The Generation and Application of Patient-Derived Xenograft Model for Cancer Research

PDX Models in Theranostic Applications: Generation and Screening for B Cell Lymphoma of Human Origin

This MIB guide briefly summarizes the generation of patient-derived xenografts (PDXs) and highlights the importance of validating PDX models for the presence of B cell lymphoma of human origin before their use in radiotheranostic applications. The use of this protocol will allow researchers to learn different methods for screening PDX models for Epstein-Barr virus (EBV)-infected B cell lymphoma.

Preclinical Models of Hepatocellular Carcinoma: Current Utility, Limitations, and Challenges

Hepatocellular carcinoma (HCC), the predominant primary liver tumor, remains one of the most lethal cancers worldwide, despite the advances in therapy in recent years. In addition to the traditional chemically and dietary-induced HCC models, a broad spectrum of novel preclinical tools have been generated following the advent of transgenic, transposon, organoid, and in silico technologies to overcome this gloomy scenario. These models have become rapidly robust preclinical instruments to unravel the molecular pathogenesis of liver cancer and establish new therapeutic approaches against this deadly disease. The present review article aims to summarize and discuss the commonly used preclinical models for HCC, evaluating their strengths and weaknesses.

Prodrug-inspired adenosine triphosphate-activatable celastrol-Fe(III) chelate for cancer therapy

Celastrol (CEL), an active compound isolated from the root of Tripterygium wilfordii, exhibits broad anticancer activities. However, its poor stability, narrow therapeutic window and numerous adverse effects limit its applications in vivo. In this study, an adenosine triphosphate (ATP) activatable CEL-Fe(III) chelate was designed, synthesized, and then encapsulated with a reactive oxygen species (ROS)-responsive polymer to obtain CEL-Fe nanoparticles (CEL-Fe NPs). In normal tissues, CEL-Fe NPs maintain structural stability and exhibit reduced systemic toxicity, while at the tumor site, an ATP-ROS-rich tumor microenvironment, drug release is triggered by ROS, and antitumor potency is restored by competitive binding of ATP. This intelligent CEL delivery system improves the biosafety and bioavailability of CEL for cancer therapy. Such a CEL-metal chelate strategy not only mitigates the challenges associated with CEL but also opens avenues for the generation of CEL derivatives, thereby expanding the therapeutic potential of CEL in clinical settings.

Burning down the house: Pyroptosis in the tumor microenvironment of hepatocellular carcinoma

A high mortality rate makes hepatocellular carcinoma (HCC) a difficult cancer to treat. When surgery is not possible, liver cancer patients are treated with chemotherapy. However, HCC management and treatment are difficult. Sorafenib, which is a first-line treatment for hepatocellular carcinoma, initially slows disease progression. However, sorafenib resistance limits patient survival. Recent studies have linked HCC to programmed cell death, which has increased researcher interest in therapies targeting cell death. Pyroptosis, which is an inflammatory mode of programmed cell death, may be targeted to treat HCC. Pyroptosis pathways, executors, and effects are examined in this paper. This review summarizes how pyroptosis affects the tumor microenvironment (TME) in HCC, including the role of cytokines such as IL-1β and IL-18 in regulating immune responses. The use of chemotherapies and their ability to induce cancer cell pyroptosis as alternative treatments and combining them with other drugs to reduce side effects is also discussed. In conclusion, we highlight the potential of inducing pyroptosis to treat HCC and suggest ways to improve patient outcomes. Studies on cancer cell pyroptosis may lead to new HCC treatments.

The potential of organoids in renal cell carcinoma research

Renal cell carcinoma, a leading cause of death in urological malignancies, arises from the nephron. Its characteristics include diversity in disease biology, varied clinical behaviors, different prognoses, and diverse responses to systemic therapies. The term 'organoids' is used to describe structures resembling tissues created through the three-dimensional cultivation of stem cells in vitro. These organoids, when derived from tumor tissues, can retain the diversity of the primary tumor, mirror its spatial tissue structure, and replicate similar organ-like functions. In contrast to conventional two-dimensional cell cultures and the transplantation of tumor tissues into other organisms, organoids derived from tumors maintain the complexity and microenvironment of the original tumor tissue. This fidelity makes them a more reliable model for the development of cancer drugs, potentially accelerating the translation of these drugs to clinical use and facilitating personalized treatment options for patients. This review aims to summarize the recent advancements in the use of organoids for studying renal cell carcinoma, focusing on their cultivation, potential applications, and inherent limitations.

Advances in the study of gastric organoids as disease models

Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques. These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research. This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids, and patient-derived organoids. The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed. The construction of gastric organoids involves several key steps, including cell extraction and culture, three-dimensional structure formation, and functional expression. Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori. In addition, in drug screening and development, gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials. They can also be used for precision medicine according to the specific conditions of patients with gastric cancer, to assess drug resistance, and to predict the possibility of adverse reactions. However, despite the impressive progress in the field of gastric organoids, there are still many unknowns that need to be addressed, especially in the field of regenerative medicine. Meanwhile, the reproducibility and consistency of organoid cultures are major challenges that must be overcome. These challenges have had a significant impact on the development of gastric organoids. Nonetheless, as technology continues to advance, we can foresee more comprehensive research in the construction of gastric organoids. Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.

Opportunities for targeted therapies: trametinib as a therapeutic approach to canine oral squamous cell carcinomas

Oral tumors are relatively common in dogs, and canine oral squamous cell carcinoma (COSCC) is the most prevalent oral malignancy of epithelial origin. COSCC is locally aggressive with up to 20% of patients showing regional or distant metastasis at the time of diagnosis. The treatment of choice most typically involves wide surgical excision. Although long-term remission is possible, treatments are associated with significant morbidity and can negatively impact functionality and quality of life. OSCCs have significant upregulation of the RAS-RAF-MEK-MAPK signaling axis, and we had previously hypothesized that small-molecule inhibitors that target RAS signaling might effectively inhibit tumor growth and progression. Here, we demonstrate that the MEK inhibitor trametinib, an FDA-approved drug for human cancers, significantly blocks the growth of several COSCC cell lines established from current patient tumor samples. We further show clinical evidence that the drug is able to cause significant tumor regression in some patients with spontaneously occurring COSCC. Given the limited treatment options available and the high rate of owner rejection of these offered options, these findings provide new hope that more acceptable treatment options may soon enter the veterinary clinic.

A review of animal models utilized in preclinical studies of approved gene therapy products: trends and insights

Scientific progress heavily relies on rigorous research, adherence to scientific standards, and transparent reporting. Animal models play a crucial role in advancing biomedical research, especially in the field of gene therapy. Animal models are vital tools in preclinical research, allowing scientists to predict outcomes and understand complex biological processes. The selection of appropriate animal models is critical, considering factors such as physiological and pathophysiological similarities, availability, and ethical considerations. Animal models continue to be indispensable tools in preclinical gene therapy research. Advancements in genetic engineering and model selection have improved the fidelity and relevance of these models. As gene therapy research progresses, careful consideration of animal models and transparent reporting will contribute to the development of effective therapies for various genetic disorders and diseases. This comprehensive review explores the use of animal models in preclinical gene therapy studies for approved products up to September 2023. The study encompasses 47 approved gene therapy products, with a focus on preclinical trials. This comprehensive analysis serves as a valuable reference for researchers in the gene therapy field, aiding in the selection of suitable animal models for their preclinical investigations.

Applied models and molecular characteristics of small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

A Case Study of a Rare Undifferentiated Spindle Cell Sarcoma of the Penis: Establishment and Characterization of Patient-Derived Models

Rare sarcomas present significant treatment challenges compared to more prevalent soft tissue sarcomas due to limited treatment options and a poor understanding of their biology. This study investigates a unique case of penile sarcoma, providing a comprehensive morphological and molecular analysis. Through the creation of experimental patient-derived models-including patient-derived xenograft (PDX), 3D, and monolayer primary cultures-we successfully replicated crucial molecular traits observed in the patient's tumor, such as smooth muscle actin and CD99 expression, along with specific mutations in genes like TSC2 and FGFR4. These models are helpful in assessing the potential for an in-depth exploration of this tumor's biology. This comprehensive approach holds promise in identifying potential therapeutic avenues for managing this exceedingly rare soft tissue sarcoma.

Transcriptomic, Proteomic, and Genomic Mutational Fraction Differences Based on HPV Status Observed in Patient-Derived Xenograft Models of Penile Squamous Cell Carcinoma

Metastatic penile squamous cell carcinoma (PSCC) has only a 50% response rate to first-line combination chemotherapies and there are currently no targeted-therapy approaches. Therefore, we have an urgent need in advanced-PSCC treatment to find novel therapies. Approximately half of all PSCC cases are positive for high-risk human papillomavirus (HR-HPV). Our objective was to generate HPV-positive (HPV+) and HPV-negative (HPV-) patient-derived xenograft (PDX) models and to determine the biological differences between HPV+ and HPV- disease. We generated four HPV+ and three HPV- PSCC PDX animal models by directly implanting resected patient tumor tissue into immunocompromised mice. PDX tumor tissue was found to be similar to patient tumor tissue (donor tissue) by histology and short tandem repeat fingerprinting. DNA mutations were mostly preserved in PDX tissues and similar APOBEC (apolipoprotein B mRNA editing catalytic polypeptide) mutational fractions in donor tissue and PDX tissues were noted. A higher APOBEC mutational fraction was found in HPV+ versus HPV- PDX tissues (p = 0.044), and significant transcriptomic and proteomic expression differences based on HPV status included p16 (CDKN2A), RRM2, and CDC25C. These models will allow for the direct testing of targeted therapies in PSCC and determine their response in correlation to HPV status.

Microfluidic Organoid Cultures Derived from Pancreatic Cancer Biopsies for Personalized Testing of Chemotherapy and Immunotherapy

Patient-derived cancer organoids (PDOs) hold considerable promise for personalizing therapy selection and improving patient outcomes. However, it is challenging to generate PDOs in sufficient numbers to test therapies in standard culture platforms. This challenge is particularly acute for pancreatic ductal adenocarcinoma (PDAC) where most patients are diagnosed at an advanced stage with non-resectable tumors and where patient tissue is in the form of needle biopsies. Here the development and characterization of microfluidic devices for testing therapies using a limited amount of tissue or PDOs available from PDAC biopsies is described. It is demonstrated that microfluidic PDOs are phenotypically and genotypically similar to the gold-standard Matrigel organoids with the advantages of 1) spheroid uniformity, 2) minimal cell number requirement, and 3) not relying on Matrigel. The utility of microfluidic PDOs is proven by testing PDO responses to several chemotherapies, including an inhibitor of glycogen synthase kinase (GSKI). In addition, microfluidic organoid cultures are used to test effectiveness of immunotherapy comprised of NK cells in combination with a novel biologic. In summary, our microfluidic device offers considerable benefits for personalizing oncology based on cancer biopsies and may, in the future, be developed into a companion diagnostic for chemotherapy or immunotherapy treatments.

Biomaterials for Drug Delivery and Human Applications

Biomaterials embody a groundbreaking paradigm shift in the field of drug delivery and human applications. Their versatility and adaptability have not only enriched therapeutic outcomes but also significantly reduced the burden of adverse effects. This work serves as a comprehensive overview of biomaterials, with a particular emphasis on their pivotal role in drug delivery, classifying them in terms of their biobased, biodegradable, and biocompatible nature, and highlighting their characteristics and advantages. The examination also delves into the extensive array of applications for biomaterials in drug delivery, encompassing diverse medical fields such as cancer therapy, cardiovascular diseases, neurological disorders, and vaccination. This work also explores the actual challenges within this domain, including potential toxicity and the complexity of manufacturing processes. These challenges emphasize the necessity for thorough research and the continuous development of regulatory frameworks. The second aim of this review is to navigate through the compelling terrain of recent advances and prospects in biomaterials, envisioning a healthcare landscape where they empower precise, targeted, and personalized drug delivery. The potential for biomaterials to transform healthcare is staggering, as they promise treatments tailored to individual patient needs, offering hope for improved therapeutic efficacy, fewer side effects, and a brighter future for medical practice.

Evaluation of chicken chorioallantoic membrane model for tumor imaging and drug development: Promising findings

BACKGROUND

The chicken chorioallantoic membrane (CAM) model is a potential alternative to the mouse model based on the 3R principles. However, its value for determination of the in vivo behaviors of radiolabeled peptides through positron emission tomography (PET) imaging needed investigation. Herein, the chicken CAM tumor models were established, and their feasibility was evaluated for evaluating the imaging properties of radiolabeled peptides using a 68 Ga-labeled HER2 affibody.

METHODS

Two human breast cancer cell lines were inoculated into chicken CAM and mice, respectively. The tumor-targeting potential and pharmacokinetic profile of a 68 Ga-labeled affibody, 68 Ga-MZHER, in both tumor models were also determined.

RESULTS

The tumor-formation time in chicken CAM model was shorter than that of mouse model. The uptake values of human epithelial growth factor receptor-2 (HER2)-positive Bcap37 tumors in chicken CAM and mouse models were 5.36 ± 0.26% ID/g and 5.26 ± 0.43% ID/g at 30 min postinjection of 68 Ga-MZHER, respectively. At the same time points, the uptake values of HER2-negative MDA-MB-231 tumors in the chicken CAM models and mouse models were 1.57 ± 0.15% ID/g and 1.67 ± 0.25% ID/g, respectively. Ex vivo biodistribution confirmed that more radioactivity accumulated in Bcap37 tumors than in MDA-MD-231 tumors in both CAM and mouse models.

CONCLUSION

In this study, the CAM tumor model was successfully prepared. The chicken CAM model is a novel tool for quickly determining the in vivo properties of radiolabeled peptides targeting biomarkers. It may be beneficial for early monitoring of the therapeutic effect of a new drug through PET imaging with specific peptides.

Statistical classification of treatment responses in mouse clinical trials for stratified medicine in oncology drug discovery

Translational oncology research strives to explore a new aspect: identifying subgroups that exhibit treatment response even during pre-clinical phases. In this study, we focus on PDX models and their implementation in mouse clinical trials (MCT). Our primary objective was to identify subgroups with different treatment responses using Latent Class Mixed Model (LCMM).We used a public dataset and focused on one treatment, encorafenib, and two indications, melanoma and colorectal cancer, for which efficacy depends on a specific mutation BRAF V600E. One LCMM per indication was implemented to classify treatment responses at the PDX level, analyzing the growth kinetics of treated tumors and matched controls within the PDX models. A simulation study was carried out to explore the performance of LCMM in this context. For both applications, LCMM identified classes for which the higher the proportion of mutated BRAF V600E PDX models the greater the treatment effect, which is aligned with encorafenib use recommendations. The simulation study showed that LCMM could identify classes with large differences in treatment effects. LCMM is a suitable tool for MCT to explore treatment response subgroups of PDX. Once these subgroups are defined, characterization of their phenotypes/genotypes could be performed to explore treatment response predictors.

Revolutionizing digestive system tumor organoids research: Exploring the potential of tumor organoids

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

Assessing Protein Expression in Patient-Derived Xenografts Using Western Blotting

The use of patient-derived xenografts (PDXs) in cancer research is increasing due to their ability to closely mimic the features of patient tumors. The ability to quickly and robustly measure protein expression levels in these tissues is a key methodology required in a broad range of experimental designs. Western blotting (WB) is a cost effective and simple tool that is highly specific and sensitive for detecting and quantifying individual proteins, posttranslational modifications and aberrant signaling pathways. Here, we described a method to assess protein expression in PDX tissues using WB to detect proteins involved in cell growth signaling pathways.

Exploratory study on the efficacy of bortezomib combining mitoxantrone or CD22-CAR T therapy targeting CD19-negative relapse after CD19-CAR T cell therapy with a simpler cell-line-based model

Target-negative relapse after CD19 chimeric antigen receptor engineered (CAR) T cell therapy for patients with B lineage acute lymphoblastic leukemia (B-ALL) presents limited treatment options with dismal outcomes. Although CD22-CAR T cells mediate similarly potent antineoplastic effects in patients with CD19dim or even CD19-negative relapse following CD19-directed immunotherapy, a high rate of relapse associated with diminished CD22 cell surface expression has also been observed. Therefore, it is unclear whether any other therapeutic options are available. Mitoxantrone has shown significant antineoplastic activity in patients with relapsed or refractory leukemia over the past decades, and in some cases, the addition of bortezomib to conventional chemotherapeutic agents has demonstrated improved response rates. However, whether this mitoxantrone and bortezomib combination therapy is effective for those patients who have relapsed B-ALL after receiving CD19-CAR T cell therapy remains to be elucidated. In this study, we established a cellular model system using a CD19-positive B-ALL cell line Nalm-6 to investigate the treatment options for CD19-negative relapsed B-ALL after CD19-CAR T cell therapy. In addition to CD22-CAR T therapy, we observed that the combination of bortezomib and mitoxantrone exhibited effective anti-leukemia activity in the CD19-negative Nalm-6 cell line by downregulating p-AKT and p-mTOR. These results suggest that this combination therapy is a possible option for target-negative refractory leukemia cells after CAR-T cell treatment.

Comparative RNA-Seq Analysis Revealed Tissue-Specific Splicing Variations during the Generation of the PDX Model

Tissue-specific gene expression generates fundamental differences in the function of each tissue and affects the characteristics of the tumors that are created as a result. However, it is unclear how much the tissue specificity is conserved during grafting of the primary tumor into an immune-compromised mouse model. Here, we performed a comparative RNA-seq analysis of four different primary-patient derived xenograft (PDX) tumors. The analysis revealed a conserved RNA biotype distribution of primary-PDX pairs, as revealed by previous works. Interestingly, we detected significant changes in the splicing pattern of PDX, which was mainly comprised of skipped exons. This was confirmed by splicing variant-specific RT-PCR analysis. On the other hand, the correlation analysis for the tissue-specific genes indicated overall strong positive correlations between the primary and PDX tumor pairs, with the exception of gastric cancer cases, which showed an inverse correlation. These data propose a tissue-specific change in splicing events during PDX formation as a variable factor that affects primary-PDX integrity.

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

BR55 Ultrasound Molecular Imaging of Clear Cell Renal Cell Carcinoma Reflects Tumor Vascular Expression of VEGFR-2 in a Patient-Derived Xenograft Model

Standard imaging cannot reliably predict the nature of renal tumors. Among malignant renal tumors, clear cell renal cell carcinoma (ccRCC) is the most common histological subtype, in which the vascular endothelial growth factor 2 (VEGFR-2) is highly expressed in the vascular endothelium. BR55, a contrast agent for ultrasound imaging, consists of gas-core lipid microbubbles that specifically target and bind to the extracellular portion of the VEGFR-2. The specific information provided by ultrasound molecular imaging (USMI) using BR55 was compared with the vascular tumor expression of the VEGFR-2 by immunohistochemical (IHC) staining in a preclinical model of ccRCC. Patients' ccRCCs were orthotopically grafted onto Nod-Scid-Gamma (NSG) mice to generate patient-derived xenografts (PdX). Mice were divided into four groups to receive either vehicle or axitinib an amount of 2, 7.5 or 15 mg/kg twice daily. Perfusion parameters and the BR55 ultrasound contrast signal on PdX renal tumors were analyzed at D0, D1, D3, D7 and D11, and compared with IHC staining for the VEGFR-2 and CD34. Significant Pearson correlation coefficients were observed between the area under the curve (AUC) and the CD34 (0.84, p < 10-4), and between the VEGFR-2-specific signal obtained by USMI and IHC (0.72, p < 10-4). USMI with BR55 could provide instant, quantitative information on tumor VEGFR-2 expression to characterize renal masses non-invasively.

Modeling Liver Development and Disease in a Dish

Historically, biological research has relied primarily on animal models. While this led to the understanding of numerous human biological processes, inherent species-specific differences make it difficult to answer certain liver-related developmental and disease-specific questions. The advent of 3D organoid models that are either derived from pluripotent stem cells or generated from healthy or diseased tissue-derived stem cells have made it possible to recapitulate the biological aspects of human organs. Organoid technology has been instrumental in understanding the disease mechanism and complements animal models. This review underscores the advances in organoid technology and specifically how liver organoids are used to better understand human-specific biological processes in development and disease. We also discuss advances made in the application of organoid models in drug screening and personalized medicine.

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.

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

Engineering liquid metal-based nanozyme for enhancing microwave dynamic therapy in breast cancer PDX model

BACKGROUNDS

The novel concept of microwave dynamic therapy (MDT) solves the problem of incomplete tumor eradication caused by non-selective heating and uneven temperature distribution of microwave thermal therapy (MWTT) in clinic, but the poor delivery of microwave sensitizer and the obstacle of tumor hypoxic microenvironment limit the effectiveness of MDT.

RESULTS

Herein, we engineer a liquid metal-based nanozyme LM@ZIF@HA (LZH) with eutectic Gallium Indium (EGaIn) as the core, which is coated with CoNi-bimetallic zeolite imidazole framework (ZIF) and hyaluronic acid (HA). The flexibility of the liquid metal and the targeting of HA enable the nanozyme to be effectively endocytosed by tumor cells, solving the problem of poor delivery of microwave sensitizers. Due to the catalase-like activity, the nanozyme catalyze excess H2O2 in the tumor microenvironment to generate O2, alleviating the restriction of the tumor hypoxic microenvironment and promoting the production of ROS under microwave irradiation. In vitro cell experiments, the nanozyme has remarkable targeting effect, oxygen production capacity, and microwave dynamic effect, which effectively solves the defects of MDT. In the constructed patient-derived xenograft (PDX) model, the nanozyme achieves excellent MDT effect, despite the heterogeneity and complexity of the tumor model that is similar to the histological and pathological features of the patient. The tumor volume in the LZH + MW group is only about 1/20 of that in the control group, and the tumor inhibition rate is as high as 95%.

CONCLUSION

The synthesized nanozyme effectively solves the defects of MDT, improves the targeted delivery of microwave sensitizers while regulating the hypoxic microenvironment of tumors, and achieves excellent MDT effect in the constructed PDX model, providing a new strategy for clinical cancer treatment.

Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research

Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.

Progress in construction of mouse models to investigate the pathogenesis and immune therapy of human hematological malignancy

Hematological malignancy is a disease arisen by complicate reasons that seriously endangers human health. The research on its pathogenesis and therapies depends on the usage of animal models. Conventional animal model cannot faithfully mirror some characteristics of human features due to the evolutionary divergence, whereas the mouse models hosting human hematological malignancy are more and more applied in basic as well as translational investigations in recent years. According to the construction methods, they can be divided into different types (e.g. cell-derived xenograft (CDX) and patient-derived xenograft model (PDX) model) that have diverse characteristics and application values. In addition, a variety of strategies have been developed to improve human hematological malignant cell engraftment and differentiation in vivo. Moreover, the humanized mouse model with both functional human immune system and autologous human hematological malignancy provides a unique tool for the evaluation of the efficacy of novel immunotherapeutic drugs/approaches. Herein, we first review the evolution of the mouse model of human hematological malignancy; Then, we analyze the characteristics of different types of models and summarize the ways to improve the models; Finally, the way and value of humanized mouse model of human immune system in the immunotherapy of human hematological malignancy are discussed.

The challenge of making the right choice: patient avatars in the era of cancer immunotherapies

Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.

Development of a small cell lung cancer organoid model to study cellular interactions and survival after chemotherapy

Introduction: Small-cell-lung-cancer (SCLC) has the worst prognosis of all lung cancers because of a high incidence of relapse after therapy. While lung cancer is the second most common malignancy in the US, only about 10% of cases of lung cancer are SCLC, therefore, it is categorized as a rare and recalcitrant disease. Therapeutic discovery for SCLC has been challenging and the existing pre-clinical models often fail to recapitulate actual tumor pathophysiology. To address this, we developed a bioengineered 3-dimensional (3D) SCLC co-culture organoid model as a phenotypic tool to study SCLC tumor kinetics and SCLC-fibroblast interactions after chemotherapy. Method: We used functionalized alginate microbeads as a scaffold to mimic lung alveolar architecture and co-cultured SCLC cell lines with primary adult lung fibroblasts (ALF). We found that SCLCs in the model proliferated extensively, invaded the microbead scaffold and formed tumors within just 7 days. We compared the bioengineered tumors with patient tumors and found them to recapitulate the pathology and immunophenotyping of the patient tumors. When treated with standard chemotherapy drugs, etoposide and cisplatin, we observed that some of the cells survived the chemotherapy and reformed the tumor in the organoid model. Result and Discussion: Co-culture of the SCLC cells with ALFs revealed that the fibroblasts play a key role in inducing faster and more robust SCLC cell regrowth in the model. This is likely due to a paracrine effect, as conditioned media from the same fibroblasts could also support this accelerated regrowth. This model can be used to study cell-cell interactions and the response to chemotherapy in SCLC and is also scalable and amenable to high throughput phenotypic or targeted drug screening to find new therapeutics for SCLC.

Association of cyclooxygenase-2 expression with endoplasmic reticulum stress and autophagy in triple-negative breast cancer

Cyclooxygenase-2 plays a role in oncogenesis and its overexpression is associated with triple-negative breast cancer. However, the mechanisms whereby cyclooxygenase-2 contribute to breast cancer are complex and not well understood. Cyclooxygenase-2 overexpression causes hypoxia, oxidative stress, and endoplasmic reticulum stress. The aim of this study is to investigate the correlations among cyclooxygenase-2 expression, endoplasmic reticulum stress-associated molecules, and autophagy-associated molecules in triple-negative breast cancer. Surgical specimens from two cohorts of triple-negative breast cancer patients without neoadjuvant systemic therapy were analyzed: cohorts 1 and 2 consisted of 218 cases from 2004 to 2006 and 221 cases from 2007 to 2009, respectively. Specimens were evaluated by immunohistochemical examination of cyclooxygenase-2, endoplasmic reticulum stress markers, and autophagy markers expression using tissue microarrays. Cyclooxygenase-2 was overexpressed in 29.8% and 23.9% of cases in cohorts 1 and 2, respectively; and it was positively correlated with two out of three endoplasmic reticulum stress-associated molecules (XBP1, p = 0.025 and p = 0.003 in cohort 1 and cohort 2, respectively; PERK, p < 0.001 in both cohorts). Cyclooxygenase-2 was also positively correlated with two out of three autophagy markers (p62, p = 0.002 and p = 0.003 in cohort 1 and cohort 2, respectively; beclin1, p < 0.001 in both cohorts). Although cyclooxygenase-2 was not an independent prognostic factor for distant metastasis free survival and overall survival, its expression was associated with the expression of endoplasmic reticulum stress and autophagy molecules in triple-negative breast cancer.

Selinexor demonstrates anti-tumor efficacy in paired patient-derived xenograft models and hydrogel-embedded histoculture drug sensitivity test of penile cancer

BACKGROUND

Penile cancer is a rare malignancy with a poor prognosis, even with various treatment options. Considering the little progress in the study of the pathogenesis and treatment of penile cancer because of the lack of models that mimic the biological properties of the tumor, we have developed a patient-derived xenograft (PDX) model and paired hydrogel-embedded histoculture drug sensitivity test (HDST) to screen for drugs that can inhibit tumors. The increased expression of XPO1, as a key nuclear export protein involved in the transport of various tumor suppressors and cell cycle regulatory proteins, is associated with the prognosis of a variety of tumors [World J Uroly 27(2):141-150, 2009]. Selinexor is an inhibitor of XPO1, which can treat cancers, such as multiple myeloma, gastric cancer, triple-negative breast cancer, and non-small cell carcinoma [Transl Androl Urol 6(5):785-790, 2017; OncoTargets Therapy 13:6405-6416, 2020]. However, whether XPO1 inhibition has a role in penile cancer remains unknown. Therefore, this article used the PDX and HDST models to investigate whether the inhibition of XPO1 has an effect on penile cancer and its underlying mechanism.

METHODS

We used penile cancer tumor tissues to construct a PDX model of penile cancer and paired PDXE model and confirmed the consistency of PDX tumor tissues in source patients. Then, we assessed the ability of Selinexor to inhibit penile cancer tissues in vivo using a PDX model and in vitro by HDST. We also examined the potential mechanism of XPO1 action on penile cancer by IHC and TUNEL. Finally, we assessed the safety of the drug treatment by H&E and biochemical blood analysis.

RESULTS

Result showed that the penile cancer PDX model and patient penile cancer tissues were clinically consistent in morphological characteristics and protein expression. In addition, Selinexor could inhibit tumor growth in PDX models and HDST. We found that P53, P21 expression was upregulated; Cyclin D1 expression was downregulated, and apoptosis of tumor cells was increased in the Selinexor-treated PDX model. Moreover, it had no significant effect on liver, kidney, and cardiac function.

CONCLUSION

The PDX model of penile cancer was a powerful tool for penile cancer research and new drug development. It showed that Selinexor can effectively inhibit penile cancer in vitro and in vivo. In addition, XPO1 may affect P53, P21, and Cyclin D1 expression to regulate the growth and apoptosis of penile carcinoma.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Alteration in molecular properties during establishment and passaging of endometrial carcinoma patient-derived xenografts

Patient-derived xenograft (PDX) tumor models are known to maintain the genomic and phenotypic profiles, including the histopathological structures, of the parental tumors. On the other hand, unique enrichment of single-nucleotide variants or copy number aberrations has been reported in several types of tumors. However, an understanding of endometrial carcinoma PDXs is limited. The purpose of the present study was to clarify the presence or absence of the molecular properties of endometrial carcinomas in PDXs passaged up to eight times. Established PDXs of endometrioid carcinomas maintained their histopathological characteristics, but those of carcinosarcomas predominantly consisted of sarcomatous components when compared to the parental tumors. Alterations in the proportion of cells with positive/negative immunohistochemical staining for estrogen receptor, PTEN, PAX8, and PAX2 were observed, whereas the proportions of cells with AE1/AE3, TP53, ARID1A, PMS2, and MSH6 staining were unchanged. Variants of cancer-associated genes were compared between PDXs and parental tumors. Mutations in POLE and a frameshift deletion in BRCA1 were observed in the parental tumor tissue in each of the six cases, and additional genomic alterations, which were not apparently related to histopathological and immunohistochemical alterations, were found in the PDXs of these cases. The genomic and phenotypic alterations observed between endometrial carcinoma PDXs and parental tumors were partly associated with endometrial cancer-specific characteristics related to cellular differentiation and gene mutations.

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.

Effects of Mouse Kidney Parvovirus on Pharmacokinetics of Chemotherapeutics and the Adenine Model of Chronic Kidney Disease

Mouse kidney parvovirus (MKPV) causes inclusion body nephropathy in severely immunocompromised mice and renal interstitial inflammation in immunocompetent mice. Here we sought to determine the effects of MKPV on pre-clinical murine models that depend on renal function. To assess the effects of MKPV infection on the pharmacokinetics of 2 renally excreted chemotherapeutic agents, methotrexate and lenalidomide, we measured drug concentrations in the blood and urine of MKPV-infected or uninfected immunodeficient NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) and immunocompetent C57BL/6NCrl (B6) female mice. No differences in plasma pharmacokinetics were observed for lenalidomide. However, the AUC of methotrexate was 1.5-fold higher in uninfected NSG mice compared with infected NSG mice, 1.9-fold higher in infected B6 mice compared with uninfected B6 mice, and 4.3-fold higher in uninfected NSG mice compared with uninfected B6 mice. MKPV infection did not significantly affect the renal clearance of either drug. To assess effects of MKPV infection on the adenine diet model of chronic kidney disease, MKPV-infected and uninfected B6 female mice were fed a 0.2% adenine diet, and clinical and histopathologic features of disease were assessed over 8 wk. MKPV infection did not significantly alter urine chemistry results, hemogram findings, or serum concentrations of BUN, creatinine, or symmetric dimethylarginine. However, infection did influence histologic outcomes. As compared with uninfected mice, MKPV-infected mice had more interstitial lymphoplasmacytic infiltrates after 4 and 8 wk of diet consumption and less interstitial fibrosis at week 8. Macrophage infiltrates and renal tubular injury were similar between in infected and uninfected mice. These findings indicate that MKPV infection had minimal effects on the renal excretion of 2 chemotherapeutics and on serum biomarkers of renal function. However, infection significantly influenced two histologic features of the adenine diet model of chronic renal disease. MKPV-free mice are critically important in studies evaluating renal histology as an experimental outcome.

Experimental mouse models for translational human cancer research

The development and growth of tumors remains an important and ongoing threat to human life around the world. While advanced therapeutic strategies such as immune checkpoint therapy and CAR-T have achieved astonishing progress in the treatment of both solid and hematological malignancies, the malignant initiation and progression of cancer remains a controversial issue, and further research is urgently required. The experimental animal model not only has great advantages in simulating the occurrence, development, and malignant transformation mechanisms of tumors, but also can be used to evaluate the therapeutic effects of a diverse array of clinical interventions, gradually becoming an indispensable method for cancer research. In this paper, we have reviewed recent research progress in relation to mouse and rat models, focusing on spontaneous, induced, transgenic, and transplantable tumor models, to help guide the future study of malignant mechanisms and tumor prevention.

Potential roles of lncRNA-XIST/miRNAs/mRNAs in human cancer cells

Long non-coding RNAs (lncRNAs) are non-coding RNAs that contain more than 200 nucleotides but do not code for proteins. In tumorigenesis, lncRNAs can have both oncogenic and tumor-suppressive properties. X inactive-specific transcript (XIST) is a known lncRNA that has been implicated in X chromosome silencing in female cells. Dysregulation of XIST is associated with an increased risk of various cancers. Therefore, XIST can be a beneficial prognostic biomarker for human malignancies. In this review, we attempt to summarize the emerging roles of XIST in human cancers.

Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study

Predicting the clinical response to chemotherapeutic or targeted treatment in patients with locally advanced or metastatic lung cancer requires an accurate and affordable tool. Tumor organoids are a potential approach in precision medicine for predicting the clinical response to treatment. However, their clinical application in lung cancer has rarely been reported because of the difficulty in generating pure tumor organoids. In this study, we have generated 214 cancer organoids from 107 patients, of which 212 are lung cancer organoids (LCOs), primarily derived from malignant serous effusions. LCO-based drug sensitivity tests (LCO-DSTs) for chemotherapy and targeted therapy have been performed in a real-world study to predict the clinical response to the respective treatment. LCO-DSTs accurately predict the clinical response to treatment in this cohort of patients with advanced lung cancer. In conclusion, LCO-DST is a promising precision medicine tool in treating of advanced lung cancer.

Preparation and application of patient-derived xenograft mice model of colorectal cancer

Objectives

Patient-derived xenograft (PDX) model becomes a more and more important tool for tumor research. This study aimed to establish a colorectal cancer PDX model and verify its applicability.

Materials and Methods

Fresh human colorectal cancer tissue was surgically removed and subcutaneously inoculated into immunodeficient mice to establish the PDX model. Hematoxylin and eosin (HE) staining and immunohistochemical staining were used to evaluate the model. The successful PDX model was selected to study the efficacy of capecitabine in treating colorectal cancer.

Results

HE staining showed that the PDX mice model of colorectal cancer could preserve the histological characteristics of the primary tumor. Immunohistochemistry staining showed α-fetoprotein (AFP), carcinoembryonic antigen (CEA), and E-cadherin were strongly positively expressed in primary human and PDX tumor tissues, with a high degree of similarity. Capecitabine significantly inhibited PDX tumor growth and reduced the expression of AFP and CEA proteins in the tumor tissues (all P s<0.05).

Conclusion

We successfully established a colorectal cancer PDX model, and the PDX model could retain the histological and biological characteristics of the primary tumor. Using this PDX model, we revealed that capecitabine at a dose of 300-400 mg/kg can effectively treat colorectal cancer, and no significant difference in toxicity was found among different dose groups. The current work provides a feasible framework for establishing and validating the PDX tumor model to better facilitate the evaluation of drug efficacy and safety.

An integrated PK/PD model investigating the impact of tumor size and systemic safety on animal survival in SW1990 pancreatic cancer xenograft

Survival is one of the most important endpoints in cancer therapy, and parametric survival analysis could comprehensively reveal the overall result of disease progression, drug efficacy, toxicity as well as their interactions. In this study we investigated the efficacy and toxicity of dexamethasone (DEX) combined with gemcitabine (GEM) in pancreatic cancer xenograft. Nude mice bearing SW1990 pancreatic cancer cells derived tumor were treated with DEX (4 mg/kg, i.g.) and GEM (15 mg/kg, i.v.) alone or in combination repeatedly (QD, Q3D, Q7D) until the death of animal or the end of study. Tumor volumes and net body weight (NBW) were assessed every other day. Taking NBW as a systemic safety indicator, an integrated pharmacokinetic/pharmacodynamic (PK/PD) model was developed to quantitatively describe the impact of tumor size and systemic safety on animal survival. The PK/PD models with time course data for tumor size and NBW were established, respectively, in a sequential manner; a parametric time-to-event (TTE) model was also developed based on the longitudinal PK/PD models to describe the survival results of the SW1990 tumor-bearing mice. These models were evaluated and externally validated. Only the mice with good tumor growth inhibition and relatively stable NBW had an improved survival result after DEX and GEM combination therapy, and the simulations based on the parametric TTE model showed that NBW played more important role in animals' survival compared with tumor size. The established model in this study demonstrates that tumor size was not always the most important reason for cancer-related death, and parametric survival analysis together with safety issues was also important in the evaluation of oncology therapies in preclinical studies.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

Development and characterization of patient-derived xenograft models of colorectal cancer for testing new pharmacological substances

The aim of the study was to create a patient-derived xenograft (PDX) model of human colorectal cancer and to determine its histologic and molecular characteristics, such as the status of KRAS, NRAS, and BRAF genes and the presence of microsatellite instability.

Materials and methods. First generation xenograft models in vivo were created using tumors from patients with colorectal cancer (n = 4) and immunodeficient Balb/c Nude mice (n = 20); second, third, and fourth generation models were created in the same mouse line (n = 3 for each generation). A caliper was used to measure subcutaneous xenografts; their size was calculated by the ellipsoid formula. Cryopreservation involved immersing the samples in a freezing medium (80% RPMI 1640, 10% fetal bovine serum, 10% dimethyl sulfoxide (DMSO)) and storing them at –80 °C. The histologic analysis was performed according to the standard technique (preparation of paraffin blocks and staining of microsections with hematoxylin and eosin). Mutations in the KRAS, NRAS, and BRAF genes were determined by direct Sanger sequencing; microsatellite instability was determined by the fragment analysis at five loci: Bat-25, Bat-26, NR21, NR24, and NR27.

Results. Stable, transplantable xenografts of colorectal cancer were obtained from two out of four patients. The average waiting time from the implantation to the growth of the first generation xenograft was 28 days. The latency phase after cryopreservation was comparable to that at the creation of the first generation PDX model. The model reproduced the histotype, grade and mutational status of the KRAS, NRAS, and BRAF genes, as well as microsatellite instability of the donor tumor.

Conclusion. The developed model of human colorectal cancer was characterized in terms of growth dynamics, cryopreservation tolerance, and histologic and molecular genetic parameters.

Small cell lung cancer co-culture organoids provide insights into cancer cell survival after chemotherapy

Small-cell-lung-cancer (SCLC) has the worst prognosis of all lung cancers because of a high incidence of relapse after therapy. We developed a bioengineered 3-dimensional (3D) SCLC co-culture organoid as a phenotypic tool to study SCLC tumor kinetics and SCLC-fibroblast interactions during relapse. We used functionalized alginate microbeads as a scaffold to mimic lung alveolar architecture and co-cultured SCLC cell lines with primary adult lung fibroblasts (ALF). We found that SCLCs in the model proliferated extensively, invaded the microbead scaffold and formed tumors within just 7 days. We compared the bioengineered tumors with patient tumors and found them to recapitulate the pathology and immunophenotyping of the patient tumors better than the PDX model developed from the same SCLC cell line. When treated with standard chemotherapy drugs, etoposide and cisplatin, the organoid recapitulated relapse after chemotherapy. Co-culture of the SCLC cells with ALFs revealed that the fibroblasts play a key role in inducing faster and more robust SCLC cell regrowth in the model. This was a paracrine effect as conditioned medium from the same fibroblasts was responsible for this accelerated cell regrowth. This model is also amenable to high throughput phenotypic or targeted drug screening to find new therapeutics for SCLC.

Spotlight on P2X7 Receptor PET Imaging: A Bright Target or a Failing Star?

The homotrimeric P2X7 receptor (P2X7R) is expressed by virtually all cells of the innate and adaptive immune system and plays a crucial role in various pathophysiological processes such as autoimmune and neurodegenerative diseases, inflammation, neuropathic pain and cancer. Consequently, the P2X7R is considered a promising target for therapy and diagnosis. As the development of tracers comes hand-in-hand with the development of potent and selective receptor ligands, there is a rising number of PET tracers available in preclinical and clinical studies. This review analyzes the development of P2X7R positron emission tomography (PET) tracers and their potential in various PET imaging applications.

A novel method to identify and characterize personalized functional driver lncRNAs in cancer samples

Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.

Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors

Establishment of clinically annotated, molecularly characterized, patient-derived xenografts (PDXs) from treatment-naïve and pretreated patients provides a platform to test precision genomics-guided therapies. An integrated multi-OMICS pipeline was developed to identify cancer-associated pathways and evaluate stability of molecular signatures in a panel of pediatric and AYA PDXs following serial passaging in mice. Original solid tumor samples and their corresponding PDXs were evaluated by whole-genome sequencing, RNA-seq, immunoblotting, pathway enrichment analyses, and the drug−gene interaction database to identify as well as cross-validate actionable targets in patients with sarcomas or Wilms tumors. While some divergence between original tumor and the respective PDX was evident, majority of alterations were not functionally impactful, and oncogenic pathway activation was maintained following serial passaging. CDK4/6 and BETs were prioritized as biomarkers of therapeutic response in osteosarcoma PDXs with pertinent molecular signatures. Inhibition of CDK4/6 or BETs decreased osteosarcoma PDX growth (two-way ANOVA, p < 0.05) confirming mechanistic involvement in growth. Linking patient treatment history with molecular and efficacy data in PDX will provide a strong rationale for targeted therapy and improve our understanding of which therapy is most beneficial in patients at diagnosis and in those already exposed to therapy.

AKR1C2 Promotes Metastasis and Regulates the Molecular Features of Luminal Androgen Receptor Subtype in Triple Negative Breast Cancer Cells

PURPOSE

Patients with triple-negative breast cancer (TNBC) have an increased risk of distant metastasis compared to those with other subtypes. In this study, we aimed to identify the genes associated with distant metastasis in TNBC and their underlying mechanisms.

METHODS

We established patient-derived xenograft (PDX) models using surgically resected breast cancer tissues from 31 patients with TNBC. Among these, 15 patients subsequently developed distant metastases. Candidate metastasis-associated genes were identified using RNA sequencing. In vitro wound healing, proliferation, migration, and invasion assays and in vivo tumor xenograft and metastasis assays were performed to determine the functional importance of aldo-keto reductase family 1 member C2 (AKR1C2). Additionally, we used the METABRIC dataset to investigate the potential role of AKR1C2 in regulating TNBC subtypes and their downstream signaling activities.

RESULTS

RNA sequencing of primary and PDX tumors showed that genes involved in steroid hormone biosynthesis, including AKR1C2, were significantly upregulated in patients who subsequently developed metastasis. In vitro and in vivo assays showed that silencing of AKR1C2 resulted in reduced cell proliferation, migration, invasion, tumor growth, and incidence of lung metastasis. AKR1C2 was upregulated in the luminal androgen receptor (LAR) subtype of TNBC in the METABRIC dataset, and AKR1C2 silencing resulted in the downregulation of LAR classifier genes in TNBC cell lines. The androgen receptor (AR) gene was a downstream mediator of AKR1C2-associated phenotypes in TNBC cells. AKR1C2 expression was associated with gene expression pathways that regulate AR expression, including JAK-STAT signaling or interleukin 6 (IL-6). The levels of phospho-signal transducer and activator of transcription and IL-6, along with secreted IL-6, were significantly downregulated in AKR1C2-silenced TNBC cells.

CONCLUSION

Our data indicate that AKR1C2 is an important regulator of cancer growth and metastasis in TNBC and may be a critical determinant of LAR subtype features.

Current methods for studying metastatic potential of tumor cells

Cell migration and invasiveness significantly contribute to desirable physiological processes, such as wound healing or embryogenesis, as well as to serious pathological processes such as the spread of cancer cells to form tumor metastasis. The availability of appropriate methods for studying these processes is essential for understanding the molecular basis of cancer metastasis and for identifying suitable therapeutic targets for anti-metastatic treatment. This review summarizes the current status of these methods: In vitro methods for studying cell migration involve two-dimensional (2D) assays (wound-healing/scratch assay), and methods based on chemotaxis (the Dunn chamber). The analysis of both cell migration and invasiveness in vitro require more complex systems based on the Boyden chamber principle (Transwell migration/invasive test, xCELLigence system), or microfluidic devices with three-dimensional (3D) microscopy visualization. 3D culture techniques are rapidly becoming routine and involve multicellular spheroid invasion assays or array chip-based, spherical approaches, multi-layer/multi-zone culture, or organoid non-spherical models, including multi-organ microfluidic chips. The in vivo methods are mostly based on mice, allowing genetically engineered mice models and transplant models (syngeneic mice, cell line-derived xenografts and patient-derived xenografts including humanized mice models). These methods currently represent a solid basis for the state-of-the art research that is focused on understanding metastatic fundamentals as well as the development of targeted anti-metastatic therapies, and stratified treatment in oncology.

Modelling metabolic diseases and drug response using stem cells and organoids

Metabolic diseases, including obesity, diabetes mellitus and cardiovascular disease, are a major threat to health in the modern world, but efforts to understand the underlying mechanisms and develop rational treatments are limited by the lack of appropriate human model systems. Notably, advances in stem cell and organoid technology allow the generation of cellular models that replicate the histological, molecular and physiological properties of human organs. Combined with marked improvements in gene editing tools, human stem cells and organoids provide unprecedented systems for studying mechanisms of metabolic diseases. Here, we review progress made over the past decade in the generation and use of stem cell-derived metabolic cell types and organoids in metabolic disease research, especially obesity and liver diseases. In particular, we discuss the limitations of animal models and the advantages of stem cells and organoids, including their application to metabolic diseases. We also discuss mechanisms of drug action, understanding the efficacy and toxicity of existing therapies, screening for new treatments and pursuing personalized therapies. We highlight the potential of combining stem cell-derived organoids with gene editing and functional genomics to revolutionize the approach to finding treatments for metabolic diseases.

Comparison of classical tumour growth models for patient derived and cell-line derived xenografts using the nonlinear mixed-effects framework

In this study we compare seven mathematical models of tumour growth using nonlinear mixed-effects which allows for a simultaneous fitting of multiple data and an estimation of both mean behaviour and variability. This is performed for two large datasets, a patient-derived xenograft (PDX) dataset consisting of 220 PDXs spanning six different tumour types and a cell-line derived xenograft (CDX) dataset consisting of 25 cell lines spanning eight tumour types. Comparison of the models is performed by means of visual predictive checks (VPCs) as well as the Akaike Information Criterion (AIC). Additionally, we fit the models to 500 bootstrap samples drawn from the datasets to expand the comparison of the models under dataset perturbations and understand the growth kinetics that are best fitted by each model. Through qualitative and quantitative metrics the best models are identified the effectiveness and practicality of simpler models is highlighted.