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Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable ...

University of Leicester

The majority of endometrial cancers are detected early with a favourable prognosis. However, for patients with advanced disease, chemotherapy response rates and overall survival remains poor. The endometrial cancer population is typically elderly with multiple co-morbidities and aggressive cytotoxic therapy may be hazardous. Therefore, there is an urgent need to define optimal treatment strategies for advanced and recurrent disease and personalise therapy based on individual tumour and patient characteristics. Three-dimensional (3D) models that preserve the tumour microenvironment and tumour-stromal interactions are increasingly important for translational research with the advent of immunotherapy and molecularly targeted agents. 3D patient-relevant pre-clinical models in endometrial cancer include spheroids, patient-derived organoids, microfluidic systems, patient-derived xenografts and patient-derived explants. Here we present a review of available 3D modelling systems in endometrial cancers, highlighting their current use, advantages, disadvantages and applications to translational research with a focus on the power of the patient-derived explant platform.

Patient-derived explants, xenografts and organoids: 3-dimensional patient-relevant pre-clinical models in endometrial cancer.

Preclinical models that can accurately predict outcomes in the clinic are much sought after in the field of cancer drug discovery and development. Existing models such as organoids and patient-derived xenografts have many advantages, but they suffer from the drawback of not contextually preserving human tumour architecture. This is a particular problem for the preclinical testing of immunotherapies, as these agents require an intact tumour human-specific microenvironment for them to be effective. In this review, we explore the potential of patient-derived explants (PDEs) for fulfilling this need. PDEs involve the ex vivo culture of fragments of freshly resected human tumours that retain the histological features of original tumours. PDE methodology for anti-cancer drug testing has been in existence for many years, but the platform has not been widely adopted in translational research facilities, despite strong evidence for its clinical predictivity. By modifying PDE endpoint analysis to include the spatial profiling of key biomarkers by using multispectral imaging, we argue that PDEs offer many advantages, including the ability to correlate drug responses with tumour pathology, tumour heterogeneity and changes in the tumour microenvironment. As such, PDEs are a powerful model of choice for cancer drug and biomarker discovery programmes.

Patient-derived explants (PDEs) as a powerful preclinical platform for anti-cancer drug and biomarker discovery.

The use of a low aerosol dispersion ablation chamber within a laser ablation inductively coupled plasma mass spectrometer (LA-ICP-MS) setup allows for high-resolution, high-speed imaging of the distribution of elements within a sample. Here we show how this enhanced capability creates new analytical problems and solutions. We report the distribution of platinum at the cellular level in non-small cell lung cancer (NSCLC) explant models after treatment with clinically relevant doses of cisplatin. This revealed for the first time a correlation between the platinum signal and the presence of carbon deposits within lung tissue. We show how complementary ion beam analysis techniques, particle-induced X-ray emission (PIXE) and elastic backscattering spectrometry (EBS), can be used to explore potential matrix effects in LA-ICP-MS data. For these samples, it was confirmed that the enhancement was unlikely to have resulted from a matrix effect alone. Thus, the presence of carbon deposits within tissue has potential implications for the effective distribution of the cisplatin drug.

Exploration of Matrix Effects in Laser Ablation Inductively Coupled Plasma Mass Spectrometry Imaging of Cisplatin-Treated Tumors.

To undertake a pilot study to develop a novel Patient-Derived-Explant (PDE) model system for use in endometrial cancer (EC) that is capable of monitoring differential drug responses in a pre-clinical setting.

Development of a patient-derived explant model for prediction of drug responses in endometrial cancer.

Patient-derived explants (PDEs) represent the direct culture of fragments of freshly-resected tumour tissue under conditions that retain the original architecture of the tumour. PDEs have advantages over other preclinical cancer models as platforms for predicting patient-relevant drug responses in that they preserve the tumour microenvironment and tumour heterogeneity. At endpoint, PDEs may either be processed for generation of histological sections or homogenised and processed for 'omic' evaluation of biomarker expression. A significant advantage of spatial profiling is the ability to co-register drug responses with tumour pathology, tumour heterogeneity and changes in the tumour microenvironment. Spatial profiling of PDEs relies on the utilisation of robust immunostaining approaches for validated biomarkers and incorporation of appropriate image analysis methods to quantitatively and qualitatively monitor changes in biomarker expression in response to anti-cancer drugs. Automation of immunostaining and image analysis would provide a significant advantage for the drug discovery pipeline and therefore, here, we have sought to optimise digital pathology approaches. We compare three image analysis software platforms (QuPath, ImmunoRatio and VisioPharm) for evaluating Ki67 as a marker for proliferation, cleaved PARP (cPARP) as a marker for apoptosis and pan-cytokeratin (CK) as a marker for tumour areas and find that all three generate comparable data to the views of a histomorphometrist. We also show that Virtual Double Staining of sequential sections by immunohistochemistry results in imperfect section alignment such that CK-stained tumour areas are over-estimated. Finally, we demonstrate that multi-immunofluorescence combined with digital image analysis is a superior method for monitoring multiple biomarkers simultaneously in tumour and stromal areas in PDEs.

Gareth Miles

Leicester Cancer Research Center

University of Leicester

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients