Ex vivo drug sensitivity screening predicts response to temozolomide in glioblastoma patients and identifies candidate biomarkers.

BACKGROUND: Patient-derived glioma stem-like cells (GSCs) have become the gold-standard in neuro-oncological research; however, it remains to be established whether loss of in situ microenvironment affects the clinically-predictive value of this model. We implemented a GSC monolayer system to investigate in situ-in vitro molecular correspondence and the relationship between in vitro and patient response to temozolomide (TMZ). METHODS: DNA/RNA-sequencing was performed on 56 glioblastoma tissues and 19 derived GSC cultures. Sensitivity to TMZ was screened across 66 GSC cultures. Viability readouts were related to clinical parameters of corresponding patients and whole-transcriptome data. RESULTS: Tumour DNA and RNA sequences revealed strong similarity to corresponding GSCs despite loss of neuronal and immune interactions. In vitro TMZ screening yielded three response categories which significantly correlated with patient survival, therewith providing more specific prediction than the binary MGMT marker. Transcriptome analysis identified 121 genes related to TMZ sensitivity of which 21were validated in external datasets. CONCLUSION: GSCs retain patient-unique hallmark gene expressions despite loss of their natural environment. Drug screening using GSCs predicted patient response to TMZ more specifically than MGMT status, while transcriptome analysis identified potential biomarkers for this response. GSC drug screening therefore provides a tool to improve drug development and precision medicine for glioblastoma.

Comparative analysis of deeply phenotyped GBM cohorts of 'short-term' and 'long-term' survivors.

BACKGROUND: Glioblastoma (GBM) is an aggressive brain cancer that typically results in death in the first 15 months after diagnosis. There have been limited advances in finding new treatments for GBM. In this study, we investigated molecular differences between patients with extremely short (≤ 9 months, Short term survivors, STS) and long survival (≥ 36 months, Long term survivors, LTS). METHODS: Patients were selected from an in-house cohort (GLIOTRAIN-cohort), using defined inclusion criteria (Karnofsky score > 70; age < 70 years old; Stupp protocol as first line treatment, IDH wild type), and a multi-omic analysis of LTS and STS GBM samples was performed. RESULTS: Transcriptomic analysis of tumour samples identified cilium gene signatures as enriched in LTS. Moreover, Immunohistochemical analysis confirmed the presence of cilia in the tumours of LTS. Notably, reverse phase protein array analysis (RPPA) demonstrated increased phosphorylated GAB1 (Y627), SRC (Y527), BCL2 (S70) and RAF (S338) protein expression in STS compared to LTS. Next, we identified 25 unique master regulators (MR) and 13 transcription factors (TFs) belonging to ontologies of integrin signalling and cell cycle to be upregulated in STS. CONCLUSION: Overall, comparison of STS and LTS GBM patients, identifies novel biomarkers and potential actionable therapeutic targets for the management of GBM.

Genomic Exploration of Distinct Molecular Phenotypes Steering Temozolomide Resistance Development in Patient-Derived Glioblastoma Cells.

Chemotherapy using temozolomide is the standard treatment for patients with glioblastoma. Despite treatment, prognosis is still poor largely due to the emergence of temozolomide resistance. This resistance is closely linked to the widely recognized inter- and intra-tumoral heterogeneity in glioblastoma, although the underlying mechanisms are not yet fully understood. To induce temozolomide resistance, we subjected 21 patient-derived glioblastoma cell cultures to Temozolomide treatment for a period of up to 90 days. Prior to treatment, the cells' molecular characteristics were analyzed using bulk RNA sequencing. Additionally, we performed single-cell RNA sequencing on four of the cell cultures to track the evolution of temozolomide resistance. The induced temozolomide resistance was associated with two distinct phenotypic behaviors, classified as "adaptive" (ADA) or "non-adaptive" (N-ADA) to temozolomide. The ADA phenotype displayed neurodevelopmental and metabolic gene signatures, whereas the N-ADA phenotype expressed genes related to cell cycle regulation, DNA repair, and protein synthesis. Single-cell RNA sequencing revealed that in ADA cell cultures, one or more subpopulations emerged as dominant in the resistant samples, whereas N-ADA cell cultures remained relatively stable. The adaptability and heterogeneity of glioblastoma cells play pivotal roles in temozolomide treatment and contribute to the tumor's ability to survive. Depending on the tumor's adaptability potential, subpopulations with acquired resistance mechanisms may arise.

Modelling tumour cell proliferation from vascular structure using tissue decomposition into avascular elements.

Computer models allow the mechanistically detailed study of tumour proliferation and its dependency on nutrients. However, the computational study of large vascular tumours requires detailed information on the 3-dimensional vessel network and rather high computation times due to complex geometries. This study puts forward the idea of partitioning vascularised tissue into connected avascular elements that can exchange cells and nutrients between each other. Our method is able to rapidly calculate the evolution of proliferating as well as dead and quiescent cells, and hence a proliferative index, from a given amount and distribution of vascularisation of arbitrary complexity. Applying our model, we found that a heterogeneous vessel distribution provoked a higher proliferative index, suggesting increased malignancy, and increased the amount of dead cells compared to a more static tumour environment when a homogenous vessel distribution was assumed. We subsequently demonstrated that under certain amounts of vascularisation, cell proliferation may even increase when vessel density decreases, followed by a subsequent decrease of proliferation. This effect was due to a trade-off between an increase in compensatory proliferation for replacing dead cells and a decrease of cell population due to lack of oxygen supply in lowly vascularised tumours. Findings were illustrated by an ectopic colorectal cancer mouse xenograft model. Our presented approach can be in the future applied to study the effect of cytostatic, cytotoxic and anti-angiogenic chemotherapy and is ideally suited for translational systems biology, where rapid interaction between theory and experiment is essential.

Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients.

To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients. Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing. Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0.87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0.013). Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment.

Implementing subtype-specific pre-clinical models of breast cancer to study pre-treatment aspirin effects.

BACKGORUND: Prior data suggest pre-diagnostic aspirin use impacts breast tumour biology and patient outcome. Here, we employed faithful surgical resection models of HER2+ and triple-negative breast cancer (TNBC), to study outcome and response mechanisms across breast cancer subtypes. METHOD: NOD/SCID mice were implanted with HER2+ MDA-MB-231/LN/2-4/H2N, trastuzumab-resistant HER2+ HCC1954 or a TNBC patient-derived xenograft (PDX). A daily low-dose aspirin regimen commenced until primary tumours reached ~250 mm3 and subsequently resected. MDA-MB-231/LN/2-4/H2N mice were monitored for metastasis utilising imaging. To interrogate the survival benefit of pre-treatment aspirin, 3 weeks post-resection, HCC1954/TNBC animals received standard-of-care (SOC) chemotherapy for 6 weeks. Primary tumour response to aspirin was interrogated using immunohistochemistry. RESULTS: Aspirin delayed time to metastasis in MDA-MB-231/LN/2-4/H2N xenografts and decreased growth of HER2+ /TNBC primary tumours. Lymphangiogenic factors and lymph vessels number were decreased in HER2+ tumours. However, no survival benefit was seen in aspirin pre-treated animals (HCC1954/TNBC) that further received adjuvant SOC, compared with animals treated with SOC alone. In an effort to study mechanisms responsible for the observed reduction in lymphangiogenesis in HER2+ BC we utilised an in vitro co-culture system of HCC1954 tumour cells and mesenchymal stromal cells (MSC). Aspirin abrogated the secretion of VEGF-C in MSCs and also decreased the lymph/angiogenic potential of the MSCs and HCC1954 by tubule formation assay. Furthermore, aspirin decreased the secretion of uPA in HCC1954 cells potentially diminishing its metastatic capability. CONCLUSION: Our data employing clinically relevant models demonstrate that aspirin alters breast tumour biology. However, aspirin may not represent a robust chemo-preventative agent in the HER2+ or TNBC setting.

Molecular Subtyping Combined with Biological Pathway Analyses to Study Regorafenib Response in Clinically Relevant Mouse Models of Colorectal Cancer.

PURPOSE: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. EXPERIMENTAL DESIGN: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. RESULTS: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance. CONCLUSIONS: Subtype classification systems represent canonical "termini a quo" (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models.

Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, 'DR_MOMP', could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that 18F-FDG-PET could independently support such predictions.

Implementing Reverse Phase Protein Array Profiling as a Sensitive Method for the Early Pre-Clinical Detection of Off-Target Toxicities Associated with Sunitinib Malate.

PURPOSE: The tyrosine kinase inhibitor (TKI) sunitinib is a multi-targeted agent approved across multiple cancer indications. Nevertheless, since approval, data has emerged to describe a worrisome side effect profile including hypertension, hand-foot syndrome, fatigue, diarrhea, mucositis, proteinuria, and (rarely) congestive heart failure. It has been hypothesized that the observed multi-parameter toxicity profile is related to "on-target" kinase inhibition in "off-target" tissues. EXPERIMENTAL DESIGN: To interrogate off-target effects in pre-clinical studies, a reverse phase protein array (RPPA) approach is employed. Mice are treated with sunitinib (40 mg kg-1 ) for 4 weeks, following which critical organs are removed. The Zeptosens RPPA platform is employed for protein expression analysis. RESULTS: Differentially expressed proteins associated with damage and/or stress are found in the majority of organs from treated animals. Proteins differentially expressed in the heart are associated with myocardial hypertrophy, ischaemia/reperfusion, and hypoxia. However, hypertrophy is not evidenced on histology. Mild proteinuria is observed; however, no changes in renal glomerular structure are visible via electron microscopy. In skin, proteins associated with cutaneous inflammation, keratinocyte hyper-proliferation, and increased inflammatory response are differentially expressed. CONCLUSIONS AND CLINICAL RELEVANCE: It is posited that pre-clinical implementation of a combined histopathological/RPPA approach provides a sensitive method to mechanistically elucidate the early manifestation of TKI on-target/organ off-target toxicities.

A Novel Positron Emission Tomography (PET) Approach to Monitor Cardiac Metabolic Pathway Remodeling in Response to Sunitinib Malate.

Sunitinib is a tyrosine kinase inhibitor approved for the treatment of multiple solid tumors. However, cardiotoxicity is of increasing concern, with a need to develop rational mechanism driven approaches for the early detection of cardiac dysfunction. We sought to interrogate changes in cardiac energy substrate usage during sunitinib treatment, hypothesising that these changes could represent a strategy for the early detection of cardiotoxicity. Balb/CJ mice or Sprague-Dawley rats were treated orally for 4 weeks with 40 or 20 mg/kg/day sunitinib. Cardiac positron emission tomography (PET) was implemented to investigate alterations in myocardial glucose and oxidative metabolism. Following treatment, blood pressure increased, and left ventricular ejection fraction decreased. Cardiac [18F]-fluorodeoxyglucose (FDG)-PET revealed increased glucose uptake after 48 hours. [11C]Acetate-PET showed decreased myocardial perfusion following treatment. Electron microscopy revealed significant lipid accumulation in the myocardium. Proteomic analyses indicated that oxidative metabolism, fatty acid ß-oxidation and mitochondrial dysfunction were among the top myocardial signalling pathways perturbed. Sunitinib treatment results in an increased reliance on glycolysis, increased myocardial lipid deposition and perturbed mitochondrial function, indicative of a fundamental energy crisis resulting in compromised myocardial energy metabolism and function. Our findings suggest that a cardiac PET strategy may represent a rational approach to non-invasively monitor metabolic pathway remodeling following sunitinib treatment.