Patient-Derived Xenograft Models of Non-Small Cell Lung Cancer and Their Potential Utility in Personalized Medicine

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.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Human patient derived organoids: an emerging precision medicine model for gastrointestinal cancer research

Gastrointestinal cancers account for approximately one-third of the total global cancer incidence and mortality with a poor prognosis. It is one of the leading causes of cancer-related deaths worldwide. Most of these diseases lack effective treatment, occurring as a result of inappropriate models to develop safe and potent therapies. As a novel preclinical model, tumor patient-derived organoids (PDOs), can be established from patients' tumor tissue and cultured in the laboratory in 3D architectures. This 3D model can not only highly simulate and preserve key biological characteristics of the source tumor tissue in vitro but also reproduce the in vivo tumor microenvironment through co-culture. Our review provided an overview of the different in vitro models in current tumor research, the derivation of cells in PDO models, and the application of PDO model technology in gastrointestinal cancers, particularly the applications in combination with CRISPR/Cas9 gene editing technology, tumor microenvironment simulation, drug screening, drug development, and personalized medicine. It also elucidates the ethical status quo of organoid research and the current challenges encountered in clinical research, and offers a forward-looking assessment of the potential paths for clinical organoid research advancement.

Ex vivo drug testing of patient-derived lung organoids to predict treatment responses for personalized medicine

Lung cancer is the leading cause of global cancer-related mortality resulting in ∼ 1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or bio-banked sections and/or biopsies, pleural effusions and PDX mouse models. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and/or immunotherapy. PDOs consistently recapitulated the genomic alterations and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remain, PDOs showed great promise in the screening of novel therapy drugs. With the technical advances of high throughput, tumor-on-chip, and combined microenvironment, the drug screening process using PDOs will enhance precision care of lung cancer patients.

Fluid-Dynamic Culture of Tumour and Immune Cells for More Predictive Infiltration Studies and Immunotherapy Drug Screening

Immunotherapies represent one of the current most promising challenges in cancer treatment. They are based on the boost of natural immune responses, aimed at cancer eradication. However, the success of immunotherapeutic approaches strictly depends on the interaction between immune cells and cancer cells. Preclinical drug tests currently available are poor in fully predicting the actual safety and efficacy of immunotherapeutic treatments under development. Indeed, conventional 2D cell culture underrepresents the complexity of the tumour microenvironment, while in vivo animal models lack in mimicking the human immune cell responses. In this context, predictability, reliability, and complete immune compatibility still represent challenges to overcome. For this aim, novel 3D, fully humanized in vitro cancer tissue models have been recently optimized by adopting emerging technologies, such as organ-on-chips (OOC) and 3D cancer cell-laden hydrogels. In particular, a novel multi-in vitro organ (MIVO) OOC platform has been recently adopted to culture 3D clinically relevant size cancer tissues under proper physiological culture conditions to investigate anti-cancer treatments and immune-tumour cell crosstalk.The proposed immune-tumour OOC-based model offers a potential tool for accurately modelling human immune-related diseases and effectively assessing immunotherapy efficacy, finally offering promising experimental approaches for personalized medicine.

Progress in building clinically relevant patient-derived tumor xenograft models for cancer research

Patient-derived tumor xenograft (PDX) models, a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice, have emerged as a pivotal approach in translational research, particularly in advancing precision medicine. As the first stage of PDX development, the patient-derived orthotopic xenograft (PDOX) models implant tumor tissue in mice in the corresponding anatomical locations of the patient. The PDOX models have several advantages, including high fidelity to the original tumor, heightened drug sensitivity, and an elevated rate of successful transplantation. However, the PDOX models present significant challenges, requiring advanced surgical techniques and resource-intensive imaging technologies, which limit its application. And then, the humanized mouse models, as well as the zebrafish models, were developed. Humanized mouse models contain a human immune environment resembling the tumor and immune system interplay. The humanized mouse models are a hot topic in PDX model research. Regarding zebrafish patient-derived tumor xenografts (zPDX) and patient-derived organoids (PDO) as promising models for studying cancer and drug discovery, zPDX models are used to transplant tumors into zebrafish as novel personalized medical animal models with the advantage of reducing patient waiting time. PDO models provide a cost-effective approach for drug testing that replicates the in vivo environment and preserves important tumor-related information for patients. The present review highlights the functional characteristics of each new phase of PDX and provides insights into the challenges and prospective developments in this rapidly evolving field.

Application of three-dimensional cell culture technology in screening anticancer drugs

The drug development process involves a variety of drug activity evaluations, which can determine drug efficacy, strictly analyze the biological indicators after the drug action, and use these indicators as the preclinical drug evaluation criteria. At present, most of the screening of preclinical anticancer drugs mainly relies on traditional 2D cell culture. However, this traditional technology cannot simulate the tumor microenvironment in vivo, let alone reflect the characteristics of solid tumors in vivo, and has a relatively poor ability to predict drug activity. 3D cell culture is a technology between 2D cell culture and animal experiments, which can better reflect the biological state in vivo and reduce the consumption of animal experiments. 3D cell culture can link the individual study of cells with the study of the whole organism, reproduce in vitro the biological phenotype of cells in vivo more greatly, and thus predict the activity and resistance of anti-tumor drugs more accurately. In this paper, the common techniques of 3D cell culture are discussed, with emphasis on its main advantages and application in the evaluation of anti-tumor resistance, which can provide strategies for the screening of anti-tumor drugs.

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.

Organoids: The current status and biomedical applications

Organoids are three-dimensional (3D) miniaturized versions of organs or tissues that are derived from cells with stem potential and can self-organize and differentiate into 3D cell masses, recapitulating the morphology and functions of their in vivo counterparts. Organoid culture is an emerging 3D culture technology, and organoids derived from various organs and tissues, such as the brain, lung, heart, liver, and kidney, have been generated. Compared with traditional bidimensional culture, organoid culture systems have the unique advantage of conserving parental gene expression and mutation characteristics, as well as long-term maintenance of the function and biological characteristics of the parental cells in vitro. All these features of organoids open up new opportunities for drug discovery, large-scale drug screening, and precision medicine. Another major application of organoids is disease modeling, and especially various hereditary diseases that are difficult to model in vitro have been modeled with organoids by combining genome editing technologies. Herein, we introduce the development and current advances in the organoid technology field. We focus on the applications of organoids in basic biology and clinical research, and also highlight their limitations and future perspectives. We hope that this review can provide a valuable reference for the developments and applications of organoids.

Patient-derived organoids of lung cancer based on organoids-on-a-chip: enhancing clinical and translational applications

Lung cancer is one of the most common malignant tumors worldwide, with high morbidity and mortality due to significant individual characteristics and genetic heterogeneity. Personalized treatment is necessary to improve the overall survival rate of the patients. In recent years, the development of patient-derived organoids (PDOs) enables lung cancer diseases to be simulated in the real world, and closely reflects the pathophysiological characteristics of natural tumor occurrence and metastasis, highlighting their great potential in biomedical applications, translational medicine, and personalized treatment. However, the inherent defects of traditional organoids, such as poor stability, the tumor microenvironment with simple components and low throughput, limit their further clinical transformation and applications. In this review, we summarized the developments and applications of lung cancer PDOs and discussed the limitations of traditional PDOs in clinical transformation. Herein, we looked into the future and proposed that organoids-on-a-chip based on microfluidic technology are advantageous for personalized drug screening. In addition, combined with recent advances in lung cancer research, we explored the translational value and future development direction of organoids-on-a-chip in the precision treatment of lung cancer.

Protocol for cell-type-specific tissue reconstruction in the murine lung fibrogenic microenvironment

Pulmonary fibrosis is a process characterized by epithelial injury and fibroblast activation. It is also well recognized as a predisposition to lung cancer. Here, we present a protocol to establish an in vivo model to evaluate the dynamics of alveolar epithelial type 2 cells and lung cancer cells in the context of the lung fibrogenic microenvironment. Utilizing the cell transfer technique, we detail a basis for therapeutic approaches in pulmonary fibrosis and tools for precision medicine against lung cancer. For complete details on the use and execution of this protocol, please refer to Miyata et al. (2022).1.

Impacts of Environmental Pollution on Brain Tumorigenesis

Pollutants consist of several components, known as direct or indirect mutagens, that can be associated with the risk of tumorigenesis. The increased incidence of brain tumors, observed more frequently in industrialized countries, has generated a deeper interest in examining different pollutants that could be found in food, air, or water supply. These compounds, due to their chemical nature, alter the activity of biological molecules naturally found in the body. The bioaccumulation leads to harmful effects for humans, increasing the risk of the onset of several pathologies, including cancer. Environmental components often combine with other risk factors, such as the individual genetic component, which increases the chance of developing cancer. The objective of this review is to discuss the impact of environmental carcinogens on modulating the risk of brain tumorigenesis, focusing our attention on certain categories of pollutants and their sources.

Tumor organoid biobank-new platform for medical research

Organoids are a new type of 3D model for tumor research, which makes up for the shortcomings of cell lines and xenograft models, and promotes the development of personalized precision medicine. Long-term culture, expansion and storage of organoids provide the necessary conditions for the establishment of biobanks. Biobanks standardize the collection and preservation of normal or pathological specimens, as well as related clinical information. The tumor organoid biobank has a good quality control system, which is conducive to the clinical transformation and large-scale application of tumor organoids, such as disease modeling, new drug development and high-throughput drug screening. This article summarized the common tumor types of patient-derived organoid (PDO) biobanks and the necessary information for biobank construction, such as the number of organoids, morphology, success rate of culture and resuscitation, pathological types. In our results, we found that patient-derived tumor organoid (PDTO) biobanks were being established more and more, with the Netherlands, the United States, and China establishing the most. Biobanks of colorectal, pancreas, breast, glioma, and bladder cancers were established more, which reflected the relative maturity of culture techniques for these tumors. In addition, we provided insights on the precautions and future development direction of PDTO biobank building.

Inhibition of Mtorc1/2 and DNA-PK via CC-115 Synergizes with Carboplatin and Paclitaxel in Lung Squamous Cell Carcinoma

Only a small percentage (<1%) of patients with late-stage lung squamous cell carcinoma (LUSC) are eligible for targeted therapy. Because PI3K/AKT/mTOR signaling, particularly Phosphatidylinositol 3-kinase CA (PIK3CA), is dysregulated in two-thirds of LUSC, and DNA damage response pathways are enriched in LUSC, we tested whether CC-115, a dual mTORC1/2 and DNA-PK inhibitor, sensitizes LUSC to chemotherapy. We demonstrate that CC-115 synergizes with carboplatin in six of 14 NSCLC cell lines, primarily PIK3CA-mutant LUSC. Synergy was more common in cell lines that had decreased basal levels of activated AKT and DNA-PK, evidenced by reduced P-S473-AKT, P-Th308-AKT, and P-S2056-DNA-PKcs. CC-115 sensitized LUSC to carboplatin by inhibiting chemotherapy-induced AKT activation and maintaining apoptosis, particularly in PIK3CA-mutant cells lacking wild-type (WT) TP53. In addition, pathway analysis revealed that enrichments in the IFNα and IFNγ pathways were significantly associated with synergy. In multiple LUSC patient-derived xenograft and cell line tumor models, CC-115 plus platinum-based doublet chemotherapy significantly inhibited tumor growth and increased overall survival as compared with either treatment alone at clinically relevant dosing schedules. IHC and immunoblot analysis of CC-115-treated tumors demonstrated decreased P-Th308-AKT, P-S473-AKT, P-S235/236-S6, and P-S2056-DNA-PKcs, showing direct pharmacodynamic evidence of inhibited PI3K/AKT/mTOR signaling cascades. Because PI3K pathway and DNA-PK inhibitors have shown toxicity in clinical trials, we assessed toxicity by examining weight and numerous organs in PRKDC-WT mice, which demonstrated that the combination treatment does not exacerbate the clinically accepted side effects of standard-of-care chemotherapy. This preclinical study provides strong support for the further investigation of CC-115 plus chemotherapy in LUSC.

Validation of a Patient-Derived Xenograft Model for Cervical Cancer Based on Genomic and Phenotypic Characterization

Simple Summary

The rate of total tumor engraftment of patient-derived xenografts is 50% in cervical cancer. These cancers retain their histopathological characteristics. The gene mutations and expression patterns associated with carcinogenesis and infiltration and the expression levels of genes in extracellular vesicles released from the tumors are similar between patient-derived xenograft models and primary tumors. Patient-derived xenograft models of cervical cancer could be potentially useful tools for translational research.

Abstract

Patient-derived xenograft (PDX) models are useful tools for preclinical drug evaluation, biomarker identification, and personalized medicine strategies, and can be developed by the heterotopic or orthotopic grafting of surgically resected tumors into immunodeficient mice. We report the PDX models of cervical cancer and demonstrate the similarities among original and different generations of PDX tumors. Fresh tumor tissues collected from 22 patients with primary cervical cancer were engrafted subcutaneously into NOD.CB17-PrkdcSCID/J mice. Histological and immunohistochemical analyses were performed to compare primary and different generations of PDX tumors. DNA and RNA sequencing were performed to verify the similarity between the genetic profiles of primary and PDX tumors. Total RNA in extracellular vesicles (EVs) released from primary and PDX tumors was also quantified to evaluate gene expression. The total tumor engraftment rate was 50%. Histologically, no major differences were observed between the original and PDX tumors. Most of the gene mutations and expression patterns related to carcinogenesis and infiltration were similar between the primary tumor and xenograft. Most genes associated with carcinogenesis and infiltration showed similar expression levels in the primary tumor and xenograft EVs. Therefore, compared with primary tumors, PDX models could be potentially more useful for translational research.

Disclosing Potential Key Genes, Therapeutic Targets and Agents for Non-Small Cell Lung Cancer: Evidence from Integrative Bioinformatics Analysis

Non-small-cell lung cancer (NSCLC) is considered as one of the malignant cancers that causes premature death. The present study aimed to identify a few potential novel genes highlighting their functions, pathways, and regulators for diagnosis, prognosis, and therapies of NSCLC by using the integrated bioinformatics approaches. At first, we picked out 1943 DEGs between NSCLC and control samples by using the statistical LIMMA approach. Then we selected 11 DEGs (CDK1, EGFR, FYN, UBC, MYC, CCNB1, FOS, RHOB, CDC6, CDC20, and CHEK1) as the hub-DEGs (potential key genes) by the protein–protein interaction network analysis of DEGs. The DEGs and hub-DEGs regulatory network analysis commonly revealed four transcription factors (FOXC1, GATA2, YY1, and NFIC) and five miRNAs (miR-335-5p, miR-26b-5p, miR-92a-3p, miR-155-5p, and miR-16-5p) as the key transcriptional and post-transcriptional regulators of DEGs as well as hub-DEGs. We also disclosed the pathogenetic processes of NSCLC by investigating the biological processes, molecular function, cellular components, and KEGG pathways of DEGs. The multivariate survival probability curves based on the expression of hub-DEGs in the SurvExpress web-tool and database showed the significant differences between the low- and high-risk groups, which indicates strong prognostic power of hub-DEGs. Then, we explored top-ranked 5-hub-DEGs-guided repurposable drugs based on the Connectivity Map (CMap) database. Out of the selected drugs, we validated six FDA-approved launched drugs (Dinaciclib, Afatinib, Icotinib, Bosutinib, Dasatinib, and TWS-119) by molecular docking interaction analysis with the respective target proteins for the treatment against NSCLC. The detected therapeutic targets and repurposable drugs require further attention by experimental studies to establish them as potential biomarkers for precision medicine in NSCLC treatment.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Novel Ex Vivo Models of Epithelial Ovarian Cancer: The Future of Biomarker and Therapeutic Research

Epithelial ovarian cancer (EOC) is a heterogenous disease associated with variations in presentation, pathology and prognosis. Advanced EOC is typified by frequent relapse and a historical 5-year survival of less than 30% despite improvements in surgical and systemic treatment. The advent of next generation sequencing has led to notable advances in the field of personalised medicine for many cancer types. Success in achieving cure in advanced EOC has however been limited, although significant prolongation of survival has been demonstrated. Development of novel research platforms is therefore necessary to address the rapidly advancing field of early diagnostics and therapeutics, whilst also acknowledging the significant tumour heterogeneity associated with EOC. Within available tumour models, patient-derived organoids (PDO) and explant tumour slices have demonstrated particular promise as novel ex vivo systems to model different cancer types including ovarian cancer. PDOs are organ specific 3D tumour cultures that can accurately represent the histology and genomics of their native tumour, as well as offer the possibility as models for pharmaceutical drug testing platforms, offering timing advantages and potential use as prospective personalised models to guide clinical decision-making. Such applications could maximise the benefit of drug treatments to patients on an individual level whilst minimising use of less effective, yet toxic, therapies. PDOs are likely to play a greater role in both academic research and drug development in the future and have the potential to revolutionise future patient treatment and clinical trial pathways. Similarly, ex vivo tumour slices or explants have also shown recent renewed promise in their ability to provide a fast, specific, platform for drug testing that accurately represents in vivo tumour response. Tumour explants retain tissue architecture, and thus incorporate the majority of tumour microenvironment making them an attractive method to re-capitulate in vivo conditions, again with significant timing and personalisation of treatment advantages for patients. This review will discuss the current treatment landscape and research models for EOC, their development and new advances towards the discovery of novel biomarkers or combinational therapeutic strategies to increase treatment options for women with ovarian cancer.

Integrative analysis of non-small cell lung cancer patient-derived xenografts identifies distinct proteotypes associated with patient outcomes

Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. Only a fraction of NSCLC harbor actionable driver mutations and there is an urgent need for patient-derived model systems that will enable the development of new targeted therapies. NSCLC and other cancers display profound proteome remodeling compared to normal tissue that is not predicted by DNA or RNA analyses. Here, we generate 137 NSCLC patient-derived xenografts (PDXs) that recapitulate the histology and molecular features of primary NSCLC. Proteome analysis of the PDX models reveals 3 adenocarcinoma and 2 squamous cell carcinoma proteotypes that are associated with different patient outcomes, protein-phosphotyrosine profiles, signatures of activated pathways and candidate targets, and in adenocarcinoma, stromal immune features. These findings portend proteome-based NSCLC classification and treatment and support the PDX resource as a viable model for the development of new targeted therapies.

With non-small cell lung cancer (NSCLC) being the leading cause of cancer deaths worldwide, the development of targeted therapies remains crucial. Here, the generation and multi-omics characterization of 137 NSCLC patient-derived xenografts provides a resource for potential classifications and targets.

Breaking the crosstalk of the Cellular Tumorigenic Network by low-dose combination therapy in lung cancer patient-derived xenografts

Non-small cell lung cancer (NSCLC) is commonly diagnosed at advanced stages limiting treatment options. Although, targeted therapy has become integral part of NSCLC treatment therapies often fail to improve patient's prognosis. Based on previously published criteria for selecting drug combinations for overcoming resistances, NSCLC patient-derived xenograft (PDX) tumors were treated with a low dose combination of cabozantinib, afatinib, plerixafor and etoricoxib. All PDX tumors treated, including highly therapy-resistant adeno- and squamous cell carcinomas without targetable oncogenic mutations, were completely suppressed by this drug regimen, leading to an ORR of 81% and a CBR of 100%. The application and safety profile of this low dose therapy regimen was well manageable in the pre-clinical settings. Overall, this study provides evidence of a relationship between active paracrine signaling pathways of the Cellular Tumorigenic Network, which can be effectively targeted by a low-dose multimodal therapy to overcome therapy resistance and improve prognosis of NSCLC.

Comparative study on the efficacy and exposure of molecular target agents in non-small cell lung cancer PDX models with driver genetic alterations

Patient-derived xenografts (PDXs) can adequately reflect clinical drug efficacy. However, the methods for evaluating drug efficacy are not fully established. We selected five non-small cell lung cancer (NSCLC) PDXs with genetic alterations from established PDXs and the corresponding molecular targeted therapy was administered orally for 21 consecutive days. Genetic analysis, measurement of drug concentrations in blood and tumors using liquid chromatography and tandem mass spectrometry, and analysis of drug distribution in tumors using matrix-assisted laser desorption/ionization mass spectrometry were performed. Fifteen (20%) PDXs were established using samples collected from 76 NSCLC patients with genetic alterations. The genetic alterations observed in original patients were largely maintained in PDXs. We compared the drug efficacy in original patients and PDX models; the efficacies against certain PDXs correlated with the clinical effects, while those against the others did not. We determined blood and intratumor concentrations in the PDX model, but both concentrations were low, and no evident correlation with the drug efficacy could be observed. The intratumoral spatial distribution of the drugs was both homogeneous and heterogeneous for each drug, and the distribution was independent of the expression of the target protein. The evaluation of drug efficacy in PDXs enabled partial reproduction of the therapeutic effect in original patients. A more detailed analysis of systemic and intratumoral pharmacokinetics may help clarify the mode of action of drugs. Further development of evaluation methods and indices to improve the prediction accuracy of clinical efficacy is warranted.

Modeling the Tumor Microenvironment of Ovarian Cancer: The Application of Self-Assembling Biomaterials

Ovarian cancer (OvCa) is one of the leading causes of gynecologic malignancies. Despite treatment with surgery and chemotherapy, OvCa disseminates and recurs frequently, reducing the survival rate for patients. There is an urgent need to develop more effective treatment options for women diagnosed with OvCa. The tumor microenvironment (TME) is a key driver of disease progression, metastasis and resistance to treatment. For this reason, 3D models have been designed to represent this specific niche and allow more realistic cell behaviors compared to conventional 2D approaches. In particular, self-assembling peptides represent a promising biomaterial platform to study tumor biology. They form nanofiber networks that resemble the architecture of the extracellular matrix and can be designed to display mechanical properties and biochemical motifs representative of the TME. In this review, we highlight the properties and benefits of emerging 3D platforms used to model the ovarian TME. We also outline the challenges associated with using these 3D systems and provide suggestions for future studies and developments. We conclude that our understanding of OvCa and advances in materials science will progress the engineering of novel 3D approaches, which will enable the development of more effective therapies.

Engineered in vitro tumor models for cell-based immunotherapy

Tumor immunotherapy is rapidly evolving as one of the major pillars of cancer treatment. Cell-based immunotherapies, which utilize patient's own immune cells to eliminate cancer cells, have shown great promise in treating a range of malignancies, especially those of hematopoietic origins. However, their performance on a broader spectrum of solid tumor types still fall short of expectations in the clinical stage despite promising preclinical assessments. In this review, we briefly introduce cell-based immunotherapies and the inhibitory mechanisms in tumor microenvironments that may have contributed to this discrepancy. Specifically, a major obstacle to the clinical translation of cell-based immunotherapies is in the lack of preclinical models that can accurately assess the efficacies and mechanisms of these therapies in a (patho-)physiologically relevant manner. Lately, tissue engineering and organ-on-a-chip tools and microphysiological models have allowed for more faithful recapitulation of the tumor microenvironments, by incorporating crucial tumor tissue features such as cellular phenotypes, tissue architecture, extracellular matrix, physical parameters, and their dynamic interactions. This review summarizes the existing engineered tumor models with a focus on tumor immunology and cell-based immunotherapy. We also discuss some key considerations for the future development of engineered tumor models for immunotherapeutics. STATEMENT OF SIGNIFICANCE: Cell-based immunotherapies have shown great promise in treating hematological malignancies and some epithelial tumors. However, their performance on a broader spectrum of solid tumor types still fall short of expectations. Major obstacles include the inhibitory mechanisms in tumor microenvironments (TME) and the lack of preclinical models that can accurately assess the efficacies and mechanisms of cellular therapies in a (patho-)physiologically relevant manner. In this review, we introduce recent progress in tissue engineering and microphysiological models for more faithful recapitulation of TME for cell-based immunotherapies, and some key considerations for the future development of engineered tumor models. This overview will provide a better understanding on the role of engineered models in accelerating immunotherapeutic discoveries and clinical translations.

Functional genomics approaches to improve pre-clinical drug screening and biomarker discovery

Advances in sequencing technology have enabled the genomic and transcriptomic characterization of human malignancies with unprecedented detail. However, this wealth of information has been slow to translate into clinically meaningful outcomes. Different models to study human cancers have been established and extensively characterized. Using these models, functional genomic screens and pre-clinical drug screening platforms have identified genetic dependencies that can be exploited with drug therapy. These genetic dependencies can also be used as biomarkers to predict response to treatment. For many cancers, the identification of such biomarkers remains elusive. In this review, we discuss the development and characterization of models used to study human cancers, RNA interference and CRISPR screens to identify genetic dependencies, large-scale pharmacogenomics studies and drug screening approaches to improve pre-clinical drug screening and biomarker discovery.

Application of Ovarian Cancer Organoids in Precision Medicine: Key Challenges and Current Opportunities

Ovarian cancer (OC) is the leading cause of death among gynecologic malignances. Over the past decades, human-derived models have advanced from monolayer cell cultures to three-dimensional (3D) organoids that could faithfully recapitulate biological characteristics and tumor heterogeneity of primary tissues. As a complement of previous studies based on cell lines or xenografts, organoids provide a 3D platform for mutation–carcinogenesis modeling, high-throughput drug screening, genetic engineering, and biobanking, which might fulfill the gap between basic research and clinical practice. Stepwise, cutting-edge bioengineering techniques of organoid-on-a-chip and 3D bioprinting might converge current challenges and contribute to personalized therapy. We comprehensively reviewed the advantages, challenges, and translational potential of OC organoids. Undeniably, organoids represent an excellent near-physiological platform for OC, paving the way for precision medicine implementation. Future efforts will doubtlessly bring this innovative technique from bench to bedside.

Increased Tumor Growth Rate and Mesenchymal Properties of NSCLC-Patient-Derived Xenograft Models during Serial Transplantation

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death worldwide. The high mortality is very often a consequence of its late diagnosis when the cancer is already locally advanced or has disseminated. Advances in the study of NSCLC tumors have been achieved by using in vivo models, such as patient-derived xenografts. Apart from drug screening, this approach may also be useful for study of the biology of the tumors. In the present study, surgically resected primary lung cancer samples (n = 33) were implanted in immunodeficient mice, and nine were engrafted successfully, including seven adenocarcinomas, one squamous-cell carcinoma, and one large-cell carcinoma. ADC tumors bearing the KRAS-G12C mutation were the most frequently engrafted in our PDX collection. Protein expression of vimentin, ezrin, and Ki67 were evaluated in NSCLC primary tumors and during serial transplantation by immunohistochemistry, using H-score. Our data indicated a more suitable environment for solid adenocarcinoma, compared to other lung tumor subtypes, to grow and preserve its architecture in mice, and a correlation between higher vimentin and ezrin expression in solid adenocarcinomas. A correlation between high vimentin expression and lung adenocarcinoma tumors bearing KRAS-G12C mutation was also observed. In addition, tumor evolution towards more proliferative and mesenchymal phenotypes was already observed in early PDX tumor passages. These PDX models provide a valuable platform for biomarker discovery and drug screening against tumor growth and EMT for lung cancer translational research.

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

Colorectal cancer (CRC) is a complex and heterogeneous disease, characterized by dismal prognosis and low survival rate in the advanced (metastatic) stage. During the last decade, the establishment of novel preclinical models, leading to the generation of translational discovery and validation platforms, has opened up a new scenario for the clinical practice of CRC patients. To bridge the results developed at the bench with the medical decision process, the ideal model should be easily scalable, reliable to predict treatment responses, and flexibly adapted for various applications in the research. As such, the improved benefit of novel therapies being tested initially on valuable and reproducible preclinical models would lie in personalized treatment recommendations based on the biology and genomics of the patient's tumor with the overall aim to avoid overtreatment and unnecessary toxicity. In this review, we summarize different in vitro and in vivo models, which proved efficacy in detection of novel CRC culprits and shed light into the biology and therapy of this complex disease. Even though cell lines and patient-derived xenografts remain the mainstay of colorectal cancer research, the field has been confidently shifting to the use of organoids as the most relevant preclinical model. Prioritization of organoids is supported by increasing body of evidence that these represent excellent tools worth further therapeutic explorations. In addition, novel preclinical models such as zebrafish avatars are emerging as useful tools for pharmacological interrogation. Finally, all available models represent complementary tools that can be utilized for precision medicine applications.

[Application of Organoids in Lung Cancer Precision Medicine]

Precision medicine is an approach to rational treatment selection in the overall management of lung cancer nowadays. The introduction of the patient-derived organoid (PDO) model has established the "black-box" decision-making system from the perspective of in-vitro functional models. This may assist as a complement to the treatment selection strategy based on gene-drug correlation. Further validation must be done in multi-dimensional characteristics recapitulation of the primary tumor in organoids and in large-scale randomized controlled clinical trials. This article will give an introduction to the organoid model and review the application scenarios of organoids in the context of the precise treatment of existing lung cancer.

Cancer Explant Models

Overcoming the challenges of understanding and treating cancer requires reliable patient-derived models of cancer (PDMCs). For decades, cancer research and therapeutic development relied primarily on cancer cell lines because of their prevalence, reproducibility, and simplicity to maintain. However, findings from research conducted in cell lines are rarely recapitulated in vivo and seldom directly translatable to patients. The tumor microenvironment (TME), tumor-stromal interactions, and associations with host immune cells produce profound changes in tumor phenotype and complexity not captured in traditional monolayer cell culture. In this chapter, we present various cancer explant models and discuss their applicability based on specific research aims. We discuss the appropriateness of these models for basic science questions, drug screening/development, and for personalized, precision medicine. We also consider logistical factors such as resource cost, technical difficulty, and accessibility. We finish this chapter with a practical guide intended to help the reader select the cancer explant model system(s) that best address their research aims.

Generation of Non-Small Cell Lung Cancer Patient-Derived Xenografts to Study Intratumor Heterogeneity

Simple Summary

It is widely thought that tumors are composed of different subpopulations of cancer cells carrying genetic alterations with some of them being common among all cells while others are unique for each subpopulation. This variable genetic profile of tumor cells is a component of what is collectively described as intratumor heterogeneity (ITH). Surviving the immune system and therapies, and establishing metastases are forces of natural selection that act upon ITH and drive tumor evolution and, eventually, the clinical presentation of patients. The aim of this prospective study was to investigate ITH in early-stage operable non-small cell lung cancer. We directly grafted human tumors in immunosuppressed mice and compared the genetic profile of the tumors grown in mice with that of the original human tumors. We identified clinical factors that affected the ability of human tumors to grow as mouse xenografts.

Abstract

Recent advances in sequencing technologies have allowed the in-depth molecular study of tumors, even at the single cell level. Sequencing efforts have uncovered a previously unappreciated heterogeneity among tumor cells, which has been postulated to be the driving force of tumor evolution and to facilitate recurrence, metastasis, and drug resistance. In the current study, focused on early-stage operable non-small cell lung cancer, we used tumor growth in patient-derived xenograft (PDX) models in mice as a fast-forward tumor evolution process to investigate the molecular characteristics of tumor cells that grow in mice, as well as the parameters that affect the grafting efficiency. We found that squamous cell carcinomas grafted significantly more efficiently compared with adenocarcinomas. Advanced stage, patient age and primary tumor size were positively correlated with grafting. Additionally, we isolated and characterized circulating tumor cells (CTC) from patients’ peripheral blood and found that the presence of CTCs expressing epithelial-to-mesenchymal (EMT) markers correlated with the grafting potential. Interestingly, exome sequencing of the PDX tumor identified genetic alterations in DNA repair and genome integrity genes that were under-represented in the human primary counterpart. In conclusion, through the generation of a PDX biobank of NSCLC, we identified the clinical and molecular properties of tumors that affected growth in mice.

Gene expression profiles of the original tumors influence the generation of PDX models of lung squamous cell carcinoma

Patient-derived xenograft (PDX) murine models are employed for preclinical research on cancers, including non-small cell lung cancers (NSCLCs). Even though lung squamous cell carcinomas (LUSCs) show the highest engraftment rate among NSCLCs, half of them nevertheless show PDX failure in immunodeficient mice. Here, using immunohistochemistry and RNA sequencing, we evaluated the distinct immunohistochemical and gene expression profiles of resected LUSCs that showed successful engraftment. Among various LUSCs, including the basal, classical, secretory, and primitive subtypes, those in the non-engrafting (NEG) group showed gene expression profiles similar to the pure secretory subtype with positivity for CK7, whereas those in the engrafting (EG) group were similar to the mixed secretory subtype with positivity for p63. Pathway analysis of 295 genes that demonstrated significant differences in expression between NEG and EG tumors revealed that the former had enriched expression of genes related to the immune system, whereas the latter had enriched expression of genes related to the cell cycle and DNA replication. Interestingly, NEG tumors showed higher infiltration of B cells (CD19+) and follicular dendritic cells (CD23+) in lymph follicles than EG tumors. Taken together, these findings suggest that the PDX cancer model of LUSC represents only a certain population of LUSCs and that CD19- and CD23-positive tumor-infiltrating immune cells in the original tumors may negatively influence PDX engraftment in immunodeficient mice.

Clinical application of a lung cancer organoid (tumoroid) culture system

Despite high expectations for lung tumoroids, they have not been applied in the clinic due to the difficulty of their long-term culture. Here, however, using AO (airway organoid) media developed by the Clevers laboratory, we succeeded in generating 3 lung tumoroid lines for long-term culture (>13 months) from 41 lung cancer cases (primary or metastatic). Use of nutlin-3a was key to selecting lung tumoroids that harbor mutant p53 in order to eliminate normal lung epithelial organoids. Next-generation sequencing (NGS) analysis indicated that each lung tumoroid carried BRAFG469A, TPM3-ROS1 or EGFRL858R/RB1E737*, respectively. Targeted therapies using small molecule drugs (trametinib/erlotinib for BRAFG469A, crizotinib/entrectinib for TPM3-ROS1 and ABT-263/YM-155 for EGFRL858R/RB1E737*) significantly suppressed the growth of each lung tumoroid line. AO media was superior to 3 different media developed by other laboratories. Our experience indicates that long-term lung tumoroid culture is feasible, allowing us to identify NGS-based therapeutic targets and determine the responsiveness to corresponding small molecule drugs.

Recent advances in preclinical models for lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) represents a major subtype of non-small cell lung cancer with limited treatment options. Previous studies have elucidated the complex genetic landscape of LUSC and revealed multiple altered genes and pathways. However, in stark contrast to lung adenocarcinoma, few targetable driver mutations have been established so far and targeted therapies for LUSC remain unsuccessful. Immunotherapy has revolutionized LUSC treatment and is currently approved as the new standard of care. To gain a better understanding of the LUSC biology, improved modeling systems are urgently needed. Preclinical models, particularly those mimicking human disease with an intact tumor immune microenvironment, are an invaluable tool to study cancer development and evaluate new therapeutic targets. Here, we discuss recent advances in LUSC preclinical models, with a focus on genetically engineered mouse models (GEMMs) and organoids, in the context of evolving precision medicine and immunotherapy.

Patient-Derived Xenograft vs. Organoids: A Preliminary Analysis of Cancer Research Output, Funding and Human Health Impact in 2014-2019

Cancer remains a major threat to mortality and morbidity globally, despite intense research and generous funding. Patient-derived xenograft (PDX) models-where tumor biopsies are injected into an animal-were developed to improve the predictive capacity of preclinical animal models. However, recent observations have called into question the clinical relevance, and therefore the translational accuracy, of these. Patient-derived organoids (PDO) use patient tumor samples to create in vitro models that maintain aspects of tumor structure and heterogeneity. We undertook a preliminary analysis of the number of breast, colorectal, and lung cancer research studies using PDX or PDO published worldwide between 2014-2019. We looked for evidence of impacts of this research on human health. The number of publications that focused on PDO is gradually increasing over time, but is still very low compared to publications using PDX models. Support for new research projects using PDO is gradually increasing, a promising indicator of a shift towards more human-relevant approaches to understanding human disease. Overall, increases in total funding for these three major cancer types does not appear to be translating to any consequential increase in outputs, defined for this purpose as publications associated with clinical trials. With increasing public discomfort in research using animals and demands for 'alternative' methods, it is timely to consider how to implement non-animal methods more effectively.

The SRG rat, a Sprague-Dawley Rag2/Il2rg double-knockout validated for human tumor oncology studies

We have created the immunodeficient SRG rat, a Sprague-Dawley Rag2/Il2rg double knockout that lacks mature B cells, T cells, and circulating NK cells. This model has been tested and validated for use in oncology (SRG OncoRat®). The SRG rat demonstrates efficient tumor take rates and growth kinetics with different human cancer cell lines and PDXs. Although multiple immunodeficient rodent strains are available, some important human cancer cell lines exhibit poor tumor growth and high variability in those models. The VCaP prostate cancer model is one such cell line that engrafts unreliably and grows irregularly in existing models but displays over 90% engraftment rate in the SRG rat with uniform growth kinetics. Since rats can support much larger tumors than mice, the SRG rat is an attractive host for PDX establishment. Surgically resected NSCLC tissue from nine patients were implanted in SRG rats, seven of which engrafted and grew for an overall success rate of 78%. These developed into a large tumor volume, over 20,000 mm3 in the first passage, which would provide an ample source of tissue for characterization and/or subsequent passage into NSG mice for drug efficacy studies. Molecular characterization and histological analyses were performed for three PDX lines and showed high concordance between passages 1, 2 and 3 (P1, P2, P3), and the original patient sample. Our data suggest the SRG OncoRat is a valuable tool for establishing PDX banks and thus serves as an alternative to current PDX mouse models hindered by low engraftment rates, slow tumor growth kinetics, and multiple passages to develop adequate tissue banks.

Patient-derived cell line, xenograft and organoid models in lung cancer therapy

Lung cancer accounts for most cancer-related deaths worldwide and has an overall 5-year survival rate of ~15%. Cell lines have played important roles in the study of cancer biology and potential therapeutic targets, as well as pre-clinical testing of novel drugs. However, most experimental therapies that have cleared preclinical testing using established cell lines have failed phase III clinical trials. This suggests that such models may not adequately recapitulate patient tumor biology and clinical outcome predictions. Here, we discuss and compare different pre-clinical lung cancer models, including established cell lines, patient-derived cell lines, xenografts and organoids, summarize the methodology for generating these models, and review their relative advantages and limitations in different oncologic research applications. We further discuss additional gaps in patient-derived pre-clinical models to better recapitulate tumor biology and improve their clinical predictive power.

CD30 and ALK combination therapy has high therapeutic potency in RANBP2-ALK-rearranged epithelioid inflammatory myofibroblastic sarcoma

BACKGROUND

Epithelioid inflammatory myofibroblastic sarcoma (eIMS) is characterised by perinuclear ALK localisation, CD30 expression and early relapse despite crizotinib treatment. We aimed to identify therapies to prevent and/or treat ALK inhibitor resistance.

METHODS

Malignant ascites, from an eIMS patient at diagnosis and following multiple relapses, were used to generate matched diagnosis and relapse xenografts.

RESULTS

Xenografts were validated by confirmation of RANBP2-ALK rearrangement, perinuclear ALK localisation and CD30 expression. Although brentuximab-vedotin (BV) demonstrated single-agent activity, tumours regrew during BV therapy. BV resistance was associated with reduced CD30 expression and induction of ABCB1. BV resistance was reversed in vitro by tariquidar, but combination BV and tariquidar treatment only briefly slowed xenograft growth compared with BV alone. Combining BV with either crizotinib or ceritinib resulted in marked tumour shrinkage in both xenograft models, and resulted in prolonged tumour-free survival in the diagnosis compared with the relapse xenograft.

CONCLUSIONS

CD30 is a therapeutic target in eIMS. BV efficacy is limited by the rapid emergence of resistance. Prolonged survival with combination ALK and CD30-targeted-therapy in the diagnosis model provides the rationale to trial this combination in eIMS patients at diagnosis. This combination could also be considered for other CD30-positive, ALK-rearranged malignancies.

Organotypic Co-Cultures as a Novel 3D Model for Head and Neck Squamous Cell Carcinoma

Background: Head and neck squamous cell carcinomas (HNSCC) are phenotypically and molecularly heterogeneous and frequently develop therapy resistance. Reliable patient-derived 3D tumor models are urgently needed to further study the complex pathogenesis of these tumors and to overcome treatment failure. Methods: We developed a three-dimensional organotypic co-culture (3D-OTC) model for HNSCC that maintains the architecture and cell composition of the individual tumor. A dermal equivalent (DE), composed of healthy human-derived fibroblasts and viscose fibers, served as a scaffold for the patient sample. DEs were co-cultivated with 13 vital HNSCC explants (non-human papillomavirus (HPV) driven, n = 7; HPV-driven, n = 6). Fractionated irradiation was applied to 5 samples (non-HPV-driven, n = 2; HPV-driven n = 3). To evaluate expression of ki-67, cleaved caspase-3, pan-cytokeratin, p16^INK4a, CD45, ∝smooth muscle actin and vimentin over time, immunohistochemistry and immunofluorescence staining were performed Patient checkup data were collected for up to 32 months after first diagnosis. Results: All non-HPV-driven 3D-OTCs encompassed proliferative cancer cells during cultivation for up to 21 days. Proliferation indices of primaries and 3D-OTCs were comparable and consistent over time. Overall, tumor explants displayed heterogeneous growth patterns (i.e., invasive, expansive, silent). Cancer-associated fibroblasts and leukocytes could be detected for up to 21 days. HPV DNA was detectable in both primary and 3D-OTCs (day 14) of HPV-driven tumors. However, p16^INK4a expression levels were varying. Morphological alterations and radioresistant tumor cells were detected in 3D-OTC after fractionated irradiation in HPV-driven and non-driven samples. Conclusions: Our 3D-OTC model for HNSCC supports cancer cell survival and proliferation in their original microenvironment. The model enables investigation of invasive cancer growth and might, in the future, serve as a platform to perform sensitivity testing upon treatment to predict therapy response.

PDX models of human lung squamous cell carcinoma: consideration of factors in preclinical and co-clinical applications

Background

Treatment of human lung squamous cell carcinoma (LUSC) using current targeted therapies is limited because of their diverse somatic mutations without any specific dominant driver mutations. These mutational diversities preventing the use of common targeted therapies or the combination of available therapeutic modalities would require a preclinical animal model of this tumor to acquire improved clinical responses. Patient-derived xenograft (PDX) models have been recognized as a potentially useful preclinical model for personalized precision medicine. However, whether the use of LUSC PDX models would be appropriate enough for clinical application is still controversial.

Methods

In the process of developing PDX models from Korean patients with LUSC, the authors investigated the factors influencing the successful initial engraftment of tumors in NOD scid gamma mice and the retainability of the pathological and genomic characteristics of the parental patient tumors in PDX tumors.

Conclusions

The authors have developed 62 LUSC PDX models that retained the pathological and genomic features of parental patient tumors, which could be used in preclinical and co-clinical studies.

Trial registration Tumor samples were obtained from 139 patients with LUSC between November 2014 and January 2019. All the patients provided signed informed consents. This study was approved by the institutional review board (IRB) of Samsung Medical Center (2018-03-110)

Human Lung Adenocarcinoma-Derived Organoid Models for Drug Screening

Lung cancer is an extremely heterogeneous disease, and its treatment remains one of the most challenging tasks in medicine. Few existing laboratory lung cancer models can faithfully recapitulate the diversity of the disease and predict therapy response. Here, we establish 12 patient-derived organoids from the most common lung cancer subtype, lung adenocarcinoma (LADC). Extensive gene and histopathology profiling show that the tumor organoids retain the histological architectures, genomic landscapes, and gene expression profiles of their parental tumors. Patient-derived lung cancer organoids are amenable for biomarker identification and high-throughput drug screening in vitro. This study should enable the generation of patient-derived lung cancer organoid lines, which can be used to further the understanding of lung cancer pathophysiology and to assess drug response in personalized medicine.

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Generation of a living biobank of patient-derived lung adenocarcinoma organoids

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Organoid biobank encompasses most of known subtypes of adenocarcinoma

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Organoids maintain the histological and mutational spectrum of original tumors

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Tumor organoids provide a tool for biomarker identification and drug testing

Modeling neoplastic disease with spheroids and organoids

Cancer is a complex disease in which both genetic defects and microenvironmental components contribute to the development, progression, and metastasization of disease, representing major hurdles in the identification of more effective and safer treatment regimens for patients. Three-dimensional (3D) models are changing the paradigm of preclinical cancer research as they more closely resemble the complex tissue environment and architecture found in clinical tumors than in bidimensional (2D) cell cultures. Among 3D models, spheroids and organoids represent the most versatile and promising models in that they are capable of recapitulating the heterogeneity and pathophysiology of human cancers and of filling the gap between conventional 2D in vitro testing and animal models. Such 3D systems represent a powerful tool for studying cancer biology, enabling us to model the dynamic evolution of neoplastic disease from the early stages to metastatic dissemination and the interactions with the microenvironment. Spheroids and organoids have recently been used in the field of drug discovery and personalized medicine. The combined use of 3D models could potentially improve the robustness and reliability of preclinical research data, reducing the need for animal testing and favoring their transition to clinical practice. In this review, we summarize the recent advances in the use of these 3D systems for cancer modeling, focusing on their innovative translational applications, looking at future challenges, and comparing them with most widely used animal models.

Establishment and Characterisation of Heterotopic Patient-Derived Xenografts for Glioblastoma

Glioblastoma is an aggressive brain tumour with a patient median survival of approximately 14 months. The development of innovative treatment strategies to increase the life span and quality of life of patients is hence essential. This requires the use of appropriate glioblastoma models for preclinical testing, which faithfully reflect human cancers. The aim of this study was to establish glioblastoma patient-derived xenografts (PDXs) by heterotopic transplantation of tumour pieces in the axillae of NMRI nude mice. Ten out of 22 patients' samples gave rise to tumours in mice. Their human origin was confirmed by microsatellite analyses, though minor changes were observed. The glioblastoma nature of the PDXs was corroborated by pathological evaluation. Latency times spanned from 48.5 to 370.5 days in the first generation. Growth curve analyses revealed an increase in the growth rate with increasing passages. The methylation status of the MGMT promoter in the primary material was maintained in the PDXs. However, a trend towards a more methylated pattern could be found. A correlation was observed between the take in mice and the proportion of Sox2⁺ cells (r = 0.49, p = 0.016) and nestin⁺ cells (r = 0.55, p = 0.007). Our results show that many PDXs maintain key features of the patients' samples they derive from. They could thus be used as preclinical models to test new therapies and biomarkers.

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

Small molecules-Giant leaps for immuno-oncology

Immuno-oncology therapies are revolutionizing the oncology landscape with checkpoint blockade becoming the treatment backbone for many indications. While inspiring, much work remains to increase the number of cancer patients that can benefit from these treatments. Thus, a new era of immuno-oncology research has begun which is focused on identifying novel combination regimes that lead to improved response rates. This review highlights the significance of small molecules in this approach and illustrates the huge progress that has been made to date.

Ex-Vivo Treatment of Tumor Tissue Slices as a Predictive Preclinical Method to Evaluate Targeted Therapies for Patients with Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the third type of urologic cancer. At time of diagnosis, 30% of cases are metastatic with no effect of chemotherapy or radiotherapy. Current targeted therapies lead to a high rate of relapse and resistance after a short-term response. Thus, a major hurdle in the development and use of new treatments for ccRCC is the lack of good pre-clinical models that can accurately predict the efficacy of new drugs and allow the stratification of patients into the correct treatment regime. Here, we describe different 3D cultures models of ccRCC, emphasizing the feasibility and the advantage of ex-vivo treatment of fresh, surgically resected human tumor slice cultures of ccRCC as a robust preclinical model for identifying patient response to specific therapeutics. Moreover, this model based on precision-cut tissue slices enables histopathology measurements as tumor architecture is retained, including the spatial relationship between the tumor and tumor-infiltrating lymphocytes and the stromal components. Our data suggest that acute treatment of tumor tissue slices could represent a benchmark of further exploration as a companion diagnostic tool in ccRCC treatment and a model to develop new therapeutic drugs.

Characterization and printability of Sodium alginate -Gelatin hydrogel for bioprinting NSCLC co-culture

3D bioprinting improves orientation of in vitro tumor models by offering layer by layer positioning of cancer cells and cancer associated fibroblasts (CAFs) which can replicate tumor microenvironment. Aim of this study was to develop a sodium alginate -gelatin (SA-GL) hydrogel by optimizing rheological parameters to print non-small cell lung cancer (NSCLC) patient derived xenograft (PDX) cells and lung CAFs co-cultures. SA-GL hydrogels were prepared, and rheological properties were evaluated. Both the cells were mixed with the hydrogel and printed using INKREDIBLE bioprinter. Hydrogels prepared with 3.25% and 3.5% (w/v) SA and 4% (w/v) GL showed higher printability and cell viability. A significant decline in viscosity with shear rate was observed in these hydrogels suggesting the shear thinning property of hydrogels. Spheroid size distribution after 15 days was in the diameter range of 50-1100 µm. Up-regulation of vimentin, α-SMA and loss of E-cadherin in co-culture spheroids confirmed cellular crosstalk. This study demonstrates that rheological optimization of SA-GL hydrogel enhances printability and viability of NSCLC PDX and CAF co-culture which allows 3D co-culture spheroid formation within the printed scaffold. Therefore, this model can be used for studying high throughput drug screening and other pre-clinical applications.

A reliable method to determine which candidate chemotherapeutic drugs effectively inhibit tumor growth in patient-derived xenografts (PDX) in single mouse trials

PURPOSE

We report on a statistical method for grouping anti-cancer drugs (GRAD) in single mouse trials (SMT). The method assigns candidate drugs into groups that inhibit or do not inhibit tumor growth in patient-derived xenografts (PDX). It determines the statistical significance of the group assignments without replicate trials of each drug.

METHODS

The GRAD method applies a longitudinal finite mixture model, implemented in the statistical package PROC TRAJ, to analyze a mixture of tumor growth curves for portions of the same tumor in different mice, each single mouse exposed to a different drug. Each drug is classified into an inhibitory or non-inhibitory group. There are several advantages to the GRAD method for SMT. It determines that probability that the grouping is correct, uses the entire longitudinal tumor growth curve data for each drug treatment, can fit different shape growth curves, accounts for missing growth curve data, and accommodates growth curves of different time periods.

RESULTS

We analyzed data for 22 drugs for 18 human colorectal tumors provided by researchers in a previous publication. The GRAD method identified 18 drugs that were inhibitory against at least one tumor, and 10 tumors for which there was at least one inhibitory drug. Analysis of simulated data indicated that the GRAD method has a sensitivity of 84% and a specificity of 98%.

CONCLUSION

A statistical method, GRAD, can group anti-cancer drugs into those that are inhibitory and those that are non-inhibitory in single mouse trials and provide probabilities that the grouping is correct.

Xenograft and organoid model systems in cancer research

Patient‐derived tumour xenografts and tumour organoids have become important preclinical model systems for cancer research. Both models maintain key features from their parental tumours, such as genetic and phenotypic heterogeneity, which allows them to be used for a wide spectrum of applications. In contrast to patient‐derived xenografts, organoids can be established and expanded with high efficiency from primary patient material. On the other hand, xenografts retain tumour–stroma interactions, which are known to contribute to tumorigenesis. In this review, we discuss recent advances in patient‐derived tumour xenograft and tumour organoid model systems and compare their promises and challenges as preclinical models in cancer research.