Patient-derived tumor xenografts: transforming clinical samples into mouse models

Discovery of WEE1 Kinase Inhibitors with Potent Activity against Patient-Derived, Metastatic Colorectal Cancer Organoids

A library of potent WEE1 kinase inhibitors was synthesized based on the discontinued frontrunner clinical candidate AZD1775 (1), many of which were more selective for WEE1 over an undesirable off-target of 1, the kinase PLK1. When tested against patient-derived organoids (PDOs) grown from TP53-mutated colorectal cancer (CRC) peritoneal metastases, 34 (IC50 value of 62 nM) exhibited stronger efficacy than 1 (IC50 value of 120 nM) and the best-in-class clinical candidate ZN-c3 (IC50 value of 127 nM). Against primary CRC PDOs with TP53-WT, 34 significantly enhanced DNA damage, replication stress and apoptosis compared to 1, as well as demonstrated high selectivity over patient-matched normal healthy colon PDOs, highlighting a potential therapeutic window for cancer treatment. Overall, this investigation provides critical insight into several potent WEE1 inhibitors that exhibited exceptional efficacy against CRC PDOs and is the first to utilize a PDO platform to assess their effect on healthy and malignant cell viability.

A patient-derived T cell lymphoma biorepository uncovers pathogenetic mechanisms and host-related therapeutic vulnerabilities

Peripheral T cell lymphomas (PTCLs) comprise heterogeneous malignancies with limited therapeutic options. To uncover targetable vulnerabilities, we generate a collection of PTCL patient-derived tumor xenografts (PDXs) retaining histomorphology and molecular donor-tumor features over serial xenografting. PDX demonstrates remarkable heterogeneity, complex intratumor architecture, and stepwise trajectories mimicking primary evolutions. Combining functional transcriptional stratification and multiparametric imaging, we identify four distinct PTCL microenvironment subtypes with prognostic value. Mechanistically, we discover a subset of PTCLs expressing Epstein-Barr virus-specific T cell receptors and uncover the capacity of cancer-associated fibroblasts of counteracting treatments. PDXs' pre-clinical testing captures individual vulnerabilities, mirrors donor patients' clinical responses, and defines effective patient-tailored treatments. Ultimately, we assess the efficacy of CD5KO- and CD30- Chimeric Antigen Receptor T Cells (CD5KO-CART and CD30_CART, respectively), demonstrating their therapeutic potential and the synergistic role of immune checkpoint inhibitors for PTCL treatment. This repository represents a resource for discovering and validating intrinsic and extrinsic factors and improving the selection of drugs/combinations and immune-based therapies.

Differences in treatment outcome between translational platforms in developing therapies for gastrointestinal cancers

The variability in translational models profoundly impacts the outcomes and predictive value of preclinical studies for gastrointestinal (GI) cancer treatments. Preclinical models, including 2D cell cultures, 3D organoids, patient-derived xenografts (PDXs), and animal models, provide distinct advantages and limitations in replicating the complex tumor microenvironment (TME) of human cancers. Each model's unique biological and structural differences contribute to discrepancies in treatment responses, challenging the direct translation of experimental results to clinical settings. While 2D cell cultures are cost-effective and suitable for high-throughput screening, they lack the 3D architecture and cellular interactions of the in vivo TME. Organoids offer a more comprehensive 3D structure that better mirrors tumor heterogeneity, yet they still face limitations in fully mimicking in vivo conditions, such as vascularization and immune cell interactions. PDXs, although more representative of human cancers due to their genetic fidelity and TME preservation, are costly and resource-intensive, with human stromal and immune components gradually replaced by murine counterparts over time. This review assesses the strengths and limitations of each model, highlighting recent advancements in translational platforms that incorporate complex TME features. Understanding the influence of model selection on treatment efficacy predictions is essential for enhancing the reliability of preclinical findings and advancing personalized therapeutic strategies for GI cancers.

Regulation of lung cancer initiation and progression by the stem cell determinant Musashi

Despite advances in therapeutic approaches, lung cancer remains the leading cause of cancer-related deaths. To understand the molecular programs underlying lung cancer initiation and maintenance, we focused on stem cell programs that are normally extinguished with differentiation but can be reactivated during oncogenesis. Here, we have used extensive genetic modeling and patient-derived xenografts (PDXs) to identify a dual role for Msi2: as a signal that acts initially to sensitize cells to transformation, and subsequently to drive tumor propagation. Using Msi reporter mice, we found that Msi2-expressing cells were marked by a pro-oncogenic landscape and a preferential ability to respond to Ras and p53 mutations. Consistent with this, genetic deletion of Msi2 in an autochthonous Ras/p53-driven lung cancer model resulted in a marked reduction of tumor burden, delayed progression, and a doubling of median survival. Additionally, this dependency was conserved in human disease as inhibition of Msi2 impaired tumor growth in PDXs. Mechanistically, Msi2 triggered a broad range of pathways critical for tumor growth, including several novel effectors of lung adenocarcinoma. Collectively, these findings reveal a critical role for Msi2 in aggressive lung adenocarcinoma, lend new insight into the biology of this disease, and identify potential new therapeutic targets.

Recent advances in 3D bioprinted neural models: A systematic review on the applications to drug discovery

The design of neural tissue models with architectural and biochemical relevance to native tissues opens the way for the fundamental study and development of therapies for many disorders with limited treatment options. Here, we systematically review the most recent literature on 3D bioprinted neural models, including their potential for use in drug screening. Neural tissues that model the central nervous system (CNS) from the relevant literature are reviewed with comprehensive summaries of each study, and discussion of the model types, bioinks and additives, cell types used, bioprinted construct shapes and culture time, and the characterization methods used. In this review, we accentuate the lack of standardization among characterization methods to analyze the functionality (including chemical, metabolic and other pathways) and mechanical relevance of the 3D bioprinted constructs, and discuss this as a critical area for future exploration. These gaps must be addressed for this technology to be applied for effective drug screening applications, despite its enormous potential for rapid and efficient drug screening. The future of biomimetic, 3D printed neural tissues is promising and evaluation of the in vivo relevance on multiple levels should be sought to adequately compare model performance and develop viable treatment options for neurodegenerative diseases, or other conditions that affect the CNS.

Glioblastoma Cortical Organoids Recapitulate Cell-State Heterogeneity and Intercellular Transfer

Glioblastoma (GBM) is characterized by heterogeneous malignant cells that are functionally integrated within the neuroglial microenvironment. In this study, we model this ecosystem by growing GBM into long-term cultured human cortical organoids that contain the major neuroglial cell types found in the cerebral cortex. Single-cell RNA sequencing analysis suggests that, compared with matched gliomasphere models, GBM cortical organoids more faithfully recapitulate the diversity and expression programs of malignant cell states found in patient tumors. Additionally, we observe widespread transfer of GBM transcripts and GFP to nonmalignant cells in the organoids. Mechanistically, this transfer involves extracellular vesicles and is biased toward defined GBM cell states and astroglia cell types. These results extend previous GBM organoid modeling efforts and suggest widespread intercellular transfer in the GBM neuroglial microenvironment. Significance: Models that recapitulate intercellular communications in GBM are limited. In this study, we leverage GBM cortical organoids to characterize widespread mRNA and GFP transfer from malignant to nonmalignant cells in the GBM neuroglial microenvironment. This transfer involves extracellular vesicles, may contribute to reprogramming the microenvironment, and may extend to other cancer types. See related commentary by Shakya et al., p. 261.

Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

Fuel for thought: targeting metabolism in lung cancer

For over a century, we have appreciated that the biochemical processes through which micro- and macronutrients are anabolized and catabolized-collectively referred to as "cellular metabolism"-are reprogrammed in malignancies. Cancer cells in lung tumors rewire pathways of nutrient acquisition and metabolism to meet the bioenergetic demands for unchecked proliferation. Advances in precision medicine have ushered in routine genotyping of patient lung tumors, enabling a deeper understanding of the contribution of altered metabolism to tumor biology and patient outcomes. This paradigm shift in thoracic oncology has spawned a new enthusiasm for dissecting oncogenotype-specific metabolic phenotypes and creates opportunity for selective targeting of essential tumor metabolic pathways. In this review, we discuss metabolic states across histologic and molecular subtypes of lung cancers and the additional changes in tumor metabolic pathways that occur during acquired therapeutic resistance. We summarize the clinical investigation of metabolism-specific therapies, addressing successes and limitations to guide the evaluation of these novel strategies in the clinic. Beyond changes in tumor metabolism, we also highlight how non-cellular autonomous processes merit particular consideration when manipulating metabolic processes systemically, such as efforts to disentangle how lung tumor cells influence immunometabolism. As the future of metabolic therapeutics hinges on use of models that faithfully recapitulate metabolic rewiring in lung cancer, we also discuss best practices for harmonizing workflows to capture patient specimens for translational metabolic analyses.

Tissue-engineered patient-derived osteosarcoma models dissecting tumour-bone interactions

Osteosarcoma is the most common malignant bone tumor, primarily affecting children and young adults. For these young patients, the current treatment options for osteosarcoma impose considerable constraints on daily life with significant morbidity and a low survival rate. Despite ongoing research efforts, the 5-year survival rate of first-diagnosed patients without metastases has not changed in the past four decades. The demand for novel treatments is currently still unmet, in particular for effective second-line therapy. Therefore, there is an urgent need for advanced preclinical models and drug-testing platforms that take into account the complex disease characteristics, the high heterogeneity of the tumour and the interactions with the bone microenvironment. In this review, we provide a comprehensive overview about state-of-the-art tissue-engineered and patient-specific models for osteosarcoma. These sophisticated platforms for advanced therapy trials aim to improve treatment outcomes for future patients by modelling the patient's disease state in a more accurate and complex way, thus improving the quality of preclinical research studies.

Treatment with novel topoisomerase inhibitors in Ewing sarcoma models reveals heterogeneity of tumor response

Introduction

The topoisomerase 1 (TOP1) inhibitor irinotecan is a standard-of-care agent for relapsed Ewing sarcoma (EWS), but its efficacy is limited by chemical instability, rapid clearance and reversibility, and dose-limiting toxicities, such as diarrhea. Indenoisoquinolines (IIQs) represent a new class of clinical TOP1 inhibitors designed to address these limitations.

Methods

In this study, we evaluated the preclinical efficacy of three IIQs (LMP400, LMP744, and LMP776) in relevant models of EWS. We characterized the pharmacokinetics of IIQs in orthotopic xenograft models of EWS, optimized the dosing regimen through tolerability studies, and tested the efficacy of IIQs in a panel of six molecularly heterogeneous EWS patient-derived xenograft (PDX) models. For each PDX, we conducted whole genome and RNA sequencing, and methylation analysis.

Results

We show that IIQs potently inhibit the proliferation of EWS cells in vitro, inducing complete cell growth inhibition at nanomolar concentrations via induction of DNA damage and apoptotic cell death. LMP400 treatment induced ≥30% tumor regression in two of six PDX models, with more durable regression compared to irinotecan treatment in one of these models. RNA sequencing of PDX models identified a candidate predictive biomarker gene signature for LMP400 response. These data, along with pharmacogenomic data on IIQs in sarcoma cell lines, are available at a new interactive public website: https://discover.nci.nih.gov/rsconnect/EwingSarcomaMinerCDB/.

Discussion

Our findings suggest that IIQs may be promising new agents for a subset of EWS patients.

Tumor-microenvironment-on-a-chip: the construction and application

Currently, despite the vast amounts of time and money invested in cancer treatment, cancer remains one of the primary threats to human life. The primary factor contributing to the low treatment efficacy is cancer heterogeneity. The unclear molecular mechanisms underlying tumorigenesis, coupled with the complexity of human physiology, and the inability of animal models to accurately replicate the human tumor microenvironment, pose significant hurdles in the development of novel cancer therapies. Tumor-microenvironment-on-chip (TMOC) represents a research platform that integrates three-dimensional cell culture with microfluidic systems, simulating the essential components and physiological traits of the in vivo tumor microenvironment. It offers a dynamic setting within the chip system to study tumor progression, potentially heralding a breakthrough in cancer research. In this review, we will summarize the current advancements in this platform, encompassing various types of TMOCs and their applications in different types of cancer. From our perspective, the TMOC platform necessitates enhanced integration with tissue engineering techniques and microphysiological environments before it can evolve into a more refined preclinical model for cancer research.

Mimicking and analyzing the tumor microenvironment

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Recent advances in lung cancer organoid (tumoroid) research (Review)

Lung cancer is the most critical type of malignant tumor that threatens human health. Traditional preclinical models have certain defects; for example, they cannot accurately reflect the characteristics of lung cancer and their development is costly and time-consuming. Through self-organization, cancer stem cells (CSCs) generate cancer organoids that have a structure similar to that of lung cancer tissues, overcoming to some extent the aforementioned challenges, thus enabling them to have broader application prospects. Lung cancer organoid (LCO) development methods can be divided into three broad categories based on the source of cells, which include cell lines, patient-derived xenografts and patient tumor tissue/pleural effusion. There are 17 different methods that have been described for the development of LCOs. These methods can be further merged into six categories based on the source of cells, the pre-treatment method used, the composition of the medium and the culture scaffold. These categories are: i) CSCs induced by defined transcription factors; ii) suspension culture; iii) relative optimal culture medium; iv) suboptimal culture medium; v) mechanical digestion and suboptimal culture medium; and vi) hydrogel scaffold. In the current review, the advantages and disadvantages of each of the aforementioned methods are summarized, and references for supporting studies are cited.

The roles of patient-derived xenograft models and artificial intelligence toward precision medicine

Patient-derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell-line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time-consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast-track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.

From Crypts to Cancer: A Holistic Perspective on Colorectal Carcinogenesis and Therapeutic Strategies

Colorectal cancer (CRC) represents a significant global health burden, with high incidence and mortality rates worldwide. Recent progress in research highlights the distinct clinical and molecular characteristics of colon versus rectal cancers, underscoring tumor location's importance in treatment approaches. This article provides a comprehensive review of our current understanding of CRC epidemiology, risk factors, molecular pathogenesis, and management strategies. We also present the intricate cellular architecture of colonic crypts and their roles in intestinal homeostasis. Colorectal carcinogenesis multistep processes are also described, covering the conventional adenoma-carcinoma sequence, alternative serrated pathways, and the influential Vogelstein model, which proposes sequential APC, KRAS, and TP53 alterations as drivers. The consensus molecular CRC subtypes (CMS1-CMS4) are examined, shedding light on disease heterogeneity and personalized therapy implications.

Reversion of pathogenic BRCA1 L1780P mutation confers resistance to PARP and ATM inhibitor in breast cancer

This study investigates the molecular characteristics and therapeutic implications of the BRCA1 L1780P mutation, a rare variant prevalent among Korean hereditary breast cancer patients. Using patient-derived xenograft (PDX) models and cell lines (PDX-derived cell line) from carriers, sequencing analyses revealed loss of heterozygosity (LOH) at the BRCA1 locus, with one patient losing the wild-type allele and the other mutated allele. This reversion mutation may cf. resistance to homologous recombination deficiency (HRD)-targeting drugs such as PARP inhibitors (PARPi) and ATM inhibitors (ATMi). Although HRDetect and CHORD analyses confirmed a strong association between the L1780P mutation and HRD, effective initially, drug resistance developed in cases with reversion mutations. These findings underscore the complexity of using HRD prediction in personalized treatment strategies for breast cancer patients with BRCA1/2 mutations, as resistance may arise in reversion cases despite high HRD scores.

ASAH1 facilitates TNBC by DUSP5 suppression-driven activation of MAP kinase pathway and represents a therapeutic vulnerability

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is prone to metastasis and therapy resistance. Owing to its aggressive nature and limited availability of targeted therapies, TNBC is associated with higher mortality as compared to other forms of breast cancer. In order to develop new therapeutic options for TNBC, we characterized the factors involved in TNBC growth and progression. Here, we demonstrate that N-acylsphingosine amidohydrolase 1 (ASAH1) is overexpressed in TNBC cells and is regulated via p53 and PI3K-AKT signaling pathways. Genetic knockdown or pharmacological inhibition of ASAH1 suppresses TNBC growth and progression. Mechanistically, ASAH1 inhibition stimulates dual-specificity phosphatase 5 (DUSP5) expression, suppressing the mitogen-activated protein kinase (MAPK) pathway. Furthermore, pharmacological cotargeting of the ASAH1 and MAPK pathways inhibits TNBC growth. Collectively, we unmasked a novel role of ASAH1 in driving TNBC and identified dual targeting of the ASAH1 and MAPK pathways as a potential new therapeutic approach for TNBC treatment.

A rat-based preclinical platform facilitating transcatheter hepatic arterial infusion in immunodeficient rats with liver xenografts of patient-derived pancreatic ductal adenocarcinoma

Liver metastases from pancreatic ductal adenocarcinoma (PDAC) are highly fatal. A rat-based patient-derived tumor xenograft (PDX) model is available for transcatheter therapy. This study aimed to create an immunodeficient rat model with liver xenografts of patient-derived primary PDAC and evaluate efficacy of hepatic arterial infusion chemotherapy with cisplatin in this model. Three patient-derived PDACs were transplanted into the livers of 21 rats each (totally, 63 rats), randomly assigned into hepatic arterial infusion, systemic venous infusion, and control groups (n = 7 each) four weeks post-implantation. Computed tomography evaluated tumor volumes before and four weeks after treatment. Post-euthanasia, resected tumor specimens underwent histopathological examination. A liver-implanted PDAC PDX rat model was established in all 63 rats, with first CT identifying all tumors. Four weeks post-treatment, arterial infusion groups exhibited significantly smaller tumor volumes than controls for all three tumors on second CT. Xenograft tumors histologically maintained adenocarcinoma features compared to original patient tumors. Ki67 expression was significantly lower in arterial infusion groups than in the other two for the three tumors, indicating reduced tumor growth in PDX rats. A liver-implanted PDAC PDX rat model was established as a rat-based preclinical platform. Arterial cisplatin infusion chemotherapy represents a potential therapy for PDAC liver metastasis.

Direct Implantation of Patient Brain Tumor Cells into Matching Locations in Mouse Brains for Patient-Derived Orthotopic Xenograft Model Development

Background: Despite multimodality therapies, the prognosis of patients with malignant brain tumors remains extremely poor. One of the major obstacles that hinders development of effective therapies is the limited availability of clinically relevant and biologically accurate (CRBA) mouse models. Methods: We have developed a freehand surgical technique that allows for rapid and safe injection of fresh human brain tumor specimens directly into the matching locations (cerebrum, cerebellum, or brainstem) in the brains of SCID mice. Results: Using this technique, we successfully developed 188 PDOX models from 408 brain tumor patient samples (both high-and low-grade) with a success rate of 72.3% in high-grade glioma, 64.2% in medulloblastoma, 50% in ATRT, 33.8% in ependymoma, and 11.6% in low-grade gliomas. Detailed characterization confirmed their replication of the histopathological and genetic abnormalities of the original patient tumors. Conclusions: The protocol is easy to follow, without a sterotactic frame, in order to generate large cohorts of tumor-bearing mice to meet the needs of biological studies and preclinical drug testing.

Anaplastic thyroid cancer spheroids as preclinical models to test therapeutics

Anaplastic thyroid cancer (ATC) is the most aggressive thyroid cancer. Despite advances in tissue culture techniques, a robust model for ATC spheroid culture is yet to be developed. In this study, we created an efficient and cost-effective 3D tumor spheroids culture system from human ATC cells and existing cell lines that better mimic patient tumors and that can enhance our understanding of in vivo treatment response. We found that patient-derived ATC cells and cell lines can readily form spheroids in culture with a unique morphology, size, and cytoskeletal organization. We observed both cohesive (dense and solid structures) and discohesive (irregularly shaped structures) spheroids within the same culture condition across different cell lines. BRAFWT ATC spheroids grew in a cohesive pattern, while BRAFV600E-mutant ATC spheroids had a discohesive organization. In the patient-derived BRAFV600E-mutant ATC spheroids, we observed both growth patterns, but mostly the discohesive type. Histologically, ATC spheroids had a similar morphology to the patient's tumor through H&E staining and proliferation marker staining. Moreover, RNA sequencing analysis revealed that the gene expression profile of tumor cells derived from the spheroids closely matched parental patient tumor-derived cells in comparison to monolayer cultures. In addition, treatment response to combined BRAF and MEK inhibition in BRAFV600E-mutant ATC spheroids exhibited a similar sensitivity to the patient clinical response. Our study provides a robust and novel ex vivo spheroid model system that can be used in both established ATC cell lines and patient-derived tumor samples to better understand the biology of ATC and to test therapeutics.

Patient-derived organoids in human cancer: a platform for fundamental research and precision medicine

Cancer is associated with a high degree of heterogeneity, encompassing both inter- and intra-tumor heterogeneity, along with considerable variability in clinical response to common treatments across patients. Conventional models for tumor research, such as in vitro cell cultures and in vivo animal models, demonstrate significant limitations that fall short of satisfying the research requisites. Patient-derived tumor organoids, which recapitulate the structures, specific functions, molecular characteristics, genomics alterations and expression profiles of primary tumors. They have been efficaciously implemented in illness portrayal, mechanism exploration, high-throughput drug screening and assessment, discovery of innovative therapeutic targets and potential compounds, and customized treatment regimen for cancer patients. In contrast to conventional models, tumor organoids offer an intuitive, dependable, and efficient in vitro research model by conserving the phenotypic, genetic diversity, and mutational attributes of the originating tumor. Nevertheless, the organoid technology also confronts the bottlenecks and challenges, such as how to comprehensively reflect intra-tumor heterogeneity, tumor microenvironment, tumor angiogenesis, reduce research costs, and establish standardized construction processes while retaining reliability. This review extensively examines the use of tumor organoid techniques in fundamental research and precision medicine. It emphasizes the importance of patient-derived tumor organoid biobanks for drug development, screening, safety evaluation, and personalized medicine. Additionally, it evaluates the application of organoid technology as an experimental tumor model to better understand the molecular mechanisms of tumor. The intent of this review is to explicate the significance of tumor organoids in cancer research and to present new avenues for the future of tumor research.

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.

Patient-Derived Xenograft Models in Cancer Research: Methodology, Applications, and Future Prospects

Patient-derived xenografts (PDXs) have emerged as a pivotal tool in translational cancer research, addressing limitations of traditional methods and facilitating improved therapeutic interventions. These models involve engrafting human primary malignant cells or tissues into immunodeficient mice, allowing for the investigation of cancer mechanobiology, validation of therapeutic targets, and preclinical assessment of treatment strategies. This chapter provides an overview of PDXs methodology and their applications in both basic cancer research and preclinical studies. Despite current limitations, ongoing advancements in humanized xenochimeric models and autologous immune cell engraftment hold promise for enhancing PDX model accuracy and relevance. As PDX models continue to refine and extend their applications, they are poised to play a pivotal role in shaping the future of translational cancer research.

Experimental models for cancer brain metastasis

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.

Small Mitochondria-Targeting Fluorophore with Multifunctional Therapeutic Activities against Prostate Cancer via the HIF1α/OATPs Pathway

Prostate cancer (PCa) is considered to be the most prevalent malignancy in males worldwide. Abiraterone is a 17α-hydroxylase/C17, 20-lyase (CYP17) inhibitor that has been approved for use in patients with prostate cancer. However, several negative aspects, such as drug resistance, toxicity, and lack of real-time monitoring of treatment responses, could appear with long-term use. Therefore, the development of anticancer agents with specific targeting to avoid side effects is imperative. Here, we used MHI-148, a type of heptamethine cyanine (HC) near-infrared fluorescence dye (NIRF), as a prototype structure to synthesize two theranostic agents, Abi-DZ-1 and Abi-783. The new compound Abi-DZ-1 retained the excellent photophysical characteristics and NIRF imaging property of MHI-148, and it could preferentially accumulate in prostate cancer cells but not in normal prostate epithelial cells via the HIF1α/organic anion-transporting polypeptides axis. NIRF imaging using Abi-DZ-1 selectively identified tumors in mice bearing PCa xenografts. Moreover, Abi-DZ-1 treatment significantly retarded the tumor growth in both a cell-derived xenograft model and a patient-derived tumor xenograft model. This finding demonstrated that Abi-DZ-1 may hold promise as a potential multifunctional theranostic agent for future tumor-targeted imaging and precision therapy. Constructing theranostic agents using the NIRF dye platform holds great promise in accurate therapy and intraoperative navigation.

Progress in the application of hydrogels in immunotherapy of gastrointestinal tumors

Gastrointestinal tumors are the most common cancers with the highest morbidity and mortality worldwide. Surgery accompanied by chemotherapy, radiotherapy and targeted therapy remains the first option for gastrointestinal tumors. However, poor specificity for tumor cells of these postoperative treatments often leads to severe side effects and poor prognosis. Tumor immunotherapy, including checkpoint blockade and tumor vaccines, has developed rapidly in recent years, showing good curative effects and minimal side effects in the treatment of gastrointestinal tumors. National Comprehensive Cancer Network guidelines recommend tumor immunotherapy as part of the treatment of gastrointestinal tumors. However, the heterogeneity of tumor cells, complicacy of the tumor microenvironment and poor tumor immunogenicity hamper the effectiveness of tumor immunotherapy. Hydrogels, defined as three-dimensional, hydrophilic, and water-insoluble polymeric networks, could significantly improve the overall response rate of immunotherapy due to their superior drug loading efficacy, controlled release and drug codelivery ability. In this article, we briefly describe the research progress made in recent years on hydrogel delivery systems in immunotherapy for gastrointestinal tumors and discuss the potential future application prospects and challenges to provide a reference for the clinical application of hydrogels in tumor immunotherapy.

Patient-derived organoids as personalized avatars and a potential immunotherapy model in cervical cancer

Cervical cancer remains a significant health issue in developing countries. However, finding a preclinical model that accurately reproduces tumor characteristics is challenging. Therefore, we established a patient-derived organoids (PDOs) biobank containing 67 cases of heterogeneous cervical cancer that mimic the histopathological and genomic characteristics of parental tumors. The in vitro response of the organoids indicated their ability to capture the radiological heterogeneity of the patients. To model individual responses to adoptive T cell therapy (ACT), we expanded tumor-infiltrating lymphocytes (TILs) ex vivo and co-cultured them with paired organoids. The PDOs-TILs co-culture system demonstrates clear responses that correspond to established immunotherapy efficiency markers like the proportion of CTLs. This study supports the potential of the PDOs platform to guide treatment in prospective interventional trials in cervical cancer.

Establishment and characterization of a non-gestational choriocarcinoma patient-derived xenograft model

BACKGROUND

Non-gestational choriocarcinoma (NGC) is a rare subtype of malignant germ cell tumour and there is no consensus on its treatment. The lack of suitable preclinical models for NGC is a challenge in drug discovery research. Patient-derived xenograft (PDX) models recapitulate the tumour microenvironment of the original cancer tissue. Therefore, they have received considerable attention for studies on rare cancer. Here, we aimed to establish a PDX model from a patient with recurrent NGC.

METHODS

Fresh NGC tumour tissue was immediately transplanted into a severely immune-deficient mouse (NOD.Cg-Prkdcscid1l2rgtm1Wjl/SzJ) and maintained for more than three in vivo passages. Subsequently, we evaluated the molecular characteristics of the PDX model using immunohistochemistry, polymerase chain reaction, and RNA sequencing. Moreover, the PDX tumours were transplanted into BALB/c nude mice, and we evaluated their sensitivity for cisplatin and methotrexate.

RESULTS

The PDX tumour maintained the morphological features of NGC. Moreover, Immunohistochemistry revealed that the human chorionic gonadotropin, cytokeratin 7, and EpCAM expression levels were similar to those in the primary tumour. Furthermore, serum human chorionic gonadotropin levels were elevated in both the primary tumour and the PDX models. Additionally, using PCR analysis with species-specific primers, we confirmed that the PDX tumour contained human genes and was derived from human tissue. Moreover, the gene expression profile of the NGC was compared with that of epithelial ovarian cancer samples and cell lines, and 568 dysregulated genes in the NGC were extracted. The expression of the dysregulated genes in PDX was significantly correlated with that in the primary tumour (R2 = 0.873, P < 0.001). Finally, we demonstrated that the PDX tumour was sensitive to cisplatin and methotrexate; therefore, its clinical response to the agents was similar to that of the primary tumour.

CONCLUSIONS

We successfully established a PDX model of NGC, to the best of our knowledge, for the first time. The established PDX retained the molecular and transcriptome characteristics of the primary tumour and can be used to predict drug effects. It may facilitate further research and the development of novel therapeutic agents for NGC.

Breast cancer organoids derived from patients: A platform for tailored drug screening

Breast cancer stands as the most prevalent and heterogeneous malignancy affecting women globally, posing a substantial health concern. Enhanced comprehension of tumor pathology and the development of novel therapeutics are pivotal for advancing breast cancer treatment. Contemporary breast cancer investigation heavily leans on in vivo models and conventional cell culture techniques. Nonetheless, these approaches often encounter high failure rates in clinical trials due to species disparities and tissue structure variations. To address this, three-dimensional cultivation of organoids, resembling organ-like structures, has emerged as a promising alternative. Organoids represent innovative in vitro models that mirror in vivo tissue microenvironments. They retain the original tumor's diversity and facilitate the expansion of tumor samples from diverse origins, facilitating the representation of varying tumor stages. Optimized breast cancer organoid models, under precise culture conditions, offer benefits including convenient sample acquisition, abbreviated cultivation durations, and genetic stability. These attributes ensure a faithful replication of in vivo traits of breast cancer cells. As intricate cellular entities boasting spatial arrangements, breast cancer organoid models harbor substantial potential in precision medicine, organ transplantation, modeling intricate diseases, gene therapy, and drug innovation. This review delivers an overview of organoid culture techniques and outlines future prospects for organoid modeling.

Introduction of Androgen Receptor Targeting shRNA Inhibits Tumor Growth in Patient-Derived Prostate Cancer Xenografts

Patient-derived xenograft (PDX) models have been established as important preclinical cancer models, overcoming some of the limitations associated with the use of cancer cell lines. The utility of prostate cancer PDX models has been limited by an inability to genetically manipulate them in vivo and difficulties sustaining PDX-derived cancer cells in culture. Viable, short-term propagation of PDX models would allow in vitro transfection with traceable reporters or manipulation of gene expression relevant to different studies within the prostate cancer field. Here, we report an organoid culture system that supports the growth of prostate cancer PDX cells in vitro and permits genetic manipulation, substantially increasing the scope to use PDXs to study the pathobiology of prostate cancer and define potential therapeutic targets. We have established a short-term PDX-derived in vitro cell culture system which enables genetic manipulation of prostate cancer PDXs LuCaP35 and BM18. Genetically manipulated cells could be re-established as viable xenografts when re-implanted subcutaneously in immunocompromised mice and were able to be serially passaged. Tumor growth of the androgen-dependent LuCaP35 PDX was significantly inhibited following depletion of the androgen receptor (AR) in vivo. Taken together, this system provides a method to generate novel preclinical models to assess the impact of controlled genetic perturbations and allows for targeting specific genes of interest in the complex biological setting of solid tumors.

Pharmacologic Ascorbate and DNMT Inhibitors Increase DUOX Expression and Peroxide-Mediated Toxicity in Pancreatic Cancer

Recent studies have demonstrated an important role for vitamin C in the epigenetic regulation of cancer-related genes via DNA demethylation by the ten-eleven translocation (TET) methylcytosine dioxygenase enzymes. DNA methyltransferase (DNMT) reverses this, increasing DNA methylation and decreasing gene expression. Dual oxidase (DUOX) enzymes produce hydrogen peroxide (H2O2) in normal pancreatic tissue but are silenced in pancreatic cancer (PDAC). Treatment of PDAC with pharmacologic ascorbate (P-AscH-, intravenous, high dose vitamin C) increases DUOX expression. We hypothesized that inhibiting DNMT may act synergistically with P-AscH- to further increase DUOX expression and cytotoxicity of PDAC. PDAC cells demonstrated dose-dependent increases in DUOX mRNA and protein expression when treated with DNMT inhibitors. PDAC cells treated with P-AscH- + DNMT inhibitors demonstrated increased DUOX expression, increased intracellular oxidation, and increased cytotoxicity in vitro and in vivo compared to either treatment alone. These findings suggest a potential therapeutic, epigenetic mechanism to treat PDAC.

L858R emerges as a potential biomarker predicting response of lung cancer models to anti-EGFR antibodies: Comparison of osimertinib vs. cetuximab

EGFR-specific tyrosine kinase inhibitors (TKIs), especially osimertinib, have changed lung cancer therapy, but secondary mutations confer drug resistance. Because other EGFR mutations promote dimerization-independent active conformations but L858R strictly depends on receptor dimerization, we herein evaluate the therapeutic potential of dimerization-inhibitory monoclonal antibodies (mAbs), including cetuximab. This mAb reduces viability of cells expressing L858R-EGFR and blocks the FOXM1-aurora survival pathway, but other mutants show no responses. Unlike TKI-treated patient-derived xenografts, which relapse post osimertinib treatment, cetuximab completely prevents relapses of L858R+ tumors. We report that osimertinib's inferiority associates with induction of mutagenic reactive oxygen species, whereas cetuximab's superiority is due to downregulation of adaptive survival pathways (e.g., HER2) and avoidance of mutation-prone mechanisms that engage AXL, RAD18, and the proliferating cell nuclear antigen. These results identify L858R as a predictive biomarker, which may pave the way for relapse-free mAb monotherapy relevant to a large fraction of patients with lung cancer.

Models to study CTCs and CTC culture methods

The vast majority of cancer-related deaths are due to the presence of disseminated disease. Understanding the metastatic process is key to achieving a reduction in cancer mortality. Particularly, there is a need to understand the molecular mechanisms that drive cancer metastasis, which will allow the identification of curative treatments for metastatic cancers. Liquid biopsies have arisen as a minimally invasive approach to gain insights into the biology of metastasis. Circulating tumour cells (CTCs), shed to the circulation from the primary tumour or metastatic lesions, are a key component of liquid biopsy. As metastatic precursors, CTCs hold the potential to unravel the mechanisms involved in metastasis formation as well as new therapeutic strategies for treating metastatic disease. However, the complex biology of CTCs together with their low frequency in circulation are factors hampering an in-depth mechanistic investigation of the metastatic process. To overcome these problems, CTC-derived models, including CTC-derived xenograft (CDX) and CTC-derived ex vivo cultures, in combination with more traditional in vivo models of metastasis, have emerged as powerful tools to investigate the biological features of CTCs facilitating cancer metastasis and uncover new therapeutic opportunities. In this chapter, we provide an up to date view of the diverse models used in different cancers to study the biology of CTCs, and of the methods developed for CTC culture and expansion, in vivo and ex vivo. We also report some of the main challenges and limitations that these models are facing.

Autologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment

BACKGROUND

Interactions between immune and tumor cells are critical to determining cancer progression and response. In addition, preclinical prediction of immune-related drug efficacy is limited by interspecies differences between human and mouse, as well as inter-person germline and somatic variation. To address these gaps, we developed an autologous system that models the tumor microenvironment (TME) from individual patients with solid tumors.

METHOD

With patient-derived bone marrow hematopoietic stem and progenitor cells (HSPCs), we engrafted a patient's hematopoietic system in MISTRG6 mice, followed by transfer of patient-derived xenograft (PDX) tissue, providing a fully genetically matched model to recapitulate the individual's TME. We used this system to prospectively study tumor-immune interactions in patients with solid tumor.

RESULTS

Autologous PDX mice generated innate and adaptive immune populations; these cells populated the TME; and tumors from autologously engrafted mice grew larger than tumors from non-engrafted littermate controls. Single-cell transcriptomics revealed a prominent vascular endothelial growth factor A (VEGFA) signature in TME myeloid cells, and inhibition of human VEGF-A abrogated enhanced growth.

CONCLUSIONS

Humanization of the interleukin 6 locus in MISTRG6 mice enhances HSPC engraftment, making it feasible to model tumor-immune interactions in an autologous manner from a bedside bone marrow aspirate. The TME from these autologous tumors display hallmarks of the human TME including innate and adaptive immune activation and provide a platform for preclinical drug testing.

Murine models to study human NK cells in human solid tumors

Since the first studies, the mouse models have provided crucial support for the most important discoveries on NK cells, on their development, function, and circulation within normal and tumor tissues. Murine tumor models were initially set to study murine NK cells, then, ever more sophisticated human-in-mice models have been developed to investigate the behavior of human NK cells and minimize the interferences from the murine environment. This review presents an overview of the models that have been used along time to study NK cells, focusing on the most popular NOG and NSG models, which work as recipients for the preparation of human-in-mice tumor models, the study of transferred human NK cells, and the evaluation of various enhancers of human NK cell function, including cytokines and chimeric molecules. Finally, an overview of the next generation humanized mice is also provided along with a discussion on how traditional and innovative in-vivo and in-vitro approaches could be integrated to optimize effective pre-clinical studies.

Prediction of pathological response grading for esophageal squamous carcinoma after neoadjuvant chemoradiotherapy based on MRI imaging using PDX

Introduction

To confirm the efficacy of magnetic resonance-diffusion weighted imaging (MR-DWI) in esophageal squamous cell carcinoma (ESCC) early pathological response prediction and assessment to neoadjuvant chemoradiotherapy (nCRT) using patient-derived xenografts (PDXs).

Methods

PDX-bearing mice were randomly divided into two groups: the experimental group receiving cisplatin combined with radiotherapy, whereas the control group receiving normal saline. MRI scans were performed in treatment groups in the before, middle, and end of treatment. The correlations between tumor volumes, ADC values and tumor pathological response at different time nodes were explored. Then, expression of proliferation marker and apoptotic marker were detected using immunohistochemistry, and apoptosis rate was detected by TUNEL assay to further verify the results observed in the PDX models.

Results

The ADC values of the experimental group were significantly higher than the control group in the both middle and end stage of treatment (all P< 0.001), however, significant difference was only observed in tumor volume at the end stage of treatment (P< 0.001). Furthermore, the △ADC_mid-pre in our study may able to identify tumors with or without pCR to nCRT at an early stage, due to these changes were prior to the changes of tumor volume after treatment. Finally, TUNEL results also showed that the apoptosis rate of the experiment groups increased the most in the middle stage of treatment, especially the groups with pCR, but the highest apoptosis rate occurred in the end of the treatment. Further, the two PDX models with pCR exhibited the highest levels of apoptotic marker (Bax), and lowest levels of proliferation marker (PCNA and Ki-67) in the both middle and end stage of the treatment.

Conclusions

ADC values could be used to determine the tumor's response to nCRT, especially in the middle stages of treatment and before the tumor tissue morphology changes, and further, the ADC values were consistent with the potential biomarkers reflecting histopathological changes. Therefore, we suggest that radiation oncologists could refer to the ADC values in the middle stages of treatment when predicting the tumor histopathological response to n CRT in patients with ESCC.

Biodynamic prediction of neoadjuvant chemotherapy response: Results from a prospective multicenter study of predictive accuracy among muscle-invasive bladder cancer patients

BACKGROUND

Biodynamic signatures (temporal patterns of microscopic motion within a 3-dimensional tumor explant) offer phenomic biomarkers that are highly predictive for therapeutic response.

OBJECTIVE

By utilizing motility contrast tomography, which provides a simple, fast assessment of motion patterns in living tissue, we evaluated the predictive accuracy of a biodynamic drug response classifier in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC).

DESIGN, SETTING, AND PARTICIPANTS

One hundred five consecutive bladder cancer patients suspected of having MIBC were screened in a multi-institutional prospective observational study (NCT03739177) from July 2018 to June 2020, of whom, 30 completed NAC and radical cystectomy.

INTERVENTION(S)

Biodynamic signatures from treatment-naïve fresh bladder tumor specimens obtained after transurethral resection were measured in living tumor fragments challenged by standard-of-care cytotoxins. Patients received gemcitabine and cisplatin or dose-dense methotrexate, vinblastine, doxorubicin, and cisplatin per institutional guidelines and were followed through radical cystectomy.

OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS

A 4-level classifier was developed to predict pathologic complete response (pCR) vs. incomplete response utilizing a one-left-out cross-validation protocol to minimize over-fitting. Area under the curve evaluated predictive utility.

RESULTS

Thirty percent (9 of 30) achieved pCR. Utilizing the 4-level classifier, biodynamically "favored" (scoring ≥ 3) and "strongly favored" (scoring 4) regimens accurately predicted pCR at rates of 66.7% (4 of 6 patients) and 100% (4 of 4 patients), respectively. Biodynamically "favored" scores predicted pCR with 88% sensitivity and 95% negative predictive value, P < 0.0001. Only 5.0% (1 of 20 patients) achieved pCR from regimens scoring 1 or 2, indicating poor to no response from NAC. Area under the receiver operating curve was 96% (95% Confidence Interval: 79%-99%, P < 0.0001). Future direction involves validating this model prospectively.

PRINCIPAL CONCLUSIONS

Biodynamic scoring accurately predicts response in MIBC patients receiving NAC and holds promise to substantially improve the scope of appropriate management intervention.

Characterization of 3D-Bioprinted In Vitro Lung Cancer Models Using RNA-Sequencing Techniques

OBJECTIVE

To construct an in vitro lung cancer model using 3D bioprinting and evaluate the feasibility of the model. Transcriptome sequencing was used to compare the differential genes and functions of 2D and 3D lung cancer cells.

METHODS

1. A549 cells were mixed with sodium alginate/gelatine/fibrinogen as 3D-printed biological ink to construct a hydrogel scaffold for the in vitro model of lung cancer; 2. A hydrogel scaffold was printed using a extrusion 3D bioprinter; 3. The printed lung cancer model was evaluated in vitro; and 4. A549 cells cultured in 2D and 3D tumour models in vitro were collected, and RNA-seq conducted bioinformatics analysis.

RESULTS

1. The in vitro lung cancer model printed using 3D-bioprinting technology was a porous microstructure model, suitable for the survival of A549 cells. Compared with the 2D cell-line model, the 3D model is closer to the fundamental human growth environment; 2. There was no significant difference in cell survival rate between the 2D and 3D groups; 3. In the cell proliferation rate measurement, it was found that the cells in the 2D group had a speedy growth rate in the first five days, but after five days, the growth rate slowed down. Cell proliferation showed a declining process after the ninth day of cell culture. However, cells in the 3D group showed a slow growth process at the beginning, and the growth rate reached a peak on the 12th day. Then, the growth rate showed a downward trend; and 4. RNA-seq compared A549 cells from 2D and 3D lung cancer models. A total of 3112 genes were differentially expressed, including 1189 up-regulated and 1923 down-regulated genes, with p-value ≤ 0.05 and |Log2Ratio| ≥ 1 as screening conditions. After functional enrichment analysis of differential genes, these differential genes affect the biological regulation of A549 cells, thus promoting lung cancer progression.

CONCLUSION

This study uses 3D-bioprinting technology to construct a tumour model of lung cancer that can grow sustainably in vitro. Three-dimensional bioprinting may provide a new research platform for studying the lung cancer TME mechanism and anticancer drug screening.

Recent Advancement in Breast Cancer Research: Insights from Model Organisms-Mouse Models to Zebrafish

Animal models have been utilized for decades to investigate the causes of human diseases and provide platforms for testing novel therapies. Indeed, breakthrough advances in genetically engineered mouse (GEM) models and xenograft transplantation technologies have dramatically benefited in elucidating the mechanisms underlying the pathogenesis of multiple diseases, including cancer. The currently available GEM models have been employed to assess specific genetic changes that underlay many features of carcinogenesis, including variations in tumor cell proliferation, apoptosis, invasion, metastasis, angiogenesis, and drug resistance. In addition, mice models render it easier to locate tumor biomarkers for the recognition, prognosis, and surveillance of cancer progression and recurrence. Furthermore, the patient-derived xenograft (PDX) model, which involves the direct surgical transfer of fresh human tumor samples to immunodeficient mice, has contributed significantly to advancing the field of drug discovery and therapeutics. Here, we provide a synopsis of mouse and zebrafish models used in cancer research as well as an interdisciplinary 'Team Medicine' approach that has not only accelerated our understanding of varied aspects of carcinogenesis but has also been instrumental in developing novel therapeutic strategies.

Organoid models derived from patients with malignant phyllodes tumor of the breast

PURPOSE

Phyllodes tumor of the breast is a kind of rare neoplasm, which accounts for less than 1% of all breast tumors. Malignant phyllodes tumor (MPT) is the highest risk subtype of phyllodes tumor, and is characterized by the tendency of local recurrence and distant metastasis. The prediction of prognosis and the individual therapy for MPT is still challenging. It's urgent to develop a new reliable in vitro preclinical model in order to understand this disease better and to explore appropriate anticancer drugs for individual patients.

METHODS

Two surgically resected MPT specimens were processed for organoid establishment. MPT organoids were subsequently subjected to H&E staining, immunohistochemical analysis and drug screening, respectively.

RESULTS

We successfully established two organoid lines from different patients with MPT. The MPT organoids can well retain the histological features and capture the marker expression in original tumor tissues, including p63, vimentin, Bcl-2, CD34, c-Kit, and Ki-67, even after a long-term culture. The dose titration tests of eight typical chemotherapeutic drugs (paclitaxel, docetaxel, vincristine, doxorubicin, cisplatin, gemcitabine, cyclophosphamide, ifosfamide) on the two MPT organoid lines showed patient-specific drug responses and varying IC₅₀ values. Of all the drugs, doxorubicin and gemcitabine showed the best anti-tumor effect on the two organoid lines.

CONCLUSION

Organoids derived from MPT may be a novel preclinical model for testing personalized therapies for patients with MPT.

Establishment of humanized mice and its application progress in cancer immunotherapy

The current high prevalence of malignant tumors has attracted considerable attention, and treating advanced malignancies is becoming increasingly difficult. Although immunotherapy is a hopeful alternative, it is effective in only a few people. Thus, development of preclinical animal models is needed. Humanized xenotransplantation mouse models can help with selecting treatment protocols, evaluating curative effects and assessing prognosis. This review discusses the establishment of humanized mouse models and their application prospects in cancer immunotherapy to identify tailored therapies for individual patients.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Patient-derived models: Promising tools for accelerating the clinical translation of breast cancer research findings

Breast cancer has become the highest incidence of cancer in women. It was extensively and deeply studied by biologists and medical workers worldwide. However, the meaningful results in lab researches cannot be realized in clinical, and a part of new drugs in clinical experiments do not obtain as good results as the preclinical researches. It is urgently that promote a kind of breast cancer research models that can get study results closer to the physiological condition of the human body. Patient-derived models (PDMs) originating from clinical tumor, contain primary elements of tumor and maintain key clinical features of tumor. So they are promising research models to facilitate laboratory researches translate to clinical application, and predict the treatment outcome of patients. In this review, we summarize the establishment of PDMs of breast cancer, reviewed the application of PDMs in clinical translational researches and personalized precision medicine with breast cancer as an example, to improve the understanding of PDMs among researchers and clinician, facilitate them to use PDMs on a large scale of breast cancer researches and promote the clinical translation of laboratory research and new drug development.

A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation

Adaptive therapy is a dynamic cancer treatment protocol that updates (or 'adapts') treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific dose modulation or dose timing. Adaptive therapy maintains high levels of tumor burden to benefit from the competitive suppression of treatment-sensitive subpopulations on treatment-resistant subpopulations. This evolution-based approach to cancer treatment has been integrated into several ongoing or planned clinical trials, including treatment of metastatic castrate resistant prostate cancer, ovarian cancer, and BRAF-mutant melanoma. In the previous few decades, experimental and clinical investigation of adaptive therapy has progressed synergistically with mathematical and computational modeling. In this work, we discuss 11 open questions in cancer adaptive therapy mathematical modeling. The questions are split into three sections: (1) integrating the appropriate components into mathematical models (2) design and validation of dosing protocols, and (3) challenges and opportunities in clinical translation.

Assessment of Drug Susceptibility for Patient-Derived Tumor Models through Lactate Biosensing and Machine Learning

A patient-derived tumor model (PDM) is a practical tool to rapidly screen chemotherapeutics for individual patients. The evaluation method of cell viability directly determines the application of PDMs for drug susceptibility testing. As one of the metabolites of "glycosis", the lactate content was used to evaluate cell viability, but these assays were not specific for tumor cells. Based on the "Warburg effect", wherein tumor cells preferentially rely on "aerobic glycolysis" to produce lactate instead of pyruvate in "anaerobic glycolysis" of normal cells, we reported a gold lactate sensor (GLS) to estimate the cell viability of PDMs in drug susceptibility testing. It demonstrated high consistency between the GLS and commercial cell viability assay. Unlike either imaging or cell viability assay, the GLS characterizes the cell viability, enables dynamic monitoring, and distinguishes tumor cells from other cells. Moreover, machine learning (ML) was employed to perform a multi-index assessment for drug susceptibility of PDMs, which proved to be accurate and practical for clinical application. Therefore, the GLS provides an ideal drug susceptibility testing tool for individualized medicine.

A novel xenograft model of human hepatocellular carcinoma in immunocompetent mice based on the microcarrier-6

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that threaten human health; thus, the establishment of an animal model with clinical features similar to human hepatocellular carcinoma is of important practical significance.

METHODS

Taking advantage of the novel microcarrier-6, human HCC cells were injected into immunocompetent mice to establish a novel human HCC patient-derived xenograft (PDX) model. Primary HCC cells were isolated from fresh hepatocellular carcinoma tissues, which were subsequently co-cultured with microcarrier-6 to construct a three-dimensional tumor cell culture model in vitro. The HCC-microcarrier complex was implanted into mice by subcutaneous inoculation, and the tumor formation time, tumor formation rate, and pathological manifestation were recorded. Changes of immune parameters in mice were detected by flow cytometry.

RESULTS

The success rate was 60% (6/10) in the establishment of hepatocellular carcinoma PDX mouse model, and the total tumor formation rate of the tumor-forming model is 90-100%. H&E staining and immunohistochemical experiments indicate that the model well retained the characteristics of the primary tumor. Interestingly, M2 macrophages in tumor-bearing mice increased significantly, and the levels of CD4⁺ T cells were significantly reduced.

CONCLUSIONS

Through the application of the microcarrier-6 in immunocompetent mice, we successfully established a novel human HCC PDX model, which can be used to better study and further elucidate the occurrence and pathogenic mechanism of HCC, improve the predictability of toxicity and drug sensitivity in HCC.

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.

Induction of pancreatic neoplasia in the KRAS/TP53 Oncopig

The 5-year survival of pancreatic cancer (PC) remains low. Murine models may not adequately mimic human PC and can be too small for medical device development. A large-animal PC model could address these issues. We induced and characterized pancreatic tumors in Oncopigs (transgenic swine containing KRASG12D and TP53R167H). The oncopigs underwent injection of adenovirus expressing Cre recombinase (AdCre) into one of the main pancreatic ducts. Resultant tumors were characterized by histology, cytokine expression, exome sequencing and transcriptome analysis. Ten of 14 Oncopigs (71%) had gross tumor within 3 weeks. At necropsy, all of these subjects had gastric outlet obstruction secondary to pancreatic tumor and phlegmon. Oncopigs with injections without Cre recombinase and wild-type pigs with AdCre injection did not show notable effect. Exome and transcriptome analysis of the porcine pancreatic tumors revealed similarity to the molecular signatures and pathways of human PC. Although further optimization and validation of this porcine PC model would be beneficial, it is anticipated that this model will be useful for focused research and development of diagnostic and therapeutic technologies for PC. This article has an associated First Person interview with the joint first authors of the paper.

Morpho-functional analysis of patient-derived xenografts reveals differential impact of gastric cancer and chemotherapy on the tumor ecosystem, affecting immune check point, metabolism, and sarcopenia

OBJECTIVES

Gastric cancer (GC) is an aggressive disease due to late diagnosis resulting from the lack of easy diagnostic tools, resistances toward immunotherapy (due to low PD-L1 expression), or chemotherapies (due to p53 mutations), and comorbidity factors, notably muscle atrophy. To improve our understanding of this complex pathology, we established patient-derived xenograft (PDX) models and characterized the tumor ecosystem using a morpho-functional approach combining high-resolution imaging with molecular analyses, regarding the expression of relevant therapeutic biomarkers and the presence of muscle atrophy.

MATERIALS AND METHODS

GC tissues samples were implanted in nude mice. Established PDX, treated with cisplatin or not, were imaged by magnetic resonance imaging (MRI) and analyzed for the expression of relevant biomarkers (p53, PD-L1, PD-1, HER-2, CDX2, CAIX, CD31, a-SAM) and by transcriptomics.

RESULTS

Three well-differentiated, one moderately and one poorly differentiated adenocarcinomas were established. All retained the architectural and histological features of their primary tumors. MRI allowed in-real-time evaluation of differences between PDX, in terms of substructure, post-therapeutic changes, and muscle atrophy. Immunohistochemistry showed differential expression of p53, HER-2, CDX2, a-SAM, PD-L1, PD-1, CAIX, and CD31 between models and upon cisplatin treatment. Transcriptomics revealed treatment-induced hypoxia and metabolic reprograming in the tumor microenvironment.

CONCLUSION

Our PDX models are representative for the heterogeneity and complexity of human tumors, with differences in structure, histology, muscle atrophy, and the different biomarkers making them valuable for the analyses of the impact of platinum drugs or new therapies on the tumor and its microenvironment.

Advances in Brain Metastasis Models

To obtain achievements in addressing the clinical challenges of brain metastasis, we need a clear understanding of its biological mechanisms. Brain metastasis research is challenged by many practical scientific barriers. Depending on the purpose of the study, experimental brain metastasis models in vivo can be used. It is now possible to re-create the architecture and physiology of human organs. Human organoids provide unique opportunities for the study of human disease and complement animal models. The translation of experimental findings to clinical application has several barriers in the development of treatment for brain metastasis. A variety of models have provided significant contributions to the knowledge of brain metastasis pathology and remain pivotal tools for examining novel therapeutic strategies.