Abstract 854: A pharmaco-pheno-multiomic integration analysis of pancreatic cancer: A highly predictive biomarker model of biomarkers of Gemcitabine/Abraxane sensitivity and resistance

The overall survival of patients diagnosed with Pancreatic Cancer remains low. Initial responses to current therapeutic interventions are below 50%, leading to a high mortality rate shortly after diagnosis. To date, only a companion diagnostic, non-specific for pancreatic cancer, has been approved for this indication. A better understanding of the tumor cell biology and resistance mechanisms may shed light onto novel therapeutic targets that improve long-term outcome and improved patient stratification. In this study, we performed an exhaustive analysis to identify predictive biomarkers for gemcitabine/abraxane sensitivity using multiomics datasets. These datasets were integrated in a pharmaco-phenotypic-multiomic (PPMO) model predictive of therapeutic sensitivity or resistance, using sparse partial least squares (sPLS). Our results reveal major cellular discriminants in genomic variants, transcriptomics, and most pronouncedly in proteomics data. Tumors exhibiting Gemcitabine/Abraxane resistance associate with increased TPRV6 RNA expression, MUC13 protein expression, and USP42 mutation among others. Prospective application of the PPMO integration model was able to accurately predict Gemcitabine/Abraxane response profiles for 4/5 additional Pancreatic samples, therefore suggesting a potential application as a predictive diagnostic tool.

Citation Format: Gilad Silberberg, Clare Killick-Cole, Yaron Mosesson, Haia Khoury, Xuan Ren, Mara Gilardi, Daniel Ciznadija, Paolo Schiavini, Marianna Zipeto, Michael Ritchie. A pharmaco-pheno-multiomic integration analysis of pancreatic cancer: A highly predictive biomarker model of biomarkers of Gemcitabine/Abraxane sensitivity and resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 854.

Abstract 456: Raptamer-drug conjugates as molecularly targeted cancer therapeutics

While antibody-drug conjugates (ADC) are an attractive modality for targeted cancer therapy, they face limitations. These include a reduced volume of distribution with limited penetration into solid tumors, and an expensive, long and complicated production process, especially for large-scale manufacturing. These factors hinder the activity of these medications in certain tumors, and limit equitable access to all population segments. Use of aptamers as a therapeutic targeting moiety, holds the promise of building on the success of ADCs. Aptamers have several advantages over mAbs as a targeting moiety including: (i) smaller size that enables better tissue/tumor penetration; (ii) chemical synthesis which allows rapid and affordable scale-up; (iii) superior safety profile from lack of immunogenicity and short half-life which reduces off-target adverse events; and (iv) room temperature stability. Therefore, the use of aptamers in conjunction with drugs (similar to ADCs) holds promise for tumor management. We have recently identified a novel therapeutic target for certain cancers (COF-01) using analysis of proteomics data and immunohistochemistry from patient-derived tumors. COF-01 was shown to have highly specific increases in protein and mRNA expression in several cancers including non-small cell lung cancer, head and neck cancer and pancreatic cancer. COF-01 expression correlated with poor overall survival. Here, we present a new therapeutic approach that targets COF-01-positive cells using next generation drug conjugated aptamers. We have generated novel next-generation base-modified ssDNA aptamers (Raptamers) against COF-01 using a cell- and protein-based selection that utilizes our proprietary bead-based oligonucleotide libraries. The binding affinities of these COF-01 Raptamer candidates were determined by concentration curves using biolayer interferometry. Dissociation constants for the COF-01 Raptamers ranged from 80 nM - 200 nM. Anti-COF-01 Raptamer-drug conjugates (Rap-DCs) were developed by conjugating the Raptamers to monomethyl auristatin F via a cleavable linker. In vitro efficacy data has shown that the COF-01 Rap-DCs can selectively induce cytotoxicity in COF-01-positive human cells. There was a significant decrease in cell viability of COF-01-positive cells when compared to COF-01-negative control cells. This study provides proof-of concept for the use of high-affinity Raptamers against novel molecular targets, such as COF-01. This platform can be used to develop Raptamers against emergent neo-antigens on cancer cells that have escaped other therapies.

Citation Format: Stephanie P. Vega, Dev Chatterjee, Atul Varadhachary, Michael Ritchie, Michael Heffernan, Daniel Ciznadija. Raptamer-drug conjugates as molecularly targeted cancer therapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 456.

Functional Genomic Identification of Predictors of Sensitivity and Mechanisms of Resistance to Multivalent Second-Generation TRAIL-R2 Agonists

Multivalent second-generation TRAIL-R2 agonists are currently in late preclinical development and early clinical trials. Herein, we use a representative second-generation agent, MEDI3039, to address two major clinical challenges facing these agents: lack of predictive biomarkers to enable patient selection and emergence of resistance. Genome-wide CRISPR knockout screens were notable for the lack of resistance mechanisms beyond the canonical TRAIL-R2 pathway (caspase-8, FADD, BID) as well as p53 and BAX in TP53 wild-type models, whereas a CRISPR activatory screen identified cell death inhibitors MCL-1 and BCL-XL as mechanisms to suppress MEDI3039-induced cell death. High-throughput drug screening failed to identify genomic alterations associated with response to MEDI3039; however, transcriptomics analysis revealed striking association between MEDI3039 sensitivity and expression of core components of the extrinsic apoptotic pathway, most notably its main apoptotic effector caspase-8 in solid tumor cell lines. Further analyses of colorectal cell lines and patient-derived xenografts identified caspase-8 expression ratio to its endogenous regulator FLIP(L) as predictive of sensitivity to MEDI3039 in several major solid tumor types and a further subset indicated by caspase-8:MCL-1 ratio. Subsequent MEDI3039 combination screening of TRAIL-R2, caspase-8, FADD, and BID knockout models with 60 compounds with varying mechanisms of action identified two inhibitor of apoptosis proteins (IAP) that exhibited strong synergy with MEDI3039 that could reverse resistance only in BID-deleted models. In summary, we identify the ratios of caspase-8:FLIP(L) and caspase-8:MCL-1 as potential predictive biomarkers for second-generation TRAIL-R2 agonists and loss of key effectors such as FADD and caspase-8 as likely drivers of clinical resistance in solid tumors.

Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors

Background

While patient-derived xenografts (PDXs) offer a powerful modality for translational cancer research, a precise evaluation of how accurately patient responses correlate with matching PDXs in a large, heterogeneous population is needed for assessing the utility of this platform for preclinical drug-testing and personalized patient cancer treatment.

Patients and methods

Tumors obtained from surgical or biopsy procedures from 237 cancer patients with a variety of solid tumors were implanted into immunodeficient mice and whole-exome sequencing was carried out. For 92 patients, responses to anticancer therapies were compared with that of their corresponding PDX models.

Results

We compared whole-exome sequencing of 237 PDX models with equivalent information in The Cancer Genome Atlas database, demonstrating that tumorgrafts faithfully conserve genetic patterns of the primary tumors. We next screened PDXs established for 92 patients with various solid cancers against the same 129 treatments that were administered clinically and correlated patient outcomes with the responses in corresponding models. Our analysis demonstrates that PDXs accurately replicate patients' clinical outcomes, even as patients undergo several additional cycles of therapy over time, indicating the capacity of these models to correctly guide an oncologist to treatments that are most likely to be of clinical benefit.

Conclusions

Integration of PDX models as a preclinical platform for assessment of drug efficacy may allow a higher success-rate in critical end points of clinical benefit.

Abstract A018: Patient-derived xenograft (PDX) models of NSCLC reflect clinical drug responses and predict effective treatments for patients

Background: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality and prognosis remains poor despite the availability of numerous therapies. Integration of drug screening and sequencing in PDX models may allow for improved understanding of mechanisms of resistance (de novo and acquired), identification of biomarkers, and optimization of therapeutic strategies for NSCLC patients. In this study, we evaluated the response of NSCLC PDX models to multiple therapies and correlated responses to known clinical outcomes and molecular characteristics. Methods: PDX models were developed from 86 patients with NSCLC and evaluated by next-generation sequencing for genomic alterations (mutations, amplifications/deletions, fusions, and gene expression changes). Models were screened against different therapies including first-line platinum and nonplatinum doublets and triplets, second-line single agent docetaxel and pemetrexed (second-line therapies), and EGFR-targeted inhibitors. Tumor regression (TR) values and RECIST criteria were determined and correlated with known literature-based response rates (RR) as well as individual patient outcomes. Results: Eighty-eight PDX models from 86 patients were interrogated. To date, 63 (72%) models have been sequenced and 39 screened against standard-of-care therapies. There was robust concordance in mutational and allelic frequency profiles between patient tumors and corresponding PDX models. Based on PDX tumor growth, regression (CR/PR RECIST) was observed for at least one regimen in 50% (12/24) of models screened against first-line therapies and 25% (2/8) screened against second-line docetaxel or pemetrexed. No tumor regression was observed in any NSCLC model treated with the EGFR inhibitor, erlotinib (0%, 0/15), despite EGFR amplification and the absence of KRAS mutations. Nine PDX responses could be correlated to clinical outcomes, with 89% (8/9) accurately reflecting patient responses to the same treatment. Conclusion: Our study demonstrated the strong alignment between PDX model response to standard-of-care therapies and patient clinical outcomes, which highlights the potential application of PDX models for translational modeling and utilizing cohorts of PDX models for clinical trial simulation. The responses of these models to different lines of therapy reflected corresponding patient outcomes both at an individual and population level. Comprehensive sequencing (WES and RNA) and standard-of-care drug testing of these PDX models is planned and could allow a deeper understanding of such mechanisms. In this context, application of PDX models to drug development and stratification of clinical trial patients for treatment will continue to evolve.

Citation Format: Daniel Ciznadija, Igor Astaturov, Haiying Cheng, Nir Peled, Jennifer Jaskowiak, Angela Davies, David Sidransky. Patient-derived xenograft (PDX) models of NSCLC reflect clinical drug responses and predict effective treatments for patients [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A018.

Abstract 1648: ImmunoGraft® platform for the evaluation of Immuno-Oncology agents in PDX tumors models

Recent breakthroughs in Immunotherapy have given new hope to treating previously untreatable tumor types and provide a better tolerated alternative to standard agents. There is an unmet need for a pre-clinical platform to test potential immune-oncology therapeutics that would also provide a tool to examine the mechanisms of response to better predict clinical outcomes. We have previously presented the Champions ImmunoGraft®, an innovative pre-clinical model enabling immunotherapeutic agents to be evaluated for efficacy in solid tumors. This platform is more reflective of the human tumor microenvironment (both immune and non-immune cell-based) and may be one of the most translationally-relevant models to date for screening therapies targeting the immune system. However, optimization of humanization and PDX implantation protocols that allow a broader reconstitution of cell linage and higher engraftment rate are necessary to further improve the pre-clinical evaluation of immune-oncology therapeutics and enhance the value of this modality for patient’s benefit.

To this end, immune-compromised NOG (PrkdcscidIl2rgtm1Sug) mice were reconstituted (humanized) with human CD34+ cells using optimized procedure and blood was collected at different time points post engraftment to check for the major leukocyte linages. At ten weeks after humanization, mature human CD45+ cells comprised close to 50% of the leukocytes detected in the circulation and secondary lymphoid tissues of the humanized animals. As a result of improved methodology of the reconstitution protocol we have achieved an 85% success rate of humanization with a shortened engraftment period utilizing fewer CD34+ cells that maintain humanization reconfirmed at 22 weeks post reconstitution.

Champions TumorGraft® database contains more than one-thousand clinically relevant well-annotated PDX models. We have complied data from extensive genetic and protein expression analyses to design applicable ImmunoGraft® studies for testing of Immuno-Oncology agents. We have identified tumors expressing key markers that may predict response to immunotherapy agents including PDL-1, CD40, IDO-1 and IDO-2 as well as tumors that harbor a high mutational load. Here we present the efficacy and clinically relevant endpoints of two well-studied checkpoint inhibitors Ipilimumab and Pembrolizumab in this highly translational PDX platform.

Citation Format: David Cerna, Daniel Ciznadija, Bhavna Verma, David Sidransky, Evgeny Izumchenko, Angela Davies, Maria Mancini. ImmunoGraft® platform for the evaluation of Immuno-Oncology agents in PDX tumors models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1648. doi:10.1158/1538-7445.AM2017-1648

Abstract 1836: Patient-derived xenograft (PDX) models expressing HER2 reflect clinical responses to targeted HER2 inhibition

Background While HER2-directed agents are most often used for treating breast cancer, there is increasing evidence that these therapies may be of value in other solid tumors. Sequencing efforts and immunohistochemistry (IHC) have identified mutations, amplifications, and overexpression of HER2 in ovarian, HNSCC, NSCLC, and GI cancers. PDX models could permit evaluation of HER2 response/resistance mechanisms to optimize therapeutic strategies. In this pilot study, we evaluated the response of PDX models to HER2-targeted therapies and correlated responses to clinical outcomes.

Materials and Methods PDX models were developed from a variety of patient solid tumors, evaluated by IHC for HER2 expression and next-generation sequencing for genomic alterations in HER2 (mutations, amplifications/deletions, and expression levels). Models were screened against single agent HER2-directed therapies including trastuzumab (n=15), trastuzumab emtansine (n=23), and lapatinib (n=10). Tumor regression (TR) values and RECIST criteria were determined and correlated with known literature-based response rates (RR) as well as individual patient outcomes.

Results 32 PDX models from 30 patients were interrogated (primarily breast and colorectal). Twenty (63%) models have been sequenced to date; 13 (65%) harbor amplification at ERBB2 gene locus. Further, 56% (18/32) have been evaluated by IHC for HER2 to date: 50% have 2+ HER2 staining, 17% 3+ staining, and 33% 1+/- staining. Based on PDX tumor growth, stable disease/regression was observed in 10% of models screened against lapatinib (CR/PR=0%), 50% screened against trastuzumab (CR/PR=8%), and 67% tested against trastuzumab emtansine (CR/PR=14%). Only models with +2/+3 HER2 staining showed regression with HER2-targeted treatment, with nearly 70% of +1/- HER2 models showing progressive disease. Finally, there were 4 correlations to patient clinical outcomes available, with 3/4 (75%) of the PDX model responses mimicking those of the patient to the same treatment.

Conclusion and Future Directions Extensive sequencing of human cancers has demonstrated HER2 amplification or mutation in numerous solid tumors, suggesting HER2-directed therapy could be applied more broadly in the clinic. Consistent with clinical findings, HER2 therapy responses depended upon the strength of HER2 expression (based on IHC). Nevertheless, response rates in PDX models varied depending on which HER2-targeted agent was deployed, highlighting the potential existence of differential mechanisms of de novo resistance/sensitivity. Comprehensive sequencing and drug testing of these PDX models is planned and could allow a deeper understanding of such mechanisms. In this context, application of PDX models for translational modeling of HER2 drug responses, particularly in the context of co-clinical trials, will continue to evolve.

Citation Format: Daniel Ciznadija, Amir Sonnenblick, Jennifer Jaskowiak, Angela Davies, David Sidransky. Patient-derived xenograft (PDX) models expressing HER2 reflect clinical responses to targeted HER2 inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1836. doi:10.1158/1538-7445.AM2017-1836

Comparative mutational landscape analysis of patient-derived tumour xenografts

Background:

Screening of patients for cancer-driving mutations is now used for cancer prognosis, remission scoring and treatment selection. Although recently emerged targeted next-generation sequencing-based approaches offer promising diagnostic capabilities, there are still limitations. There is a pressing clinical need for a well-validated, rapid, cost-effective mutation profiling system in patient specimens. Given their speed and cost-effectiveness, quantitative PCR mutation detection techniques are well suited for the clinical environment. The qBiomarker mutation PCR array has high sensitivity and shorter turnaround times compared with other methods. However, a direct comparison with existing viable alternatives are required to assess its true potential and limitations.

Methods:

In this study, we evaluated a panel of 117 patient-derived tumour xenografts by the qBiomarker array and compared with other methods for mutation detection, including Ion AmpliSeq sequencing, whole-exome sequencing and droplet digital PCR.

Results:

Our broad analysis demonstrates that the qBiomarker's performance is on par with that of other labour-intensive and expensive methods of cancer mutation detection of frequently altered cancer-associated genes, and provides a foundation for supporting its consideration as an option for molecular diagnostics.

Conclusions:

This large-scale direct comparison and validation of currently available mutation detection approaches is extremely relevant for the current scenario of precision medicine and will lead to informed choice of screening methodologies, especially in lower budget conditions or time frame limitations.

Abstract A21: Accurate molecular fidelity of patient-derived xenograft (PDX) models to original human tumors and to The Cancer Genome Atlas (TCGA)

Background: Patient-derived xenograft (PDX) models, also known as Champions TumorGraft® models, maintain the complex intra-tumoral biology of the primary tumor. Over 250 of the Champions models, ranging over a wide variety of solid tumors and passaging generations, have been analyzed using whole exome sequencing (WES) and RNA sequencing (RNAseq). SNPs, InDels and copy number alterations (CNAs) data have been generated for each model, following the Genome Analysis Toolkit (GATK). While several publications compare small numbers of PDX models and human tumors on the molecular level, this is the first known comprehensive analysis whereby the molecular fidelity of the PDX platform is corroborated across several cancer types and throughout different mouse generations.

Method and Results: First, we compared PDXs to their human original counterparts using a preliminary group of four PDX models with available matching human patient WES data. Patient tumor source included dedifferentiated liposarcoma, synovial sarcoma, renal cell carcinoma and squamous cell carcinoma of the lung. PDX passages ranged from 2 to 4. We compared called mutations and a high percentage of identified human tumor mutations were present in the PDX models (42-82%), with the lowest scoring model also showing signs of normal contamination in the human tumor sample. For CNAs in oncogenic sites, we saw an average of 65% of human tumor alterations recurring in the PDX models. This was observed, despite inherent difficulties due to exome- based CNA analysis methods.

Encouraged by the individual patient results, we subjected our largest (per cancer type) PDX cohorts to a molecular comparison with the equivalent TCGA cohorts. More than 200 of the sequenced models, grouped into colorectal adenocarcinoma (COADREAD), lung adenocarcinoma (LUAD), breast carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC) and ovarian serous carcinoma (OV) cohorts were compared. We applied mutation category (MC) and significantly mutated genes (SMG) analysis, as well as comparison of mutation population frequencies for TCGA SMG. Results showed high correlation between the TCGA and the Champions PDX cohorts, although the level of matching varied between cancer types. For instance, COADREAD was highly correlative, while other cancer types, such as BRCA, showed bias toward CpG site mutations. In SMG analysis and population frequency analysis, major SMGs recur across the cohorts, while, as expected, weaker signals from the TCGA were often missed in the smaller cohorts.

Conclusions: Detailed comparison of several PDX models to the human tumor counterpart demonstrated high fidelity, not only at the gene level but also the mutation and CNA level. Cohort comparisons were correlative as well, but a certain bias was discerned in both MC and SMG analyses. There could be several causes for this, including statistical artifacts due to small cohort sizes, clinical and demographic differences between the Champions and TCGA patient profiles, or biological factors such as clonal selection and engraftment pressure. Further analysis is ongoing to better understand the model at a molecular level and maximize its utility as a robust translational research tool.

Citation Format: Ido Sloma, Ido Ben-zvi, Tin Khor, Daniel Ciznadija, Amanda Katz, David Vasquez, Jennifer Jaskowiak, Lindsay Ryland, Angela Davies, David Sidransky, Keren Paz. Accurate molecular fidelity of patient-derived xenograft (PDX) models to original human tumors and to The Cancer Genome Atlas (TCGA). [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr A21.

Abstract A40: The ImmunoGraftTM: A humanized mouse model for translational assessment of immunotherapy in solid tumors

Background: Therapeutics reactivating the immune system have demonstrated promise, with durable objective responses in patients with a variety of solid tumors. Despite these successes, current animal models do not reliably identify immunotherapeutic targets with the greatest clinical potential, due in part to differences between human and murine immune systems. Hence, development of robust preclinical tools to test such drugs against human tumors in the context of an allogeneic immune system remains an imperative. We have previously demonstrated the generation of its ImmunoGraft platform, whereby two technologies, the patient-derived xenograft (PDX) and humanized mice (immunodeficient mice reconstituted with a human immune system), are combined in a single platform. We now report on the utility of the ImmunoGraft for assessing the effect of immune-modulating agents in solid tumors.

Materials and Methods: Immune-compromised NOG (PrkdcscidIl2rgtm1Sug) mice were reconstituted with human CD34+ cells and monitored for the expansion of human immune cells (humanized). Humanized mice were engrafted with solid tumors that had been subjected to histocompatibility typing and characterized for a number of molecular markers, including PD-L1 expression. Tumor growth in the ImmunoGrafts was compared against non-humanized counterparts, as well as the level of immune reconstitution. Finally, ImmunoGrafts were treated with drugs blocking the immune checkpoints CTLA4 and PD1 and human immune activation and tumor growth inhibition evaluated.

Results: Mature human CD45+ cells comprised close to 50% of the leukocytes detected in the circulation and lymphoid organs of humanized mice. Solid tumors, including NSCLC, melanoma, and head and neck cancer, were successfully engrafted in the humanized mice. Moderate to high expression of PD-L1 was found in approximately 80% of these tumors. ImmunoGrafts treated with anti-CTLA4 or anti-PD1 antibodies exhibited systemic immune responses characterized by robust proliferation of splenic and circulating huCD3+ T cells, as well as activated huCD4+ Th1 cells. There was also an increase in tumor-infiltrating huCD8+ cytotoxic T lymphocytes and huCD68+ macrophages, along with elevated secretion of human-specific cytokines. Tumor growth inhibition, and in some instances tumor regression, was demonstrated in treated ImmunoGrafts. The magnitude of growth inhibition correlated with the level of immune activation.

Conclusion : The ImmunoGraft is an innovative pre-clinical model enabling immunotherapeutic agents to be evaluated for efficacy in solid tumors. This platform is more reflective of the human tumor microenvironment (both immune and non-immune cell-based) and may be one of the most translationally-relevant models to date for screening therapies targeting the immune system. To gauge the clinical potential of the ImmunoGraft, a retrospective analysis is currently ongoing using PDX models developed from patients treated with immuno-oncology drugs. The ImmunoGraft has the potential to revolutionize translational drug discovery and development for immunotherapeutic agents in oncology.

Citation Format: Gilson Baia, David Vasquez, David Cerna, Daniel Ciznadija, David Sidransky, Jennifer Jaskowiak, Lindsay Ryland, Angela Davies, Amanda Katz, Keren Paz. The ImmunoGraftTM: A humanized mouse model for translational assessment of immunotherapy in solid tumors. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr A40.

Abstract B40: Mouse clinical trials: integrating PDX models of sarcoma subtypes with genomics to replicate patient responses to cancer therapeutics

Objective: Sarcomas are clinically and genetically heterogeneous tumors that are often difficult to treat. Patient-derived xenograft (PDX or TumorGraft) models have been shown to accurately reflect the characteristics of patient tumors and may be useful tools for developing personalized treatment strategies and deployment in mouse clinical trials assessing novel therapies. We evaluated the accuracy of PDX models in reproducing clinical responses to standard and experimental drugs used for sarcoma treatment.

Methods: Fresh tumor tissue (comprising 172 distinct explants) was collected by surgery or biopsy from 150 patients with sarcoma and implanted into immunodeficient mice. Tumors successfully engrafting were screened using next-generation sequencing technology to identify key genomic alterations with therapeutic implications. PDX sensitivity to standard of care and experimental agents was evaluated and tumor growth inhibition/regression values and clinical RECIST outcomes determined. Drug screening results were correlated with individual patient outcomes.

Results: Of the 172 implanted tumors, 145 have completed the implantation process, with 86 (59%) successfully establishing a PDX model. Engraftment rate depended on sarcoma subtype and specimen origin (surgical explant versus biopsy). Next generation sequencing of models from major sarcoma subtypes (Ewing sarcoma, leiomyosarcoma, liposarcoma, osteosarcoma, and rhabdomyosarcoma) highlighted alterations in 454 genes, including those informing treatment selection such as PIK3CA, MET, and CDK4. A total of 26 PDX models from 25 patients across the major sarcoma subtypes were screened in 148 drug tests employing 64 FDA-approved drugs/combinations such as ifosfamide, and gemcitabine/docetaxel, and 26 experimental therapies in clinical trial. In 13/13 (100%) cases with available data, a significant correlation between patient clinical response and PDX model outcome was noted (p=0.0004; Fisher's exact test).

Conclusions: Given the close match between patient clinical responses and PDX model outcomes, these results validate the concept of mouse clinical trials for determining the efficacy of novel therapies in sarcoma prior to broad application in expensive human trials. Moreover, the retention of alterations in key genes influencing therapeutic decision-making suggests a use for PDX models in functionally validating genomic hypotheses in a pre-clinical setting.

Citation Format: Amanda Katz, Raphael E. Pollock, Leonard H. Wexler, Carlos Rodriguez-Galindo, Jonathan C. Trent, Robert Maki, Jennifer Jaskowiak, Lindsay Ryland, Daniel Ciznadija, Angela Davies, Keren Paz. Mouse clinical trials: integrating PDX models of sarcoma subtypes with genomics to replicate patient responses to cancer therapeutics. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr B40.

Abstract A8: The ImmunoGraft: A humanized mouse model for translational assessment of immunotherapy in solid tumors

Background: Therapeutics reactivating the immune system have demonstrated promise, with durable objective responses in patients with a variety of solid tumors. Despite these successes, current animal models do not reliably identify immunotherapeutic targets with the greatest clinical potential, due in part to differences between human and murine immune systems. Hence, development of robust preclinical tools to test such drugs against human tumors in the context of an allogeneic immune system remains an imperative. We have previously demonstrated the generation of its ImmunoGraftTM platform, whereby two technologies, the patient-derived xenograft (PDX) and humanized mice (immunodeficient mice reconstituted with a human immune system), are combined in a single platform. We now report on the utility of the ImmunoGraftTM for assessing the effect of immune-modulating agents in solid tumors.

Materials and Methods: Immune-compromised NOG (PrkdcscidIl2rgtm1Sug) mice were reconstituted with human CD34+ cells and monitored for the expansion of human immune cells (humanized). Humanized mice were engrafted with solid tumors that had been subjected to histocompatibility typing and characterized for a number of molecular markers, including PD-L1 expression. Tumor growth in the ImmunoGraftsTM was compared against non-humanized counterparts, as well as the level of immune reconstitution. Finally, ImmunoGraftsTM were treated with drugs blocking the immune checkpoints CTLA4 and PD1 and human immune activation and tumor growth inhibition evaluated.

Results: Mature human CD45+ cells comprised close to 50% of the leukocytes detected in the circulation and lymphoid organs of humanized mice. Solid tumors, including NSCLC, melanoma, and head and neck cancer, were successfully engrafted in the humanized mice. Moderate to high expression of PD-L1 was found in approximately 80% of these tumors. ImmunoGraftsTM treated with anti-CTLA4 or anti-PD1 antibodies exhibited systemic immune responses characterized by robust proliferation of splenic and circulating huCD3+ T cells, as well as activated huCD4+ Th1 cells. There was also an increase in tumor-infiltrating huCD8+ cytotoxic T lymphocytes and huCD68+ macrophages, along with elevated secretion of human-specific cytokines. Tumor growth inhibition, and in some instances tumor regression, was demonstrated in treated ImmunoGraftsTM. The magnitude of growth inhibition correlated with the level of immune activation.

Conclusion: The ImmunoGraftTM is an innovative pre-clinical model enabling immunotherapeutic agents to be evaluated for efficacy in solid tumors. This platform is more reflective of the human tumor microenvironment (both immune and non-immune cell-based) and may be one of the most translationally-relevant models to date for screening therapies targeting the immune system. To gauge the clinical potential of the ImmunoGraftTM, a retrospective analysis is currently ongoing using PDX models developed from patients treated with immuno-oncology drugs. The ImmunoGraftTMhas the potential to revolutionize translational drug discovery and development for immunotherapeutic agents in oncology.

Citation Format: Gilson Baia, David Vasquez, David Cerna, Daniel Ciznadija, David Sidransky, Amanda Katz, Keren Paz. The ImmunoGraft: A humanized mouse model for translational assessment of immunotherapy in solid tumors. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A8.

Abstract A14: Molecular fidelity of patient derived xenograft (PDX) models to original human tumor and to the cancer genome atlas (TCGA)

Background

Patient-derived xenograft (PDX) models, also known as Champions TumorGraft® models, maintain the complex intra-tumoral biology of the primary tumor. Over 250 of the Champions models, ranging over a wide variety of solid tumors and passaging generations, have been analyzed using whole exome sequencing (WES) and RNA sequencing (RNAseq). SNPs, InDels and copy number alterations (CNAs) data have been generated for each model, following the Genome Analysis Toolkit (GATK). While several publications compare small numbers of PDX models and human tumors on the molecular level, this is the first known comprehensive analysis whereby the molecular fidelity of the PDX platform is corroborated across several cancer types and throughout different mouse generations.

Method and Results

First, we compared PDXs to their human original counterparts using a preliminary group of four PDX models with available matching human patient WES data. Patient tumor source included dedifferentiated liposarcoma, synovial sarcoma, renal cell carcinoma and squamous cell carcinoma of the lung. PDX passages ranged from 2 to 4. We compared called mutations and a high percentage of identified human tumor mutations were present in the PDX models (42-82%), with the lowest scoring model also showing signs of normal contamination in the human tumor sample. For CNAs in oncogenic sites, we saw an average of 65% of human tumor alterations recurring in the PDX models. This was observed, despite inherent difficulties due to exome based CNA analysis methods.

Encouraged by the individual patients results, we subjected our largest (per cancer type) PDX cohorts to a molecular comparison with the equivalent TCGA cohorts. More than 200 of the sequenced models, grouped into colorectal adenocarcinoma (COADREAD), lung adenocarcinoma (LUAD), breast carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC) and ovarian serous carcinoma (OV) cohorts were compared. We applied mutation category (MC) and significantly mutated genes (SMG) analysis, as well as comparison of mutation population frequencies for TCGA SMG. Results showed high correlation between the TCGA and the Champions PDX cohorts, although the level of matching varied between cancer types. For instance, COADREAD was highly correlative, while other cancer types, such as BRCA, showed bias toward CpG site mutations. In SMG analysis and population frequency analysis, major SMGs recur across the cohorts, while, as expected, weaker signals from the TCGA were often missed in the smaller cohorts.

Conclusion

Detailed comparison of several PDX models to the human tumor counterpart demonstrated high fidelity, not only at the gene level but also the mutation and CNA level. Cohort comparisons were correlative as well, but a certain bias was discerned in both MC and SMG analyses. There could be several causes for this, including statistical artifacts due to small cohort sizes, clinical and demographic differences between the Champions and TCGA patient profiles, or biological factors such as clonal selection and engraftment pressure. Further analysis is ongoing to better understand the model at a molecular level and maximize its utility as a robust translational research tool.

Citation Format: Ido Ben-Zvi, Ido Sloma, Tin Khor, Daniel Ciznadija, Amanda Katz, David Vasquez, David Sidransky, Keren Paz. Molecular fidelity of patient derived xenograft (PDX) models to original human tumor and to the cancer genome atlas (TCGA). [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A14.

Abstract 3219: A patient-centric repository of PDX models for translational oncology research

Patient-derived xenograft (PDX) models maintain the complex intra-tumoral biology and heterogeneity of an intact malignancy, as well as the interplay with stromal components and other cells fluxing into the tumor environment. This intrinsic cross-talk between different elements of the tumor makes PDX models a superior tool for translational drug discovery research and personalized oncology studies. Champions PDX models were originally developed for personalizing cancer treatments through the different Champions clinical programs. These models accurately reflect the population of patients enrolling in clinical trials. We describe herein our extensive TumorBank of PDX models, a valuable resource for translational oncology research to predetermine target populations for intervention with novel therapeutics in specific cancer subtypes.

Tumor tissue from over 950 patients with a variety of primary and metastatic solid malignancies, across all ages and ethnicities and encompassing both treatment-naïve and heavily-pretreated individuals, has been implanted into immunodeficient mice with successful engraftment observed in ∼72% of cases. Comprehensive and translational-relevant clinical annotations have been maintained for these PDX models, including patient demographics, disease stage, anatomic location, tumor grade and histology, and treatment history. Importantly, whole exome and RNA sequencing, tissue histopathology, and protein immunohistochemistry have all been applied to 297 of these models. Finally, 70 of the models were screened against the corresponding patient's treatment used in the clinic, demonstrating a sensitivity of 98%, specificity of 76%, positive predictive value of 89% and negative predictive value of 96%. This wealth of information can be accessed through the Champions TumorGraft Database. The combination of extensive molecular and clinical annotation, together with opportunities for unlimited prospective preclinical testing, makes Champions TumorBank a pioneering resource for pharmaceutical companies seeking to identify target populations for therapeutic intervention.

Citation Format: Tin O. Khor, Ido Ben Zvi, Amanda Katz, David Vasquez-Dunddel, Ido Sloma, Daniel Ciznadija, David Sidransky, Keren Paz. A patient-centric repository of PDX models for translational oncology research. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3219. doi:10.1158/1538-7445.AM2015-3219

Abstract P3-06-31: Patient-derived xenografts accurately predict patient response in breast cancer patients

PURPOSE/OBJECTIVES: A growing body of evidence demonstrates that patient-derived xenografts (PDXs) represent living tumor models that accurately reflect the biology of the primary patient tumor. More importantly, we have previously shown that PDX models show responses to therapeutic agents that are concordant with patient clinical response and can be used to direct personalized cancer treatments (Stebbing, 2014). Here we report the ability of PDX models to predict for patient response to drug treatment in a cohort of breast cancer patients.

MATERIALS/METHODS: Tumors were resected from patients with either primary or metastatic breast cancer and implanted into immunodeficient mice to establish PDX models. Successfully engrafted PDX models were expanded and randomized for drug sensitivity testing. Tumor growth inhibition and tumor regression were captured and results were correlated with a patient’s clinical response. In some cases, PDX results were used to personalize cancer treatment and some patients used PDX-directed treatments over multiple lines of therapy.

RESULTS: A total of 42 tumors from 40 patients were implanted resulting in 21 successfully engrafted PDX models (50% engraftment rate). Notably, engraftment rates were much higher for patients with triple negative breast cancer (TNBC) and resulted in 7 successful PDX models from 8 TNBC patients (87.5% engraftment rate). Drug sensitivity testing was offered to patients with established PDX models. Drugs and drug combinations tested included standard and nonstandard chemotherapy as well as biologics. At that time of this publication, 4 patients (3 TNBC and 1 HER2+) with completed drug sensitivity tests also had clinical data available resulting in 7 clinical correlations; 4 retrospective and 3 prospective. In all 7 cases, the PDX model accurately predicted patient clinical response demonstrating an accuracy of 100%. Five of the drug tests predicted drug sensitivity and 2 tests predicted resistance, indicating the potential of the PDX platform to predict for both sensitivity and resistance to therapy. The 3 prospective correlations resulted in concordant clinical benefit in 2 patients for duration greater than 6 months each.

CONCLUSIONS: These data support the use of the personalized PDX model as a platform for therapeutic decision making that can guide treatment for patients with breast cancer. A prospective clinical trial in TNBC is currently underway.

Citation Format: Lisa Stow, Amanda Katz, Hanna Irie, Elisa Port, Justin Stebbing, Daniel Ciznadija, Angela Davies, Keren Paz. Patient-derived xenografts accurately predict patient response in breast cancer patients [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-31.

Abstract 1187: The Champions TumorGraft Bank: A demographically-rich repository of preclinical TumorGraft models

Many oncology pharmaceuticals fail during phased clinical trials, having been advanced based on research using flawed preclinical models that do not accurately replicate human tumor biology. For example, numerous models are based on genetically-engineered mice, which are often generated from limited numbers of genetic aberrations. As such, they may not accurately represent either the chaotic heterogeneity that exists within intact human tumors or throughout the clinical population. TumorGrafts, in which patient-derived tumor tissue is directly engrafted into immunodeficient mice, offer a step forward in this unresolved issue. These models maintain the complex intra-tumoral heterogeneity and biology of an intact malignancy, as well its 3-dimensional interplay with stromal components and other cells fluxing into the immediate environment. The intrinsic cross-talk between the different compartments of the tumor is also retained.

We wanted to generate a repository of these tumor models and make them available to the research community for use in pharmaceutical development and basic research processes. Here we describe our extensive bank of live TumorGrafts comprising a range of different tumor types, from more common cancers, including lung, colon, and breast, to a number of rare subtypes such as adenoid cystic carcinoma. These models were originally developed for personalizing cancer treatments and are derived from patient populations across all ages and ethnicities, encompassing both treatment-naïve and heavily-treated individuals. Furthermore, because of our distinct patient-focus, we maintain detailed clinical histories, as well as molecular data where available. Hence, the bank is a reasonable surrogate of the population from which treatment groups are typically drawn for clinical trials and could potentially be of value for predetermining target populations for therapeutic intervention. The Champions TumorGraft Bank provides superior pre-clinical models that faithfully capture all the biological and molecular features of cancer and can serve basic and clinical research groups as an increasingly valuable source for drug development and biomarker discovery.

Citation Format: Tin Khor, David Vasquez, Amanda Katz, Gilson Baia, Daniel Ciznadija, David Sidransky, Keren Paz. The Champions TumorGraft Bank: A demographically-rich repository of preclinical TumorGraft models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1187. doi:10.1158/1538-7445.AM2014-1187

Abstract 1190: Multifactorial biological processes govern engraftment of patient-derived tumor tissue in immunodeficient mice

TumorGrafts (also known as patient-derived xenografts) are a valuable tool for the personalization of oncology treatment, as well as development of new cancer therapeutics. Tumor explants are engrafted into immunodeficient mice and allowed to develop prior to screening against a panel of drugs or drug combinations to assess which best inhibit tumor growth. These models capture the chaotic heterogeneity, histopathology, and biology of the original tumor, as well its 3-dimensional interaction with the surrounding stroma and other cells migrating into the tumor environment. TumorGrafts will serve basic and clinical research groups as an increasingly valuable preclinical model of cancer. One important variable governing the generation of these models is the take rate, or the percentage of patient tumors that successfully engraft and grow in the mice. This is a potentially critical limitation to applying these preclinical models for improving patient treatment and advancing novel drug regimens to the clinic. Hence, there is a need to understand and exploit the mechanisms that influence take rate in order to ensure that the majority of tumor explants readily engraft and expand. We describe here our experience in optimizing the engraftment of patient tumor tissue in immunodeficient mice. We found a number of factors contribute to take rate including tumor type, tissue quantity and quality, engraftment site, oxygenation state, neovascularization and the presence of extracellular stromal components and cells. We have also uncovered a correlation between the growth rate of tumors in the mice and the clinical aggressiveness of the original malignancy, information that may be useful in guiding clinical management. Moreover, we describe how we are now able to consistently use biopsy material rather than surgical explants to establish TumorGrafts, a crucial step forward that allows this technology to benefit patients diagnosed with early-stage cancers or where surgery is not indicated. Although engraftment of patient tumor tissue in immunodeficient mice is a complex process, with multiple factors impacting success, we have effectively optimized this process, improving our take rate and at the same time, reducing the time to obtaining drug screening results, all without compromising tumor integrity.

Citation Format: David M. Vasquez-Dunddel, Gilson Baia, Amanda Katz, Daniel Ciznadija, David Sidransky, Keren Paz. Multifactorial biological processes govern engraftment of patient-derived tumor tissue in immunodeficient mice. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1190. doi:10.1158/1538-7445.AM2014-1190

Abstract 1674: Humanized mouse models for personalized preclinical testing of monoclonal antibodies targeting immune checkpoints

The blockade of immune checkpoints with monoclonal antibodies (mAbs) is a promising therapeutic avenue, with durable objective responses observed in patients with solid tumors, particularly melanoma, non-small cell lung cancer (NSCLC) and renal cell carcinoma. Preclinical models that recapitulate a functional human immune system will therefore be essential tools for the continued investigation of immunotherapy approaches. Champions Oncology is engaged in advanced personalized solutions and our TumorGraft models have been developed and extensively characterized as a platform for use in personalizing cancer patient care, as well as pharmaceutical development. However, because TumorGrafts are established by engrafting patient tumors into immune-deficient mice, the therapeutic efficacy of immune-modulatory drugs cannot be directly examined. To circumvent this limitation, we reconstituted the human immune system by engrafting human hematopoietic cells (HLA-A2; CD34+) into immune-compromised mice (PrkdcscidIl2rgtm1Sug) carrying the scid mutation and a targeted mutation of the Il2r-gamma gene. Ten to twelve weeks later, mature CD45+ human T cells could be detected in these mice, at which time TumorGrafts were established, followed by drug-sensitivity testing with various mAbs targeting the immune system. Fifty six well-established melanoma, colorectal, breast and lung TumorGraft models were characterized and selected with regard to their HLA type and other molecular characteristics such as BRAF mutation status (in melanoma) and KRAS mutation status (in colorectal and lung cancer) as well as expression of PD-L1. With the present study, we demonstrated the potential of combining the humanized mouse with Champions TumorGraft to generate a preclinical platform for assessing the therapeutic value of mAbs targeting immune checkpoints in various solid tumors.

Citation Format: Gilson S. Baia, David Vasquez, Daniel Ciznadija, Brandy Wilkinson, David Sidransky, Amanda Katz, Keren Paz. Humanized mouse models for personalized preclinical testing of monoclonal antibodies targeting immune checkpoints. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1674. doi:10.1158/1538-7445.AM2014-1674

Patient-derived xenografts for individualized care in advanced sarcoma

BACKGROUND

Patients with advanced, metastatic sarcoma have a poor prognosis, and the overall benefit from the few standard-of-care therapeutics available is small. The rarity of this tumor, combined with the wide range of subtypes, leads to difficulties in conducting clinical trials. The authors previously reported the outcome of patients with a variety of common solid tumors who received treatment with drug regimens that were first tested in patient-derived xenografts using a proprietary method ("TumorGrafts").

METHODS

Tumors resected from 29 patients with sarcoma were implanted into immunodeficient mice to identify drug targets and drugs for clinical use. The results of drug sensitivity testing in the TumorGrafts were used to personalize cancer treatment.

RESULTS

Of 29 implanted tumors, 22 (76%) successfully engrafted, permitting the identification of treatment regimens for these patients. Although 6 patients died before the completion of TumorGraft testing, a correlation between TumorGraft results and clinical outcome was observed in 13 of 16 (81%) of the remaining individuals. No patients progressed during the TumorGraft-predicted therapy.

CONCLUSIONS

The current data support the use of the personalized TumorGraft model as an investigational platform for therapeutic decision-making that can guide treatment for rare tumors such as sarcomas. A randomized phase 3 trial versus physician's choice is warranted.

TRIM3, a tumor suppressor linked to regulation of p21(Waf1/Cip1.)

The TRIM family of genes is largely studied because of their roles in development, differentiation and host cell antiviral defenses; however, roles in cancer biology are emerging. Loss of heterozygosity of the TRIM3 locus in ∼20% of human glioblastomas raised the possibility that this NHL-domain containing member of the TRIM gene family might be a mammalian tumor suppressor. Consistent with this, reducing TRIM3 expression increased the incidence of and accelerated the development of platelet-derived growth factor -induced glioma in mice. Furthermore, TRIM3 can bind to the cdk inhibitor p21(WAF1/CIP1). Thus, we conclude that TRIM3 is a tumor suppressor mapping to chromosome 11p15.5 and that it might block tumor growth by sequestering p21 and preventing it from facilitating the accumulation of cyclin D1-cdk4.

Tyrosine phosphorylation of the p21 cyclin-dependent kinase inhibitor facilitates the development of proneural glioma

Phosphorylation of Tyr-88/Tyr-89 in the 3(10) helix of p27 reduces its cyclin-dependent kinase (CDK) inhibitory activity. This modification does not affect the interaction of p27 with cyclin-CDK complexes but does interfere with van der Waals and hydrogen bond contacts between p27 and amino acids in the catalytic cleft of the CDK. Thus, it had been suggested that phosphorylation of this site could switch the tumor-suppressive CDK inhibitory activity to an oncogenic activity. Here, we examined this hypothesis in the RCAS-PDGF-HA/nestin-TvA proneural glioma mouse model, in which p21 facilitates accumulation of nuclear cyclin D1-CDK4 and promotes tumor development. In these tumor cells, approximately one-third of the p21 is phosphorylated at Tyr-76 in the 3(10) helix. Mutation of this residue to glutamate reduced inhibitory activity in vitro. Mutation of this residue to phenylalanine reduced the tumor-promoting activity of p21 in the animal model, whereas glutamate or alanine substitution allowed tumor formation. Consequently, we conclude that tyrosine phosphorylation contributes to the conversion of CDK inhibitors from tumor-suppressive roles to oncogenic roles.

Cyclin D1 and cdk4 mediate development of neurologically destructive oligodendroglioma

Although the molecular changes that characterize gliomas have been studied, the pathogenesis of tumor development remains unclear. p21 contributes to gliomagenesis by stabilizing cyclin D1-cdk4 kinase complexes, suggesting that cyclin D1 and cdk4 may also be required for glial tumor development. In this study, we used a mouse model to attempt to confirm this hypothesis, finding that cyclin D1 and cdk4 played active roles in not only the tumor but also the tumor microenvironment. Loss of cdk4 blocked tumor development, but loss of cyclin D1 did not prevent gliomas from developing. Instead, loss of cyclin D1 impeded progression to higher stages of malignancy. Enforcing expression of cyclin D1 was insufficient to correct the progression defect observed in cyclin D1-deficient animals. In contrast, restoration of cdk4 in the cdk4-deficient animals restored cell proliferation and tumor formation, although at lower tumor grades. Notably, the failure of tumors in the cyclin D1- and cdk4-deficient animals to progress to higher grades was correlated with a failure to fully activate microglia in the tumor microenvironment. Moreover, when platelet-derived growth factor-transformed glial cells were engrafted orthotopically into the mice, the tumors that formed progressed to high grades in wild-type mice but not cyclin D1-deficient animals. Together, our findings establish that the cyclin D1-cdk4 axis is not only critical in glial tumor cells but also in stromal-derived cells in the surrounding tumor microenvironment that are vital to sustain tumor outgrowth.

Hdm2- and proteasome-dependent turnover limits p21 accumulation during S phase

Double-strand DNA breaks detected in different phases of the cell cycle induce molecularly distinct checkpoints downstream of the ATM kinase. p53 is known to induce arrest of cells in G 1 and occasionally G 2 phase but not S phase following ionizing radiation, a time at which the MRN complex and cdc25-dependent mechanisms induce arrest. Our understanding of how cell cycle phase modulates pathway choice and the reasons certain pathways might be favored at different times is limited. In this report, we examined how cell cycle phase affects the activation of the p53 checkpoint and its ability to induce accumulation of the cdk2 inhibitor p21. Using flow cytometric tools and centrifugal elutriation, we found that the p53 response to ionizing radiation is largely intact in all phases of the cell cycle; however, the accumulation of p21 protein is limited to the G 1 and G 2 phase of the cell cycle because of the activity of a proteasome-dependent p21 turnover pathway in S-phase cells. We found that the turnover of p21 was independent of the SCF (skp2) E3 ligase but could be inhibited, at least in part, by reducing hdm2, although this depended on the cell type studied. Our results suggest that there are several redundant pathways active in S-phase cells that can prevent the accumulation of p21.

Immunohistochemical assessment of signal transduction and cell-cycle networks in neural tumors

The ability to detect transient changes in molecular networks lies at the heart of cancer biology research. This is especially apparent during tumorigenesis, where initiating mutations typically affect mitogens and cell-cycle molecules such as PDGF or retinoblastoma protein (Rb). One of the primary consequences of such processes is the inappropriate stimulation of downstream targets, normally through posttranslational modification. Immunohistochemistry (IHC) provides an important tool for assessing such changes in situ, permitting different aspects of tumor biology to be examined as a tissue undergoes transformation. Nevertheless, this can be difficult to achieve, particularly in complex environments like the brain. Here, we provide the automated methodology we have employed for the successful detection of phosphorylation of S6 ribosomal protein (S6-RP) and the retinoblastoma protein (Rb) in response to PDGF stimulation in a mouse model of glial brain tumor development.

A novel magnetic bead-based assay with high sensitivity and selectivity for analysis of telomerase in exfoliated cells from patients with bladder and colon cancer

Telomerase activity is elevated in more than 85% of cancer cells and absent in most of the normal cells and thus represents a potential cancer biomarker. We report its measurement in colon and bladder cancer cells captured using antibody-coated magnetic beads. The cells are lysed and telomerase activity is detected using a biosensor assay that employs an oligonucleotide containing the telomerase recognition sequence also covalently coupled to magnetic beads. Telomerase activity is measured by the incorporation of multiple biotinylated nucleotides at the 3'-end of the oligonucleotide strands during elongation which are then reacted with streptavidin-conjugated horseradish peroxidase. A luminescent signal is generated when hydrogen peroxidase is added in the presence of luminol and a signal enhancer. LOD experiments confirm sensitivity down to ten cancer cell equivalents. The telomerase assay reliably identified patient samples considered by an independent pathological review to contain cancer cells. Samples from normal healthy volunteers were all telomerase negative. The assay, which is amenable to automation, demonstrated high sensitivity and specificity in a small clinical cohort, making it of potential benefit as a first line assay for detection and monitoring of colon and bladder cancer.

Expression of stress response protein glucose regulated protein-78 mediated by c-Myb

Glucose regulated protein-78, GRP78 has been implicated in the protection of tumor cells from cytotoxic damage and apoptosis. When protein profiles of colon cell lines were investigated we found remarkably high GRP78 expression in two cell lines. These cell lines express elevated levels of the transcription factor c-Myb due to genomic amplification of the c-myb locus and we hypothesized that c-Myb regulates GRP78 expression in colon cancer cells. The promoters of human and murine GRP78 and the related family member GRP94 were examined and potential c-Myb binding sites were identified and characterized. DNA binding studies with recombinant c-Myb and nuclear extracts together with ChIP assays on colon cell lines validated these sites. Endogenous GRP78 expression was further induced in these colon cells in response to Thapsigargin treatment, a potent inducer of the unfolded protein response. Transactivation studies with the human GRP78 promoter in colon cell lines showed reporter activity was dependent upon the presence of a conserved c-Myb binding site independent of sequences associated with the unfolded protein response. Finally, over-expression of c-Myb induced the endogenous GRP78 gene. These data suggest that amplification of c-myb in tumor cells may lead to robust GRP78 gene induction, which may in turn assist cells in survival under conditions of oxygen deprivation and nutrient stress.

Colon Epithelial Cell Differentiation Is Inhibited by Constitutive c-Myb Expression or Mutant APC Plus Activated RAS

Blocked differentiation is a hallmark of cancer cells and the restoration of differentiation programs in vivo is an actively pursued clinical aim. Understanding the key regulators of cyto-differentiation may focus therapies on molecules that reactivate this process. c-myb expression declines rapidly when human colon cancer epithelial cells are induced to differentiate with the physiologically relevant short-chain fatty acid, sodium butyrate. These cells show increased expression of alkaline phosphatase and cytokeratin 8. Similarly, murine Immorto-epithelial cells derived from wild-type colon cells also show c-myb mRNA declines when induced to differentiate with sodium butyrate. Immorto-cells harboring a single APC mutation are indistinguishable from wild-type cells with regard to differentiation, while addition of activated RAS alone markedly enhances differentiation. In marked contrast, complete differentiation arrest occurs when both APC and RAS are mutated. Expression of MybER, a 4-hydroxytamoxifen-activatable form of c-Myb, blocks differentiation in wildtype and APC mutant Immorto-cell lines as well as LIM1215 human colon carcinoma cells. These data identify two pathways of oncogenic change that lead to retarded epithelial cell differentiation, one involving the presence of a single APC mutation in conjunction with activated RAS or alternatively constitutive c-myb expression.

Transcriptional regulation of cyclo-oxygenase expression: three pillars of control

Blocking cyclo-oxygenase (COX) isoform activities with non-steroidal anti-inflammatory drugs (NSAIDS) is widely employed in the treatment of arthritis. These agents also hold great promise in the context of pre and post-neoplastic diseases such as colorectal cancer (CRC). Nevertheless, issues of isoform specificity and delivery necessitate the exploration of other strategies to specifically block expression of the COX genes. Approaches that target gene transcription may complement enzyme inhibition. Thus, understanding the regulation of COX isoform transcription may improve the specific inhibition of expression. Three tiers of transcriptional regulation are evident: initiation, alternative splicing and messenger RNA stability. Transcription factors that activate COX-2 expression are elevated in certain disease states and emergency responses such as infection and are therefore potential targets. These factors include C/EBP-beta, phospho- CREB, NF-IL6, AP1, NFkB, and TCF-4/LEF-1. In this review we highlight another factor, c-MYB as a key COX-2 regulator in CRC. Alternative exon usage is another tier of regulation that has not received much attention. For instance, COX-1 splice variants (also known as COX-3 and PCOX-1a) may broaden the spectrum of COX activities in disease. Similarly, whilst mRNA stability is clearly modulated by steroids in the case of COX-2, the wider implications of targeting mRNA stability have not been afforded the same attention. Finally, it seems that some NSAIDS exert part of their action directly on COX-2 transcriptional regulation explaining why such agents display greater effects on this isoform than enzyme inhibition data would suggest.