Abstract Purpose: Glioblastoma is the most frequent and lethal primary brain tumor. Development of novel therapies relies on the availability of relevant preclinical models. We have established a panel of 96 glioblastoma patient-derived xenografts (PDX) and undertaken its genomic and phenotypic characterization. Experimental Design: PDXs were established from glioblastoma, IDH-wildtype (n = 93), glioblastoma, IDH-mutant (n = 2), diffuse midline glioma, H3 K27M-mutant (n = 1), and both primary (n = 60) and recurrent (n = 34) tumors. Tumor growth rates, histopathology, and treatment response were characterized. Integrated molecular profiling was performed by whole-exome sequencing (WES, n = 83), RNA-sequencing (n = 68), and genome-wide methylation profiling (n = 76). WES data from 24 patient tumors was compared with derivative models. Results: PDXs recapitulate many key phenotypic and molecular features of patient tumors. Orthotopic PDXs show characteristic tumor morphology and invasion patterns, but largely lack microvascular proliferation and necrosis. PDXs capture common and rare molecular drivers, including alterations of TERT, EGFR, PTEN, TP53, BRAF, and IDH1, most at frequencies comparable with human glioblastoma. However, PDGFRA amplification was absent. RNA-sequencing and genome-wide methylation profiling demonstrated broad representation of glioblastoma molecular subtypes. MGMT promoter methylation correlated with increased survival in response to temozolomide. WES of 24 matched patient tumors showed preservation of most genetic driver alterations, including EGFR amplification. However, in four patient–PDX pairs, driver alterations were gained or lost on engraftment, consistent with clonal selection. Conclusions: Our PDX panel captures the molecular heterogeneity of glioblastoma and recapitulates many salient genetic and phenotypic features. All models and genomic data are openly available to investigators.
TMOD-18. THE PATIENT DERIVED XENOGRAFT NATIONAL RESOURCE: A COMPREHENSIVE COLLECTION OF HIGH-GRADE GLIOMA MODELS FOR PRE-CLINICAL AND TRANSLATIONAL STUDIES
Abstract BACKGROUND/PURPOSE The Mayo Clinic has developed a large panel of patient-derived xenografts (PDX) from patients with glioblastoma multiforme (GBM). Here we report initial molecular profiling of the Mayo PDX panel and a comparison of patient and PDX molecular profile and response to therapy. METHODS & MATERIALS Clinical data was retrieved by retrospective chart review. Animal data from all PDX investigations conducted between 2004-2014 were retrieved from experimental logs and subsequently consolidated into a database for analysis. RESULTS From 1999 to 2014, 182 patient tumor samples of varying histological grades were attempted for xenograft with 73 resulting viable PDX lines. Viable xenografts were only produced from WHO grade IV tumor specimens, yielding an overall success rate of 49% for these tumors. GBM patients that produced viable xenografts compared to those that did not exhibited a trend for decreased overall survival (P = 0.18). There was no significant association between successful xenografting and whether tissue was from newly diagnosed (45/93%) or recurrent (20/40; 50%) tumors. Patient age > 45 at diagnosis was correlated with increased PDX viability in GBMs (p = 0.05). Of the viable PDX models analyzed, EGFR mutation was identified in 17 lines, TERT mutation was found in 13 lines, IDH mutation in 1 line, and MGMT hypermethylation in 25 lines. RNAseq was performed on orthotopic tumor samples from 53 PDX models. After excluding contaminating murine sequence reads, expression analysis demonstrated 32 models with a mesenchymal phenotype. Array comparative genomic hybridization was performed on 9 patient samples and derivative early, mid and late passage PDX tumors. Using unbiased hierarchical clustering, there was a high concordance between patient and xenograft models. Within the PDX panel, fractionated radiation (RT) alone and RT combined with temozolomide (TMZ) was tested in orthotopic tumors in 38 lines. The overall median survival benefit (ratio of median survival for treated vs. placebo) in PDX lines treated with RT only was 1.6 (range: 0.9-2.5) and with RT/TMZ was 2.5 (range: 1.1 - 8.9). There was a positive association between observed patient survival and the corresponding survival benefit in the PDX for subjects treated with RT/TMZ (r = 0.2; n = 17). Response to adjuvant TMZ was evaluated in 42 tumor lines, and response to bevacizumab was tested in 33 tumor lines, and correlations with clinical treatment response are being evaluated. CONCLUSIONS: The Mayo GBM PDX panel is widely used in the neuro-oncology community. The initial molecular analysis suggests a good correlation between patient and PDX at the level of genotypic characteristics and therapeutic sensitivity. Citation Format: Dioval A. Remonde, Brett L. Carlson, Mark A. Schroeder, Brock Armstrong, Sen Peng, Lisa Evers, Paul A. Decker, Jeanette Eckel Passow, Michael E. Berens, Nhan L. Tran, Robert B. Jenkins, Jann N. Sarkaria. Characterization of patient-derived xenograft (PDX) models to evaluate clinical and therapeutic responses of glioblastoma multiforme. [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 1468. doi:10.1158/1538-7445.AM2015-1468
Abstract P2-03-07: Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in breast cancer
Abstract Background: Breast tumors exhibit intratumor heterogeneity resulting in targeted therapy resistance and other challenges in disease management. To address the sources of heterogeneity, we performed a unique, in-depth analysis of clonal architecture in primary chemoradiation-naïve breast cancers. We combined DNA content-based flow cytometry and ploidy analysis with aCGH and next-generation sequencing (NGS) in multiple biopsies from the tumors and involved lymph nodes (LNs). Material and methods: We used DNA content-based flow sorting to isolate nuclei from distinct populations of diploid and aneuploid tumor cells in surgical tumor samples from two chemoradiation-naïve patients. Each sorted tumor cell population was interrogated with aCGH and exome NGS. In Patient #1, we used 12 fresh frozen sections morphologically mapped from within a HER2+, ER+, PR- primary invasive ductal carcinoma (IDC) of histological grade 3 with LN involvement and 2-3 sections from 2 out of 5 LNs. In Patient #2, 11 morphologically mapped fresh frozen sections were analyzed from a grade 2, ER+, PR+, HER2+, BRCA2 mutant LN- IDC. In parallel, matching samples were processed for IHC assays. Results: We identified multiple co-existing aneuploid populations within the biopsies. The 17 primary and LN biopsies from Patient #1 fell into 6 distinct ploidy groups albeit with aberrant but homogenous aCGH profiles, characterized by SARC amplification and homozygous deletions in ROBO1 and ROBO2. In contrast a dominant ploidy was identified throughout Patient #2 but with heterogeneous aCGH profiles. Mutation profiles obtained through exome sequencing further confirmed that ploidy was the main driver in Patient #1 whereas copy number aberrations played the key role in Patient #2 with the BRCA2 mutation (R3129X). A dendrogram based on exome variant calls of the aneuploid populations in Patient #1 strongly correlated with ploidy group and further revealed the specific clonal population characterized by a 5N ploidy and homozygous mutations in TP53 and PIK3CA as the progenitor to the ploidies present in the distant LNs. Strikngly, both patients had no HER2 amplification or mutation across their clonal populations, contradicting the initial IHC staining in a single core biopsy. Conclusions Rather than inferring the presence of distinct tumor cell populations, our novel flow-sorting based approach of first identifying the clonal populations and then interrogating their genomes, provides an objective method of exploring the sources and clinical significance of tumor heterogeneity. Our approach of clonal analysis has broad implications in the study of tumor heterogeneity and the identification of drivers in breast and other solid tumors that can advance more effective treatment and clinical management of patients with this disease. Citation Format: Princy Francis, Lucretia M Alvarez, Elizabeth Lenkiewicz, Mia Champion, Lisa Evers, Karen L Anderson, Ann E McCullough, Michael T Barrett, Barbara Pockaj. Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in breast cancer [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 P2-03-07.
Abstract PD4-7: Deep clonal profiling of primary breast cancer and distant lymph node metastases
Abstract Background: Breast and other solid tumors exhibit high and varying degrees of intra-tumor heterogeneity that make the management and treatment of these diseases rather difficult. In order to study clinically relevant tumor heterogeneity in detail we performed an in-depth analysis of the clonal architecture of primary chemoradiation-naive breast cancers and their lymph node metastases. We combined DNA content-based flow cytometry and ploidy analysis with high-definition array comparative genomic hybridization (aCGH) and next-generation sequencing technologies to interrogate the genomes and transcriptomes of multiple biopsies from the tumors and involved lymph nodes. Thus rather than inferring the presence of distinct tumor cell populations, our flow-sorting based approach of first identifying and defining the clonal populations and then interrogating their genomes provides a highly objective method of exploring the clinical significance of tumor heterogeneity in solid tumors. Material and methods: We used DAPI-based DNA content measurements and flow sorting to isolate nuclei from distinct clonal populations of diploid and aneuploid tumor cells in surgical tumor samples and distant lymph nodes from chemoradiation naive patients. In parallel, matching samples were processed for pathological, transcriptome, and IHC based assays. Each distinct sorted tumor cell population was then interrogated with aCGH and next generation sequencing. For each patient, the detailed profiles of ploidy, copy number aberrations and mutations were used to recreate and map the lineages present in the primary tumor and lymph. In one detailed case, we used 12 fresh frozen sections morphologically mapped from within a chemo-naïve primary invasive ductal carcinoma of histological grade 3 with lymph node involvement, 2-3 fresh frozen sections from 2 out of 5 lymph nodes with metastatic carcinoma, formalin-fixed paraffin-embedded (FFPE) tissue sections from 2 more of the involved lymph nodes and 5 morphologically mapped FFPE samples of normal tissue adjacent to the tumor. Results: We identified multiple coexisting aneuploid populations within biopsies from individual patients. Our clonal analysis determined the genomic aberrations arising in lineages that spread throughout the primary tumor and later bifurcated to distinct lymph nodes, revealing distinct therapeutic targets in the trunk and branches of the tumor. We identified driver events including high-level focal amplifications (e.g. SARC) and homozygous deletions (e.g. ROBO1 and ROBO2), that converge on distinct cellular signaling pathways. Conclusion: The approach highlighted here has broad implications in the study of tumor heterogeneity in breast and other solid tumors by providing a unique ultra-high resolution view of tumor heterogeneity that can advance more effective treatment and clinical management of patients with this disease. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr PD4-7.