERBB2, indicating an anti-oncogenic effect of clorgyline. Another striking effect of clorgyline was the induction of androgen receptor (AR) and classic AR target genes such as prostate-specific antigen together with other secretory epithelial cell-specific genes, suggesting that clorgyline promotes differentiation of cancer cells. Moreover, clorgyline downregulated EZH2, a critical component of the Polycomb Group (PcG) complex that represses the expression of differentiation-related genes. Indeed, many genes in the PcG repression signature that predicts PCa outcome were upregulated by clorgyline, suggesting that the differentiation-promoting effect of clorgyline may be mediated by its downregulation of EZH2.</p> <p>Conclusion</p> <p>Our results suggest that inhibitors of MAO-A, already in clinical use to treat depression, may have potential application as therapeutic PCa drugs by inhibiting oncogenic pathway activity and promoting differentiation.</p

A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity

Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue–ECM boundary, rather than by differential homo- and heterotypic energies of cell–cell interaction. Surprisingly, interactions with the tissue–ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell–cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell–cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell–ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer

Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients\u27 tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials

The Alternative Splice Variant of Protein Tyrosine Kinase 6 Negatively Regulates Growth and Enhances PTK6-Mediated Inhibition of β-Catenin

Protein tyrosine kinase 6 (PTK6), also called breast tumor kinase (BRK), is expressed in epithelial cells of various tissues including the prostate. Previously it was shown that PTK6 is localized to epithelial cell nuclei in normal prostate, but becomes cytoplasmic in human prostate tumors. PTK6 is also primarily cytoplasmic in the PC3 prostate adenocarcinoma cell line. Sequencing revealed expression of wild type full-length PTK6 transcripts in addition to an alternative transcript lacking exon 2 in PC3 cells. The alternative transcript encodes a 134 amino acid protein, referred to here as ALT-PTK6, which shares the first 77 amino acid residues including the SH3 domain with full length PTK6. RT-PCR was used to show that ALT-PTK6 is coexpressed with full length PTK6 in established human prostate and colon cell lines, as well as in primary cell lines derived from human prostate tissue and tumors. Although interaction between full-length PTK6 and ALT-PTK6 was not detected, ALT-PTK6 associates with the known PTK6 substrates Sam68 and β-catenin in GST pull-down assays. Coexpression of PTK6 and ALT-PTK6 led to suppression of PTK6 activity and reduced association of PTK6 with tyrosine phosphorylated proteins. While ALT-PTK6 alone did not influence β-catenin/TCF transcriptional activity in a luciferase reporter assay, it enhanced PTK6-mediated inhibition of β-catenin/TCF transcription by promoting PTK6 nuclear functions. Ectopic expression of ALT-PTK6 led to reduced expression of the β-catenin/TCF targets Cyclin D1 and c-Myc in PC3 cells. Expression of tetracycline-inducible ALT-PTK6 blocked the proliferation and colony formation of PC3 cells. Our findings suggest that ALT-PTK6 is able to negatively regulate growth and modulate PTK6 activity, protein-protein associations and/or subcellular localization. Fully understanding functions of ALT-PTK6 and its impact on PTK6 signaling will be critical for development of therapeutic strategies that target PTK6 in cancer