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.

Molecular and non-invasive imaging are rapidly emerging fields in preclinical cancer drug discovery. This is driven by the need to develop more efficacious and safer treatments, the advent of molecular-targeted therapeutics, and the requirements to reduce and refine current preclinical in vivo models. Such bioimaging strategies include MRI, PET, single positron emission computed tomography, ultrasound, and optical approaches such as bioluminescence and fluorescence imaging. These molecular imaging modalities have several advantages over traditional screening methods, not least the ability to quantitatively monitor pharmacodynamic changes at the cellular and molecular level in living animals non-invasively in real time. This review aims to provide an overview of non-invasive molecular imaging techniques, highlighting the strengths, limitations and versatility of these approaches in preclinical cancer drug discovery and development.

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 β-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.

Glioblastoma represents the most common primary malignancy of the central nervous system in adults and remains a largely incurable disease. The elucidation of disease subtypes based on mutational profiling, gene expression and DNA methylation has so far failed to translate into improved clinical outcomes. However, new knowledge emerging from the subtyping effort in the IDH-wild-type setting may provide directions for future precision therapies. Here, we review recent learnings in the field, and further consider how tumour microenvironment differences across subtypes may reveal novel contexts of vulnerability. We discuss recent treatment approaches and ongoing trials in the IDH-wildtype glioblastoma setting, and propose an integrated discovery stratagem incorporating multi-omics, single-cell technologies and computational approaches.

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41 a PDXNET consortium 42 b EurOPDX consortium 43 # These authors contributed equally to this work.44 § These authors jointly supervised this work. ABSTRACT 107Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical 108 studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution 109 during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human 110 cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched 111 patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing 112 and microarray data displayed substantially higher resolution and dynamic range than gene 113 expression-based inferences, and they also showed strong CNA conservation from PTs through 114 late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-115 late trios confirmed high-resolution CNA retention. We observed no significant enrichment of 116 cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between 117 patient and PDX tumors were comparable to variations in multi-region samples within patients. 118Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse 119 host. 121 MAIN 122A variety of models of human cancer have been used to study basic biological processes and 123 predict responses to treatment. For example, mouse models with genetically engineered 124 mutations in oncogenes and tumor suppressor genes have clarified the genetic and molecular 125 basis of tumor initiation and progression 1,2 , though responses sometimes differ between human 126 and mouse 3 . Cell lines have also been widely used to study cancer cells, but they lack the 127 heterogeneity and microenvironment of in vivo tumors and have shown limitations for predicting 128 clinical response 4 . Human tumors engrafted into transplant-compliant recipient mice (patient-129 derived xenografts, PDX) have advantages over prior systems for preclinical drug efficacy studies 130 because they allow researchers to directly study human cells and tissues in vivo 5-8 . Comparisons131 of genome characteristics and histopathology of primary tumors and xenografts of human breast 132 cancer 9-13 , ovarian cancer 14 , colorectal cancer 15 and lung cancer 16-18 , have demonstrated that the 133 biological properties of patient-derived tumors are largely preserved in xenografts. A growing body 134 of literature supports their use in cancer drug discovery and development 19-21 . 135A caveat to PDX models is that intratumoral evolution can occur during engraftment and 136 passaging 11,22-25 . Such evolution could potentially modify treatment response of PDXs with 137 respect to the patient tumors 23,26,27 , particularly if the evolution were to systematically alter cancer-138 related genes. This issue is related to multi-region comparisons of patient tumors 28-31 , for which 139 local mutational and immune infiltration variations have sugg...

Background: Combining bevacizumab and chemotherapy produced superior response rates compared with chemotherapy alone in metastatic breast cancer. As bevacizumab may cause hypertension (HTN) and increase the risk of cardiac failure, we performed a pilot study to evaluate the feasibility and toxicity of a non-anthracycline-containing combination of docetaxel with cyclophosphamide and bevacizumab in early stage breast cancer patients. Methods: Treatment consisted of four 3-weekly cycles of docetaxel and cyclophosphamide (75/600 mg/m2). Bevacizumab was administered 15 mg/kg intravenously on day 1, and then every 3 weeks to a total of 18 cycles of treatment. Serum biomarker concentrations of vascular endothelial growth factor (VEGF), cardiac troponin-I (cTnI), myeloperoxidase (MPO), and placental growth factor (PlGF) were quantified using enzyme-linked immunosorbent assay (ELISA) in 62 patients at baseline and whilst on treatment to determine their utility as biomarkers of cardiotoxicity, indicated by left ventricular ejection fraction (LVEF). Results: A total of 106 patients were accrued in nine sites. Median follow up was 65 months (1–72 months). Seventeen protocol-defined relapse events were observed, accounting for an overall disease-free survival (DFS) rate of 84%. The DFS rates for hormone receptor positive (HR+) and triple-negative (TN) patients were 95% versus 43%, respectively. The median time to relapse was 25 (12–54) months in TN patients versus 38 (22–71) months in HR+ patients. There have been 13 deaths related to breast cancer . The overall survival (OS) rate was 88%. The 5-year OS rate in HR+ versus TN was 95% versus 57%. None of the measured biomarkers predicted the development of cardiotoxicity. Conclusions: We observed a low relapse rate in node-positive, HR+ patients; however, results in TN breast cancer were less encouraging. Given the negative results of three large phase III trials, it is unlikely that this approach will be investigated further. Trial Registration ClinicalTrials.gov Identifier: NCT00911716.

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.