Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine

Human Organoids: Tools for Understanding Biology and Treating Diseases

Organoids are in vitro-cultured three-dimensional structures that recapitulate key aspects of in vivo organs. They can be established from pluripotent stem cells and from adult stem cells, the latter being the subject of this review. Organoids derived from adult stem cells exploit the tissue regeneration process that is driven by these cells, and they can be established directly from the healthy or diseased epithelium of many organs. Organoids are amenable to any experimental approach that has been developed for cell lines. Applications in experimental biology involve the modeling of tissue physiology and disease, including malignant, hereditary, and infectious diseases. Biobanks of patient-derived tumor organoids are used in drug development research, and they hold promise for developing personalized and regenerative medicine. In this review, we discuss the applications of adult stem cell-derived organoids in the laboratory and the clinic.

Cancer metabolism gets physical

Patient-derived culture models enable assessment of drug sensitivity and can connect personalized genomics with therapeutic options. However, their clinical translation is constrained by limited fidelity. We outline how the physical microenvironment regulates cell metabolism and describe how engineered culture systems could enhance the predictive power for precision medicine.

Integrative Molecular Analysis of Patients With Advanced and Metastatic Cancer

PURPOSE

We developed a precision medicine program for patients with advanced cancer using integrative whole-exome sequencing and transcriptome analysis.

PATIENTS AND METHODS

Five hundred fifteen patients with locally advanced/metastatic solid tumors were prospectively enrolled, and paired tumor/normal sequencing was performed. Seven hundred fifty-nine tumors from 515 patients were evaluated.

RESULTS

Most frequent tumor types were prostate (19.4%), brain (16.5%), bladder (15.4%), and kidney cancer (9.2%). Most frequently altered genes were TP53 (33%), CDKN2A (11%), APC (10%), KTM2D (8%), PTEN (8%), and BRCA2 (8%). Pathogenic germline alterations were present in 10.7% of patients, most frequently CHEK2 (1.9%), BRCA1 (1.5%), BRCA2 (1.5%), and MSH6 (1.4%). Novel gene fusions were identified, including a RBM47-CDK12 fusion in a metastatic prostate cancer sample. The rate of clinically relevant alterations was 39% by whole-exome sequencing, which was improved by 16% by adding RNA sequencing. In patients with more than one sequenced tumor sample (n = 146), 84.62% of actionable mutations were concordant.

CONCLUSION

Integrative analysis may uncover informative alterations for an advanced pan-cancer patient population. These alterations are consistent in spatially and temporally heterogeneous samples.

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.

Addressing Patient Specificity in the Engineering of Tumor Models

Cancer treatment is challenged by the heterogeneous nature of cancer, where prognosis depends on tumor type and disease stage, as well as previous treatments. Optimal patient stratification is critical for the development and validation of effective treatments, yet pre-clinical model systems are lacking in the delivery of effective individualized platforms that reflect distinct patient-specific clinical situations. Advances in cancer cell biology, biofabrication, and microengineering technologies have led to the development of more complex in vitro three-dimensional (3D) models to act as drug testing platforms and to elucidate novel cancer mechanisms. Mostly, these strategies have enabled researchers to account for the tumor microenvironment context including tumor-stroma interactions, a key factor of heterogeneity that affects both progression and therapeutic resistance. This is aided by state-of-the-art biomaterials and tissue engineering technologies, coupled with reproducible and high-throughput platforms that enable modeling of relevant physical and chemical factors. Yet, the translation of these models and technologies has been impaired by neglecting to incorporate patient-derived cells or tissues, and largely focusing on immortalized cell lines instead, contributing to drug failure rates. While this is a necessary step to establish and validate new models, a paradigm shift is needed to enable the systematic inclusion of patient-derived materials in the design and use of such models. In this review, we first present an overview of the components responsible for heterogeneity in different tumor microenvironments. Next, we introduce the state-of-the-art of current in vitro 3D cancer models employing patient-derived materials in traditional scaffold-free approaches, followed by novel bioengineered scaffold-based approaches, and further supported by dynamic systems such as bioreactors, microfluidics, and tumor-on-a-chip devices. We critically discuss the challenges and clinical prospects of models that have succeeded in providing clinical relevance and impact, and present emerging concepts of novel cancer model systems that are addressing patient specificity, the next frontier to be tackled by the field.

Current and Future Horizons of Patient-Derived Xenograft Models in Colorectal Cancer Translational Research

Our poor understanding of the intricate biology of cancer and the limited availability of preclinical models that faithfully recapitulate the complexity of tumors are primary contributors to the high failure rate of novel therapeutics in oncology clinical studies. To address this need, patient-derived xenograft (PDX) platforms have been widely deployed and have reached a point of development where we can critically review their utility to model and interrogate relevant clinical scenarios, including tumor heterogeneity and clonal evolution, contributions of the tumor microenvironment, identification of novel drugs and biomarkers, and mechanisms of drug resistance. Colorectal cancer (CRC) constitutes a unique case to illustrate clinical perspectives revealed by PDX studies, as they overcome limitations intrinsic to conventional ex vivo models. Furthermore, the success of molecularly annotated "Avatar" models for co-clinical trials in other diseases suggests that this approach may provide an additional opportunity to improve clinical decisions, including opportunities for precision targeted therapeutics, for patients with CRC in real time. Although critical weaknesses have been identified with regard to the ability of PDX models to predict clinical outcomes, for now, they are certainly the model of choice for preclinical studies in CRC. Ongoing multi-institutional efforts to develop and share large-scale, well-annotated PDX resources aim to maximize their translational potential. This review comprehensively surveys the current status of PDX models in translational CRC research and discusses the opportunities and considerations for future PDX development.

Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening

Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalised medicine. Here, we report lung cancer organoids and normal bronchial organoids established from patient tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2-mutant organoid to olaparib, an EGFR-mutant organoid to erlotinib, and an EGFR-mutant/MET-amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

Gut organoids: mini-tissues in culture to study intestinal physiology and disease

In vitro, cell cultures are essential tools in the study of intestinal function and disease. For the past few decades, monolayer cellular cultures, such as cancer cell lines or immortalized cell lines, have been widely applied in gastrointestinal research. Recently, the development of three-dimensional cultures known as organoids has permitted the growth of normal crypt-villus units that recapitulate many aspects of intestinal physiology. Organoid culturing has also been applied to study gastrointestinal diseases, intestinal-microbe interactions, and colorectal cancer. These models are amenable to CRISPR gene editing and drug treatments, including high-throughput small-molecule testing. Three-dimensional intestinal cultures have been transplanted into mice to develop versatile in vivo models of intestinal disease, particularly cancer. Limitations of currently available organoid models include cost and challenges in modeling nonepithelial intestinal cells, such as immune cells and the microbiota. Here, we describe the development of organoid models of intestinal biology and the applications of organoids for study of the pathophysiology of intestinal diseases and cancer.

Predictive Potential of Head and Neck Squamous Cell Carcinoma Organoids

In this issue of Cancer Discovery, Driehuis and colleagues establish culture conditions for the rapid, efficient, and long-term expansion of healthy human oral mucosa and head and neck squamous cell carcinoma (HNSCC) tumor organoids. The HNSCC tumor organoids provide a functional platform for analyzing tumor cell phenotype, tumorigenic potential, and drug and radiotherapy response, and they have a potential role in clinical decision-making.See related article by Driehuis et al., p. 852.

Evaluating vandetanib in the treatment of medullary thyroid cancer: patient-reported outcomes

Medullary thyroid cancers (MTCs) are neuroendocrine tumors, which secrete calcitonin and carcinoembryonic antigen, both of which can serve as tumor markers. Extensive and accurate surgical resection is the primary treatment for MTC, whereas the use of external beam radiotherapy is limited. Moreover, since MTC is derived from thyroid parafollicular cells or C cells, it is not responsive to either radioiodine or thyroid-stimulating hormone suppression, and therefore, they cannot be considered as treatment strategies. Traditional therapies for advanced or metastatic progressive medullary thyroid cancer (pMTC) are poorly effective. Among the new approaches tested in clinical trials, targeted chemotherapies with tyrosine kinase inhibitors (TKIs) are now available and they represent effective interventions for progressive disease, with additional investigational options emerging. This paper reviews the efficacy and safety of vandetanib in patients with a pMTC, as it has been shown to improve progression-free survival (30.5 vs 19.3 months in controls). Vandetanib is approved by the FDA and EMA for symptomatic or progressive MTC in patients with unresectable locally advanced or metastatic disease in adults, adolescents, and children older than 5 years. The most common adverse events in vandetanib-treated patients are diarrhea, rash, folliculitis, nausea, QTc prolongation, hypertension, and fatigue. More data are required to deepen our knowledge on molecular biology of tumor and host defense, with the aim to achieve better prognosis and higher quality of life for affected patients.

An Interplay Between Reaction-Diffusion and Cell-Matrix Adhesion Regulates Multiscale Invasion in Early Breast Carcinomatosis

The progression of cancer in the breast involves multiple reciprocal interactions between malignantly transformed epithelia, surrounding untransformed but affected stromal cells, and the extracellular matrix (ECM) that is remodeled during the process. A quantitative understanding of the relative contribution of such interactions to phenotypes associated with cancer cells can be arrived at through the construction of increasingly complex experimental and computational models. Herein, we introduce a multiscale three-dimensional (3D) organo- and pathotypic experimental assay that approximates, to an unprecedented extent, the histopathological complexity of a tumor disseminating into its surrounding stromal milieu via both bulk and solitary motility dynamics. End point and time-lapse microscopic observations of this assay allow us to study the earliest steps of cancer invasion as well as the dynamical interactions between the epithelial and stromal compartments. We then simulate our experimental observations using the modeling environment Compucell3D that is based on the Glazier-Graner-Hogeweg model. The computational model, which comprises adhesion between cancer cells and the matrices, cell proliferation and apoptosis, and matrix remodeling through reaction-diffusion-based morphogen dynamics, is first trained to phenocopy controls run with the experimental model, wherein one or the other matrices have been removed. The trained computational model successfully predicts phenotypes of the experimental counterparts that are subjected to pharmacological treatments (inhibition of N-linked glycosylation and matrix metalloproteinase activity) and scaffold modulation (alteration of collagen density). Further parametric exploration-based simulations suggest that specific permissive regimes of cell-cell and cell-matrix adhesions, operating in the context of a reaction-diffusion-regulated ECM dynamics, promote multiscale invasion of breast cancer cells and determine the extent to which the latter migrate through their surrounding stroma.

A Pharmacogenomic Landscape in Human Liver Cancers

Liver cancers are highly heterogeneous with poor prognosis and drug response. A better understanding between genetic alterations and drug responses would facilitate precision treatment for liver cancers. To characterize the landscape of pharmacogenomic interactions in liver cancers, we developed a protocol to establish human liver cancer cell models at a success rate of around 50% and generated the Liver Cancer Model Repository (LIMORE) with 81 cell models. LIMORE represented genomic and transcriptomic heterogeneity of primary cancers. Interrogation of the pharmacogenomic landscape of LIMORE discovered unexplored gene-drug associations, including synthetic lethalities to prevalent alterations in liver cancers. Moreover, predictive biomarker candidates were suggested for the selection of sorafenib-responding patients. LIMORE provides a rich resource facilitating drug discovery in liver cancers.

Clinical Implementation of Precision Medicine in Gastric Cancer

Gastric cancer (GC) is one of the deadliest malignancies in the world. Currently, clinical treatment decisions are mostly made based on the extent of the tumor and its anatomy, such as tumor-node-metastasis staging. Recent advances in genome-wide molecular technology have enabled delineation of the molecular characteristics of GC. Based on this, efforts have been made to classify GC into molecular subtypes with distinct prognosis and therapeutic response. Simplified algorithms based on protein and RNA expressions have been proposed to reproduce the GC classification in the clinical field. Furthermore, a recent study established a single patient classifier (SPC) predicting the prognosis and chemotherapy response of resectable GC patients based on a 4-gene real-time polymerase chain reaction assay. GC patient stratification according to SPC will enable personalized therapeutic strategies in adjuvant settings. At the same time, patient-derived xenografts and patient-derived organoids are now emerging as novel preclinical models for the treatment of GC. These models recapitulate the complex features of the primary tumor, which is expected to facilitate both drug development and clinical therapeutic decision making. An integrated approach applying molecular patient stratification and patient-derived models in the clinical realm is considered a turning point in precision medicine in GC.

Patient-Derived Xenografts and Matched Cell Lines Identify Pharmacogenomic Vulnerabilities in Colorectal Cancer

PURPOSE

Patient-derived xenograft (PDX) models accurately recapitulate the tumor of origin in terms of histopathology, genomic landscape, and therapeutic response, but some limitations due to costs associated with their maintenance and restricted amenability for large-scale screenings still exist. To overcome these issues, we established a platform of 2D cell lines (xeno-cell lines, XL), derived from PDXs of colorectal cancer with matched patient germline gDNA available.

EXPERIMENTAL DESIGN

Whole-exome and transcriptome sequencing analyses were performed. Biomarkers of response and resistance to anti-HER therapy were annotated. Dependency on the WRN helicase gene was assessed in MSS, MSI-H, and MSI-like XLs using a reverse genetics functional approach.

RESULTS

XLs recapitulated the entire spectrum of colorectal cancer transcriptional subtypes. Exome and RNA-seq analyses delineated several molecular biomarkers of response and resistance to EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XLs were confirmed in vivo in the matched PDXs. MSI-H models were dependent upon WRN gene expression, while loss of WRN did not affect MSS XLs growth. Interestingly, one MSS XL with transcriptional MSI-like traits was sensitive to WRN depletion.

CONCLUSIONS

The XL platform represents a preclinical tool for functional gene validation and proof-of-concept studies to identify novel druggable vulnerabilities in colorectal cancer.

Cancer Cell Lines Are Useful Model Systems for Medical Research

Cell lines are in vitro model systems that are widely used in different fields of medical research, especially basic cancer research and drug discovery. Their usefulness is primarily linked to their ability to provide an indefinite source of biological material for experimental purposes. Under the right conditions and with appropriate controls, authenticated cancer cell lines retain most of the genetic properties of the cancer of origin. During the last few years, comparing genomic data of most cancer cell lines has corroborated this statement and those that were observed studying the tumoral tissue equivalents included in the The Cancer Genome Atlas (TCGA) database. We are at the disposal of comprehensive open access cell line datasets describing their molecular and cellular alterations at an unprecedented level of accuracy. This aspect, in association with the possibility of setting up accurate culture conditions that mimic the in vivo microenvironment (e.g., three-dimensional (3D) coculture), has strengthened the importance of cancer cell lines for continuing to sustain medical research fields. However, it is important to consider that the appropriate use of cell lines needs to follow established guidelines for guaranteed data reproducibility and quality, and to prevent the occurrence of detrimental events (i.e., those that are linked to cross-contamination and mycoplasma contamination).

Patient-derived organoids from endometrial disease capture clinical heterogeneity and are amenable to drug screening

Endometrial disorders represent a major gynaecological burden. Current research models fail to recapitulate the nature and heterogeneity of these diseases, thereby hampering scientific and clinical progress. Here we developed long-term expandable organoids from a broad spectrum of endometrial pathologies. Organoids from endometriosis show disease-associated traits and cancer-linked mutations. Endometrial cancer-derived organoids accurately capture cancer subtypes, replicate the mutational landscape of the tumours and display patient-specific drug responses. Organoids were also established from precancerous pathologies encompassing endometrial hyperplasia and Lynch syndrome, and inherited gene mutations were maintained. Endometrial disease organoids reproduced the original lesion when transplanted in vivo. In summary, we developed multiple organoid models that capture endometrial disease diversity and will provide powerful research models and drug screening and discovery tools.

Disease modelling in human organoids

The past decade has seen an explosion in the field of in vitro disease modelling, in particular the development of organoids. These self-organizing tissues derived from stem cells provide a unique system to examine mechanisms ranging from organ development to homeostasis and disease. Because organoids develop according to intrinsic developmental programmes, the resultant tissue morphology recapitulates organ architecture with remarkable fidelity. Furthermore, the fact that these tissues can be derived from human progenitors allows for the study of uniquely human processes and disorders. This article and accompanying poster highlight the currently available methods, particularly those aimed at modelling human biology, and provide an overview of their capabilities and limitations. We also speculate on possible future technological advances that have the potential for great strides in both disease modelling and future regenerative strategies.

Summary: Human organoids are important tools for modelling disease. This At a Glance article summarises the current organoid models of several human diseases, and discusses future prospects for these technologies.

Distinct Colorectal Cancer-Associated APC Mutations Dictate Response to Tankyrase Inhibition

The majority of colorectal cancers show hyperactivated WNT signaling due to inactivating mutations in the adenomatous polyposis coli (APC) tumor suppressor. Genetically restoring APC suppresses WNT and induces rapid and sustained tumor regression, implying that reengaging this endogenous tumor-suppressive mechanism may be an effective therapeutic strategy. Here, using new animal models, human cell lines, and ex vivo organoid cultures, we show that tankyrase (TNKS) inhibition can control WNT hyperactivation and provide long-term tumor control in vivo, but that effective responses are critically dependent on how APC is disrupted. Mutant APC proteins truncated within the mutation cluster region physically engage the destruction complex and suppress the WNT transcriptional program, while APC variants with early truncations (e.g., Apc ^Min) show limited interaction with AXIN1 and β-catenin, and do not respond to TNKS blockade. Together, this work shows that TNKS inhibition, like APC restoration, can reestablish endogenous control of WNT/β-catenin signaling, but that APC genotype is a crucial determinant of this response. SIGNIFICANCE: This study reveals how subtle changes to the mutations in a critical colorectal tumor suppressor, APC, influence the cellular response to a targeted therapy. It underscores how investigating the specific genetic alterations that occur in human cancer can identify important biological mechanisms of drug response and resistance.This article is highlighted in the In This Issue feature, p. 1325.

Establishment and characterization of patient-derived organoids from a young patient with cervical clear cell carcinoma

Cervical clear cell carcinoma (cCCC) constitutes an extremely rare subtype of cervical cancer. Consequently, its pathogenesis remains largely unknown, with no cell lines established from primary tumors. Here, we report the first establishment of cCCC organoids, from biopsy samples of a 23‐year‐old patient diagnosed with cCCC. By applying a protocol that we recently optimized for gynecological tumors, we were able to propagate a patient‐derived cell line (PDC) for more than 6 months as organoids. This PDC tolerated cryopreservation and proliferated either as spheroids or adherent cells, and developed xenografts in immunodeficient mice, ensuring robust utility as a cell line. Intriguingly, the resected tumor focally contained serous carcinoma (SC) in a tiny protruding lesion. Both organoids and derivative xenografts resembled the CCC component of the original tumor in histology, immunostaining profile, and genome‐wide copy number changes, including focal gain of MET. Genomic analysis revealed that both organoids and the CCC component harbored only a few mutations, of which 2 mutations were shared in common. In contrast, the SC component showed a mutator‐phenotype and prominent genome instability along with biallelic inactivation of TP53, but none of them were found in organoids or the CCC component. The PDC proved sensitive to major chemotherapeutic agents and MET inhibitors. These observations clearly indicated that the PDC, designated as YMC7, can be used as a novel cCCC cell line and provide novel insights into the pathogenesis of mixed cervical adenocarcinoma. As a valuable resource for rare cancer, it will likely contribute to investigations in many fields.

Utilizing gastric cancer organoids to assess tumor biology and personalize medicine

While the incidence and mortality of gastric cancer (GC) have declined due to public health programs, it remains the third deadliest cancer worldwide. For patients with early disease, innovative endoscopic and complex surgical techniques have improved survival. However, for patients with advanced disease, there are limited treatment options and survival remains poor. Therefore, there is an urgent need for more effective therapies. Since novel therapies require extensive preclinical testing prior to human trials, it is important to identify methods to expedite this process. Traditional cancer models are restricted by the inability to accurately recapitulate the primary human tumor, exorbitant costs, and the requirement for extended periods of development time. An emerging in vitro model to study human disease is the patient-derived organoid, which is a three-dimensional system created from fresh surgical or biopsy tissues of a patient’s gastric tumor. Organoids are cultured in plastic wells and suspended in a gelatinous matrix, providing a substrate for extension and growth in all dimensions. They are rapid-growing and highly representative of the molecular landscape, histology, and morphology of the various subtypes of GC. Organoids uniquely model tumor initiation and growth, including steps taken by normal stomach cells to transform into invasive, intestinal-type tumor cells. Additionally, they provide ample material for biobanking and screening novel therapies. Lastly, organoids are a promising model for personalized therapy and warrant further investigation in drug sensitivity studies for GC patients.

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.

The cancer microbiome

Collectively known as the microbiota, the commensal bacteria and other microorganisms that colonize the epithelial surfaces of our body have been shown to produce small molecules and metabolites that have both local and systemic effects on cancer onset, progression and therapy response. To date, most studies focusing on the microbiome have used traditional preclinical mouse models and identified correlative relationships between microbial species and cancer phenotypes. Now, the profound influence of the microbiota on the efficacy of cancer treatments, such as immunotherapies, has begun to be extensively characterized in humans. Paramount to the development of microbiota-based therapeutics, the next challenge in microbiome research will be to identify individual microbial species that causally affect cancer phenotypes and unravel the underlying mechanisms. In this Viewpoint article, we asked four scientists working on the cancer microbiome for their opinions on the current state of the field, where the research is heading and how we can advance our understanding to rationally design microbial-based therapeutics to transform treatment strategies for patients with cancer.

Tracing Clonal Dynamics Reveals that Two- and Three-dimensional Patient-derived Cell Models Capture Tumor Heterogeneity of Clear Cell Renal Cell Carcinoma

BACKGROUND

Extensive DNA sequencing has led to an unprecedented view of the diversity of individual genomes and their evolution among patients with clear cell renal cell carcinoma (ccRCC).

OBJECTIVE

To understand subclonal architecture and dynamics of patient-derived two-dimensional (2D) and three-dimensional (3D) ccRCC models in vitro, in order to determine whether they mirror ccRCC inter- and intratumor heterogeneity.

DESIGN, SETTING, AND PARTICIPANTS

We have established a comprehensive platform of living renal cancer cell models from ccRCC surgical specimens.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We confirmed the concordance of 2D and 3D patient-derived cell (PDC) models with the original tumor tissue in terms of histology, biomarker expression, cancer driver mutations, and copy number alterations. We addressed inter- and intrapatient heterogeneity by analyzing clonal dynamics during serial passaging.

RESULTS AND LIMITATIONS

In-depth genetic characterization verified the presence of heterogeneous cell populations, and revealed a high degree of similarity between subclonal compositions of monolayer and organoid cell cultures and the corresponding parental ccRCCs. Clonal dynamics were evident during serial passaging of cells in vitro, suggesting that PDC cultures can offer insights into evolutionary potential and treatment susceptibility of ccRCC subclones in vivo. Proof-of-concept drug profiling using selected ccRCC-targeted therapy agents highlighted patient-specific vulnerabilities in PDC models that could not be anticipated by interrogating commercially available cell lines.

CONCLUSIONS

We demonstrate that PDC models mirror inter- and intratumor heterogeneity of ccRCC in vitro. Based on our findings, we envision that the use of these models will advance our understanding of the trajectories that cause genetic diversity and their consequences for treatment on an individual level.

PATIENT SUMMARY

In this study, we developed two- and three-dimensional patient-derived models from clear cell renal cell carcinoma (ccRCC) as "mini-tumors in a dish." We show that these cell models retain important features of the human ccRCCs such as the profound tumor heterogeneity, thus highlighting their importance for cancer research and precision medicine.

New Advances in the Study of Bone Tumors: A Lesson From the 3D Environment

Bone primary tumors, such as osteosarcoma, are highly aggressive pediatric tumors that in 30% of the cases develop lung metastasis and are characterized by poor prognosis. Bone is also the third most common metastatic site in patients with advanced cancer and once tumor cells become homed to the skeleton, the disease is usually considered incurable, and treatment is only palliative. Bone sarcoma and bone metastasis share the same tissue microenvironment and niches. 3D cultures represent a new promising approach for the study of interactions between tumor cells and other cellular or acellular components of the tumor microenvironment (i.e., fibroblasts, mesenchymal stem cells, bone ECM). Indeed, 3D models can mimic physiological interactions that are crucial to modulate response to soluble paracrine factors, tumor drug resistance and aggressiveness and, in all, these innovative models might be able of bypassing the use of animal-based preclinical cancer models. To date, both static and dynamic 3D cell culture models have been shown to be particularly suited for screening of anticancer agents and might provide accurate information, translating in vitro cell cultures into precision medicine. In this mini-review, we will summarize the current state-of-the-art in the field of bone tumors, both primary and metastatic, illustrating the different methods and techniques employed to realize 3D cell culture systems and new results achieved in a field that paves the way toward personalized medicine.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

The role of mouse tumour models in the discovery and development of anticancer drugs

Our understanding of cancer biology has increased substantially over the past 30 years. Despite this, and an increasing pharmaceutical company expenditure on research and development, the approval of novel oncology drugs during the past decade continues to be modest. In addition, the attrition of agents during clinical development remains high. This attrition can be attributed, at least in part, to the clinical development being underpinned by the demonstration of predictable efficacy in experimental models of human tumours. This review will focus on the range of models available for the discovery and development of anticancer drugs, from traditional subcutaneous injection of tumour cell lines to mice genetically engineered to spontaneously give rise to tumours. It will consider the best time to use the models, along with practical applications and shortcomings. Finally, and most importantly, it will describe how these models reflect the underlying cancer biology and how well they predict efficacy in the clinic. Developing a line of sight to the clinic early in a drug discovery project provides clear benefit, as it helps to guide the selection of appropriate preclinical models and facilitates the investigation of relevant biomarkers.

Patient-Derived Cancer Organoid Cultures to Predict Sensitivity to Chemotherapy and Radiation

PURPOSE

Cancer treatment is limited by inaccurate predictors of patient-specific therapeutic response. Therefore, some patients are exposed to unnecessary side effects and delays in starting effective therapy. A clinical tool that predicts treatment sensitivity for individual patients is needed.

EXPERIMENTAL DESIGN

Patient-derived cancer organoids were derived across multiple histologies. The histologic characteristics, mutation profile, clonal structure, and response to chemotherapy and radiation were assessed using bright-field and optical metabolic imaging on spheroid and single-cell levels, respectively.

RESULTS

We demonstrate that patient-derived cancer organoids represent the cancers from which they were derived, including key histologic and molecular features. These cultures were generated from numerous cancers, various biopsy sample types, and in different clinical settings. Next-generation sequencing reveals the presence of subclonal populations within the organoid cultures. These cultures allow for the detection of clonal heterogeneity with a greater sensitivity than bulk tumor sequencing. Optical metabolic imaging of these organoids provides cell-level quantification of treatment response and tumor heterogeneity allowing for resolution of therapeutic differences between patient samples. Using this technology, we prospectively predict treatment response for a patient with metastatic colorectal cancer.

CONCLUSIONS

These studies add to the literature demonstrating feasibility to grow clinical patient-derived organotypic cultures for treatment effectiveness testing. Together, these culture methods and response assessment techniques hold great promise to predict treatment sensitivity for patients with cancer undergoing chemotherapy and/or radiation.

Cancer modeling meets human organoid technology

Organoids are microscopic self-organizing, three-dimensional structures that are grown from stem cells in vitro. They recapitulate many structural and functional aspects of their in vivo counterpart organs. This versatile technology has led to the development of many novel human cancer models. It is now possible to create indefinitely expanding organoids starting from tumor tissue of individuals suffering from a range of carcinomas. Alternatively, CRISPR-based gene modification allows the engineering of organoid models of cancer through the introduction of any combination of cancer gene alterations to normal organoids. When combined with immune cells and fibroblasts, tumor organoids become models for the cancer microenvironment enabling immune-oncology applications. Emerging evidence indicates that organoids can be used to accurately predict drug responses in a personalized treatment setting. Here, we review the current state and future prospects of the rapidly evolving tumor organoid field.

Preclinical Modelling of PDA: Is Organoid the New Black?

Pancreatic ductal adenocarcinoma (PDA) is a malignancy of the exocrine pancreas with the worst prognosis among all solid tumours, and soon to become the second leading cause of cancer-related deaths. A more comprehensive understanding of the molecular mechanisms underlying this disease is crucial to the development of diagnostic tools as well as to the identification of more effective therapies. High-frequency mutations in PDA occur in “undruggable” genes, and molecular subtyping based on bulk transcriptome analysis does not yet nominate valid therapeutic intervention strategies. Genome-wide sequencing studies have also demonstrated a considerable intra- and inter-patient’s genetic heterogeneity, which further complicate this dire scenario. More than in other malignancies, functionalization of the PDA genome and preclinical modelling at the individual patient level appear necessary to substantially improve survival rates for pancreatic cancer patients. Traditional human PDA models, including monolayer cell cultures and patient-derived xenografts, have certainly led to valuable biological insights in the past years. However, those model systems suffer from several limitations that have contributed to the lack of concordance between preclinical and clinical studies for PDA. Pancreatic ductal organoids have recently emerged as a reliable culture system to establish models from both normal and neoplastic pancreatic tissues. Pancreatic organoid cultures can be efficiently generated from small tissue biopsies, which opens up the possibility of longitudinal studies in individual patients. A proof-of-concept study has demonstrated that patient-derived PDA organoids are able to predict responses to conventional chemotherapy. The use of this three-dimensional culture system has already improved our understanding of PDA biology and promises to implement precision oncology by enabling the alignment of preclinical and clinical platforms to guide therapeutic intervention in PDA.

Current Status of Patient-Derived Ovarian Cancer Models

Ovarian cancer (OC) is one of the leading causes of female cancer death. Recent studies have documented its extensive variations as a disease entity, in terms of cell or tissue of origin, pre-cancerous lesions, common mutations, and therapeutic responses, leading to the notion that OC is a generic term referring to a whole range of different cancer subtypes. Despite such heterogeneity, OC treatment is stereotypic; aggressive surgery followed by conventional chemotherapy could result in chemo-resistant diseases. Whereas molecular-targeted therapies will become shortly available for a subset of OC, there still remain many patients without effective drugs, requiring development of groundbreaking therapeutic agents. In preclinical studies for drug discovery, cancer cell lines used to be the gold standard, but now this has declined due to frequent failure in predicting therapeutic responses in patients. In this regard, patient-derived cells and tumors are gaining more attention in precise and physiological modeling of in situ tumors, which could also pave the way to implementation of precision medicine. In this article, we comprehensively overviewed the current status of various platforms for patient-derived OC models. We highly appreciate the potentials of organoid culture in achieving high success rate and retaining tumor heterogeneity.

Bioinformatics for precision oncology

Molecular profiling of tumor biopsies plays an increasingly important role not only in cancer research, but also in the clinical management of cancer patients. Multi-omics approaches hold the promise of improving diagnostics, prognostics and personalized treatment. To deliver on this promise of precision oncology, appropriate bioinformatics methods for managing, integrating and analyzing large and complex data are necessary. Here, we discuss the specific requirements of bioinformatics methods and software that arise in the setting of clinical oncology, owing to a stricter regulatory environment and the need for rapid, highly reproducible and robust procedures. We describe the workflow of a molecular tumor board and the specific bioinformatics support that it requires, from the primary analysis of raw molecular profiling data to the automatic generation of a clinical report and its delivery to decision-making clinical oncologists. Such workflows have to various degrees been implemented in many clinical trials, as well as in molecular tumor boards at specialized cancer centers and university hospitals worldwide. We review these and more recent efforts to include other high-dimensional multi-omics patient profiles into the tumor board, as well as the state of clinical decision support software to translate molecular findings into treatment recommendations.

Treatment resistance in urothelial carcinoma: an evolutionary perspective

The emergence of treatment-resistant clones is a critical barrier to cure in patients with urothelial carcinoma. Setting the stage for the evolution of resistance, urothelial carcinoma is characterized by extensive mutational heterogeneity, which is detectable even in patients with early stage disease. Chemotherapy and immunotherapy both act as selective pressures that shape the evolutionary trajectory of urothelial carcinoma throughout the course of the disease. A detailed understanding of the dynamics of evolutionary drivers is required for the rational development of curative therapies. Herein, we describe the molecular basis of the clonal evolution of urothelial carcinomas and the use of genomic approaches to predict treatment responses. We discuss various mechanisms of resistance to chemotherapy with a focus on the mutagenic effects of the DNA dC->dU-editing enzymes APOBEC3 family of proteins. We also review the evolutionary mechanisms underlying resistance to immunotherapy, such as the loss of clonal tumour neoantigens. By dissecting treatment resistance through an evolutionary lens, the field will advance towards true precision medicine for urothelial carcinoma.

An In Vitro System for Evaluating Molecular Targeted Drugs Using Lung Patient-Derived Tumor Organoids

Patient-derived tumor organoids (PDOs) represent a promising preclinical cancer model that better replicates disease, compared with traditional cell culture models. We have established PDOs from various human tumors to accurately and efficiently recapitulate the tissue architecture and function. Molecular targeted therapies with remarkable efficacy are currently in use against various tumors. Thus, there is a need for in vitro functional-potency assays that can be used to test the efficacy of molecular targeted drugs and model complex interactions between immune cells and tumor cells to evaluate the potential for cancer immunotherapy. This study represents an in vitro evaluation of different classes of molecular targeted drugs, including small-molecule inhibitors, monoclonal antibodies, and an antibody-drug conjugate, using lung PDOs. We evaluated epidermal growth factor receptor and human epidermal growth factor receptor 2 (HER2) inhibitors using a suitable high-throughput assay system. Next, the antibody-dependent cellular cytotoxicity (ADCC) activity of an anti-HER2 monoclonal antibody was evaluated to visualize the interactions of immune cells with PDOs during ADCC responses. Moreover, an evaluation system was developed for the immune checkpoint inhibitors, nivolumab and pembrolizumab, using PDOs. Our results demonstrate that the in vitro assay systems using PDOs were suitable for evaluating molecular targeted drugs under conditions that better reflect pathological conditions.

Application of Cancer Organoid Model for Drug Screening and Personalized Therapy

Drug screening—i.e., testing the effects of a number of drugs in multiple cell lines—is used for drug discovery and development, and can also be performed to evaluate the heterogeneity of a disease entity. Notably, intertumoral heterogeneity is a large hurdle to overcome for establishing standard cancer treatment, necessitating disease models better than conventional established 2D cell lines for screening novel treatment candidates. In the present review, we outline recent progress regarding experimental cancer models having more physiological and clinical relevance for drug screening, which are important for the successful evaluation of cellular response to drugs. The review is particularly focused on drug screening using the cancer organoid model, which is emerging as a better physiological disease model than conventional established 2D cell lines. We also review the use of cancer organoids to examine intertumor and intratumor heterogeneity, and introduce the perspective of the clinical use of cancer organoids to enable precision medicine.

Organoid technology in cancer precision medicine

Organoid technology has been remarkably improved over the last decade. Various organoids have been derived from different types of tissues and recapitulate their organ-specific gene expression signatures, particular tissue spatial structures and functions of their original tissue. The patient-derived organoids (PDOs) have been used to elucidate crucial scientific questions, including the relationships between genetic/epigenetic alterations and drug responses, cell plasticity during disease progressions, and mechanisms of drug resistances. With the great expectations, PDOs will be widely used to facilitate the personalized medical decisions, which have the potential to profoundly improve patient outcomes. In this review, we will discuss the developmental details, current achievements, applications and challenges of organoid technology in precision cancer medicine.

An acquired scaffolding function of the DNAJ-PKAc fusion contributes to oncogenic signaling in fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a rare liver cancer. FLCs uniquely produce DNAJ-PKAc, a chimeric enzyme consisting of a chaperonin-binding domain fused to the Cα subunit of protein kinase A. Biochemical analyses of clinical samples reveal that a unique property of this fusion enzyme is the ability to recruit heat shock protein 70 (Hsp70). This cellular chaperonin is frequently up-regulated in cancers. Gene-editing of mouse hepatocytes generated disease-relevant AML12^DNAJ-PKAc cell lines. Further analyses indicate that the proto-oncogene A-kinase anchoring protein-Lbc is up-regulated in FLC and functions to cluster DNAJ-PKAc/Hsp70 sub-complexes with a RAF-MEK-ERK kinase module. Drug screening reveals Hsp70 and MEK inhibitor combinations that selectively block proliferation of AML12^DNAJ-PKAc cells. Phosphoproteomic profiling demonstrates that DNAJ-PKAc biases the signaling landscape toward ERK activation and engages downstream kinase cascades. Thus, the oncogenic action of DNAJ-PKAc involves an acquired scaffolding function that permits recruitment of Hsp70 and mobilization of local ERK signaling.

Fibrolamellar carcinoma (or FLC for short) is a rare type of liver cancer that affects teenagers and young adults. FLC tumors are often resistant to standard radiotherapy or chemotherapy treatments. The only way to treat FLC is to remove tumors by surgery. However, often the tumors come back after initial treatment and spread to other locations. Therefore, there is a genuine need to improve the treatment options available to FLC patients.

The tumor cells of FLC patients contain a genetic defect that fuses together two genes, which produce proteins called DNAJ and PKAc. Normally, DNAJ helps other proteins in the cell to fold into their correct shapes, while PKAc is an enzyme that can control how cells communicate. However, it is not clear what the abnormal DNAJ-PKAc fusion protein does, or how it causes FLC.

Turnham, Smith et al. have now used gene editing to make mouse liver cells that mimic the human FLC mutation. Biochemical experiments on these cells showed that the DNAJ-PKAc protein brings together unique combinations of enzymes that drive uncontrolled cell growth. Analyzing cells taken from tumors in FLC patients confirmed that these enzymes are also activated in the human disease. Turnham, Smith et al. also found that combinations of drugs that simultaneously target the DNAJ-PKAc protein and the recruited enzymes slowed down the growth of FLC cells. More experiments are now needed to test these drug combinations on human FLC cells or in mice.

Systematic Review of Patient-Derived Xenograft Models for Preclinical Studies of Anti-Cancer Drugs in Solid Tumors

Patient-derived xenograft (PDX) models are used as powerful tools for understanding cancer biology in PDX clinical trials and co-clinical trials. In this systematic review, we focus on PDX clinical trials or co-clinical trials for drug development in solid tumors and summarize the utility of PDX models in the development of anti-cancer drugs, as well as the challenges involved in this approach, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Recently, the assessment of drug efficacy by PDX clinical and co-clinical trials has become an important method. PDX clinical trials can be used for the development of anti-cancer drugs before clinical trials, with their efficacy assessed by the modified response evaluation criteria in solid tumors (mRECIST). A few dozen cases of PDX models have completed enrollment, and the efficacy of the drugs is assessed by 1 × 1 × 1 or 3 × 1 × 1 approaches in the PDX clinical trials. Furthermore, co-clinical trials can be used for personalized care or precision medicine with the evaluation of a new drug or a novel combination. Several PDX models from patients in clinical trials have been used to assess the efficacy of individual drugs or drug combinations in co-clinical trials.

Ongoing chromosomal instability and karyotype evolution in human colorectal cancer organoids

Chromosome segregation errors cause aneuploidy and genomic heterogeneity, which are hallmarks of cancer in humans. A persistent high frequency of these errors (chromosomal instability (CIN)) is predicted to profoundly impact tumor evolution and therapy response. It is unknown, however, how prevalent CIN is in human tumors. Using three-dimensional live-cell imaging of patient-derived tumor organoids (tumor PDOs), we show that CIN is widespread in colorectal carcinomas regardless of background genetic alterations, including microsatellite instability. Cell-fate tracking showed that, although mitotic errors are frequently followed by cell death, some tumor PDOs are largely insensitive to mitotic errors. Single-cell karyotype sequencing confirmed heterogeneity of copy number alterations in tumor PDOs and showed that monoclonal lines evolved novel karyotypes over time in vitro. We conclude that ongoing CIN is common in colorectal cancer organoids, and propose that CIN levels and the tolerance for mitotic errors shape aneuploidy landscapes and karyotype heterogeneity.

[Establishment of a living biobank : Improved guidance of precision cancer care with in vitro and in vivo cancer models]

BACKGROUND

Precision oncology is a clinical approach aimed towards tailoring treatment strategies for patients based on the genetic profile of each patient's cancer. The integration of a living biobank, consisting of patient-derived tumor organoids and PDXs, with next generation sequencing approaches and high-throughput drug screening help to guide clinical decision-making and clinical trial development.

METHODS

Tumor organoids derived from fresh tumor samples were used for in vitro and in vivo high-throughput drug testing.

RESULTS

Over a period of two years we established 56 in vitro tumor organoids and 19 in vivo xenografts from 18 different solid tumor types. Tumor morphology and molecular profiles show good concordance between the in vitro and in vivo models compared to their native tumor. High-throughput drug screening (up to 160 drugs) has been tested on eight tumor organoid lines. Seven of them underwent an additional combination drug screen. We nominated several targeted small molecules and novel combinations that have been validated in corresponding xenograft models.

CONCLUSION

This precision medicine approach outlines the integration of genomic data with drug screening from personalized preclinical cancer models to guide precision cancer care. It also fuels next generation research and has been implemented for clinical trial development.

CHD1 Loss Alters AR Binding at Lineage-Specific Enhancers and Modulates Distinct Transcriptional Programs to Drive Prostate Tumorigenesis

Deletion of the gene encoding the chromatin remodeler CHD1 is among the most common alterations in prostate cancer (PCa); however, the tumor-suppressive functions of CHD1 and reasons for its tissue-specific loss remain undefined. We demonstrated that CHD1 occupied prostate-specific enhancers enriched for the androgen receptor (AR) and lineage-specific cofactors. Upon CHD1 loss, the AR cistrome was redistributed in patterns consistent with the oncogenic AR cistrome in PCa samples and drove tumor formation in the murine prostate. Notably, this cistrome shift was associated with a unique AR transcriptional signature enriched for pro-oncogenic pathways unique to this tumor subclass. Collectively, these data credential CHD1 as a tumor suppressor in the prostate that constrains AR binding/function to limit tumor progression.

Tumor organoids: From inception to future in cancer research

Tumor models have created new avenues for personalized medicine and drug development. A new culture model derived from a three-dimensional system, the tumor organoid, is gradually being used in many fields. An organoid can simulate the physiological structure and function of tissue in situ and maintain the characteristics of tumor cells in vivo, overcoming the disadvantages of traditional experimental tumor models. Organoids can mimic pathological features of tumors and maintain genetic stability, making them suitable for both molecular mechanism studies and pharmacological experiments of clinical transformation. In addition, the application of tumor organoids combined with other technologies, such as liquid biopsy technology, microraft array (MRA), and high-content screening (HCS), for the development of personalized diagnosis and cancer treatment has a promising future. In this review, we introduce the evolution of organoids and discuss their specific application and advantages. We also summarize the characteristics of several tumor organoids culture systems.

Approaches to functionally validate candidate genetic variants involved in colorectal cancer predisposition

Most next generation sequencing (NGS) studies identified candidate genetic variants predisposing to colorectal cancer (CRC) but do not tackle its functional interpretation to unequivocally recognize a new hereditary CRC gene. Besides, germline variants in already established hereditary CRC-predisposing genes or somatic variants share the same need when trying to categorize those with relevant significance. Functional genomics approaches have an important role in identifying the causal links between genetic architecture and phenotypes, in order to decipher cellular function in health and disease. Therefore, functional interpretation of identified genetic variants by NGS platforms is now essential. Available approaches nowadays include bioinformatics, cell and molecular biology and animal models. Recent advances, such as the CRISPR-Cas9, ZFN and TALEN systems, have been already used as a powerful tool with this objective. However, the use of cell lines is of limited value due to the CRC heterogeneity and its close interaction with microenvironment. Access to tridimensional cultures or organoids and xenograft models that mimic the in vivo tissue architecture could revolutionize functional analysis. This review will focus on the application of state-of-the-art functional studies to better tackle new genes involved in germline predisposition to this neoplasm.

Heterogeneous pathway activation and drug response modelled in colorectal-tumor-derived 3D cultures

Organoid cultures derived from colorectal cancer (CRC) samples are increasingly used as preclinical models for studying tumor biology and the effects of targeted therapies under conditions capturing in vitro the genetic make-up of heterogeneous and even individual neoplasms. While 3D cultures are initiated from surgical specimens comprising multiple cell populations, the impact of tumor heterogeneity on drug effects in organoid cultures has not been addressed systematically. Here we have used a cohort of well-characterized CRC organoids to study the influence of tumor heterogeneity on the activity of the KRAS/MAPK-signaling pathway and the consequences of treatment by inhibitors targeting EGFR and downstream effectors. MAPK signaling, analyzed by targeted proteomics, shows unexpected heterogeneity irrespective of RAS mutations and is associated with variable responses to EGFR inhibition. In addition, we obtained evidence for intratumoral heterogeneity in drug response among parallel “sibling” 3D cultures established from a single KRAS-mutant CRC. Our results imply that separate testing of drug effects in multiple subpopulations may help to elucidate molecular correlates of tumor heterogeneity and to improve therapy response prediction in patients.

Commonly occurring genetic alterations and patient-specific genetic features are increasingly used to predict the possible action of targeted cancer therapies. Although several lines of evidence have suggested that preclinical and clinical responses concur, the heterogeneity of tumors remains a severe obstacle in routinely translating preclinical data to patient treatments. Here we present a rapid work flow that integrates drug testing of three-dimensional patient tumor-derived (organoid) cultures and assessment of their genetic make-up as well as that of their donor tumors by amplicon sequencing and targeted proteomics. While the organoid cultures largely recapitulated the genomic profiles of donor tumors, the overall treatment responses and inhibitor effects on the intracellular signaling system were quite variable. Notably, organoid cultures obtained by synchronous multi-regional sampling of the same colorectal tumor showed an up to 30-fold difference in drug response. A combinatorial drug treatment improved the response. These data were confirmed in matched mouse xenograft models from the same tumor. Our findings may help to refine preclinical testing of individual tumors by modelling heterogeneity in cultures, to better understand therapeutic failure in clinical settings and to find ways to overcome treatment resistance.

Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment

The immense costs in both financial terms and preclinical research effort that occur in the development of anticancer drugs are unfortunately not matched by a substantial increase in improved clinical therapies due to the high rate of failure during clinical trials. This may be due to issues with toxicity or lack of clinical effectiveness when the drug is evaluated in patients. Currently, much cancer research is driven by the need to develop therapies that can exploit cancer cell adaptations to conditions in the tumor microenvironment such as acidosis and hypoxia, the requirement for more-specific, targeted treatments, or the exploitation of 'precision medicine' that can target known genomic changes in patient DNA. The high attrition rate for novel anticancer therapies suggests that the preclinical methods used in screening anticancer drugs need improvement. This chapter considers the advantages and disadvantages of 3D organotypic models in both cancer research and cancer drug screening, particularly in the areas of targeted drugs and the exploitation of genomic changes that can be used for therapeutic advantage in precision medicine.

Pleural Effusion Aspirate for use in 3D Lung Cancer Modeling and Chemotherapy Screening

Lung cancer is the leading cause of cancer-related death worldwide yet in vitro disease models have been limited to traditional 2D culture utilizing cancer cell lines. In contrast, recently developed 3D models (organoids) have been adopted by researchers to improve the physiological relevance of laboratory study. We have hypothesized that 3D hydrogel-based models will allow for improved disease replication and characterization over standard 2D culture using cells taken directly from patients. Here, we have leveraged the use of 3D hydrogel-based models to create lung cancer organoids using a unique cell source, pleural effusion aspirate, from multiple lung cancer patients. With these 3D models, we have characterized the cell populations comprising the pleural effusion aspirate and have tracked phenotypic changes that develop during short-term in vitro culture. We found that isolated, patient cells placed directly into organoids created anatomically relevant structures and exhibited lung cancer specific behaviors. On the other hand, cells first grown in plastic dishes and then cultured in 3D did not create similar structures. Further, we have been able to compare chemotherapeutic response of patient cells between 2D and 3D cell culture systems. Our results show that cells in 2D culture were more sensitive to treatment when compared with 3D organoids. Collectively, we have been able to utilize tumor cells from pleural effusion fluid of lung cancer patients to create organoids that display in vivo like anatomy and drug response and thus could serve as more accurate disease models for study of tumor progression and drug development.

Organoid Models for Cancer Research

Organoid cultures have emerged as powerful model systems accelerating discoveries in cellular and cancer biology. These three-dimensional cultures are amenable to diverse techniques, including high-throughput genome and transcriptome sequencing, as well as genetic and biochemical perturbation, making these models well suited to answer a variety of questions. Recently, organoids have been generated from diverse human cancers, including breast, colon, pancreas, prostate, bladder, and liver cancers, and studies involving these models are expanding our knowledge of the etiology and characteristics of these malignancies. Co-cultures of cancer organoids with non-neoplastic stromal cells enable investigation of the tumor microenvironment. In addition, recent studies have established that organoids have a place in personalized medicine approaches. Here, we describe the application of organoid technology to cancer discovery and treatment.

Targeting Cancer at the Intersection of Signaling and Epigenetics

While mutations resulting in the chronic activation of signaling pathways drive human cancer, the epigenetic state of a cell ultimately dictates the biological response to any given oncogenic signal. Moreover, large-scale genomic sequencing efforts have now identified a plethora of mutations in chromatin regulatory genes in human tumors, which can amplify, modify, or complement traditional oncogenic events. Nevertheless, the co-occurrence of oncogenic and epigenetic defects appears to create novel therapeutic vulnerabilities, which can be targeted by specific drug combinations. Here we discuss general mechanisms by which oncogenic and epigenetic alterations cooperate in human cancer and synthesize the field's early efforts in developing promising therapeutic combinations. Collectively, these studies reveal common themes underlying potential chemical synthetic lethal interactions and support both the expansion and refinement of this type of therapeutic approach.

Organoids as a new model for improving regenerative medicine and cancer personalized therapy in renal diseases

The pressure towards innovation and creation of new model systems in regenerative medicine and cancer research has fostered the development of novel potential therapeutic applications. Kidney injuries provoke a high request of organ transplants making it the most demanding system in the field of regenerative medicine. Furthermore, renal cancer frequently threaten patients’ life and aggressive forms still remain difficult to treat. Ethical issues related to the use of embryonic stem cells, has fueled research on adult, patient-specific pluripotent stem cells as a model for discovery and therapeutic development, but to date, normal and cancerous renal experimental models are lacking. Several research groups are focusing on the development of organoid cultures. Since organoids mimic the original tissue architecture in vitro, they represent an excellent model for tissue engineering studies and cancer therapy testing. We established normal and tumor renal cell carcinoma organoids previously maintained in a heterogeneous multi-clone stem cell-like enriching medium. Starting from adult normal kidney specimens, we were able to isolate and propagate organoid 3D-structures composed of both differentiated and undifferentiated cells while expressing nephron specific markers. Furthermore, we were capable to establish organoids derived from cancer tissues although with a success rate inferior to that of their normal counterpart. Cancer cultures displayed epithelial and mesenchymal phenotype while retaining tumor specific markers. Of note, tumor organoids recapitulated neoplastic masses when orthotopically injected into immunocompromised mice. Our data suggest an innovative approach of long-term establishment of normal- and cancer-derived renal organoids obtained from cultures of fleshly dissociated adult tissues. Our results pave the way to organ replacement pioneering strategies as well as to new models for studying drug-induced nephrotoxicity and renal diseases. Along similar lines, deriving organoids from renal cancer patients opens unprecedented opportunities for generation of preclinical models aimed at improving therapeutic treatments.