Identification of potentially deleterious mutations in gastric cancer using patient-derived xenograft models

Background: Patient-derived xenograft (PDX) models has been widely accepted as a suitable preclinical model. However, the number of PDX models as well as cell-lines from gastric cancer (GC) are limited. We started our DEF study project on May 2013 for establishing new GC PDX models and cell lines for accelerating the development of new therapeutics for GC. Methods: Two hundred and fifty (250) patients, including 233 patients underwent gastrectomy and 17 patients received cell-free and concentrated ascites reinfusion therapy (CART) in our hospitals, were enrolled. We subcutaneously engrafted 232 surgically resected gastric cancer tissues into immune-deficient NOG mice. Primary or PDX tumor tissues or ascites from CART patients were cultivated for establishing GC cell lines. Results and Discussion: From 233 surgically resected tumor tissues, we have successfully established 35 gastric cancer PDX models. PDX-establishment rate was 15.1%, and differentiated type adenocarcinomas (DAs) were more effectively established than poorly differentiated type adenocarcinomas (PDAs). The histology of PDX resembled their primary tumors, and the concordance of histological differentiation grade between primary tumors and PDXs was significant (28/35, p<0.01). Twenty-three (23) GC cell lines have been established from surgically resected primary or subsequently transplanted PDX tissues. Another 2 GC lines were established by cultivating primary GC tissues directly. Among 25 GC cell lines, 24 lines could develop subcutaneous tumors (CDXs) in SCID mice. In contrast to PDX, the concordance of histological differentiation grade between primary tumors and CDXs was not significant. In addition, we have also established 7 GC cell lines from ascites from 17 patients received CART, and six of them could develop CDXs. All of the CDXs from CART cases showed PD histology. As the results, we have established both PDX and Cell lines simultaneously from 21 patients, which allowed us to invest a direct histological and molecular comparison between primary, PDX, and CDX tumors. We would also like to discuss about lymphoproliferative lesions, most of which showed proliferation of B cell with various cytological atypia, encountered during the PDX establishment process. Citation Format: Takeshi Kuwata. Clinicopathological factors associated with establishment of gastric cancer PDXs and cell lines [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A005. doi:10.1158/1535-7163.TARG-19-A005

Background: Antibody-drug conjugates (ADCs) have become promising antitumor agents in recent years. ADCs are comprised of a monoclonal antibody, targeting antigens expressed at higher levels on tumor cells than on normal cells, cross-linked to small molecule payloads with cytotoxic activity. Human Claudin 18.2 (CLDN18.2) is overexpressed in a large proportion of gastric and pancreatic cancers, with restricted normal tissue expression. The monoclonal antibody targeting CLDN18.2 (IMAB362) has demonstrated promising clinical benefit in combination with chemotherapies for gastric cancer patients. However, the same antibody shows suboptimal efficacy in patients with low CLDN18.2 expression. Here we report the potent in vivo efficacy of ATG-022, a CLDN18.2 ADC, in multiple gastric cancer patient-derived xenograft (PDX) models, including those with low CLDN18.2 expression. Methods: The binding affinity of ATG-022 with CLDN18.2 was detected by SPR and FACs analysis. The in vitro 50% inhibition concentration (IC50) of ATG-022 was determined in CLDN18.2 positive cell lines using CellTiter-Glo luminescent cell viability assay. In vivo efficacy of ATG-022 was evaluated in a series of gastric cancer PDX models with different expression level of CLDN18.2 The expression level of CLDN18.2 was determined using IHC staining. ATG-022 was dosed twice at 1 mg/kg, 3 mg/kg or 10 mg/kg every two weeks. Results: ATG-022 binds to CLDN18.2 protein with sub-nM affinity. It induced potent in vitro cytotoxicity in CHOK1 cells overexpressing CLDN18.2, with an IC50 of 5-7nM. Bystander killing by ATG-022 was observed. ATG-022 demonstrated potent in vivo antitumor efficacy in a gastric cancer PDX model with high CLDN18.2 expression. Intravenous dosing of 1 mg/kg, 3 mg/kg, and 10 mg/kg ATG-022 induced 35.41%, 71.56% tumor growth inhibition (%TGI) and tumor regression respectively. In a PDX model with low CLDN18.2 expression, 3 mg/kg ATG-022 or 10 mg/kg clinical benchmark CLDN18.2-ADC did not inhibit tumor growth, while 10 mg/kg ATG-022 induced tumor regression. Conclusions: ATG-022 demonstrated potent in vitro and in vivo antitumor effects, with in vivo efficacy observed in CLDN18.2-low expression PDX models, suggesting a promising therapeutic strategy for gastric cancer patients with a broad range of CLDN18.2 expression levels. Citation Format: Peng Chen, Yun Liu, Min Deng, Linjie Tian, Kevin Lynch, Bo Shan, Jay Mei, Bing Hou. ATG-022, an antibody-drug conjugate targeting Claudin 18.2, demonstrated potent in vivo efficacy in gastric cancer patient-derived xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1143.

Patient-derived xenograft (PDX) models have been recognized as being more suitable for predicting therapeutic efficacy than cell-culture models. However, there are several limitations in applying PDX models in preclinical studies, including their availability—especially for cancers such as gastric cancer—that are not frequently encountered in Western countries. In addition, the differences in morphology between primary, PDX, and tumor cell line-derived xenograft (CDX) models have not been well established. In this study, we aimed to establish a series of gastric cancer PDXs and cell-lines from a relatively large number of gastric cancer patients. We also investigated the clinicopathological factors associated with the establishment of PDX and CDX models, and compared the histology between the primary tumor, PDX, and CDX that originated from the same patient. We engrafted 232 gastric cancer tissues into immune-deficient mice subcutaneously and successfully established 35 gastric cancer PDX models (15.1% success rate). Differentiated type adenocarcinomas (DAs, 19.4%) were more effectively established than poorly differentiated type adenocarcinomas (PDAs, 10.8%). For establishing CDXs, the success rate was less influenced by histological differentiation grade (DA vs. PDA, 12.1% vs. 9.8%). In addition, concordance of histological differentiation grade between primary tumors and PDXs was significant (p < 0.01), while concordance between primary tumors and CDXs was not. Among clinicopathological factors investigated, pathological nodal metastasis status (pN) was significantly associated with the success rate of PDX establishment. Although establishing cell lines from ascites fluid was more efficient (41.2%, 7/17) than resected tissues, it should be noted that all CDXs from ascites fluid had the PDA phenotype. In conclusion, we established 35 PDX and 32 CDX models from 249 gastric cancer patients; among them, 21 PDX/CDX models were established from the same patients. Our findings may provide helpful insights for establishing PDX and CDX models not only from gastric but from other cancer types, as well as select preclinical models for developing new therapeutics.

IA29: Mice host selection for patient-derived xenograft (PDX) model development and other critical factors for success

The phosphoinositide 3-kinase (PI3K) pathway is a key driver of hormone receptor (HR)–positive breast cancer growth and survival. It is estimated that 40-45% of HR+ breast cancers harbor oncogenic mutations in the PIK3CA gene, which encodes the p110α isoform of PI3K. Taselisib (GDC-0032) is a mutant-selective PI3K inhibitor that demonstrates enhanced potency in PIK3CA mutant breast cancer cells and is being developed as a treatment for metastatic breast cancer that targets PIK3CA-mutant, HR-positive, HER2-negative patients. Activating mutations in the ESR1 gene were recently described in metastatic breast cancer. These mutations confer hormone independent growth and may be associated with resistance to aromatase inhibitors. Drugs that selectively bind and antagonize the Estrogen Receptor alpha (ERα) protein and target it for degradation, such as fulvestrant, are referred to as selective estrogen receptor degraders (SERDs). Preclinical activity of the orally bioavailable SERD, GDC-0810, has not been well characterized in ESR1 mutant PDX models. Therefore, our aim was to evaluate the efficacy and pharmacodynamic responses to agents that target ERα and PI3K as monotherapies and in combination, in ESR1 and PIK3CA mutant HR+ breast cancer patient-derived xenograft (PDX) models. We hypothesized that mutational status of ESR1 and PIK3CA may predict the responsiveness of HR+ PDX models to SERDs and PI3K inhibitors in vivo. Characterization of seven PDX models included authentication of hormone receptor status by immunohistochemistry (IHC) and determination of ESR1 and PIK3CA genotype and allele frequency by exome sequencing. For a subset of models that utilize estrogen for growth, mice were supplemented with 17β-estradiol, and cells or tumor fragments were implanted into the fat pad of intact female NOD-SCID or NOD-SCID-IL2Rgamma null mice and treated with fulvestrant, GDC-0810, or taselisib. Both fulvestrant and GDC-0810 were efficacious in ESR1 wild type (WT) and mutant PDX models but to variable degrees ranging from tumor stasis to growth delay, with GDC-0810 resulting in superior single agent activity at relevant clinical exposure in the WHIM20 and WHIM43 ESR1 mutant models. PIK3CA mutations (E542K, E545K, M1004V, and H1047R) were confirmed in six PDX models and PI3K pathway activation verified by strong pS6RP IHC staining. Taselisib induced tumor growth inhibition and tumor regressions in models harboring PIK3CA mutations, and models with no detectable expression of WT p110α were the most sensitive. In the WHIM43 (ESR1 D538G, PIK3CA M1004V), HCI-011 (ESR1 WT, PIK3CA E545K) and HCI-013 (ESR1 Y537S, PIK3CA H1047R) PDX models, combining fulvestrant and taselisib treatment further enhanced tumor growth inhibition with respect to either treatment alone. Our studies demonstrate the diverse anti-tumor responses of HR+ PDX models to SERDs and the PI3K inhibitor taselisib in the context of clinically relevant ESR1 and PIK3CA mutations. Pharmacological and genomic characterization of additional PDX models may aid in strengthening associations between genotype, drug sensitivity and predictive biomarkers of response. Citation Format: Young A, Crocker L, Cheng E, Lacap J, Hamilton P, Oeh J, Ingalla E, Arrazate A, Hager J, Nannini M, Friedman L, Daemen A, Giltnane J, Sampath D. Treatment of ESR1 mutant and PIK3CA mutant patient-derived breast cancer xenograft models reveals differential anti-tumor responses to estrogen receptor degraders and PI3K inhibitors in vivo [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-06-05.

Objective:Patient-derived xenograft (PDX) models have shown great promise in preclinical and translational applications, but their consistency with primary tumors in phenotypic, genetic, and pharmacodynamic heterogeneity has not been well-studied. This study aimed to establish a PDX repository for non-small cell lung cancer (NSCLC) and to further elucidate whether it could preserve the heterogeneity within and between tumors in patients.Methods:A total of 75 surgically resected NSCLC specimens were implanted into immunodeficient NOD/SCID mice. Based on the successful establishment of the NSCLC PDX model, we compared the expressions of vimentin, Ki67, EGFR, and PD-L1 proteins between cancer tissues and PDX models using hematoxylin and eosin staining and immunohistochemical staining. In addition, we detected whole gene expression profiling between primary tumors and PDX generations. We also performed whole exome sequencing (WES) analysis in 17 first generation xenografts to further assess whether PDXs retained the patient heterogeneities. Finally, paclitaxel, cisplatin, doxorubicin, atezolizumab, afatininb, and AZD4547 were used to evaluate the responses of PDX models to the standard-of-care agents.Results:A large collection of serially transplantable PDX models for NSCLC were successfully developed. The histology and pathological immunohistochemistry of PDX xenografts were consistent with the patients’ tumor samples. WES and RNA-seq further confirmed that PDX accurately replicated the molecular heterogeneities of primary tumors. Similar to clinical patients, PDX models responded differentially to the standard-of-care treatment, including chemo-, targeted- and immuno-therapeutics.Conclusions:Our established PDX models of NSCLC faithfully reproduced the molecular, histopathological, and therapeutic characteristics, as well as the corresponding tumor heterogeneities, which provides a clinically relevant platform for drug screening, biomarker discovery, and translational research.

cMet is a well-characterized oncogene that is the target of many drugs including small molecule and biologic pathway inhibitors, and more recently, antibody drug conjugates (ADCs). However, clinical benefit from c-Met targeted therapy has been limited up to this point. We developed an optimized c-Met targeted antibody drug conjugate TR1801-ADC that utilized optimization at all steps including specificity, stability, internalization, toxin linkers, conjugation site, PK, and in vivo efficacy. The results were a highly potent c-Met ADC that was superior in comparison to a conventional MMAE (monomethylauristatin E) cMet ADC in potency, efficacy and duration of response. TR1801-ADC is site-specifically conjugated to a PBD-toxin linker and has low picomolar activity in multiple cancer cell lines derived from different solid tumors including lung cancer, colorectal cancer and gastric cancer. The potency of our cMet ADC is independent of MET gene copy number and its activity was high not only in high cMet cell lines but also in medium to low cell lines (100,000 to 40,000 cMet/cell). We identified potential Phase 1 cancer indications based on IHC and cMet H-score from tissue micro arrays (TMAs). 3 cancer indications (gastric, colorectal and head &amp; neck cancer) were chosen based on high abundance of high cMet expression (&amp;gt;20% abundance of H-Score higher than 150) and were used to assess the efficacy of our cMet ADC in PDX models. For each indication 10 PDX (patient-derived xenograft) models were chosen based on their cMet expression. TR1801-ADC was administered in all models as single i.v. dose at 1, 0.5, 0.25 and 0.125 mg/kg. Control ADC was administered at 1mg/kg. Tumor growth inhibition varying from &amp;gt;100% to around 40% was seen in all gastric cancer PDX models with single dose injections of 1 mg/kg and 0.5 mg/kg. Complete tumor regression was seen in 70% of the 1 mg/kg group, in 50% of the 0.5 mg/kg group and in 40% of the 0.25 mg/kg group. TR1801-ADC produced statistically significant growth inhibition in comparison to untreated controls in 9 colorectal cancer PDX models. Complete tumor regression was observed in 40% (4/10) PDX models when treated with 1 mg/kg TR1801-ADC. The further 50% showed partial regression (5/10 models) and one showed no significant tumor response. The head &amp; neck cancer PDX models were in general least sensitive to TR1801-ADC. TR1801-ADC produced statistically significant growth inhibition in comparison to untreated controls in 8/10 head &amp; neck cancer PDX models. Complete tumor regression was observed in 30% (3/10) PDX models when treated with 1 mg/kg TR1801-ADC. 50% showed statistical significant partial regression while two models (20%) showed no significant tumor inhibition. Altogether, TR1801-ADC is a novel highly potent cMet ADC that shows very promising efficacy in PDX models of gastric, colorectal and head &amp; neck cancer with long lasting anti-tumor effect with a single dose. Citation Format: Marco Gymnopoulos, Oscar Betancourt, Vincent Blot, Ryo Fujita, Diana Ly, Sophie Nguyen, Jeanette Snedden, Jose Villicana, Jon Wojciak, Eley Wong, Neki Patel, Francois D'Hooge, Balakumar Vijayakrishnan, Conor Barry, John A. Hartley, Phil W. Howard, Roland Newman, Julia Coronella. TR1801-ADC, an optimized anti cMet PBD ADC with high efficacy in solid tumors of the GI tract and head &amp; neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 225.

PATIENT-DERIVED ORTHOTOPIC GRAFT MODEL OF ORAL CANCER: HISTOPATHOLOGICAL AND IMMUNOHISTOCHEMICAL COMPARISON.

[Introduction: Solid tumors of the nervous system are the most common childhood cancers after leukemias. Even though we might be able to cure more and more patients, survivors still severely suffer long-term from the intensive treatments. Therefore, new treatment strategies are urgently needed. Orthotopic patient-derived xenograft (PDX) models are an excellent platform for biomarker and preclinical drug development. However, the rarity of pediatric brain tumors and the multitude of different sub entities hinder the generation of large collection of PDX models of specific entities within single institutions. In order to generate an overview about existing PDX models in the community, we started collecting established PDX models from various centers all over the world and performed extensive molecular characterization to precisely determine the distinct molecular subgroup and constellation of genetic alterations for each PDX model, and thus identify its targetable oncogenic drivers. Material and Methods: PDX models were established and maintained by dissociating tumor material into a single cell suspension and then orthotopically injecting it into the brain of immunodeficient animals. All PDX models and matching primary tumors (if available) have been analyzed by whole-exome and low-coverage whole-genome sequencing, as well as DNA methylation and gene expression profiling at the German Cancer Research Center (DKFZ). Results and Discussion: Thus far, we have collected and characterized 70 established PDX models from 6 ATRTs, 8 ependymomas, 16 high-grade gliomas, 38 medulloblastomas, and 2 CNS-PNETs. PDX models always retain their molecular subtype and in the vast majority of cases also the mutations and copy number alterations when compared to their primary tumors. Only in rare cases do we observe additional aberrations, which most likely represent outgrowths of subclones from the primary tumor. Analysis of our entire cohort identified an overrepresentation of the most aggressive tumor subtypes, but also subtypes which have not been available for preclinical testing before due to lack of genetically engineered mouse models or suitable cell lines, such as Group 4 medulloblastoma. Based on our current analysis, the PDX models within the community are not yet covering the entire heterogeneity within the patient population. As a follow up, we aim to make these models and data accessible in a user-friendly manner so that the community can use them for preclinical research. Conclusion: PDX models of pediatric brain tumors are very rare. Our molecular characterization allows researchers all over the world to find the right models for their specific scientific question. Therefore, this work will provide an unprecedented resource to study tumor biology and pave the way for improving treatment strategies for children with malignant brain tumors. Citation Format: Sebastian Brabetz, Susanne N. Gröbner, Huriye Seker-Cin, Florian Selt, Till Milde, David T. Jones, Madison T. Wise, Jessica M. Rusert, Kyle Pedro, Andy Strand, Olaf Witt, Sarah E. Leary, Xiao-Nan Li, Robert J. Wechsler-Reya, James M. Olson, Stefan M. Pfister, Marcel Kool. Molecular characterization of orthotopic patient-derived xenograft models of pediatric brain tumors [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 1935. doi:10.1158/1538-7445.AM2017-1935

Carcinoembryonic antigen cell adhesion molecule 5, CEACAM5, is a glycosylphosphatidylinositol-anchored glycoprotein expressed on the cell surface of most of the colorectal cancer (CRC) and pancreatic ductal adenocarcinoma (PDAC) and of more than 2/3 of gastric cancer (GC) and non-small cell lung cancer (NSCLC) while normal tissue expression is limited. The high prevalence of CEACAM5 expression prompted us to develop a novel CEACAM5 topoisomerase I inhibitor (Topo1i) antibody drug conjugate (ADC) with a DAR of 8, SGN-CEACAM5C/SAR445953. The anti-CEACAM5 antibody was chosen based on its high selectivity for CEACAM5 and its potential to direct cytotoxic payloads to tumor. The Topo1i payload was optimized for potency and enhanced bystander activity. SGN-CEACAM5C/SAR445953 is rapidly internalized and demonstrates in vitro cytotoxicity with EC50 values in the sub-nM range while it induces no toxicity on CEACAM5-negative cells. The potent anti-tumor activity is mediated by direct cytotoxicity on CEACAM5-expressing tumor cells and by a strong bystander effect due to the diffusion of the payload to the neighboring CEACAM5-negative tumor cells. Accordingly, the ADC incubated in a co-culture of CEACAM5-positive and -negative cells at a ratio of 1/1 induces a ~50% growth inhibition of CEACAM5-negative cells. Interestingly, with incubated ADC, only 1% of CEACAM5-positive cells in co-culture are sufficient to provide 11% growth inhibition of CEACAM5-negative cells. In vivo, SGN-CEACAM5C/SAR445953 is stable in circulation in SCID mice with a t1/2 close to 15 days. In vivo efficacy at 1, 3 and 10 mg/kg (single administration) was evaluated in panels of 4 CRC, 3 PDAC, 4 NSCLC and 3 GC patient-derived xenograft (PDX) models. At 10 mg/kg, the ADC elicits antitumor regression in 14/14 models. At 3 mg/kg, tumor regression occurs in 12/14 models. This potent, specific and dose dependent anti-tumor activity was further confirmed in Single Mouse Trials (SMT) of 20 CRC PDX models, 31 lung cancer PDX models and 19 gastric cancer PDX models. SMT consists in use of one animal per PDX model per treatment arm and for which the evaluation of efficacy is based on RECIST (Response Evaluation Criteria In Solid Tumors) criteria used in clinic. In CRC, gastric and lung cancer SMT, disease control rates are 95%, 84% and 87%, respectively with overall response rates of 55%, 68% and 71% including 15%, 10% and 26% of complete responses, respectively. The high anti-tumor activity across panels of PDX models of several CEACAM5 positive indications supports further evaluation of SGN-CEACAM5C/SAR445953 in patients with CRC, PDAC, GC and lung cancers (NCT06131840). Citation Format: Yves Baudat, Celine Nicolazzi, Johann Petur Sigurjonsson, Celine Amara, Astrid Clarke, Ryan lyski, Dave Meyer, Valeria Fantin, Marielle Chiron, Stephanie Decary. SGN-CEACAM5C/SAR445953, a novel topoisomerase I inhibitor antibody-drug conjugate targeting CEACAM5, has potent anti-tumor activity in CRC, PDAC, GC and lung cancer tumor models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2118.

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.

Brain tumors are the leading cause of cancer-related mortality in childhood. Based on the many recent genomic studies, we know now that multiple molecular subtypes of brain cancers exist that are not only biologically but also clinically highly distinct. These findings may lead to novel treatment strategies. For this we need better preclinical models that correctly reflect the proper tumor (sub)type. Orthotopic patient-derived xenograft (PDX) models generated by intracranial injection of primary patient material into the brain of NOD scid gamma (NSG) mice offer the unique possibility to test novel substances in primary patient tissue in an in vivo environment. Prior to drug selection and testing, extensive molecular characterizations are needed to learn about targetable oncogenic drivers in each model. Therefore, we aim to generate a large repertoire of PDX models reflecting the many different molecular subtypes of pediatric brain cancer. For each established PDX model, we perform DNA methylation profiling, gene expression profiling, low-coverage whole genome sequencing and whole exome sequencing and compare these data with the matching primary tumor. Thus far, as a collaborative effort between different laboratories, we have established and fully characterized 34 PDX models from 1 atypical teratoid rhabdoid tumor (ATRT), 4 ependymoma, 9 glioblastoma, 18 medulloblastoma, and 2 primitive neuroectodermal tumors (PNET). Molecular analysis of all available PDX models identified a clear overrepresentation of most aggressive tumors such as models characterized by MYC- or MYCN amplification. Other, less aggressive cancers, like Wnt medulloblastoma, are underrepresented. For in vivo imaging during treatment of PDX models we created luciferase labeled PDX sublines. Our data demonstrate that PDX models retain characteristics of the primary human tumors from which they were derived. These reagents provide an unprecedented resource to study tumor biology and pave the way for improving treatment strategies of malignant pediatric brain tumors.

Background: Extrachromosomal DNA (ecDNA) is a driver of tumor heterogeneity and is associated with poor survival in many different adult and childhood cancer types. Patient-derived xenograft (PDX) models facilitate preclinical drug testing in an in vivo environment that enables analysis of tumor growth and survival and molecular tumor profiling. These models, combined with single-cell profiling, can be used to study intratumoral heterogeneity under therapeutic pressure and the emergence of drug resistance. Here we investigate the abundance and conservation of ecDNA in PDX models with the aim of assessing the faithful representation of ecDNA compared to the tumors from which they are derived. Methods: Whole-genome sequencing (WGS) was applied to 27 medulloblastoma (MB) PDX models and their tumors of origin using Amplicon Architect, a tool used to reconstruct focally amplified regions of DNA to provide insights into the landscape of cancer genomes. The frequency of ecDNA in these models was also compared to that of ecDNA in the MB patient population. Optical genome mapping enabled accurate and reliable ecDNA sequence reconstructions. Multiome single-cell RNA and ATAC-sequencing of a PDX tumor enabled analysis of ecDNA conservation and intratumoral heterogeneity compared to similar data previously obtained from the primary tumor. Results: Comparative analyses revealed that ecDNA is largely conserved in PDX models, emphasizing their relevance as faithful models of the primary tumors. In addition, we find that ecDNA is significantly more frequent in MB PDX models (16 out of 27 analyzed patient-derived tumors) as compared to their frequency in the overall patient population (~18% of all medulloblastoma tumors contain ecDNA), suggesting ecDNA as a driver for successful establishment of MB PDX models. Single-cell analysis revealed that ecDNA is omnipresent in almost all PDX tumor cells, while its presence was limited to only ~9% of tumor cells in the primary tumor. Conclusion: Analysis of ecDNA in medulloblastoma primary tumors and in PDX models revealed that ecDNA is preserved in PDX models. This is an important characteristic that renders patient-derived mouse xenografts as faithful models of their primary tumors. These results emphasize the relevance of PDX models for preclinical in vivo studies aimed at analyzing the role of ecDNA under therapeutic pressure and for analyzing clonal selection along with molecular evolution of ecDNA during the development of therapeutic resistance. Citation Format: Rishaan Kenkre, Owen Chapman, Jens Luebeck, Vineet Bafna, Robert Wechsler-Reya, Jill Mesirov, Lukas Chavez. Conservation and faithful representation of circular extrachromosomal DNA in orthotopic patient-derived medulloblastoma xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2271.

Prostate Cancer (PCa) is the second most frequent cancer in men worldwide and the fifth leading cause of cancer death with an incidence rate of 13.5%. PCa is driven by multiple genomic alterations, with distinct patterns and clinical implications. These genomic alterations occurring both early and later in the natural history of the disease (ranging from localized disease, initially responsive to androgen deprivation therapy, to Castrate Resistant Prostate Cancers -CRPC) allow classification of PCa in several molecular subtypes with potential clinical relevance. Patient-Derived Xenograft (PDX) models have become the most reliable in vivo human cancer models. Developing such models that capture the biological heterogeneity and mutational landscape of PCa, remains a challenge, but is essential for delivery of precision medicine in metastatic castrate resistant stages. In this study, we present the genomic and transcriptomic landscapes, as well as the pharmacological status of an established bank of seven (7) prostate PDX models ranging from hormone naïve to hormone-resistance PCa specimens. Samples of PCa along with normal corresponding tissues were obtained directly from patients at surgery. Fragments were subcutaneously xenografted into immunocompromised mice to establish PDX models. After the first growth in mice, they were serially passaged in vivo and considered to be established from P3. To ensure model stability, PDX tumors at multiple passages and patients' primary tumors were processed for histological, transcriptomic (Affymetrix U133 plus 2.0 microarray) and STR profile analyses. Genomic characteristics (WES, CNA) were also investigated. Finally, the responses of the PDX models to androgen deprivation and docetaxel were also evaluated. 7 PDX models were successfully established (&amp;gt; P3 in mice) out of 253 primary prostatic tumors collected from surgery. Within those models, one matched pair of responsive adenocarcinoma and neuroendocrine castration-resistant (NE-CRPC) models from the same patient was generated. Histological, transcriptomic and STR profiling validated the stability of the models compared to the parental tumor. The genomic analyses revealed i) the mutational burden rise with the resistance to treatments of the models, correlating with clinical results ii) an increase of metastatic genes loss in the NE-CRPC compared to the corresponding hormone sensitive adenocarcinoma. Furthermore, for all the PDX models generated, genomic and mutational analyses revealed specific molecular features and allowed molecular classification depending on tumor stage. Based on the molecular taxonomy of primary prostate cancers, the presented panel covers the different progression steps of the pathology. Considering the scarcity of useful models for PCa and the difficulties to develop such models, the prostate PDX models collection presented here should clearly help understanding disease progression and supporting precision medicine approaches for patients with advanced PCa. Citation Format: Myriam Lassalle, Claire Béraud, Hervé Lang, Véronique Lindner, Yves Allory, Eric Potiron, Thierry Massfelder, Philippe Lluel, Yolande Misseri. Mutational landscape and pharmacological profiling of a panel of prostate PDX models including hormone-naïve, hormone-sensitive and castrate-resistant prostate cancer specimens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1668.

Introduction: Gastric cancer is a leading cause of global cancer mortality with an overall 5-year survival rate of approximately 20% and is particularly prevalent in many Asian countries. ASC amino acid transporter 2 (ASCT2), also known as SLC1A5, is a Na+-dependent glutamine/neutral amino acid transporter. ASCT2 acts as a high-affinity transporter of L-glutamine (Gln) and has been reported to be upregulated in a variety of cancerous tissues, including stomach. Several studies have shown that glutamine is a major nutrient contributing to cancer cell growth, so the glutamine metabolism pathway is an attractive target for gastric cancer treatment. In this study, we evaluated the efficacy of a novel anti-ASCT2 humanized monoclonal antibody, KM8094, as a therapeutic agent against gastric cancer and explored predictive biomarker candidates using patient-derived xenograft (PDX) mouse models. Materials and Methods: The tumor tissues from which the PDX models were generated were provided by Dr. Chan Shing Leng (NUS, Singapore). For the glutamine uptake assay, PDX-tumor cells were incubated with 3H-glutamine in the presence of KM8094. Intracellular 3H-glutamine was measured by liquid scintillation spectrophotometry. In vitro ADCC activity against human gastric cancer cells (SNU-16) was evaluated using human peripheral blood mononuclear cells (PBMC) from either gastric cancer patients or healthy controls as effector cells. In vivo antitumor activity of KM8094 was examined using PDX models. Mice were treated with KM8094 at 10 mg/kg i.v. or phosphate-buffered saline once weekly for 2-3 weeks. Finally, omics analyses of PDX tumor tissues were performed via a gene expression array analysis, DNA methylation array analysis, and metabolomics analysis. Results: All five gastric cancer PDX models histologically expressed ASCT2. KM8094 significantly inhibited the 3H-glutamine uptake in vitro and showed in vivo antitumor efficacy in the gastric cancer PDX models. In addition, KM8094 showed in vitro ADCC activity against gastric cancer cells using PBMCs from gastric cancer patients. These results indicated that KM8094 is a potential new therapeutic agent for gastric cancer treatment. Finally, we explored predictive biomarker candidates of KM8094 by a multi-omics analysis on the PDX models, and a few candidates were selected by genomic analyses. In addition, a metabolomics analysis revealed clear differences in the intracellular energy and redox status between responsive and nonresponsive PDX models. Conclusions: These results demonstrated the therapeutic potential of KM8094 for the treatment of gastric cancer and provide some insight into predictive biomarker candidates for antitumor efficacy. Citation Format: Noriyuki Kasai, Aya Sasakawa, Kenta Hosomi, Tze Wei Poh, Bernadette Lynn Chua, Wei Peng Yong, Jimmy So, Shing Leng Chan, Richie Soong, Koji Kono, Toshihiko Ishii, Kazuya Yamano. Evaluation of a novel monoclonal antibody targeting ASC amino acid transporter 2 using patient-derived xenograft mouse models of gastric cancer [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 B035.