PDXliver: a database of liver cancer patient derived xenograft mouse models

Liver organoids: updates on generation strategies and biomedical applications

The liver is the most important metabolic organ in the body. While mouse models and cell lines have further deepened our understanding of liver biology and related diseases, they are flawed in replicating key aspects of human liver tissue, particularly its complex structure and metabolic functions. The organoid model represents a major breakthrough in cell biology that revolutionized biomedical research. Organoids are in vitro three-dimensional (3D) physiological structures that recapitulate the morphological and functional characteristics of tissues in vivo, and have significant advantages over traditional cell culture methods. In this review, we discuss the generation strategies and current advances in the field focusing on their application in regenerative medicine, drug discovery and modeling diseases.

Liver and bile duct organoids and tumoroids

Organoids refer to 3D cultures established to recapitulate histology, pathology, architecture, and genetic traits of various organs and tissues in the body, thereby replacing 2D cell cultures, xenograft, and animal models. Organoids form a 3D in vitro mimic of original tissues like the liver and are derived from embryonic or adult tissue stem cells. Liver and bile duct tumor organoids, also called, tumoroids capture genetic diversity, cellular, and pathophysiological properties of original tumors. Moreover, co-culture techniques along with genetic modulation of organoids allow for using tumoroids in liver and bile duct cancer research and drug screening/testing. Therefore, tumoroids are promising platforms for studying liver and bile duct cancer, which paves the way for the new era of personalized therapies. In the current review, we aimed to discuss liver and bile duct organoids with special emphasis on tumoroids and their applications, advantages, and shortcomings.

Esophageal organoids: applications and future prospects

Organoids have been developed in the last decade as a new research tool to simulate organ cell biology and disease. Compared to traditional 2D cell lines and animal models, experimental data based on esophageal organoids are more reliable. In recent years, esophageal organoids derived from multiple cell sources have been established, and relatively mature culture protocols have been developed. Esophageal inflammation and cancer are two directions of esophageal organoid modeling, and organoid models of esophageal adenocarcinoma, esophageal squamous cell carcinoma, and eosinophilic esophagitis have been established. The properties of esophageal organoids, which mimic the real esophagus, contribute to research in drug screening and regenerative medicine. The combination of organoids with other technologies, such as organ chips and xenografts, can complement the deficiencies of organoids and create entirely new research models that are more advantageous for cancer research. In this review, we will summarize the development of tumor and non-tumor esophageal organoids, the current application of esophageal organoids in disease modeling, regenerative medicine, and drug screening. We will also discuss the future prospects of esophageal organoids.

Personalized treatment for hepatocellular carcinoma in the era of targeted medicine and bioengineering

Hepatocellular carcinoma (HCC) is a major global health burden, causing approximately 8.3 million deaths each year, and it is the third leading cause of cancer-related death worldwide, with a relative 5-year survival rate of around 18%. Due to the advanced stage of diagnosis in most patients, systemic treatment based on targeted therapy has become the only feasible option. Genomic studies have established a profile of molecular alterations in hepatocellular carcinoma with potentially actionable mutations, but these mutations have yet to be translated into clinical practice. The first targeted drug approved for systemic treatment of patients with advanced hepatocellular carcinoma was Sorafenib, which was a milestone. Subsequent clinical trials have identified multiple tyrosine kinase inhibitors, such as Lenvatinib, Cabozantinib, and Regorafenib, for the treatment of hepatocellular carcinoma, with survival benefits for the patient. Ongoing systemic therapy studies and trials include various immune-based combination therapies, with some early results showing promise and potential for new therapy plans. Systemic therapy for hepatocellular carcinoma is complicated by the significant heterogeneity of the disease and its propensity for developing drug resistance. Therefore, it is essential to choose a better, individualized treatment plan to benefit patients. Preclinical models capable of preserving in vivo tumor characteristics are urgently needed to circumvent heterogeneity and overcome drug resistance. In this review, we summarize current approaches to targeted therapy for HCC patients and the establishment of several patient-derived preclinical models of hepatocellular carcinoma. We also discuss the challenges and opportunities of targeted therapy for hepatocellular carcinoma and how to achieve personalized treatment with the continuous development of targeted therapies and bioengineering technologies.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

Human liver cancer organoids: Biological applications, current challenges, and prospects in hepatoma therapy

Liver cancer and disease are among the most socially challenging global health concerns. Although organ transplantation, surgical resection and anticancer drugs are the main methods for the treatment of liver cancer, there are still no proven cures owing to the lack of donor livers and tumor heterogeneity. Recently, advances in tumor organoid technology have attracted considerable attention as they can simulate the spatial constructs and pathophysiological characteristics of tumorigenesis and metastasis in a more realistic manner. Organoids may further contribute to the development of tailored therapies. Combining organoids with other emerging techniques, such as CRISPR-HOT, organ-on-a-chip, and 3D bioprinting, may further develop organoids and address their bottlenecks to create more practical models that generalize different tissue or organ interactions in tumor progression. In this review, we summarize the various methods in which liver organoids may be generated and describe their biological and clinical applications, present challenges, and prospects for their integration with emerging technologies. These rapidly developing liver organoids may become the focus of in vitro clinical model development and therapeutic research for liver diseases in the near future.

Establishment and genetically characterization of patient-derived xenograft models of cervical cancer

Purpose

Patient-derived xenograft (PDX) models were established to reproduce the clinical situation of original cancers and have increasingly been applied to preclinical cancer research. Our study was designed to establish and genetically characterize cervical cancer PDX models.

Methods

A total of 91 fresh fragments obtained from 22 surgically resected cervical cancer tissues were subcutaneously engrafted into female NOD-SCID mice. Hematoxylin and eosin (H&E) staining was performed to assess whether the established PDX models conserved the histological features of original patient cervical cancer tissues. Moreover, a Venn diagram was applied to display the overlap of all mutations detected in whole-genome sequencing (WGS) data from patient original cervical cancer (F0) and F2-, F3-PDX models. The whole exome sequencing (WES) and the “maftools” package were applied to determine the somatic mutations among primary cervical cancers and the established PDX models.

Results

Our study successfully developed a panel of cervical cancer PDX models and the latency time of cervical cancer PDX model establishment was variable with a progressive decrease as the passage number increased, with a mean time to initial growth of 94.71 days in F1 engraftment to 40.65 days in F3 engraftment. Moreover, the cervical cancer PDX models preserved the histological features of their original cervical cancer. WGS revealed that the genome of original cervical cancer was preserved with high fidelity in cervical cancer PDX models throughout the xenografting and passaging process. Furthermore, WES demonstrated that the cervical cancer PDX models maintained the majority somatic mutations of original cervical cancer, of which the KMT2D, LRP1B, NAV3, TP53, FAT1, MKI67 and PKHD1L1 genes were identified as the most frequently mutated genes.

Conclusions

The cervical cancer PDX models preserved the histologic and genetic characteristics of their original cervical cancer, which helped to gain a deeper insight into the genetic alterations and lay a foundation for further investigation of the molecular targeted therapy of cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01342-5.

Zebrafish Xenotransplantation Models for Studying Gene Function and Drug Treatment in Hepatocellular Carcinoma

INTRODUCTION

Zebrafish is a promising model organism for human disease including hepatocellular cancer (HCC). Recently, zebrafish has emerged also as a host for xenograft studies of liver cancer cell lines and patient derived tumors of HCC. Zebrafish embryos enable drug screening and gene function studies of xenografted cells via ease of microinjection and visualization of tumor growth and metastasis.

OBJECTIVES

In this review, we aimed to overview zebrafish HCC and liver cancer xenotransplantation studies focusing on 'gene functional analysis' and 'drug/chemical screening'.

METHODS

Herein, a comprehensive literature search was performed for liver and HCC xenografts in zebrafish on PubMed using different key words and filters for molecular modifications or drug exposure.

RESULTS

Our literature search revealed around 250 studies which were filtered and summarized in a table (Table 1) revealing comprehensive collection of experimental and technical details on microinjection, injected cell lines, molecular modifications of injected cells, types and doses of drug treatments as well as biological assessments.

CONCLUSION

This review provides a platform for HCC and liver xenografts and highlights studies performed to understand gene functionality and drug efficacy in vivo in zebrafish.

Liver Organoids: Updates on Disease Modeling and Biomedical Applications

Liver organoids are stem cell-derived 3D structures that are generated by liver differentiation signals in the presence of a supporting extracellular matrix. Liver organoids overcome low complexity grade of bidimensional culture and high costs of in vivo models thus representing a turning point for studying liver disease modeling. Liver organoids can be established from different sources as induced pluripotent stem cells (iPSCs), embryonic stem cells (ESCs), hepatoblasts and tissue-derived cells. This novel in vitro system represents an innovative tool to deeper understand the physiology and pathological mechanisms affecting the liver. In this review, we discuss the current advances in the field focusing on their application in modeling diseases, regenerative medicine and drug discovery.

Large-scale pharmacogenomic studies and drug response prediction for personalized cancer medicine

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of cancer and the complex mechanism of drug action. Personalized treatment that stratifies patients into subgroups using molecular biomarkers is promising to improve clinical benefit. With the accumulation of preclinical models and advances in computational approaches of drug response prediction, pharmacogenomics has made great success over the last 20 years and is increasingly used in the clinical practice of personalized cancer medicine. In this article, we first summarize FDA-approved pharmacogenomic biomarkers and large-scale pharmacogenomic studies of preclinical cancer models such as patient-derived cell lines, organoids, and xenografts. Furthermore, we comprehensively review the recent developments of computational methods in drug response prediction, covering network, machine learning, and deep learning technologies and strategies to evaluate immunotherapy response. In the end, we discuss challenges and propose possible solutions for further improvement.

Patient-Derived Xenograft Models for Intrahepatic Cholangiocarcinoma and Their Application in Guiding Personalized Medicine

Background

Intrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance.

Methods

We generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed.

Results

Forty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05–3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11–4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance.

Conclusion

PDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

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.

Predicting HCC Response to Multikinase Inhibitors With In Vivo Cirrhotic Mouse Model for Personalized Therapy

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) arises in a cirrhotic, pro-angiogenic microenvironment. Inhibiting angiogenesis is a key mode of action of multikinase inhibitors and current non-cirrhotic models are unable to predict treatment response. We present a novel mouse cirrhotic model of xenotransplant that predicts the natural biology of HCC and allows personalized therapy.

METHODS

Cirrhosis was induced in NOD Scid gamma mice with 4 months of thioacetamide administration. Patient derived xenografts (PDXs) were created by transplant of human HCC subcutaneously into non-cirrhotic mice and intra-hepatically into both cirrhotic and non-cirrhotic mice. The applicability of cirrhotic PDXs for drug testing was tested with 16 days of either sorafenib or lenvatinib. Treatment response was evaluated by MRI.

RESULTS

8 out of 19 (42%) human HCC engrafted in the cirrhotic model compared with only 3 out of 19 (16%) that engrafted in the subcutaneous non-cirrhotic model. Tumor vasculature was preserved in the cirrhotic model but was diminished in the non-cirrhotic models. Metastasis developed in 3 cirrhotic PDX lines and was associated with early HCC recurrence in all 3 corresponding patients (100%), compared with only 5 out of 16 (31%) of the other PDX lines, P = .027. The cirrhotic model was able to predict response and non-response to lenvatinib and sorafenib respectively in the corresponding patients. Response to lenvatinib in the cirrhotic PDX was associated with reduction in CD34, VEGFR2 and CLEC4G immunofluorescence area and intensity (all P ≤ .03).

CONCLUSIONS

A clinically relevant cirrhotic PDX model preserves tumor angiogenesis and allows prediction of response to multikinase inhibitors for personalized therapy.

ZenoFishDb v1.1: A Database for Xenotransplantation Studies in Zebrafish

Rapidly accumulating literature has proven feasibility of the zebrafish xenograft models in cancer research. Nevertheless, online databases for searching the current zebrafish xenograft literature are in great demand. Herein, we have developed a manually curated database, called ZenoFishDb v1.1 (https://konulab.shinyapps.io/zenofishdb), based on R Shiny platform aiming to provide searchable information on ever increasing collection of zebrafish studies for cancer cell line transplantation and patient-derived xenografts (PDXs). ZenoFishDb v1.1 user interface contains four modules: DataTable, Visualization, PDX Details, and PDX Charts. The DataTable and Visualization pages represent xenograft study details, including injected cell lines, PDX injections, molecular modifications of cell lines, zebrafish strains, as well as technical aspects of the xenotransplantation procedures in table, bar, and/or pie chart formats. The PDX Details module provides comprehensive information on the patient details in table format and can be searched and visualized. Overall, ZenoFishDb v1.1 enables researchers to effectively search, list, and visualize different technical and biological attributes of zebrafish xenotransplantation studies particularly focusing on the new trends that make use of reporters, RNA interference, overexpression, or mutant gene constructs of transplanted cancer cells, stem cells, and PDXs, as well as distinguished host modifications.

iPSC-Derived Liver Organoids: A Journey from Drug Screening, to Disease Modeling, Arriving to Regenerative Medicine

Liver transplantation is the most common treatment for patients suffering from liver failure that is caused by congenital diseases, infectious agents, and environmental factors. Despite a high rate of patient survival following transplantation, organ availability remains the key limiting factor. As such, research has focused on the transplantation of different cell types that are capable of repopulating and restoring liver function. The best cellular mix capable of engrafting and proliferating over the long-term, as well as the optimal immunosuppression regimens, remain to be clearly well-defined. Hence, alternative strategies in the field of regenerative medicine have been explored. Since the discovery of induced pluripotent stem cells (iPSC) that have the potential of differentiating into a broad spectrum of cell types, many studies have reported the achievement of iPSCs differentiation into liver cells, such as hepatocytes, cholangiocytes, endothelial cells, and Kupffer cells. In parallel, an increasing interest in the study of self-assemble or matrix-guided three-dimensional (3D) organoids have paved the way for functional bioartificial livers. In this review, we will focus on the recent breakthroughs in the development of iPSCs-based liver organoids and the major drawbacks and challenges that need to be overcome for the development of future applications.

Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a decade with sorafenib as the only approved treatment, multiple new agents have demonstrated efficacy in clinical trials, including the targeted therapies regorafenib, lenvatinib and cabozantinib, the anti-angiogenic antibody ramucirumab, and the immune checkpoint inhibitors nivolumab and pembrolizumab. Although these agents offer new promise to patients with HCC, the optimal choice and sequence of therapies remains unknown and without established biomarkers, and many patients do not respond to treatment. The advances and the decreasing costs of molecular measurement technologies enable profiling of HCC molecular features (such as genome, transcriptome, proteome and metabolome) at different levels, including bulk tissues, animal models and single cells. The release of such data sets to the public enhances the ability to search for information from these legacy studies and provides the opportunity to leverage them to understand HCC mechanisms, rationally develop new therapeutics and identify candidate biomarkers of treatment response. Here, we provide a comprehensive review of public data sets related to HCC and discuss how emerging artificial intelligence methods can be applied to identify new targets and drugs as well as to guide therapeutic choices for improved HCC treatment.

Advances in molecular classification and precision oncology in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) arises from hepatocytes through the sequential accumulation of multiple genomic and epigenomic alterations resulting from Darwinian selection. Genes from various signalling pathways such as telomere maintenance, Wnt/β-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase are frequently mutated in HCC. Several subclasses of HCC have been identified based on transcriptomic dysregulation and genetic alterations that are closely related to risk factors, pathological features and prognosis. Undoubtedly, integration of data obtained from both preclinical models and human studies can help to accelerate the identification of robust predictive biomarkers of response to targeted biotherapy and immunotherapy. The aim of this review is to describe the main advances in HCC in terms of molecular biology and to discuss how this knowledge could be used in clinical practice in the future.

Novel patient-derived preclinical models of liver cancer

Preclinical models of cancer based on the use of human cancer cell lines and mouse models have enabled discoveries that have been successfully translated into patients. And yet the majority of clinical trials fail, emphasising the urgent need to improve preclinical research to better interrogate the potential efficacy of each therapy and the patient population most likely to benefit. This is particularly important for liver malignancies, which lack highly efficient treatments and account for hundreds of thousands of deaths around the globe. Given the intricate network of genetic and environmental factors that contribute to liver cancer development and progression, the identification of new druggable targets will mainly depend on establishing preclinical models that mirror the complexity of features observed in patients. The development of new 3D cell culture systems, originating from cells/tissues isolated from patients, might create new opportunities for the generation of more specific and personalised therapies. However, these systems are unable to recapitulate the tumour microenvironment and interactions with the immune system, both proven to be critical influences on therapeutic outcomes. Patient-derived xenografts, in particular with humanised mouse models, more faithfully mimic the physiology of human liver cancer but are costly and time-consuming, which can be prohibitive for personalising therapies in the setting of an aggressive malignancy. In this review, we discuss the latest advances in the development of more accurate preclinical models to better understand liver cancer biology and identify paradigm-changing therapies, stressing the importance of a bi-directional communicative flow between clinicians and researchers to establish reliable model systems and determine how best to apply them to expanding our current knowledge.

Tumor-triggered personalized microRNA cocktail therapy for hepatocellular carcinoma

miRNA cocktail therapy based on pH-responsive nanoparticles featuring PEG detachment and size transformation is a potential strategy for HCC treatment.

Liver organoids: from basic research to therapeutic applications

Organoid cultures have emerged as an alternative in vitro system to recapitulate tissues in a dish. While mouse models and cell lines have furthered our understanding of liver biology and associated diseases, they suffer in replicating key aspects of human liver tissue, in particular its complex architecture and metabolic functions. Liver organoids have now been established for multiple species from induced pluripotent stem cells, embryonic stem cells, hepatoblasts and adult tissue-derived cells. These represent a promising addition to our toolbox to gain a deeper understanding of this complex organ. In this perspective we will review the advances in the liver organoid field, its limitations and potential for biomedical applications.