Clinically relevant glioblastoma patient-derived xenograft models to guide drug development and identify molecular signatures

Abstract

Glioblastoma (GBM) heterogeneity, aggressiveness and infiltrative growth drastically limit success of current standard of care drugs and efficacy of various new therapeutic approaches. There is a need for new therapies and models reflecting the complex biology of these tumors to analyze the molecular mechanisms of tumor formation and resistance, as well as to identify new therapeutic targets. We established and screened a panel of 26 patient-derived subcutaneous (s.c.) xenograft (PDX) GBM models on immunodeficient mice, of which 15 were also established as orthotopic models. Sensitivity toward a drug panel, selected for their different modes of action, was determined. Best treatment responses were observed for standard of care temozolomide, irinotecan and bevacizumab. Matching orthotopic models frequently show reduced sensitivity, as the blood-brain barrier limits crossing of the drugs to the GBM. Molecular characterization of 23 PDX identified all of them as IDH-wt (R132) with frequent mutations in EGFR, TP53, FAT1, and within the PI3K/Akt/mTOR pathway. Their expression profiles resemble proposed molecular GBM subtypes mesenchymal, proneural and classical, with pronounced clustering for gene sets related to angiogenesis and MAPK signaling. Subsequent gene set enrichment analysis identified hallmark gene sets of hypoxia and mTORC1 signaling as enriched in temozolomide resistant PDX. In models sensitive for mTOR inhibitor everolimus, hypoxia-related gene sets reactive oxygen species pathway and angiogenesis were enriched. Our results highlight how our platform of s.c. GBM PDX can reflect the complex, heterogeneous biology of GBM. Combined with transcriptome analyses, it is a valuable tool in identification of molecular signatures correlating with monitored responses. Available matching orthotopic PDX models can be used to assess the impact of the tumor microenvironment and blood-brain barrier on efficacy. Our GBM PDX panel therefore represents a valuable platform for screening regarding molecular markers and pharmacologically active drugs, as well as optimizing delivery of active drugs to the tumor.

Keywords: blood-brain barrier; drug efficacy; glioblastoma; glioma; mTORC1; patient-derived xenograft (PDX); preclinical oncology; targeted therapy.

Figure 1

Histological and biological characteristics of GBM PDX. (A) Analysis of three representative patient tissue samples and respective s.c. PDX tissue from in vivo passage #2 revealed comparable histology (HE), MGMT expression (red staining) and expression of proliferation marker Ki-67 (brown staining), 200-fold magnification, inset 800-fold magnification. (B) Comparable growth over several consecutive s.c. passages of PDX models Glio11368 and Glio12464. (C) Heterogeneous tumor doubling times in our panel of established PDX models, n=3-6. Mean and standard deviation (SD). (D) Comparison of nodular and infiltrative growth in two different orthotopic (intracerebral, i.cer.) PDX models (cresyl violet staining, tumor tissue stained purple) (0.9-fold magnification). (E) Analysis of PDX Glio12464 revealed comparable histology and Ki-67 expression over several consecutive s.c. passages and parallel orthotopic inoculation. Examination of Ki-67 expression (proliferation marker) in PDX tumor tissue via IHC. Positive areas in the sections are stained brown. 20-fold magnification, inset 160-fold magnification.

Figure 2

Chemosensitivity of established glioma PDX. (A) Examples of drug testings of three s.c. glioma PDX models, illustrating model-specific growth characteristics and treatment responses to different drugs, like temozolomide. N=3-5. Mean and standard deviation (SD). One-way ANOVA, Dunnett’s multiple comparison test. Significant differences to control (PBS) at study end: * p < 0.05, ** p < 0.01, *** p < 0.001. (B) Treatment response evaluation as mean tumor volume of treated tumors divided by mean tumor volume of tumors in the corresponding control group (T/C optimal in %) revealed PDX individual sensitivity profiles. In addition, RTV as response criteria is indicated as progression, stable disease or regression in respective groups. N=2-6 per group. (C) T/C values at study end of orthotopic PDX models Glio10535, Glio10618, Glio12032 and Glio13066 revealed reduced sensitivities when compared to matching s.c. models. The maximum tumor area in coronal plane was used as measure for i.cer. tumor growth. RTV could not be calculated for orthotopic PDX, as tumor sizes were only measured once at study end.

Figure 3

Mutation status of selected genes and their expression in GBM PDX models. (A) Using available RNA sequencing data, a selection of genes frequently mutated in GBM was analyzed for mutations in our panel of GBM PDX, revealing PDX individual profiles. (B) Expression of the genes listed, with comparably high EGFR expression in most PDX bearing EGFR mutations.

Figure 4

Molecular characteristics of s.c. glioma PDX models. (A) Global gene expression of 23 glioma PDX models by principal component analysis. Similarity of transcriptomes is represented by their spacial distribution in the plot, with three custers visible. (B) The observed clustering into three groups could be replicated in subsequent analyses of expressions of gene sets characteristic for proposed molecular subtypes mesenchymal (◊), classical (×) and proneural (no indication). (C) Single sample gene set enrichment analysis of glioma PDX models regarding 34 selected hallmarks and clustering of models resembling the mesenchymal subtype. (D) Combined enrichment scores of gene sets related to MAPK/Erk, JAK/STAT, VEGF, PI3K/Akt and mTOR signaling, as well as angiogenesis. Gene sets analyzed individually in Figure S3 . Red (positive Z-score): higher expression of gene set than in the average of all models. Blue (negative Z-score): lower expression.

Figure 5

Selected gene set enrichment analysis plots of s.c. PDX tumor tissue based on results in chemosensitivity testing. (A) Enriched hallmark gene sets (p < 0.1 and FDR < 25%) in temozolomide resistant PDX and (B) PDX responding to mTOR inhibitor everolimus indicate possible implications of mTOR signaling and hypoxia for the monitored phenotypes.