Preclinical models as patients' avatars for precision medicine in colorectal cancer: past and future challenges

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.

Novel frontiers in urogenital cancers: from molecular bases to preclinical models to tailor personalized treatments in ovarian and prostate cancer patients

Over the last few decades, the incidence of urogenital cancers has exhibited diverse trends influenced by screening programs and geographical variations. Among women, there has been a consistent or even increased occurrence of endometrial and ovarian cancers; conversely, prostate cancer remains one of the most diagnosed malignancies, with a rise in reported cases, partly due to enhanced and improved screening efforts.Simultaneously, the landscape of cancer therapeutics has undergone a remarkable evolution, encompassing the introduction of targeted therapies and significant advancements in traditional chemotherapy. Modern targeted treatments aim to selectively address the molecular aberrations driving cancer, minimizing adverse effects on normal cells. However, traditional chemotherapy retains its crucial role, offering a broad-spectrum approach that, despite its wider range of side effects, remains indispensable in the treatment of various cancers, often working synergistically with targeted therapies to enhance overall efficacy.For urogenital cancers, especially ovarian and prostate cancers, DNA damage response inhibitors, such as PARP inhibitors, have emerged as promising therapeutic avenues. In BRCA-mutated ovarian cancer, PARP inhibitors like olaparib and niraparib have demonstrated efficacy, leading to their approval for specific indications. Similarly, patients with DNA damage response mutations have shown sensitivity to these agents in prostate cancer, heralding a new frontier in disease management. Furthermore, the progression of ovarian and prostate cancer is intricately linked to hormonal regulation. Ovarian cancer development has also been associated with prolonged exposure to estrogen, while testosterone and its metabolite dihydrotestosterone, can fuel the growth of prostate cancer cells. Thus, understanding the interplay between hormones, DNA damage and repair mechanisms can hold promise for exploring novel targeted therapies for ovarian and prostate tumors.In addition, it is of primary importance the use of preclinical models that mirror as close as possible the biological and genetic features of patients' tumors in order to effectively translate novel therapeutic findings "from the bench to the bedside".In summary, the complex landscape of urogenital cancers underscores the need for innovative approaches. Targeted therapy tailored to DNA repair mechanisms and hormone regulation might offer promising avenues for improving the management and outcomes for patients affected by ovarian and prostate cancers.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

Deciphering the Tumor Microenvironment of Colorectal Cancer and Guiding Clinical Treatment With Patient-Derived Organoid Technology: Progress and Challenges

Colorectal cancer (CRC) is one of the most prevalent malignant tumors of the digestive tract worldwide. Despite notable advancements in CRC treatment, there is an urgent requirement for preclinical model systems capable of accurately predicting drug efficacy in CRC patients, to identify more effective therapeutic options. In recent years, substantial strides have been made in the field of organoid technology, patient-derived organoid models can phenotypically replicate the original intra-tumor and inter-tumor heterogeneity of CRC, reflecting cellular interactions of the tumor microenvironment. Patient-derived organoid models have become an indispensable tool for investigating the pathogenesis of CRC and facilitating translational research. This review focuses on the application of organoid technology in CRC modeling, tumor microenvironment, and guiding clinical treatment, particularly in drug screening and personalized medicine. It also examines the existing challenges encountered in clinical organoid research and provides a prospective outlook on the future development directions of clinical organoid research, encompassing the standardization of organoid culture technology and the application of tissue engineering technology.

Advances towards the use of gastrointestinal tumor patient-derived organoids as a therapeutic decision-making tool

In December 2022 the US Food and Drug Administration (FDA) removed the requirement that drugs in development must undergo animal testing before clinical evaluation, a declaration that now demands the establishment and verification of ex vivo preclinical models that closely represent tumor complexity and that can predict therapeutic response. Fortunately, the emergence of patient-derived organoid (PDOs) culture has enabled the ex vivo mimicking of the pathophysiology of human tumors with the reassembly of tissue-specific features. These features include histopathological variability, molecular expression profiles, genetic and cellular heterogeneity of parental tissue, and furthermore growing evidence suggests the ability to predict patient therapeutic response. Concentrating on the highly lethal and heterogeneous gastrointestinal (GI) tumors, herein we present the state-of-the-art and the current methodology of PDOs. We highlight the potential additions, improvements and testing required to allow the ex vivo of study the tumor microenvironment, as well as offering commentary on the predictive value of clinical response to treatments such as chemotherapy and immunotherapy.

Advances of Osteosarcoma Models for Drug Discovery and Precision Medicine

The management of osteosarcoma (OS) patients presents a significant clinical challenge. Despite progress in conventional and targeted therapies, the survival rate of OS patients remains limited largely due to therapy resistance and the high metastatic potential of the disease. OS models that accurately reflect the fundamental characteristics are vital to the innovation and validation of effective therapies. This review provides an insight into the advances and challenges in OS drug development, focusing on various preclinical models, including cell lines, 3D culture models, murine models, and canine models. The relevance, strengths, and limitations of each model in OS research are explored. In particular, we highlight a range of potential therapeutics identified through these models. These instances of successful drug development represent promising pathways for personalized OS treatment.

Intergenic CircRNA Circ_0007379 Inhibits Colorectal Cancer Progression by Modulating miR-320a Biogenesis in a KSRP-Dependent Manner

Circular RNAs (circRNAs) are covalently closed RNA structures that play multiple roles in tumorigenesis and progression. Compared with exon‒intron circRNAs, the biological functions and implications of intergenic circRNAs in human cancer are still poorly understood. Here, we performed circRNA microarray analysis and identified an intergenic circRNA, circ_0007379, that was significantly downregulated in patients with colorectal cancer (CRC). The biogenesis of circ_0007379 was mediated by reverse complementary matches (RCMs) and was negatively regulated by the RNA helicase DHX9. Functionally, circ_0007379 suppressed CRC cell growth and metastasis in cell culture as well as in patient-derived organoid and xenograft models. Mechanistically, circ_0007379 acted as a scaffold to facilitate the processing of both pri-miR-320a and pre-miR-320a in a KSRP-dependent manner, leading to miR-320a maturation and subsequent repression of transcription factor RUNX1 expression. Thus, our findings establish a previously unrecognized function of circRNA in inhibiting CRC progression.

Orthotopic model of pancreatic cancer using CD34+ humanized mice and generation of tumor organoids from humanized tumors

In pancreatic cancer (PC) as intractable solid cancer, current research is focused mainly on targeted immunotherapies such as antibodies and immune cell modulators. To identify promising immune-oncological agents, animal models that recapitulate the essential features of human immune status are essential. To this end, we constructed an orthotopic xenograft model using CD34⁺ human hematopoietic stem cell-based humanized NOD scid gamma mouse (NSG) mice injected with luciferase-expressing PC cell lines AsPC1 and BxPC3. The growth of orthotopic tumors was monitored using noninvasive multimodal imaging, while the subtype profiles of human immune cells in blood and tumor tissues were determined by flow cytometry and immunohistopathology. In addition, the correlations of blood and tumor-infiltrating immune cell count with tumor extracellular matrix density were calculated using Spearman's test. Tumor-derived cell lines and tumor organoids with continuous passage capacity in vitro were isolated from orthotopic tumors. It was further confirmed that these tumor-derived cells and organoids have reduced PD-L1 expression and are suitable for testing the efficacy of specific targeted immunotherapeutic agents. These animal and culture models could facilitate the development and validation of immunotherapeutic agents for intractable solid cancers including PC.

Towards an optimal model for gastric cancer peritoneal metastasis: current challenges and future directions

Peritoneal metastasis is a challenging aspect of clinical practice for gastric cancer. Animal models are crucial in understanding molecular mechanisms, assessing drug efficacy, and conducting clinical intervention studies, including those related to gastric cancer peritoneal metastasis. Unlike other xenograft models, peritoneal metastasis models should not only present tumor growth at the transplant site, but also recapitulate tumor cell metastasis in the abdominal cavity. Developing a reliable model of gastric cancer peritoneal metastasis involves several technical aspects, such as the selection of model animals, source of xenograft tumors, technology of transplantation, and dynamic monitoring of the tumor progression. To date, challenges remain in developing a reliable model that can completely recapitulate peritoneal metastasis. Thus, this review aims to summarize the techniques and strategies used to establish animal models of gastric cancer peritoneal metastasis, providing a reference for future model establishment.

Addressing blood-brain-tumor-barrier heterogeneity in pediatric brain tumors with innovative preclinical models

Brain tumors represent the leading cause of disease-related mortality and morbidity in children, with effective treatments urgently required. One factor limiting the effectiveness of systemic therapy is the blood-brain-barrier (BBB), which limits the brain penetration of many anticancer drugs. BBB integrity is often compromised in tumors, referred to as the blood-brain-tumor-barrier (BBTB), and the impact of a compromised BBTB on the therapeutic sensitivity of brain tumors has been clearly shown for a few selected agents. However, the heterogeneity of barrier alteration observed within a single tumor and across distinct pediatric tumor types represents an additional challenge. Herein, we discuss what is known regarding the heterogeneity of tumor-associated vasculature in pediatric brain tumors. We discuss innovative and complementary preclinical model systems that will facilitate real-time functional analyses of BBTB for all pediatric brain tumor types. We believe a broader use of these preclinical models will enable us to develop a greater understanding of the processes underlying tumor-associated vasculature formation and ultimately more efficacious treatment options.

Case report: Preclinical efficacy of NEDD8 and proteasome inhibitors in patient-derived models of signet ring high-grade mucinous colorectal cancer from a Lynch syndrome patient

High-grade mucinous colorectal cancer (HGM CRC) is particularly aggressive, prone to metastasis and treatment resistance, frequently accompanied by "signet ring" cancer cells. A sizeable fraction of HGM CRCs (20-40%) arises in the context of the Lynch Syndrome, an autosomal hereditary syndrome that predisposes to microsatellite instable (MSI) CRC. Development of patient-derived preclinical models for this challenging subtype of colorectal cancer represents an unmet need in oncology. We describe here successful propagation of preclinical models from a case of early-onset, MSI-positive metastatic colorectal cancer in a male Lynch syndrome patient, refractory to standard care (FOLFOX6, FOLFIRI-Panitumumab) and, surprisingly, also to immunotherapy. Surgical material from a debulking operation was implanted in NOD/SCID mice, successfully yielding one patient-derived xenograft (PDX). PDX explants were subsequently used to generate 2D and 3D cell cultures. Histologically, all models resembled the tumor of origin, displaying a high-grade mucinous phenotype with signet ring cells. For preclinical exploration of alternative treatments, in light of recent findings, we considered inhibition of the proteasome by bortezomib and of the related NEDD8 pathway by pevonedistat. Indeed, sensitivity to bortezomib was observed in mucinous adenocarcinoma of the lung, and we previously found that HGM CRC is preferentially sensitive to pevonedistat in models with low or absent expression of cadherin 17 (CDH17), a differentiation marker. We therefore performed IHC on the tumor and models, and observed no CDH17 expression, suggesting sensitivity to pevonedistat. Both bortezomib and pevonedistat showed strong activity on 2D cells at 72 hours and on 3D organoids at 7 days, thus providing valid options for in vivo testing. Accordingly, three PDX cohorts were treated for four weeks, respectively with vehicle, bortezomib and pevonedistat. Both drugs significantly reduced tumor growth, as compared to the vehicle group. Interestingly, while bortezomib was more effective in vitro, pevonedistat was more effective in vivo. Drug efficacy was further substantiated by a reduction of cellularity and of Ki67-positive cells in the treated tumors. These results highlight proteasome and NEDD8 inhibition as potentially effective therapeutic approaches against Lynch syndrome-associated HGM CRC, also when the disease is refractory to all available treatment options.

Potential therapeutic strategies for quercetin targeting critical pathological mechanisms associated with colon adenocarcinoma and COVID-19

Patients with colon adenocarcinoma (COAD) are at a higher probability of infection with COVID-19 than healthy individuals. However, there is no globally accepted treatment protocol for patients with COAD/COVID-19. Quercetin has been found to have significant antitumor, antiviral and anti-inflammatory effects in several studies. Therefore, this study sought to evaluate the potential of quercetin as the agent for COAD/COVID-19 and to explore its mechanisms. We used bioinformatics algorithms to obtain COAD/COVID-19-related genes (CCRG) from COAD-related transcriptome data and COVID-related transcriptome sequencing data, and used these genes to construct a COAD prognostic model. We intersected the CCRG with the therapeutic target genes of quercetin and obtained a total of 105 genes (potential target genes of quercetin for the treatment of COAD/COVID-19). By constructing a protein-protein interaction (PPI) network, we ascertained FOS, NFKB1, NFKB1A, JUNB, and JUN as possible core target genes of quercetin for the treatment of COAD/COVID-19. Bioinformatic analysis of these 105 genes revealed that the mechanisms for quercetin the treatment of COAD/COVID-19 may be associated with oxidative stress, apoptosis, anti-inflammatory, immune, anti-viral and multiple pathways containing IL-17, TNF, HIF-1. In this study, we constructed a prognostic model of COAD/COVID19 patients by using CCRG and elucidated for the first time the potential target genes and molecular mechanisms of quercetin for the treatment of COAD/COVID-19, which may benefit the clinical treatment of COAD/COVID-19 patients. However, no clinical trials have yet been conducted to further validate the findings, but this will be the future direction of our research.

Targeting the DNA Damage Response Pathways and Replication Stress in Colorectal Cancer

PURPOSE

Genomic instability is a hallmark of cancer and targeting DNA damage response (DDR) is emerging as a promising therapeutic strategy in different solid tumors. The effectiveness of targeting DDR in colorectal cancer has not been extensively explored.

EXPERIMENTAL DESIGN

We challenged 112 cell models recapitulating the genomic landscape of metastatic colorectal cancer with ATM, ATR, CHK1, WEE1, and DNA-PK inhibitors, in parallel with chemotherapeutic agents. We focused then on ATR inhibitors (ATRi) and, to identify putative biomarkers of response and resistance, we analyzed at multiple levels colorectal cancer models highly sensitive or resistant to these drugs.

RESULTS

We found that around 30% of colorectal cancers, including those carrying KRAS and BRAF mutations and unresponsive to targeted agents, are sensitive to at least one DDR inhibitor. By investigating potential biomarkers of response to ATRi, we found that ATRi-sensitive cells displayed reduced phospho-RPA32 foci at basal level, while ATRi-resistant cells showed increased RAD51 foci formation in response to replication stress. Lack of ATM and RAD51C expression was associated with ATRi sensitivity. Analysis of mutational signatures and HRDetect score identified a subgroup of ATRi-sensitive models. Organoids derived from patients with metastatic colorectal cancer recapitulated findings obtained in cell lines.

CONCLUSIONS

In conclusion, a subset of colorectal cancers refractory to current therapies could benefit from inhibitors of DDR pathways and replication stress. A composite biomarker involving phospho-RPA32 and RAD51 foci, lack of ATM and RAD51C expression, as well as analysis of mutational signatures could be used to identify colorectal cancers likely to respond to ATRi.

Puerarin: A Potential Therapeutic for Colon Adenocarcinoma (COAD) Patients Suffering From SARS-CoV-2 Infection

Patients with colonic adenocarcinoma (COAD) are at relatively high risk of SARS-CoV-2 infection. However, there is a lack of medical strategies to treat COVID-19/COAD comorbidity. Puerarin, a natural product, is a known antiviral, antitumor, and immunomodulatory effect. Therefore, we hypothesised that puerarin could be used to treat COVID-19/COAD patients. Based on network pharmacology and bioinformatics analysis, the potential targets and pharmacological mechanisms of puerarin in COVID-19/COAD were identified. By intersecting therapeutic target genes for puerarin, COVID-19-related genes and COAD-related genes, 42 target genes of puerarin that could potentially treat COVID-19/COAD comorbidity were obtained. By using the 42 potential target genes to construct the protein-protein interaction (PPI) network, we obtained five core target genes, namely RELA, BCL2, JUN, FOS, and MAPK1. The results of bioinformatics analysis revealed that puerarin could be able to treat COVID-19/COAD comorbidity through apoptosis, antiviral, antioxidant, NF-κB signaling pathway, MAPK signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway etc. This study found that puerarin has the potential to treat COVID-19/COAD patients and that the therapeutic target genes obtained in the study may provide clues for the treatment of COVID19/COAD comorbidity.

Biomarkers and 3D models predicting response to immune checkpoint blockade in head and neck cancer (Review)

Immunotherapy has evolved into a powerful tool in the fight against a number of types of cancer, including head and neck squamous cell carcinomas (HNSCC). Although checkpoint inhibition (CPI) has definitely enriched the treatment options for advanced stage HNSCC during the past decade, the percentage of patients responding to treatment is widely varying between 14-32% in second-line setting in recurrent or metastatic HNSCC with a sporadic durability. Clinical response and, consecutively, treatment success remain unpredictable in most of the cases. One potential factor is the expression of target molecules of the tumor allowing cancer cells to acquire therapy resistance mechanisms. Accordingly, analyzing and modeling the complexity of the tumor microenvironment (TME) is key to i) stratify subgroups of patients most likely to respond to CPI and ii) to define new combinatorial treatment regimens. Particularly in a heterogeneous disease such as HNSCC, thoroughly studying the interactions and crosstalking between tumor and TME cells is one of the biggest challenges. Sophisticated 3D models are therefore urgently needed to be able to validate such basic science hypotheses and to test novel immuno-oncologic treatment regimens in consideration of the individual biology of each tumor. The present review will first summarize recent findings on immunotherapy, predictive biomarkers, the role of the TME and signaling cascades eliciting during CPI. Second, it will highlight the significance of current promising approaches to establish HNSCC 3D models for new immunotherapies. The results are encouraging and indicate that data obtained from patient-specific tumors in a dish might be finally translated into personalized immuno-oncology.

Mouse mutagenesis and phenotyping to generate models of development and disease

For many years, the laboratory mouse has been the favored model organism to study mammalian development, biology and disease. Among its advantages for these studies are its close concordance with human biology, the syntenic relationship between the mouse and other mammalian genomes, the existence of many inbred strains, its short gestation period, its relatively low cost for housing and husbandry, and the wide array of tools for genome modification, mutagenesis, and for cryopreserving embryos, sperm and eggs. The advent of CRISPR genome modification techniques has considerably broadened the landscape of model organisms available for study, including other mammalian species. However, the mouse remains the most popular and utilized system to model human development, biology, and disease processes. In this review, we will briefly summarize the long history of mice as a preferred mammalian genetic and model system, and review current large-scale mutagenesis efforts using genome modification to produce improved models for mammalian development and disease.

Patient-Derived Organoids of Colorectal Cancer: A Useful Tool for Personalized Medicine

Colorectal cancer is one of the most important malignancies worldwide, with high incidence and mortality rates. Several studies have been conducted using two-dimensional cultured cell lines; however, these cells do not represent a study model of patient tumors very well. In recent years, advancements in three-dimensional culture methods have facilitated the establishment of patient-derived organoids, which have become indispensable for molecular biology-related studies of colorectal cancer. Patient-derived organoids are useful in both basic science and clinical practice; they can help predict the sensitivity of patients with cancer to chemotherapy and radiotherapy and provide the right treatment to the right patient. Regarding precision medicine, combining gene panel testing and organoid-based screening can increase the effectiveness of medical care. In this study, we review the development of three-dimensional culture methods and present the most recent information on the clinical application of patient-derived organoids. Moreover, we discuss the problems and future prospects of organoid-based personalized medicine.

Zebrafish Patient-Derived Avatars from Digestive Cancers for Anti-cancer Therapy Screening

Patient-derived xenografts (PDXs), also called "avatars," are generated by the implantation of human primary tumor cells or tissues into a host animal. Given the complexity and unique characteristics of each tumor, PDXs are models of choice in cancer research and precision medicine. In this context, the zebrafish PDX model (zPDX or zAvatar) has been recognized as a promising in vivo model to directly challenge patient cells with anti-cancer therapies in a personalized manner. The assay relies on the injection of tumor cells from patients into zebrafish embryos to then test and identify the best available drug combination for a particular patient. Compared to mouse PDXs, zAvatar assays take less time and do not require in vitro or in vivo cell expansion. The present article describes how to generate zAvatars from resected digestive cancer from surgeries and how to then use them for anti-cancer therapy screening. We describe the steps for tumor sample collection and cryopreservation, sample preparation and fluorescent labeling for microinjection into zebrafish embryos, drug administration, and analysis of tumor behavior by single-cell confocal imaging. We provide detailed protocols and helpful tips for performing this assay, and we address the technical challenges associated with the workflow. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Patient tumor sample collection and cryopreservation Basic Protocol 2: Generation of zAvatars and anti-cancer treatment Basic Protocol 3: Whole-mount immunofluorescence Basic Protocol 4: Confocal imaging and analysis.

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment

The tumor's physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.

Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review

BACKGROUND

Patient-derived xenograft (PDX) models have been a focus of attention because they closely resemble the tumor features of patients and retain the molecular and histological features of diseases. They are promising tools for translational research. In the current systematic review, we identify publications on PDX models of cervical cancer (CC-PDX) with descriptions of main methodological characteristics and outcomes to identify the most suitable method for CC-PDX.

METHODS

We searched on PubMed to identify articles reporting CC-PDX. Briefly, the main inclusion criterion for papers was description of PDX created with fragments obtained from human cervical cancer specimens, and the exclusion criterion was the creation of xenograft with established cell lines.

RESULTS

After the search process, 10 studies were found and included in the systematic review. Among 98 donor patients, 61 CC-PDX were established, and the overall success rate was 62.2%. The success rate in each article ranged from 0% to 75% and was higher when using severe immunodeficient mice such as severe combined immunodeficient (SCID), nonobese diabetic (NOD) SCID, and NOD SCID gamma (NSG) mice than nude mice. Subrenal capsule implantation led to a higher engraftment rate than orthotopic and subcutaneous implantation. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. No relationship was found between the engraftment rate and characteristics of the tumor and donor patient, including histology, staging, and metastasis. The latency period varied from 10 days to 12 months. Most studies showed a strong similarity in pathological and immunohistochemical features between the original tumor and the PDX model.

CONCLUSION

Severe immunodeficient mice and subrenal capsule implantation led to a higher engraftment rate; however, orthotopic and subcutaneous implantation were alternatives. When using nude mice, subrenal implantation may be better. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. Few reports have been published about CC-PDX; the results were not confirmed because of the small sample size.