Zebrafish Patient-Derived Xenograft Model to Predict Treatment Outcomes of Colorectal Cancer Patients

The potential of zebrafish as drug discovery research tool in immune-mediated inflammatory disease

Immune-mediated inflammatory disease (IMID) prevalence is estimated at 3-7% for Westernised populations, with annual incidence reported at almost 1 in 100 people globally. More recently, drug discovery approaches have been evolving towards more targeted therapies with an improved long-term safety profile, while the requirement for individualisation of medicine in complex conditions such as IMIDs, is acknowledged. However, existing preclinical models-such as cellular and in vivo mammalian models-are not ideal for modern drug discovery model requirements, such as real-time in vivo visualisation of drug effects, logistically feasible safety assessment over the course of a lifetime, or dynamic assessment of physiological changes during disease development. Zebrafish share high homology with humans in terms of proteins and disease-causing genes, with high conservation of physiological processes at organ, tissue, cellular and molecular level. These and other unique attributes, such as high fecundity, relative transparency and ease of genetic manipulation, positions zebrafish as the next major role player in IMID drug discovery. This review provides a brief overview of the suitability of this organism as model for human inflammatory disease and summarises the range of approaches used in zebrafish-based drug discovery research. Strengths and limitations of zebrafish as model organism, as well as important considerations in research study design, are discussed. Finally, under-utilised avenues for investigation in the IMID context are highlighted.

Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer

Cancer patients often undergo rounds of trial-and-error to find the most effective treatment because there is no test in the clinical practice for predicting therapy response. Here, we conduct a clinical study to validate the zebrafish patient-derived xenograft model (zAvatar) as a fast predictive platform for personalized treatment in colorectal cancer. zAvatars are generated with patient tumor cells, treated exactly with the same therapy as their corresponding patient and analyzed at single-cell resolution. By individually comparing the clinical responses of 55 patients with their zAvatar-test, we develop a decision tree model integrating tumor stage, zAvatar-apoptosis, and zAvatar-metastatic potential. This model accurately forecasts patient progression with 91% accuracy. Importantly, patients with a sensitive zAvatar-test exhibit longer progression-free survival compared to those with a resistant test. We propose the zAvatar-test as a rapid approach to guide clinical decisions, optimizing treatment options and improving the survival of cancer patients.

New developments in pre-clinical models of ALS to guide translation

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder in which selective death of motor neurons leads to muscle weakness and paralysis. Most research has focused on understanding and treating monogenic familial forms, most frequently caused by mutations in SOD1, FUS, TARDBP and C9orf72, although ALS is mostly sporadic and without a clear genetic cause. Rodent models have been developed to study monogenic ALS, but despite numerous pre-clinical studies and clinical trials, few disease-modifying therapies are available. ALS is a heterogeneous disease with complex underlying mechanisms where several genes and molecular pathways appear to play a role. One reason for the high failure rate of clinical translation from the current models could be oversimplification in pre-clinical studies. Here, we review advances in pre-clinical models to better capture the heterogeneous nature of ALS and discuss the value of novel model systems to guide translation and aid in the development of precision medicine.

Zebrafish xenograft as a tool for the study of colorectal cancer: a review

Colorectal cancer (CRC) is the second leading cause of cancer-related death, mostly due to metastatic disease and the fact that many patients already show signs of metastasis at the time of first diagnosis. Current CRC therapies negatively impact patients' quality of life and have little to no effect on combating the tumor once the dissemination has started. Danio rerio (zebrafish) is a popular animal model utilized in cancer research. One of its main advantages is the ease of xenograft transplantation due to the fact that zebrafish larvae lack the adaptative immune system, guaranteeing the impossibility of rejection. In this review, we have presented the many works that choose zebrafish xenograft as a tool for the study of CRC, highlighting the methods used as well as the promising new therapeutic molecules that have been identified due to this animal model.

Combination of multiple omics techniques for a personalized therapy or treatment selection

Despite targeted therapies and immunotherapies have revolutionized the treatment of cancer patients, only a limited number of patients have long-term responses. Moreover, due to differences within cancer patients in the tumor mutational burden, composition of the tumor microenvironment as well as of the peripheral immune system and microbiome, and in the development of immune escape mechanisms, there is no "one fit all" therapy. Thus, the treatment of patients must be personalized based on the specific molecular, immunologic and/or metabolic landscape of their tumor. In order to identify for each patient the best possible therapy, different approaches should be employed and combined. These include (i) the use of predictive biomarkers identified on large cohorts of patients with the same tumor type and (ii) the evaluation of the individual tumor with "omics"-based analyses as well as its ex vivo characterization for susceptibility to different therapies.

Models to study CTCs and CTC culture methods

The vast majority of cancer-related deaths are due to the presence of disseminated disease. Understanding the metastatic process is key to achieving a reduction in cancer mortality. Particularly, there is a need to understand the molecular mechanisms that drive cancer metastasis, which will allow the identification of curative treatments for metastatic cancers. Liquid biopsies have arisen as a minimally invasive approach to gain insights into the biology of metastasis. Circulating tumour cells (CTCs), shed to the circulation from the primary tumour or metastatic lesions, are a key component of liquid biopsy. As metastatic precursors, CTCs hold the potential to unravel the mechanisms involved in metastasis formation as well as new therapeutic strategies for treating metastatic disease. However, the complex biology of CTCs together with their low frequency in circulation are factors hampering an in-depth mechanistic investigation of the metastatic process. To overcome these problems, CTC-derived models, including CTC-derived xenograft (CDX) and CTC-derived ex vivo cultures, in combination with more traditional in vivo models of metastasis, have emerged as powerful tools to investigate the biological features of CTCs facilitating cancer metastasis and uncover new therapeutic opportunities. In this chapter, we provide an up to date view of the diverse models used in different cancers to study the biology of CTCs, and of the methods developed for CTC culture and expansion, in vivo and ex vivo. We also report some of the main challenges and limitations that these models are facing.

Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes

The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor's molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient's tumor in an animal or dish and provide the means to functionally assess heterogeneity's impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines.

Combining preclinical tools and models to unravel tumor complexity: Jump into the next dimension

Tumors are complex and heterogeneous diseases characterized by an intricate milieu and dynamically in connection with surrounding and distant tissues. In the last decades, great efforts have been made to develop novel preclinical models able to recapitulate the original features of tumors. However, the development of an in vitro functional and realistic tumor organ is still utopic and represents one of the major challenges to reproduce the architecture of the tumor ecosystem. A strategy to decrypt the whole picture and predict its behavior could be started from the validation of simplified biomimetic systems and then proceed with their integration. Variables such as the cellular and acellular composition of tumor microenvironment (TME) and its spatio-temporal distribution have to be considered in order to respect the dynamic evolution of the oncologic disease. In this perspective, we aim to explore the currently available strategies to improve and integrate in vitro and in vivo models, such as three-dimensional (3D) cultures, organoids, and zebrafish, in order to better understand the disease biology and improve the therapeutic approaches.

Role of Patient-Derived Models of Cancer in Translational Oncology

Cancer is a heterogeneous disease. Each individual tumor is unique and characterized by structural, cellular, genetic and molecular features. Therefore, patient-derived cancer models are indispensable tools in cancer research and have been actively introduced into the healthcare system. For instance, patient-derived models provide a good reproducibility of susceptibility and resistance of cancer cells against drugs, allowing personalized therapy for patients. In this article, we review the advantages and disadvantages of the following patient-derived models of cancer: (1) PDC-patient-derived cell culture, (2) PDS-patient-derived spheroids and PDO-patient-derived organoids, (3) PDTSC-patient-derived tissue slice cultures, (4) PDX-patient-derived xenografts, humanized PDX, as well as PDXC-PDX-derived cell cultures and PDXO-PDX-derived organoids. We also provide an overview of current clinical investigations and new developments in the area of patient-derived cancer models. Moreover, attention is paid to databases of patient-derived cancer models, which are collected in specialized repositories. We believe that the widespread use of patient-derived cancer models will improve our knowledge in cancer cell biology and contribute to the development of more effective personalized cancer treatment strategies.