Aim

This work aimed to determine if the treatment outcomes of bladder cancer could be improved by targeting micelles that are decorated with bladder cancer-specific ligands on the surface and loaded with the chemotherapeutic drug paclitaxel.

Materials & methods

Targeting efficacy and specificity was determined with cell lines. An in vivo targeting and anti-tumor efficacy study was conducted in mice carrying patient-derived xenografts.

Results & discussion

Targeting micelles were more efficient than nontargeting micelles in delivering the drug load into bladder cancer cells both in vitro and in vivo (p < 0.05). The micelle formulation of paclitaxel was less toxic than free paclitaxel in Cremophor(®) (Sigma, MO, USA) and allowed administration of three-times the maximum tolerated dose without increasing the toxicity. Targeting micelles were more effective than the nontargeting micelles in controlling cancer growth (p = 0.0002) and prolonging overall survival (p = 0.002).

Conclusion

Targeting micelles loaded with paclitaxel offer strong potential for clinical applications in treating bladder cancer.

Background

Renal medullary carcinoma (RMC) is a rare but aggressive tumor often complicated by early lung metastasis with few treatment options and very poor outcomes. There are currently no verified RMC patient-derived xenograft (PDX) mouse models established from metastatic pleural effusion (PE) available to study RMC and evaluate new therapeutic options.

Methods

Renal tumor tissue and malignant PE cells from an RMC patient were successfully engrafted into 20 NOD.Cg-Prkdc^scid Il2rg^tm1Wjl/SzJ (NSG) mice. We evaluated the histopathological similarity of the renal tumor and PE PDXs with the original patient renal tumor and PE, respectively. We then evaluated the molecular integrity of the renal tumor PDXs between passages, as well as the PE PDX compared to two generations of renal tumor PDXs, by microarray analysis. The therapeutic efficacy of sunitinib and temsirolimus was tested in a serially-transplanted generation of 27 PE PDX mice.

Results

The pathologic characteristics of the patient renal tumor and patient PE were retained in the PDXs. Gene expression profiling revealed high concordance between the two generations of renal tumor PDXs (RMC-P0 vs. RMC-P1, r=0.865), as well as between the first generation PE PDX and each generation of the renal tumor PDX (PE-P0 vs. RMC-P0, r=0.919 and PE-P0 vs. RMC-P1, r=0.843). A low number (626) of differentially-expressed genes (DEGs) was seen between the first generation PE PDX and the first generation renal tumor PDX. In the PE-P1 xenograft, sunitinib significantly reduced tumor growth (p<0.001) and prolonged survival (p=0.004) compared to the vehicle control.

Conclusions

A metastatic PE-derived RMC PDX model was established and shown to maintain histologic features of the patient cancer. Molecular integrity of the PDX models was well maintained between renal tumor and PE PDX as well as between two successive renal tumor PDX generations. Using the PE PDX model, sunitinib demonstrated therapeutic efficacy for RMC. This model can serve as a foundation for future mechanistic and therapeutic studies for primary and metastatic RMC.

Embryonal rhabdomyosarcoma (eRMS) is one of the most common soft tissue sarcomas in children and adolescents. Parameningeal eRMS is a variant that is often more difficult to treat than eRMS occurring at other sites. A 14-year-old female with persistent headaches and rapid weight loss was diagnosed with parameningeal eRMS. She progressed and died despite chemotherapy with vincristine, actinomycin-D, and cyclophosphamide plus 50.4 Gy radiation therapy to the primary tumor site. Tumor specimens were acquired by rapid autopsy and tumor tissue was transplanted into immunodeficient mice to create a patient-derived xenograft (PDX) animal model. As autopsy specimens had an ALK R1181C mutation, PDX tumor bearing animals were treated with the pan-kinase inhibitor lestaurtinib but demonstrated no decrease in tumor growth, suggesting that single agent kinase inhibitor therapy may be insufficient in similar cases. This unique parameningeal eRMS PDX model is publicly available for preclinical study.

Background/aim

The therapeutic potential of bromodomain and extra-terminal motif (BET) inhibitors in hematological cancers has been well established in preclinical and early-stage clinical trials, although as of yet, no BETtargeting agent has achieved approval. To add insight into potential response to mivebresib (ABBV-075), a broadspectrum BET inhibitor, co-clinical modeling of individual patient biopsies was conducted in the context of a Phase I trial in acute myeloid leukemia (AML).

Materials and methods

Co-clinical modeling involves taking the patient's biopsy and implanting it in mice with limited passage so that it closely retains the original characteristics of the malignancy and allows comparisons of response between animal model and clinical data. Procedures were developed, initially with neonate NOD/Shi-scid-IL2rγnull (NOG) mice and then optimized with juvenile NOG-EXL as host mice, eventually resulting in a robust rate of engraftment (16 out of 26, 62%).

Results

Results from the co-clinical AML patient-derived xenograft (PDX) modeling (6 with >60% inhibition of bone marrow blasts) were consistent with the equivalent clinical data from patients receiving mivebresib in monotherapy, and in combination with venetoclax. The modeling system also demonstrated the activity of a novel BD2-selective BET inhibitor (ABBV-744) in the preclinical AML setting. Both agents were also highly effective in inhibiting blast counts in the spleen (10/10 and 5/6 models, respectively).

Conclusion

These findings confirm the validity of the model system in the co-clinical setting, establish highly relevant in vivo models for the discovery of cancer therapy, and indicate the therapeutic value of BET inhibitors for AML and, potentially, myelofibrosis treatment.

New approaches to optimization of cancer drug development in the laboratory and the clinic will be required to fully achieve the goal of individualized, precision cancer therapy. Improved preclinical models that more closely reflect the now recognized genomic complexity of human cancers are needed. Here we describe a collaborative research project that integrates core resources of The Jackson Laboratory Basic Science Cancer Center with genomics and clinical research facilities at the UC Davis Comprehensive Cancer Center to establish a clinically and genomically annotated patient-derived xenograft (PDX) platform designed to enhance new drug development and strategies for targeted therapies. Advanced stage non-small-cell lung cancer (NSCLC) was selected for initial studies because of emergence of a number of "druggable" molecular targets, and recent recognition of substantial inter- and intrapatient tumor heterogeneity. Additionally, clonal evolution after targeted therapy interventions make this tumor type ideal for investigation of this platform. Using the immunodeficient NOD scid gamma mouse, > 200 NSCLC tumor biopsies have been xenotransplanted. During the annotation process, patient tumors and subsequent PDXs are compared at multiple levels, including histomorphology, clinically applicable molecular biomarkers, global gene expression patterns, gene copy number variations, and DNA/chromosomal alterations. NSCLC PDXs are grouped into panels of interest according to oncogene subtype and/or histologic subtype. Multiregimen drug testing, paired with next-generation sequencing before and after therapy and timed tumor pharmacodynamics enables determination of efficacy, signaling pathway alterations, and mechanisms of sensitivity-resistance in individual models. This approach should facilitate derivation of new therapeutic strategies and the transition to individualized therapy.

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.

Significance

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.