Fast, In Vivo Model for Drug-Response Prediction in Patients with B-Cell Precursor Acute Lymphoblastic Leukemia

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.

Zebrafish tumour xenograft models: a prognostic approach to epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the gynaecological malignancy with highest mortality. Although adjuvant treatment with carboplatin and paclitaxel leads to an objective response in ~80% of these patients, a majority will relapse within two years. Better methods for assessing long-term treatment outcomes are needed. To address this, we established safe and efficacious doses of carboplatin and paclitaxel using IGROV-1 zebrafish-CDX models. Then fluorescently-labelled cell suspensions from 83 tumour biopsies collected at exploratory laparotomy of women with suspected EOC were generated and 37 (45%) were successfully implanted in zebrafish larvae. Among these 19 of 27 pathology-confirmed EOC samples (70%) engrafted. These zebrafish patient-derived tumour xenograft (ZTX) models were treated with carboplatin or paclitaxel and tumour growth/regression and metastatic dissemination were recorded. In a subgroup of nine patients, four ZTX models regressed during carboplatin treatment. All four corresponding patients had >24 months PFS. Furthermore, both ZTX models established from two patients having <24 months PFS failed to regress during carboplatin treatment. Seven of eight models seeding <6 metastatic cells were established from patients having >24 months PFS. In eleven of fourteen patients, FIGO stage I + II or III tumours gave rise to ZTX models seeding <4 or >4 metastatic cells, respectively. In conclusion, ZTX models predicted patients having >24 or <24 months PFS, based on response/no response to carboplatin. Furthermore, high metastatic dissemination in ZTX models correlated to shorter PFS and more advanced disease at diagnosis. These preliminary results suggest that ZTX models could become a useful prognostic tool in EOC treatment planning.

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.

Refined high-content imaging-based phenotypic drug screening in zebrafish xenografts

Zebrafish xenotransplantation models are increasingly applied for phenotypic drug screening to identify small compounds for precision oncology. Larval zebrafish xenografts offer the opportunity to perform drug screens at high-throughput in a complex in vivo environment. However, the full potential of the larval zebrafish xenograft model has not yet been realized and several steps of the drug screening workflow still await automation to increase throughput. Here, we present a robust workflow for drug screening in zebrafish xenografts using high-content imaging. We established embedding methods for high-content imaging of xenografts in 96-well format over consecutive days. In addition, we provide strategies for automated imaging and analysis of zebrafish xenografts including automated tumor cell detection and tumor size analysis over time. We also compared commonly used injection sites and cell labeling dyes and show specific site requirements for tumor cells from different entities. We demonstrate that our setup allows us to investigate proliferation and response to small compounds in several zebrafish xenografts ranging from pediatric sarcomas and neuroblastoma to glioblastoma and leukemia. This fast and cost-efficient assay enables the quantification of anti-tumor efficacy of small compounds in large cohorts of a vertebrate model system in vivo. Our assay may aid in prioritizing compounds or compound combinations for further preclinical and clinical investigations.

Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features

Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the bone marrow producing many white blood cells (WBC). ALL is one of the most common types of cancer in children and adults. Doctors determine the treatment of leukemia according to its stages and its spread in the body. Doctors rely on analyzing blood samples under a microscope. Pathologists face challenges, such as the similarity between infected and normal WBC in the early stages. Manual diagnosis is prone to errors, differences of opinion, and the lack of experienced pathologists compared to the number of patients. Thus, computer-assisted systems play an essential role in assisting pathologists in the early detection of ALL. In this study, systems with high efficiency and high accuracy were developed to analyze the images of C-NMC 2019 and ALL-IDB2 datasets. In all proposed systems, blood micrographs were improved and then fed to the active contour method to extract WBC-only regions for further analysis by three CNN models (DenseNet121, ResNet50, and MobileNet). The first strategy for analyzing ALL images of the two datasets is the hybrid technique of CNN-RF and CNN-XGBoost. DenseNet121, ResNet50, and MobileNet models extract deep feature maps. CNN models produce high features with redundant and non-significant features. So, CNN deep feature maps were fed to the Principal Component Analysis (PCA) method to select highly representative features and sent to RF and XGBoost classifiers for classification due to the high similarity between infected and normal WBC in early stages. Thus, the strategy for analyzing ALL images using serially fused features of CNN models. The deep feature maps of DenseNet121-ResNet50, ResNet50-MobileNet, DenseNet121-MobileNet, and DenseNet121-ResNet50-MobileNet were merged and then classified by RF classifiers and XGBoost. The RF classifier with fused features for DenseNet121-ResNet50-MobileNet reached an AUC of 99.1%, accuracy of 98.8%, sensitivity of 98.45%, precision of 98.7%, and specificity of 98.85% for the C-NMC 2019 dataset. With the ALL-IDB2 dataset, hybrid systems achieved 100% results for AUC, accuracy, sensitivity, precision, and specificity.

Novel Zebrafish Patient-Derived Tumor Xenograft Methodology for Evaluating Efficacy of Immune-Stimulating BCG Therapy in Urinary Bladder Cancer

BACKGROUND

Bacillus Calmette-Guérin (BCG) immunotherapy is the standard-of-care adjuvant therapy for non-muscle-invasive bladder cancer in patients at considerable risk of disease recurrence. Although its exact mechanism of action is unknown, BCG significantly reduces this risk in responding patients but is mainly associated with toxic side-effects in those facing treatment resistance. Methods that allow the identification of BCG responders are, therefore, urgently needed.

METHODS

Fluorescently labelled UM-UC-3 cells and dissociated patient tumor samples were used to establish zebrafish tumor xenograft (ZTX) models. Changes in the relative primary tumor size and cell dissemination to the tail were evaluated via fluorescence microscopy at three days post-implantation. The data were compared to the treatment outcomes of the corresponding patients. Toxicity was evaluated based on gross morphological evaluation of the treated zebrafish larvae.

RESULTS

BCG-induced toxicity was avoided by removing the water-soluble fraction of the BCG formulation prior to use. BCG treatment via co-injection with the tumor cells resulted in significant and dose-dependent primary tumor size regression. Heat-inactivation of BCG decreased this effect, while intravenous BCG injections were ineffective. ZTX models were successfully established for six of six patients based on TUR-B biopsies. In two of these models, significant tumor regression was observed, which, in both cases, corresponded to the treatment response in the patients.

CONCLUSIONS

The observed BCG-related anti-tumor effect indicates that ZTX models might predict the BCG response and thereby improve treatment planning. More experiments and clinical studies are needed, however, to elucidate the BCG mechanism and estimate the predictive value.

Modeling leukemia with zebrafish (Danio rerio): Towards precision medicine

Leukemia is a type of blood cancer characterized by high genetic heterogeneity and fatality. While chemotherapy remains the primary form of treatment for leukemia, its effectiveness was profoundly diminished by the genetic heterogeneity and cytogenetic abnormalities of leukemic cells. Therefore, there is an unmet need to develop precision medicine for leukemia with distinct genetic backgrounds. Zebrafish (Danio rerio), a freshwater fish with exceptional feasibility in genome editing, is a powerful tool for rapid human cancer modeling. In the past decades, zebrafish have been adopted in modeling human leukemia, exploring the molecular mechanisms of underlying genetic abnormalities, and discovering novel therapeutic agents. Although many recurrent mutations of leukemia have been modeled in zebrafish for pathological study and drug discovery, its great potential in leukemia modeling was not yet fully exploited, particularly in precision medicine. In this review, we evaluated the current zebrafish models of leukemia/pre-leukemia and genetic techniques and discussed the potential of zebrafish models with novel techniques, which may contribute to the development of zebrafish as a disease model for precision medicine in treating leukemia.

Effective tumor cell abrogation via Venetoclax-mediated BCL-2 inhibition in KMT2A-rearranged acute B-lymphoblastic leukemia

Dysregulation of the intrinsic BCL-2 pathway-mediated apoptosis cascade is a common feature of hematological malignancies including acute B-lymphoblastic leukemia (B-ALL). The KMT2A-rearranged high-risk cytogenetic subtype is characterized by high expression of antiapoptotic protein BCL-2, likely due to the direct activating binding of KMT2A fusion proteins to the BCL2 gene. The BCL-2 inhibitor venetoclax (VEN) has proven great clinical value in other blood cancers, however, data on B-ALL is sparse and past studies have not so far described the effects of VEN on gene and protein expression profiles. Using cell lines and patient-derived in vivo xenograft models, we show BCL-2 pathway-mediated apoptosis induction and decelerated tumor cell counts in KMT2A-rearranged B-ALL but not in other cytogenetic subtypes. VEN treatment of cell line- and patient-derived xenografts reduced blast frequencies in blood, bone marrow, and spleen, and tumor cell doubling times were increased. Growth rates are further correlated with VEN concentrations in blood. In vitro incubation with VEN resulted in BCL-2 dephosphorylation and targeted panel RNA sequencing revealed reduced gene expression of antiapoptotic pathway members BCL2, MCL1, and BCL2L1 (BCL-XL). Reinforced translocation of BAX proteins towards mitochondria induced caspase activation and cell death commitment. Prolonged VEN application led to upregulation of antiapoptotic proteins BCL-2, MCL-1, and BCL-XL. Interestingly, the extrinsic apoptosis pathway was strongly modulated in SEM cells in response to VEN. Gene expression of members of the tumor necrosis factor signaling cascade was increased, resulting in canonical NF-kB signaling. This possibly suggests a previously undescribed mechanism of BCL-2-independent and NF-kB-mediated upregulation of MCL-1 and BCL-XL. In summary, we herein prove that VEN is a potent option to suppress tumor cells in KMT2A-rearranged B-ALL in vitro and in vivo. Possible evasion mechanisms, however, must be considered in subsequent studies.

Zebrafish—An Optimal Model in Experimental Oncology

A thorough understanding of cancer pathogenesis is a necessary step in the development of more effective and safer therapy. However, due to the complexity of the process and intricate interactions, studying tumor development is an extremely difficult and challenging task. In bringing this issue closer, different scientific models with various advancement levels are helpful. Cell cultures is a system that is too simple and does not allow for multidirectional research. On the other hand, rodent models, although commonly used, are burdened with several limitations. For this reason, new model organisms that will allow for the studying of carcinogenesis stages and factors reliably involved in them are urgently sought after. Danio rerio, an inconspicuous fish endowed with unique features, is gaining in importance in the world of scientific research. Including it in oncological research brings solutions to many challenges afflicting modern medicine. This article aims to illustrate the usefulness of Danio rerio as a model organism which turns out to be a powerful and unique tool for studying the stages of carcinogenesis and solving the hitherto incomprehensible processes that lead to the development of the disease.

What Zebrafish and Nanotechnology Can Offer for Cancer Treatments in the Age of Personalized Medicine

Cancer causes millions of deaths each year and thus urgently requires the development of new therapeutic strategies. Nanotechnology-based anticancer therapies are a promising approach, with several formulations already approved and in clinical use. The evaluation of these therapies requires efficient in vivo models to study their behavior and interaction with cancer cells, and to optimize their properties to ensure maximum efficacy and safety. In this way, zebrafish is an important candidate due to its high homology with the human genoma, its large offspring, and the ease in developing specific cancer models. The role of zebrafish as a model for anticancer therapy studies has been highly evidenced, allowing researchers not only to perform drug screenings but also to evaluate novel therapies such as immunotherapies and nanotherapies. Beyond that, zebrafish can be used as an “avatar” model for performing patient-derived xenografts for personalized medicine. These characteristics place zebrafish in an attractive position as a role model for evaluating novel therapies for cancer treatment, such as nanomedicine.

Microscopic multifrequency MR elastography for mapping viscoelasticity in zebrafish

PURPOSE

The zebrafish (Danio rerio) has become an important animal model in a wide range of biomedical research disciplines. Growing awareness of the role of biomechanical properties in tumor progression and neuronal development has led to an increasing interest in the noninvasive mapping of the viscoelastic properties of zebrafish by elastography methods applicable to bulky and nontranslucent tissues.

METHODS

Microscopic multifrequency MR elastography is introduced for mapping shear wave speed (SWS) and loss angle (φ) as markers of stiffness and viscosity of muscle, brain, and neuroblastoma tumors in postmortem zebrafish with 60 µm in-plane resolution. Experiments were performed in a 7 Tesla MR scanner at 1, 1.2, and 1.4 kHz driving frequencies.

RESULTS

Detailed zebrafish viscoelasticity maps revealed that the midbrain region (SWS = 3.1 ± 0.7 m/s, φ = 1.2 ± 0.3 radian [rad]) was stiffer and less viscous than telencephalon (SWS = 2.6 ± 0. 5 m/s, φ = 1.4 ± 0.2 rad) and optic tectum (SWS = 2.6 ± 0.5 m/s, φ = 1.3 ± 0.4 rad), whereas the cerebellum (SWS = 2.9 ± 0.6 m/s, φ = 0.9 ± 0.4 rad) was stiffer but less viscous than both (all p < .05). Overall, brain tissue (SWS = 2.9 ± 0.4 m/s, φ = 1.2 ± 0.2 rad) had similar stiffness but lower viscosity values than muscle tissue (SWS = 2.9 ± 0.5 m/s, φ = 1.4 ± 0.2 rad), whereas neuroblastoma (SWS = 2.4 ± 0.3 m/s, φ = 0.7 ± 0.1 rad, all p < .05) was the softest and least viscous tissue.

CONCLUSION

Microscopic multifrequency MR elastography-generated maps of zebrafish show many details of viscoelasticity and resolve tissue regions, of great interest in neuromechanical and oncological research and for which our study provides first reference values.

Systematic Roadmap for Cancer Drug Screening Using Zebrafish Embryo Xenograft Cancer Models: Melanoma Cell Line as a Case Study

Simple Summary

Currently, there is no consensus in the scientific literature regarding the zebrafish embryo xenotransplantation procedure for drug screening. Thus, this study sets systematic guidelines for maximizing the reproducibility of drug screening in zebrafish-embryo cancer xenograft models based on evaluating every step of the procedure in a real case scenario in which the chemical properties of the compounds are unknown or not optimal. It aims to be a stepping stone to bring the versatility of zebrafish embryos to drug screening for cancer. The present work helps our group to pursue the objective of establishing zebrafish embryos as a valuable alternative to mice models; and hopefully, will help other groups in this field to progress in the same direction.

Abstract

Zebrafish embryo tumor transplant models are widely utilized in cancer research. Compared with traditional murine models, the small size and transparency of zebrafish embryos combined with large clutch sizes that increase statistical power and cheap husbandry make them a cost-effective and versatile tool for in vivo drug discovery. However, the lack of a comprehensive analysis of key factors impacting the successful use of these models impedes the establishment of basic guidelines for systematic screening campaigns. Thus, we explored the following crucial factors: (i) user-independent inclusion criteria, focusing on sample homogeneity; (ii) metric definition for data analysis; (iii) tumor engraftment criteria; (iv) image analysis versus quantification of human cancer cells using qPCR (RNA and gDNA); (v) tumor implantation sites; (vi) compound distribution (intratumoral administration versus alternative inoculation sites); and (vii) efficacy (intratumoral microinjection versus compound solution in media). Based on these analyses and corresponding assessments, we propose the first roadmap for systematic drug discovery screening in zebrafish xenograft cancer models using a melanoma cell line as a case study. This study aims to help the wider cancer research community to consider the adoption of this versatile model for cancer drug screening projects.