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Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors., Patient-derived xenograft models (PDX) have been extensively used to study the molecular and clinical features of cancers. Here the authors present a cohort of 536 PDX models from 25 cancers, as well as their genomic and evolutionary profiles and their suitability for clinical trials.

Background Targeted therapies for triple-negative breast cancer (TNBC) are limited; however, the epidermal growth factor receptor (EGFR) represents a potential target, as the majority of TNBC express EGFR. The purpose of these studies was to evaluate the effectiveness of two EGFR-targeted antibody-drug conjugates (ADC: ABT-414; ABBV-321) in combination with navitoclax, an antagonist of the anti-apoptotic BCL-2 and BCL-XL proteins, in order to assess the translational relevance of these combinations for TNBC. Methods The pre-clinical efficacy of combined treatments was evaluated in multiple patient-derived xenograft (PDX) models of TNBC. Microscopy-based dynamic BH3 profiling (DBP) was used to assess mitochondrial apoptotic signaling induced by navitoclax and/or ADC treatments, and the expression of EGFR and BCL-2/XL was analyzed in 46 triple-negative patient tumors. Results Treatment with navitoclax plus ABT-414 caused a significant reduction in tumor growth in five of seven PDXs and significant tumor regression in the highest EGFR-expressing PDX. Navitoclax plus ABBV-321, an EGFR-targeted ADC that displays more effective wild-type EGFR-targeting, elicited more significant tumor growth inhibition and regressions in the two highest EGFR-expressing models evaluated. The level of mitochondrial apoptotic signaling induced by single or combined drug treatments, as measured by DBP, correlated with the treatment responses observed in vivo. Lastly, the majority of triple-negative patient tumors were found to express EGFR and co-express BCL-XL and/or BCL-2. Conclusions The dramatic tumor regressions achieved using combined agents in pre-clinical TNBC models underscore the abilities of BCL-2/XL antagonists to enhance the effectiveness of EGFR-targeted ADCs and highlight the clinical potential for usage of such targeted ADCs to alleviate toxicities associated with combinations of BCL-2/XL inhibitors and systemic chemotherapies.

Patient-derived xenografts (PDX) are valuable, clinically-relevant models of cancer. Their close genomic, phenotypic, and temporal association with patient tumors makes them well-suited for pre-clinical and co-clinical studies that assess the potential of new therapeutics. However, PDX models are not amenable to large-scale drug sensitivity studies due to their high cost and low throughput capacity. To address this, we established and characterized long-term PDX organoid (PDxO) cultures from breast cancer (BC) PDXs and evaluated their utility in therapeutic studies. To establish PDxO culture conditions, we extensively tested medium supplements, including growth factors, kinase inhibitors, conditioned medium, and antioxidants, along with extracellular matrix composition in 3D gels. Using optimized culture conditions for each BC subtype, we established PDxOs from 16 PDX lines in the HCI series, with a PDX to PDxO success rate of 85%. Around 20% of PDxOs contained aggressive mouse stroma, which had to be eliminated by FACS for long-term culture success. PDxOs were maintained for over 1 year, during which we tracked viability, doubling time, organoid size, genomics, epithelial character, and tumorigenicity. Doubling times stabilized after 60 days of initial culture, with a mean of 6.4±1.7 days for triple negative (TN) lines and 7.2±1 days for ER+ lines. Mean organoid size remained stable, with ER+ PDxOs significantly smaller than TN PDxOs, at 91 and 262 cells/organoid respectively (p=0.0012). PDxOs histologically resembled their PDX counterparts when stained for H&E, Vimentin, and CAM 5.2. RNA-Seq and copy-number variation analyses showed that PDxOs clustered with their PDXs and patient tumors. To assess if culturing affected tumorigenicity, we re-implanted PDxOs into mice following early and late passaging. 5/5 early passage and 5/6 late passage PDxOs engrafted and formed tumors. Resulting tumors showed similar gene expression profiles as their original PDXs by RNA-Seq. These data suggest that PDxOs generally recapitulate the molecular and genomic features of their originating PDXs and patient tumors. Having established PDxO cultures, we evaluated their utility as a therapeutic screening platform. We developed a screen to differentiate compounds with cytotoxic and cytostatic effects. NCI CTEP and clinically-approved BC therapies (n=40) were screened in quadruplicate 8-point dose response curves on all 16 PDxOs across three biological replicates. Drug response profiles were stable across biological replicates, spanning up to 1 year in culture. PDxOs exhibited diverse responses to therapies targeting cIAP1, PI3K, and CHK1/2. Initial work to evaluate concordance between PDxO and in vivo PDX responses returned trending linear correlations between PDxO dose response data and change in PDX growth rate following treatment (R2 = 0.52-0.77; p = 0.045-0.12, across 3 PDXs and 9 compounds). Ongoing work aims to confirm concordance between PDX and PDxO models. Our work demonstrates that PDxO models are cost-efficient, easy to maintain, and grow indefinitely - making them renewable and accessible cancer models. PDxOs are a powerful parallel resource to PDX models, especially useful for efficient determination of PDX drug response. We are currently expanding our PDxO bank to include 100 models which will be deposited with the NCI as part of the PDXNet effort. Citation Format: Katrin P. Guillen, Sandra D. Scherer, Yi Qiao, Satya S. Pathi, James M. Graham, Maihi Fujita, Yoko S. DeRose, Jason Gertz, Gabor T. Marth, Katherine E. Varley, Alana L. Welm, Bryan E. Welm. Predicting breast cancer therapy response using a patient-derived xenograft organoid screening platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-038.