Patient-derived xenograft models in hepatopancreatobiliary cancer

Biological characteristics and immune responses of NK Cells in commonly used experimental mouse models

The biology of natural killer (NK) cells in commonly used mouse models is discussed in this review, along with their crucial function in a variety of immunological responses. It has been demonstrated that the formation, maturation, subtype variety, and immunological recognition mechanisms of NK cells from various mice strains exhibit notable differences. These variations shed light on the intricacy of NK cell function and offer crucial information regarding their possible uses in treating human illnesses. The application of flow cytometry in mouse NK cell research is also covered in the article. Improved knowledge of the biology of NK cells across species may facilitate the development of new NK cell-based therapeutic approaches.

Selinexor targeting XPO1 promotes PEG3 nuclear accumulation and suppresses cholangiocarcinoma progression

BACKGROUND

The role of selinexor, a targeted inhibitor of exportin 1 (XPO1), in the treatment of cholangiocarcinoma is not yet fully understood. This study conducted comprehensive in vitro and in vivo investigations to elucidate the effects of selinexor on cholangiocarcinoma, with a focus on its mechanistic relationship with the cellular localization of Paternally Expressed Gene 3 (PEG3).

METHODS

A patient-derived xenograft (PDX) model was established using samples from a cholangiocarcinoma patient in immunodeficient mice to assess the in vivo effects of selinexor. Additionally, cholangiocarcinoma cell lines HuCC-T1 and BRE were cultured to evaluate selinexor's impact on cell proliferation, invasion, migration, cell cycle, and apoptosis. HuCC-T1 cells were also implanted in immunodeficient mice for further investigation. Immunofluorescence and Western blotting were employed to observe the expression and localization of the PEG3 protein.

RESULTS

The results demonstrated that selinexor significantly inhibited tumor growth in the cholangiocarcinoma PDX model and promoted the accumulation of PEG3 protein within the nuclei of tumor cells. In vitro experiments showed that selinexor effectively suppressed cholangiocarcinoma cell proliferation, invasion, and migration, while also impeding the cell cycle and inducing apoptosis. Notably, selinexor markedly facilitated the nuclear accumulation of PEG3 protein in cholangiocarcinoma cells. However, when PEG3 expression was knocked down, the effects of selinexor on cholangiocarcinoma were significantly reversed.

CONCLUSION

These findings suggest that selinexor inhibits the progression of cholangiocarcinoma by targeting XPO1 and promoting the nuclear accumulation of PEG3 protein, thereby hindering the cell cycle and inducing apoptosis.

Basic models to advanced systems: harnessing the power of organoids-based microphysiological models of the human brain

Understanding the complexities of the human brain's function in health and disease is a formidable challenge in neuroscience. While traditional models like animals offer valuable insights, they often fall short in accurately mirroring human biology and drug responses. Moreover, recent legislation has underscored the need for more predictive models that more accurately represent human physiology. To address this requirement, human-derived cell cultures have emerged as a crucial alternative for biomedical research. However, traditional static cell culture models lack the dynamic tissue microenvironment that governs human tissue function. Advancedin vitrosystems, such as organoids and microphysiological systems (MPSs), bridge this gap by offering more accurate representations of human biology. Organoids, which are three-dimensional miniaturized organ-like structures derived from stem cells, exhibit physiological responses akin to native tissues, but lack essential tissue-specific components such as functional vascular structures and immune cells. Recent endeavors have focused on incorporating endothelial cells and immune cells into organoids to enhance vascularization, maturation, and disease modeling. MPS, including organ-on-chip technologies, integrate diverse cell types and vascularization under dynamic culture conditions, revolutionizing brain research by bridging the gap betweenin vitroandin vivomodels. In this review, we delve into the evolution of MPS, with a particular focus on highlighting the significance of vascularization in enhancing the viability, functionality, and disease modeling potential of organoids. By examining the interplay of vasculature and neuronal cells within organoids, we can uncover novel therapeutic targets and gain valuable insights into disease mechanisms, offering the promise of significant advancements in neuroscience and improved patient outcomes.

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

Fucoxanthin Inhibits Development of Sigmoid Colorectal Cancer in a PDX Model With Alterations of Growth, Adhesion, and Cell Cycle Signals

BACKGROUND/AIM

Fucoxanthin (Fx), a dietary marine xanthophyll, exerts potent anticancer effects in various colorectal cancer (CRC) animal models. However, therapeutic effects of Fx in human cancer tissues remain unclear. A patient-derived xenograft (PDX) mouse model transplanted with cancer tissues from patients is widely accepted as the best preclinical model for evaluating the anticancer potential of drug candidates.

MATERIALS AND METHODS

Herein, we investigated the anticancer effects of Fx in PDX mice transplanted with cancer tissues derived from a patient with CRC (CRC-PDX) using LC-MS/MS- and western blot-based proteome analysis.

RESULTS

The tumor in the patient with CRC was a primary adenocarcinoma (T3N0M0, stage II) showing mutations of certain genes that were tumor protein p53 (TP53), AT-rich interaction domain 1A (ARID1A), neuroblastoma RAS viral oncogene homolog (NRAS), and PMS1 homolog 2 (PMS2). Administration of Fx significantly suppressed the tumor growth (0.6-fold) and tended to induce differentiation in CRC-PDX mice. Fx up-regulated glycanated-decorin (Gc-DCN) expression, and down-regulated Kinetochore-associated protein DSN1 homolog (DSN1), phospho(p) focal adhesion kinase (pFAK)(Tyr397), pPaxillin(Tyr31), and c-MYC involved in growth, adhesion, and/or cell cycle, in the tumors of CRC-PDX mice than in control mice. Alterations in the five proteins were consistent with those in human CRC HT-29 and HCT116 cells treated with fucoxanthinol (FxOH, a major metabolite of Fx).

CONCLUSION

Fx suppresses development of human-like CRC tissues, especially through growth, adhesion, and cell cycle signals.

Identification of biomarkers, pathways, and therapeutic targets for EGFR-TKI resistance in NSCLC

This study aimed to map the hub genes and potential pathways that might be involved in the molecular pathogenesis of EGFR-TKI resistance in NSCLC. We performed bioinformatics analysis to identify differentially expressed genes, their function, gene interactions, and pathway analysis between EGFR-TKI-sensitive and EGFR-TKI-resistant patient-derived xenotransplantation samples based on Gene Expression Omnibus database. Survival analysis was performed via the GEPIA database (GEO). The relationship between the key gene ITGAM and the therapeutic candidates was retrieved from DGIdb. A total of 1,302 differentially expressed genes were identified based on GEO. The PPI network highlighted 10 potential hub genes. Only ITGAM was linked to poor DSF in NSCLC patients. A total of 10 drugs were predicted to be potential therapeutics for NSCLC with EGFR-TKI resistance. This study indicates the hub genes related to EGFR-TKI resistance in NSCLC through bioinformatics technologies which can improve the understanding of the mechanisms of EGFR-TKI resistance and provide novel insights into therapeutics.

Patient-derived tumor models: a suitable tool for preclinical studies on esophageal cancer

Esophageal cancer (EC) is the tenth most common cancer worldwide and has high morbidity and mortality. Its main subtypes include esophageal squamous cell carcinoma and esophageal adenocarcinoma, which are usually diagnosed during their advanced stages. The biological defects and inability of preclinical models to summarize completely the etiology of multiple factors, the complexity of the tumor microenvironment, and the genetic heterogeneity of tumors severely limit the clinical treatment of EC. Patient-derived models of EC not only retain the tissue structure, cell morphology, and differentiation characteristics of the original tumor, they also retain tumor heterogeneity. Therefore, compared with other preclinical models, they can better predict the efficacy of candidate drugs, explore novel biomarkers, combine with clinical trials, and effectively improve patient prognosis. This review discusses the methods and animals used to establish patient-derived models and genetically engineered mouse models, especially patient-derived xenograft models. It also discusses their advantages, applications, and limitations as preclinical experimental research tools to provide an important reference for the precise personalized treatment of EC and improve the prognosis of patients.

Breast Cancer Tissue Explants: An Approach to Develop Personalized Therapy in Public Health Services

Breast cancer is one of the main causes of death worldwide. Lately, there is great interest in developing methods that assess individual sensitivity and/or resistance of tumors to antineoplastics to provide personalized therapy for patients. In this study we used organotypic culture of human breast tumor slices to predict the experimental effect of antineoplastics on the viability of tumoral tissue. Samples of breast tumor were taken from 27 patients with clinically advanced breast cancer; slices were obtained and incubated separately for 48 h with paclitaxel, docetaxel, epirubicin, 5-fluorouracil, cyclophosphamide, and cell culture media (control). We determined an experimental tumor sensitivity/resistance (S/R) profile by evaluating tissue viability using the Alamar Blue® metabolic test, and by structural viability (histopathological analyses, necrosis, and inflammation). These parameters were related to immunohistochemical expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. The predominant histological type found was infiltrating ductal carcinoma (85.2%), followed by lobular carcinoma (7.4%) and mixed carcinoma (7.4%). Experimental drug resistance was related to positive hormone receptor status in 83% of samples treated with cyclophosphamide (p = 0.027). Results suggest that the tumor S/R profile can help to predict personalized therapy or optimize chemotherapeutic treatments in breast cancer.

Organoids technology for advancing the clinical translation of cancer nanomedicine

The past decades have witnessed the rapid development and widespread application of nanomedicines in cancer treatment; however, the clinical translation of experimental findings has been low, as evidenced by the low percentage of commercialized nanomedicines. Incomplete understanding of nanomedicine-tumor interactions and inappropriate evaluation models are two important challenges limiting the clinical translation of cancer nanomedicines. Currently, nanomedicine-tumor interaction and therapeutic effects are mainly investigated using cell lines or mouse models, which do not recapitulate the complex tumor microenvironment in human patients. Thus, information obtained from cell lines and mouse models cannot provide adequate guidance for the rational redesign of nanomedicine. Compared with other preclinical models, tumor organoids constructed from patient-derived tumor tissues are superior in retaining the key histopathological, genetic, and phenotypic features of the parent tumor. We speculate that organoid technology would help elucidate nanomedicine-tumor interaction in the tumor microenvironment and guide the design of nanomedicine, making it a reliable tool to accurately predict drug responses in patients with cancer. This review highlighted the advantages of drug delivery systems in cancer treatment, challenges limiting the clinical translation of antitumor nanomedicines, and potential application of patient-derived organoids (PDO) in nanomedicine. We propose that combining organoids and nanotechnology would facilitate the development of safe and effective cancer nanomedicines and accelerate their clinical application. This review discussed the potential translational value of integrative research using organoids and cancer nanomedicine. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

In Vitro/In Vivo Translation of Synergistic Combination of MDM2 and MEK Inhibitors in Melanoma Using PBPK/PD Modelling: Part III

The development of in vitro/in vivo translational methods and a clinical trial framework for synergistically acting drug combinations are needed to identify optimal therapeutic conditions with the most effective therapeutic strategies. We performed physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) modelling and virtual clinical trial simulations for siremadlin, trametinib, and their combination in a virtual representation of melanoma patients. In this study, we built PBPK/PD models based on data from in vitro absorption, distribution, metabolism, and excretion (ADME), and in vivo animals' pharmacokinetic-pharmacodynamic (PK/PD) and clinical data determined from the literature or estimated by the Simcyp simulator (version V21). The developed PBPK/PD models account for interactions between siremadlin and trametinib at the PK and PD levels. Interaction at the PK level was predicted at the absorption level based on findings from animal studies, whereas PD interaction was based on the in vitro cytotoxicity results. This approach, combined with virtual clinical trials, allowed for the estimation of PK/PD profiles, as well as melanoma patient characteristics in which this therapy may be noninferior to the dabrafenib and trametinib drug combination. PBPK/PD modelling, combined with virtual clinical trial simulation, can be a powerful tool that allows for proper estimation of the clinical effect of the above-mentioned anticancer drug combination based on the results of in vitro studies. This approach based on in vitro/in vivo extrapolation may help in the design of potential clinical trials using siremadlin and trametinib and provide a rationale for their use in patients with melanoma.

Exploration of Patient-Derived Pancreatic Ductal Adenocarcinoma Ex Vivo Tissue for Treatment Response

Patient-derived tissue culture models are valuable tools to investigate drug effects and targeted treatment approaches. Resected tumor slices cultured ex vivo have recently gained interest in precision medicine, since they reflect the complex microenvironment of cancer tissue. In this study, we examined the treatment response to an internally developed ex vivo tissue culture model from pancreatic ductal adenocarcinoma (PDAC) and in vitro analysis. Seven PDAC tissues were cultured and subsequently treated with indole-3-pyruvic acid (IPA). IPA, which is known as an agonist of the aryl hydrocarbon receptor (AHR) pathway, has antioxidant properties. Genome-wide transcriptome sequencing analysis revealed activation of AHR pathway genes (CYP1A1 and CYP1B1, p ≤ 0.05). Additionally, significant upregulation of AHR repressor genes AHRR and TiPARP was also observed (p ≤ 0.05), which is indicative of the negative feedback loop activation of AHR pathway signaling. The overall transcriptomic response to IPA indicated that the tissues are biologically active and respond accordingly to exogenous treatment. Cell culture analysis confirmed the significant induction of selected AHR genes by IPA. A morphological examination of the paraffin-embedded formalin-fixed tissue did not show obvious signs of IPA treatment related to tumor cell damage. This study is a proof of concept that ex vivo patient-derived tissue models offer a valuable tool in precision medicine to monitor the effect of personalized treatments.

Research Status of Mouse Models for Non-Small-Cell Lung Cancer (NSCLC) and Antitumor Therapy of Traditional Chinese Medicine (TCM) in Mouse Models

Non-small-cell lung cancer (NSCLC) is known as one of the most lethal cancers, causing more than 1 million deaths annually worldwide. Therefore, the development of novel therapeutic drugs for NSCLC has become an urgent need. Herein, various mouse models provide great convenience not only for researchers but also for the development of antitumor drug. Meanwhile, TCM, as a valuable and largely untapped resource pool for modern medicine, provides research resources for the treatment of various diseases. Until now, cell-derived xenograft (CDX) model, patient-derived xenograft (PDX) model, syngeneic model, orthotopic model, humanized mouse model (HIS), and genetically engineered mouse models (GEMMs) have been reported in TCM evaluation. This review shows the role and current status of kinds of mouse models in antitumor research and summarizes the application progress of TCM including extracts, formulas, and isolated single molecules for NSCLC therapy in various mouse models; more importantly, it provides a theoretical exploration of what kind of mouse models is ideal for TCM efficacy evaluation in future. However, there are still huge challenges and limitations in the development of mouse models specifically for the TCM research, and none of the available models are perfectly matching the characteristics of TCM, which suppress the tumor growth through various mechanisms, especially by regulating immune function. Nevertheless, with fully functional immune system existing in syngeneic model and humanized mouse model (HIS), it is still suggested that these two models are more suitable for development of TCM especially for TCM extracts or formulas. Moreover, continued efforts are needed to generate more reliable mouse models to test TCM formulas in future research.

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.