ABSTRACT
The complexity of the cellular and acellular players within the tumor microenvironment (TME) allows for significant variation in TME constitution and role in anticancer treatment response. Spatial alterations in populations of tumor cells and adjacent non-malignant cells, including endothelial cells, fibroblasts and tissue-infiltrating immune cells, often have a major role in determining disease progression and treatment response in cancer. Many current standard systemic antineoplastic treatments target the cancer cells and could be further refined to directly target commonly dysregulated cell populations of the TME. Recent developments in immuno-oncology and bioengineering have created an attractive potential to model these complexities at the level of the individual patient. These developments, along with the increasing momentum in precision medicine research and application, have catalysed exciting new discoveries in understanding drug-TME interactions, target identification, and improved efficacy of therapies. While rapid progress has been made, there are still many challenges to overcome in the development of accurate in vitro, in vivo and ex vivo models incorporating the cellular interactions that take place in the TME. In this review, we describe how advances in immuno-oncology and patient-derived models, such as patient-derived organoids and explant cultures, have enhanced the landscape of personalised immunotherapy prediction and treatment of solid organ malignancies. We describe and compare different immunological targets and perspectives on two-dimensional and three-dimensional modelling approaches that may be used to better rationalise immunotherapy use, ultimately providing a knowledge base for the integration of the autologous TME into these predictive models.
ABSTRACT
Current in vitro therapeutic testing platforms lack relevance to tumor pathophysiology, typically employing cancer cell lines established as two-dimensional (2D) cultures on tissue culture plastic. There is a critical need for more representative models of tumor complexity that can accurately predict therapeutic response and sensitivity. The development of three-dimensional (3D) ex vivo culture of patient-derived organoids (PDOs), derived from fresh tumor tissues, aims to address these shortcomings. Organoid cultures can be used as tumor surrogates in parallel to routine clinical management to inform therapeutic decisions by identifying potential effective interventions and indicating therapies that may be futile. Here, this procedure aims to describe strategies and a detailed step-by-step protocol to establish bladder cancer PDOs from fresh, viable clinical tissue. Our well-established, optimized protocols are practical to set up 3D cultures for experiments using limited and diverse starting material directly from patients or patient-derived xenograft (PDX) tumor material. This procedure can also be employed by most laboratories equipped with standard tissue culture equipment. The organoids generated using this protocol can be used as ex vivo surrogates to understand both the molecular mechanisms underpinning urological cancer pathology and to evaluate treatments to inform clinical management.
Subject(s)
Urinary Bladder Neoplasms , Urologic Neoplasms , Humans , Organoids/pathology , Precision Medicine , Urinary Bladder Neoplasms/pathology , Urologic Neoplasms/pathologyABSTRACT
Precision medicine approaches that inform clinical management of individuals with cancer are progressively advancing. Patient-derived explants (PDEs) provide a patient-proximal ex vivo platform that can be used to assess sensitivity to standard of care (SOC) therapies and novel agents. PDEs have several advantages as a patient-proximal model compared to current preclinical models, as they maintain the phenotype and microenvironment of the individual tumor. However, the longevity of PDEs is not compatible with the timeframe required to incorporate candidate therapeutic options identified by whole exome sequencing (WES) of the patient's tumor. This review investigates how PDE longevity varies across tumor streams and how this is influenced by tissue preparation. Improving longevity of PDEs will enable individualized therapeutics testing, and thus contribute to improving outcomes for people with cancer.