Choosing wisely - Preclinical test models in the era of precision medicine

Methods to study xenografted human cancer in genetically diverse mice

Xenografting human cancer tissues into mice to test new cures against cancers is critical for understanding and treating the disease. However, only a few inbred strains of mice are used to study cancers, and derivatives of mainly one strain, mostly NOD/ShiLtJ, are used for therapy efficacy studies. As it has been demonstrated when human cancer cell lines or patient-derived tissues (PDX) are xenografted into mice, the neoplastic cells are human but the supporting cells that comprise the tumor (the stroma) are from the mouse. Therefore, results of studies of xenografted tissues are influenced by the host strain. We previously published that when the same neoplastic cells are xenografted into different mouse strains, the pattern of tumor growth, histology of the tumor, number of immune cells infiltrating the tumor, and types of circulating cytokines differ depending on the strain. Therefore, to better comprehend the behavior of cancer in vivo, one must xenograft multiple mouse strains. Here we describe and report a series of methods that we used to reveal the genes and proteins expressed when the same cancer cell line, MDA-MB-231, is xenografted in different hosts. First, using proteomic analysis, we show how to use the same cell line in vivo to reveal the protein changes in the neoplastic cell that help it adapt to its host. Then, we show how different hosts respond molecularly to the same cell line. We also find that using multiple strains can reveal a more suitable host than those traditionally used for a "difficult to xenograft" PDX. In addition, using complex trait genetics, we illustrate a feasible method for uncovering the alleles of the host that support tumor growth. Finally, we demonstrate that Diversity Outbred mice, the epitome of a model of mouse-strain genetic diversity, can be xenografted with human cell lines or PDX using 2-deoxy-D-glucose treatment.

Fabricating a low-temperature synthesized graphene-cellulose acetate-sodium alginate scaffold for the generation of ovarian cancer spheriod and its drug assessment

3D cell culture can mimic tumor pathophysiology, which reflects cellular morphology and heterogeneity, strongly influencing gene expression, cell behavior, and intracellular signaling. It supports cell-cell and cell-matrix interaction, cell attachment, and proliferation, resulting in rapid and reliable drug screening models. We have generated an ovarian cancer spheroid in interconnected porous scaffolds. The scaffold is fabricated using low-temperature synthesized graphene, cellulose acetate, and sodium alginate. Graphene nanosheets enhance cell proliferation and aggregation, which aids in the formation of cancer spheroids. The spheroids are assessed after day 7 and 14 for the generation of reactive oxygen species (ROS), expression of the hypoxia inducing factor (HIF-1⍺) and vascular endothelial growth factor (VEGF). Production of ROS was observed due to the aggregated tumor mass, and enhanced production of HIF-1⍺ and VEGF results from a lack of oxygen and nutrition. Furthermore, the efficacy of anticancer drug doxorubicin at varying concentrations is assessed on ovarian cancer spheroids by studying the expression of caspase-3/7 at day 7 and 14. The current findings imply that the graphene-cellulose-alginate (GCA) scaffold generates a reliable ovarian cancer spheroid model to test the efficacy of the anticancer drug.

Establishment and Characterization of Patient-Derived Xenograft Model of Non-Small-Cell Lung Cancer Derived from Malignant Pleural Effusions

Purpose

Non-small-cell lung cancer (NSCLC) comprises approximately 80% of all lung malignancies. The 5-year survival rate of patients with advanced lung cancer who lost their chances of surgery is approximately 15%. Suitable animal models are important in screening individualized treatment plans for patients with lung cancer, evaluating the pre-clinical efficacy of new drugs, and conducting basic research.

Patients and Methods

In this study, we collected malignant pleural effusion (MPE) samples from 31 patients with NSCLC, successfully constructed 11 NSCLC patient-derived xenografts (PDXs), and analyzed the factors affecting their successful establishment. Primary PDX tumors were characterized using histological analysis, immunohistochemistry, short tandem repeat (STR) profiling, and cytogenetic analysis.

Results

The PDXs preserved the histopathology and protein expression pattern of parental tumors. STR analysis revealed the PDX tissue and a tumor tissue of the same individual origin. Statistical analysis showed that the survival time of patients reflected the malignant degree of MPEs to a certain extent, thus affecting the establishment of PDXs. However, the age, gender, and clinical and biochemical indicators of the patients did not affect the establishment of PDX models.

Conclusion

These data suggest that the established NSCLC PDXs preserved the molecular characteristics of primary lung cancer and can serve as a new tool to elucidate the pathogenesis of tumors, explore new treatment methods, and conduct the research and development of new drugs for tumors.

Targeting cancer drug resistance utilizing organoid technology

Cancer organoids generated from 3D in vitro cell cultures have contributed to the study of drug resistance. Maintenance of genomic and transcriptomic similarity between organoids and parental cancer allows organoids to have the ability of accurate prediction in drug resistance testing. Protocols of establishing therapy-sensitive and therapy-resistant organoids are concluded in two aspects, which are generated directly from respective patients' cancer and by induction of anti-cancer drug. Genomic and transcriptomic analyses and gene editing have been applied to organoid studies to identify key targets in drug resistance and FGFR3, KHDRBS3, lnc-RP11-536 K7.3 and FBN1 were found to be key targets. Furthermore, mechanisms contributing to resistance have been identified, including metabolic adaptation, activation of DNA damage response, defects in apoptosis, reduced cellular senescence, cellular plasticity, subpopulation interactions and gene fusions. Additionally, cancer stem cells (CSCs) have been verified to be involved in drug resistance utilizing organoid technology. Reversal of drug resistance can be achieved by targeting key genes and CSCs in cancer organoids. In this review, we summarize applications of organoids to cancer drug resistance research, indicating prospects and limitations.

The role of massive demographic databases in intractable illnesses: Denomics for dementia

Despite intensive research, effective treatments for many common and devastating diseases are lacking. For example, huge efforts and billions of dollars have been invested in Alzheimer's disease (AD), which affects over 50 million people worldwide. However, there is still no effective drug that can slow or cure AD. This relates, in part, to the absence of an animal model or cellular system that incorporates all the relevant features of the disease. Therefore, large scale studies on human populations and tissues will be key to better understanding dementia and developing methods to prevent or treat it. This is especially difficult because the dementia phenotype can result from many different processes and is likely to be affected by multiple personal and environmental variables. We hypothesize that analyzing massive volumes of demographic data that are currently available and combining this with genomic, proteomic, and metabolomic profiles of AD patients and their families, new insights into pathophysiology and treatment of AD may arise. While this requires much coordination and cooperation among large institutions, the potential for advancement would be life-changing for millions of people. In many ways this represents the next step in the information revolution started by the Human Genome Project.

Patient-derived cancer models: Valuable platforms for anticancer drug testing

Molecularly targeted treatments and immunotherapy are cornerstones in oncology, with demonstrated efficacy across different tumor types. Nevertheless, the overwhelming majority metastatic disease is incurable due to the onset of drug resistance. Preclinical models including genetically engineered mouse models, patient-derived xenografts and two- and three-dimensional cell cultures have emerged as a useful resource to study mechanisms of cancer progression and predict efficacy of anticancer drugs. However, variables including tumor heterogeneity and the complexities of the microenvironment can impair the faithfulness of these platforms. Here, we will discuss advantages and limitations of these preclinical models, their applicability for drug testing and in co-clinical trials and potential strategies to increase their reliability in predicting responsiveness to anticancer medications.

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Models of Renal Cell Carcinoma Used to Investigate Molecular Mechanisms and Develop New Therapeutics

Modeling renal cell carcinoma is critical to investigating tumor biology and therapeutic mechanisms. Multiple systems have been developed to represent critical components of the tumor and its surrounding microenvironment. Prominent in vitro models include traditional cell cultures, 3D organoid models, and microphysiological devices. In vivo models consist of murine patient derived xenografts or genetically engineered mice. Each system has unique advantages as well as limitations and researchers must thoroughly understand each model to properly investigate research questions. This review addresses common model systems for renal cell carcinoma and critically evaluates their performance and ability to measure tumor characteristics.

Monitoring and modulation of the tumor microenvironment for enhanced cancer modeling

Cancer treatments utilizing biologic or cytotoxic drugs compose the frontline of therapy, and though gains in treatment efficacy have been persistent in recent decades, much work remains in understanding cancer progression and treatment. Compounding this situation is the low rate of success when translating preclinical drug candidates to the clinic, which raises costs and development timelines. This underperformance is due in part to the poor recapitulation of the tumor microenvironment, a critical component of cancer biology, in cancer model systems. New technologies capable of both accurately observing and manipulating the tumor microenvironment are needed to effectively model cancer response to treatment. In this review, conventional cancer models are summarized, and a primer on emerging techniques for monitoring and modulating the tumor microenvironment is presented and discussed.

Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling

Ovarian cancer (OC) grows and interacts constantly with a complex microenvironment, in which immune cells, fibroblasts, blood vessels, signal molecules and the extracellular matrix (ECM) coexist. This heterogeneous environment provides structural and biochemical support to the surrounding cells and undergoes constant and dynamic remodeling that actively promotes tumor initiation, progression, and metastasis. Despite the fact that traditional 2D cell culture systems have led to relevant medical advances in cancer research, 3D cell culture models could open new possibilities for the development of an in vitro tumor microenvironment more closely reproducing that observed in vivo. The implementation of materials science and technology into cancer research has enabled significant progress in the study of cancer progression and drug screening, through the development of polymeric scaffold-based 3D models closely recapitulating the physiopathological features of native tumor tissue. This article provides an overview of state-of-the-art in vitro tumor models with a particular focus on 3D OC cell culture in pre-clinical studies. The most representative OC models described in the literature are presented with a focus on hydrogel-based scaffolds, which guarantee soft tissue-like physical properties as well as a suitable 3D microenvironment for cell growth. Hydrogel-forming polymers of either natural or synthetic origin investigated in this context are described by highlighting their source of extraction, physical-chemical properties, and application for 3D ovarian cancer cell culture.

Molecular Targets for Gastric Cancer Treatment and Future Perspectives from a Clinical and Translational Point of View

Gastric cancer is a leading cause of cancer death worldwide. Systemic treatment comprising chemotherapy and targeted therapy is the standard of care in advanced/metastatic gastric cancer. Comprehensive molecular characterization of gastric adenocarcinomas by the TCGA Consortium and ACRG has resulted in the definition of distinct molecular subtypes. These efforts have in parallel built a basis for the development of novel molecularly stratified treatment approaches. Based on this molecular characterization, an increasing number of specific genomic alterations can potentially serve as treatment targets. Consequently, the development of promising compounds is ongoing. In this review, key molecular alterations in gastric and gastroesophageal junction cancers will be addressed. Finally, the current status of the translation of targeted therapy towards clinical applications will be reviewed.

Tissue regulatory T cells: regulatory chameleons

The FOXP3⁺CD4⁺ regulatory T (T_reg) cells located in non-lymphoid tissues differ in phenotype and function from their lymphoid organ counterparts. Tissue T_reg cells have distinct transcriptomes, T cell receptor repertoires and growth and survival factor dependencies that arm them to survive and operate in their home tissue. Their functions extend beyond immune surveillance to tissue homeostasis, including regulation of local and systemic metabolism, promotion of tissue repair and regeneration, and control of the proliferation, differentiation and fate of non-lymphoid cell progenitors. T_reg cells in diverse tissues share a common FOXP3⁺CD4⁺ precursor located within lymphoid organs. This precursor undergoes definitive specialization once in the home tissue, following a multilayered array of common and tissue-distinct transcriptional programmes. Our deepening knowledge of tissue T_reg cell biology will inform ongoing attempts to harness T_reg cells for precision immunotherapeutics.

PD-1 inhibition in patient derived tissue cultures of human gastric and gastroesophageal adenocarcinoma

Emerging immunotherapies quest for better patient stratification in cancer treatment decisions. Moderate response rates of PD-1 inhibition in gastric and esophagogastric junction cancers urge for meaningful human model systems that allow for investigating immune responses ex vivo. Here, the standardized patient-derived tissue culture (PDTC) model was applied to investigate tumor response to the PD-1 inhibitor Nivolumab and the CD3/CD28 t-lymphocyte activator ImmunoCult^TM. Resident t-lymphocytes, tumor proliferation and apoptosis, as well as bulk gene expression data were analyzed after 72 h of PD-1 inhibition either as monotherapy or combined with Oxaliplatin or ImmunoCult^TM. Individual responses to PD-1 inhibition were found ex vivo and combination with chemotherapy or t-lymphocyte activation led to enhanced antitumoral effects in PDTCs. T-lymphocyte activation as well as the addition of pre-cultured peripheral blood mononuclear cells improved PDTC for studying t-lymphocyte and tumor cell communication. These data support the potential of PDTC to investigate immunotherapy ex vivo in gastric and esophagogastric junction cancer.

Therapeutic response differences between 2D and 3D tumor models of magnetic hyperthermia

Magnetic hyperthermia-based cancer therapy (MHCT) has surfaced as one of the promising techniques for inaccessible solid tumors. It involves generation of localized heat in the tumor tissues on application of an alternating magnetic field in the presence of magnetic nanoparticles (MNPs). Unfortunately, lack of precise temperature and adequate MNP distribution at the tumor site under in vivo conditions has limited its application in the biomedical field. Evaluation of in vitro tumor models is an alternative for in vivo models. However, generally used in vitro two-dimensional (2D) models cannot mimic all the characteristics of a patient's tumor and hence, fail to establish or address the experimental variables and concerns. Considering that three-dimensional (3D) models have emerged as the best possible state to replicate the in vivo conditions successfully in the laboratory for most cell types, it is possible to conduct MHCT studies with higher clinical relevance for the analysis of the selection of magnetic parameters, MNP distribution, heat dissipation, action and acquired thermotolerance in cancer cells. In this review, various forms of 3D cultures have been considered and the successful implication of MHCT on them has been summarized, which includes tumor spheroids, and cultures grown in scaffolds, cell culture inserts and microfluidic devices. This review aims to summarize the contrast between 2D and 3D in vitro tumor models for pre-clinical MHCT studies. Furthermore, we have collated and discussed the usefulness, suitability, pros and cons of these tumor models. Even though numerous cell culture models have been established, further investigations on the new pre-clinical models and selection of best fit model for successful MHCT applications are still necessary to confer a better understanding for researchers.

Engineering Breast Cancer On-chip-Moving Toward Subtype Specific Models

Breast cancer is the second leading cause of death among women worldwide, and while hormone receptor positive subtypes have a clear and effective treatment strategy, other subtypes, such as triple negative breast cancers, do not. Development of new drugs, antibodies, or immune targets requires significant re-consideration of current preclinical models, which frequently fail to mimic the nuances of patient-specific breast cancer subtypes. Each subtype, together with the expression of different markers, genetic and epigenetic profiles, presents a unique tumor microenvironment, which promotes tumor development and progression. For this reason, personalized treatments targeting components of the tumor microenvironment have been proposed to mitigate breast cancer progression, particularly for aggressive triple negative subtypes. To-date, animal models remain the gold standard for examining new therapeutic targets; however, there is room for in vitro tools to bridge the biological gap with humans. Tumor-on-chip technologies allow for precise control and examination of the tumor microenvironment and may add to the toolbox of current preclinical models. These new models include key aspects of the tumor microenvironment (stroma, vasculature and immune cells) which have been employed to understand metastases, multi-organ interactions, and, importantly, to evaluate drug efficacy and toxicity in humanized physiologic systems. This review provides insight into advanced in vitro tumor models specific to breast cancer, and discusses their potential and limitations for use as future preclinical patient-specific tools.

Patient-Derived Xenografts from Solid Tumors (PDX) for Models of Metastasis

In cancer research, availability of clinically relevant tumor models is still essential for drug testing, proof of concept studies, and also molecular analyses. To achieve this, models are of advantage, which more closely reflect heterogeneity of tumors. In this regard, patient-derived xenograft (PDX) models more closely recapitulate the native tumor biology, tissue composition, and molecular characteristics. Since metastasis is still the major challenge of tumor therapy, models are pivotal, which resemble this particular property. In this context, PDX model-derived metastasis is of particular interest for testing antimetastatic therapies for their efficacy to better target this systemic disease. This protocol describes the establishment of PDX models from tumor specimen and their applicability for PDX-derived metastasis at metastatic sites such as liver and lung, which are also clinically relevant for the systemic spread of cancer. Analysis of metastasis and methods for quantification of metastatic spread are provided.

circRNA expression profiling of colon tissue from mesalazine-treated mouse of inflammatory bowel disease reveals an important circRNA-miRNA-mRNA pathway

Mesalazine (5-aminosalicylic acid, 5-ASA) has been widely used to treat inflammatory bowel disease (IBD). However, it remains unclear about the underlying biological mechanisms of IBD pathogenesis and mesalazine treatment, which could be partially clarified by exploring the profiling of circular RNAs (circRNAs) using RNA-seq. A total of 15 mice (C57BL/6) were randomly assigned to three equally sized groups: control, dextran sulfate sodium (DSS, using DSS to induce IBD), and DSS+5-ASA (using mesalazine to treat IBD). We randomly selected three mice of each group to collect colon tissues for RNA-seq and then performed bioinformatic analysis for two comparisons: DSS vs. control and DSS+5-ASA vs. DSS. Comparisons of a series of indicators (e.g., body weight) verified the establishment of DSS-induced IBD mouse model and the effectiveness of mesalazine in treating IBD. We identified 182 differentially expressed circRNAs, including 55 up-regulated and 47 down-regulated circRNAs when comparing the DSS+5-ASA with the DSS group. These 102 circRNA-associated genes were significantly involved in the N-Glycan biosynthesis and lysine degradation. The network analysis of circRNA-miRNA-mRNAs identified an important pathway, i.e., chr10:115386962-115390436+/mmu-miR-6914-5p/Atg7, which is related to autophagy. The findings provide new insights into the biological mechanisms of IBD pathogenesis and mesalazine treatment, particularly highlighting the circRNA-miRNA-mRNA pathway.

Three-Dimensional Ex Vivo Culture for Drug Responses of Patient-Derived Gastric Cancer Tissue

Gastric cancer (GC) is one of the most common malignancies with high mortality and substantial morbidity. Although the traditional treatment strategies for GC revolve around surgery, radiotherapy, and chemotherapy, none have been able to optimally treat most affected patients. To improve clinical outcomes and overcome potential GC resistance, we established a three-dimensional (3D) culturing platform that accurately predicts drug responses in a time- and cost-effective manner. We collected tumor tissues from patients following surgeries and cultured them for 3 days using our protocol. We first evaluated cell proliferation, viability, and apoptosis using the following markers: Ki67 and cleaved caspase 3 (Cas3). We demonstrated that cell viability was maintained for 72 h in culture and that the tumor microenvironments and vascular integrities of the tissues were intact throughout the culture period. We then administered chemotherapeutics to assess drug responses and found differential sensitivity across different patient-derived tissues, enabling us to determine individualized medication plans. Overall, our study validated this rapid, cost-effective, scalable, and reproducible protocol for GC tissue culture that can be employed for drug response assessments. Our 3D culture platform paves a new way for personalized medication in GC and other tumors and can greatly impact future oncological research.

Single-Cell Gene Network Analysis and Transcriptional Landscape of MYCN-Amplified Neuroblastoma Cell Lines

Neuroblastoma (NBL) is a pediatric cancer responsible for more than 15% of cancer deaths in children, with 800 new cases each year in the United States alone. Genomic amplification of the MYC oncogene family member MYCN characterizes a subset of high-risk pediatric neuroblastomas. Several cellular models have been implemented to study this disease over the years. Two of these, SK-N-BE-2-C (BE2C) and Kelly, are amongst the most used worldwide as models of MYCN-Amplified human NBL. Here, we provide a transcriptome-wide quantitative measurement of gene expression and transcriptional network activity in BE2C and Kelly cell lines at an unprecedented single-cell resolution. We obtained 1105 Kelly and 962 BE2C unsynchronized cells, with an average number of mapped reads/cell of roughly 38,000. The single-cell data recapitulate gene expression signatures previously generated from bulk RNA-Seq. We highlight low variance for commonly used housekeeping genes between different cells (ACTB, B2M and GAPDH), while showing higher than expected variance for metallothionein transcripts in Kelly cells. The high number of samples, despite the relatively low read coverage of single cells, allowed for robust pathway enrichment analysis and master regulator analysis (MRA), both of which highlight the more mesenchymal nature of BE2C cells as compared to Kelly cells, and the upregulation of TWIST1 and DNAJC1 transcriptional networks. We further defined master regulators at the single cell level and showed that MYCN is not constantly active or expressed within Kelly and BE2C cells, independently of cell cycle phase. The dataset, alongside a detailed and commented programming protocol to analyze it, is fully shared and reusable.

Patient-derived xenograft (PDX) models of colorectal carcinoma (CRC) as a platform for chemosensitivity and biomarker analysis in personalized medicine

Patient-derived xenograft (PDX) tumor models represent a valuable platform for identifying new biomarkers and novel targets, to evaluate therapy response and resistance mechanisms. This study aimed at establishment, characterization and therapy testing of colorectal carcinoma-derived PDX. We generated 49 PDX and validated identity between patient tumor and corresponding PDX. Sensitivity of PDX toward conventional and targeted drugs revealed that 92% of PDX responded toward irinotecan, 45% toward 5-FU, 65% toward bevacizumab, and 61% toward cetuximab. Expression of epidermal growth factor receptor (EGFR) ligands correlated to the sensitivity toward cetuximab. Proto-oncogene B-RAF, EGFR, Kirsten rat sarcoma virus oncogene homolog gene copy number correlated positively with cetuximab and erlotinib sensitivity. The mutational analyses revealed an individual mutational profile of PDX and mainly identical profiles of PDX from primary tumor vs corresponding metastasis. Mutation in PIK3CA was a determinant of accelerated tumor doubling time. PDX with wildtype Kirsten rat sarcoma virus oncogene homolog, proto-oncogene B-RAF, and phosphatidylinositol-4,5-bisphosphate 3-kinaseM catalytic subunit alfa showed higher sensitivity toward cetuximab and erlotinib. To study the molecular mechanism of cetuximab resistance, cetuximab resistant PDX models were generated, and changes in HER2, HER3, betacellulin, transforming growth factor alfa were observed. Global proteome and phosphoproteome profiling showed a reduction in canonical EGFR-mediated signaling via PTPN11 (SHP2) and AKT1S1 (PRAS40) and an increase in anti-apoptotic signaling as a consequence of acquired cetuximab resistance. This demonstrates that PDX models provide a multitude of possibilities to identify and validate biomarkers, signaling pathways and resistance mechanisms for clinically relevant improvement in cancer therapy.

RNA Sequencing of Hepatobiliary Cancer Cell Lines: Data and Applications to Mutational and Transcriptomic Profiling

Cancer cell lines allow the identification of clinically relevant alterations and the prediction of drug response. However, sequencing data for hepatobiliary cancer cell lines in general, and particularly gallbladder cancer (GBC), are sparse. Here, we apply RNA sequencing to characterize 10 GBC, eight hepatocellular carcinoma, and five cholangiocarcinoma (CCA) cell lines. RNA extraction, quality control, library preparation, sequencing, and pre-processing of sequencing data were implemented using state-of-the-art techniques. Public data from the MSK-IMPACT database and a large cohort of Japanese biliary tract cancer patients were used to illustrate the usage of the released data. The total number of exonic mutations varied from 7207 for the cell line NOZ to 9760 for HuCCT1. Researchers planning experiments that require TP53 mutations could use the cell lines NOZ, OCUG-1, SNU308, or YoMi. Mz-Cha-1 showed mutations in ATM, SNU308 presented SMAD4 mutations, and the only investigated cell line that showed ARID1A mutations was GB-d1. SNU478 was the cell line with the global gene expression pattern most similar to GBC, intrahepatic CCA, and extrahepatic CCA. EGFR, KMT2D, and KMT2C generally presented a higher expression in the investigated cell lines than in Japanese primary GBC tumors. We provide the scientific community with detailed mutation and gene expression data, together with three showcase applications, with the aim of facilitating the design of future in vitro cell culture assays for research on hepatobiliary cancer.

Modeling clear cell renal cell carcinoma and therapeutic implications

Renal cell carcinoma (RCC) comprises a diverse group of malignancies arising from the nephron. The most prevalent type, clear cell renal cell carcinoma (ccRCC), is characterized by genetic mutations in factors governing the hypoxia signaling pathway, resulting in metabolic dysregulation, heightened angiogenesis, intratumoral heterogeneity, and deleterious tumor microenvironmental (TME) crosstalk. Identification of specific genetic variances has led to therapeutic innovation and improved survival for patients with ccRCC. Current barriers to effective long-term therapeutic success highlight the need for continued drug development using improved modeling systems. ccRCC preclinical models can be grouped into three broad categories: cell line, mouse, and 3D models. Yet, the breadth of important unanswered questions in ccRCC research far exceeds the accessibility of model systems capable of carrying them out. Accordingly, we review the strengths, weaknesses, and therapeutic implications of each model system that are relied upon today.

Deep sequencing and automated histochemistry of human tissue slice cultures improve their usability as preclinical model for cancer research

Cancer research requires models closely resembling the tumor in the patient. Human tissue cultures can overcome interspecies limitations of animal models or the loss of tissue architecture in in vitro models. However, analysis of tissue slices is often limited to histology. Here, we demonstrate that slices are also suitable for whole transcriptome sequencing and present a method for automated histochemistry of whole slices. Tumor and peritumoral tissue from a patient with glioblastoma was processed to slice cultures, which were treated with standard therapy including temozolomide and X-irradiation. Then, RNA sequencing and automated histochemistry were performed. RNA sequencing was successfully accomplished with a sequencing depth of 243 to 368 x 10⁶ reads per sample. Comparing tumor and peritumoral tissue, we identified 1888 genes significantly downregulated and 2382 genes upregulated in tumor. Treatment significantly downregulated 2017 genes, whereas 1399 genes were upregulated. Pathway analysis revealed changes in the expression profile of treated glioblastoma tissue pointing towards downregulated proliferation. This was confirmed by automated analysis of whole tissue slices stained for Ki67. In conclusion, we demonstrate that RNA sequencing of tissue slices is possible and that histochemical analysis of whole tissue slices can be automated which increases the usability of this preclinical model.

Modulation of Respiration and Mitochondrial Dynamics by SMAC-Mimetics for Combination Therapy in Chemoresistant Cancer

Inhibitor of apoptosis proteins (IAP) are cell death regulators that bind caspases and interfere with apoptotic signalling via death receptors or intrinsic cell death pathways. BIRC4/XIAP is the most potent anti-apoptotic IAP-member and it physically interacts with caspases via its BIR2 and its BIR3 domain. These domains are also critical for the interaction with mitochondria-derived SMAC/Diablo and with the IAP protein survivin. Survivin is frequently overexpressed in neuroblastoma due to a gain of 17q and we have demonstrated that survivin confers resistance to chemotherapeutic agents and reprograms metabolism of neuroblastoma cells towards glycolysis. As regulator of mitochondrial fission and autophagy survivin acts at the crossroads of mitochondrial architecture, autophagy and cellular energy metabolism.

Methods: We tested the effect of SMAC-mimetics on the XIAP/survivin axis as modulator of cellular metabolism analysing mitochondrial morphology, metabolic intermediates and cellular survival. Finally, the impact of the combined treatment was evaluated in a xenograft neuroblastoma mouse model assessing the therapy effect on tumour size and volume.

Results: Here we demonstrated that XIAP sequesters significant amounts of survivin within the cell that can be mobilized by so called SMAC-mimetics. SMAC-mimetics are drugs that are designed to bind with high affinity to XIAP-BIR2 / BIR3 domains to release caspases and re-sensitize XIAP-overexpressing tumors for chemotherapy. However, SMAC-mimetic treatment releases also survivin from XIAP and thereby induces mitochondrial fragmentation, prevents ROS accumulation and leads to the Warburg effect, an unwanted side effect of this therapy. Importantly, cells that drift into a highly glycolytic state due to SMAC-mimetic treatment become also highly sensitive to non-genotoxic treatment with glycolysis inhibitors such as 2-Deoxy-D-glucose (2DG) in vitro and in vivo.

Conclusion: A combinational therapy of non-genotoxic SMAC-mimetics and glycolysis-inhibitors overcomes IAP-mediated cell survival in cancer and provides therefore an attractive usage of SMAC-mimetics.

3D Cell-Based Assays for Drug Screens: Challenges in Imaging, Image Analysis, and High-Content Analysis

The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity.

Metastatic Tumor-in-a-Dish, a Novel Multicellular Organoid to Study Lung Colonization and Predict Therapeutic Response

Metastasis is a major cause of cancer-related deaths. A dearth of preclinical models that recapitulate the metastatic microenvironment has impeded the development of therapeutic agents that are effective against metastatic disease. Because the majority of solid tumors metastasize to the lung, we developed a multicellular lung organoid that mimics the lung microenvironment with air sac-like structures and production of lung surfactant protein. We used these cultures, called primitive lung-in-a-dish (PLiD), to recreate metastatic disease using primary and established cancer cells. The metastatic tumor-in-a-dish (mTiD) cultures resemble the architecture of metastatic tumors in the lung, including angiogenesis. Pretreating PLiD with tumor exosomes enhanced cancer cell colonization. We next tested the response of primary and established cancer cells to current chemotherapeutic agents and an anti-VEGF antibody in mTiD against cancer cells in two-dimensional (2D) or 3D cultures. The response of primary patient-derived colon and ovarian tumor cells to therapy in mTiD cultures matched the response of the patient in the clinic, but not in 2D or single-cell-type 3D cultures. The sensitive mTiD cultures also produced significantly lower circulating markers for cancer similar to that seen in patients who responded to therapy. Thus, we have developed a novel method for lung colonization in vitro, a final stage in tumor metastasis. Moreover, the technique has significant utility in precision/personalized medicine, wherein this phenotypic screen can be coupled with current DNA pharmacogenetics to identify the ideal therapeutic agent, thereby increasing the probability of response to treatment while reducing unnecessary side effects. SIGNIFICANCE: A lung organoid that exhibits characteristics of a normal human lung is developed to study the biology of metastatic disease and therapeutic intervention.

Differential innervation of tissues located at traditional acupuncture points in the rat forehead and face

OBJECTIVES

To compare the neural pathways associated with the tissues located at different traditional acupuncture points in the rat forehead and face using the cholera toxin B subunit (CTB) neural tracing technique.

METHODS

After injection of CTB into the tissues at GB14, ST2 and ST6 in the rat, the neural labelling associated with each acupuncture point was revealed by fluorescent immunohistochemistry of the nervous system, including the trigeminal ganglion (TRG), cervical dorsal root ganglia (DRG), spinal cord and brain.

RESULTS

The CTB labelling included sensory neurons and their transganglionic axonal terminals, as well as motor neurons. The labelled sensory neurons associated with GB14, ST2 and ST6 were distributed in both the TRG and cervical DRG, and their centrally projected axons terminated in an orderly fashion at their corresponding targets in the spinal trigeminal nucleus and cervical spinal dorsal horn. In addition, labelled motor neurons were observed in the facial motor nucleus, trigeminal motor nucleus and cervical spinal ventral horn, in which facial motor neurons projected to the tissues located at all three acupuncture points. Trigeminal motor neurons innervated both ST2 and ST6, while spinal motor neurons only correlated with ST6.

CONCLUSIONS

These results indicate that the tissues located at each of these three traditional acupuncture points in the rat forehead and face has its own sensory and motor connection with the nervous system in a region-specific pattern through distinct neural pathways. Understanding the neuroanatomical characteristics of acupuncture points from the peripheral nervous system to the central nervous system should help inform acupuncture point selection according to the demands of the clinical situation.

Preclinical optimization of antibody-based radiopharmaceuticals for cancer imaging and radionuclide therapy-Model, vector, and radionuclide selection

Intact antibodies and their truncated counterparts (eg, Fab, scFv fragments) are generally exquisitely specific and selective vectors, enabling recognition of individual cancer-associated molecular phenotypes against a complex and dynamic biomolecular background. Complementary alignment of these advantages with unique properties of radionuclides is a defining paradigm in both radioimmunoimaging and radioimmunotherapy, which remain some of the most adept and promising tools for cancer diagnosis and treatment. This review discusses how translational potency can be maximized through rational selection of antibody-nuclide couples for radioimmunoimaging/therapy in preclinical models.

Patient-derived conditionally reprogrammed cells maintain intra-tumor genetic heterogeneity

Preclinical in vitro models provide an essential tool to study cancer cell biology as well as aid in translational research, including drug target identification and drug discovery efforts. For any model to be clinically relevant, it needs to recapitulate the biology and cell heterogeneity of the primary tumor. We recently developed and described a conditional reprogramming (CR) cell technology that addresses many of these needs and avoids the deficiencies of most current cancer cell lines, which are usually clonal in origin. Here, we used the CR cell method to generate a collection of patient-derived cell cultures from non-small cell lung cancers (NSCLC). Whole exome sequencing and copy number variations are used for the first time to address the capability of CR cells to keep their tumor-derived heterogeneity. Our results indicated that these primary cultures largely maintained the molecular characteristics of the original tumors. Using a mutant-allele tumor heterogeneity (MATH) score, we showed that CR cells are able to keep and maintain most of the intra-tumoral heterogeneity, suggesting oligoclonality of these cultures. CR cultures therefore represent a pre-clinical lung cancer model for future basic and translational studies.

Comparing the genomes of cutaneous melanoma tumors to commercially available cell lines

Insulated culture environment and prolonged propagation contribute to known limitations of cell lines, and selection is often limited to availability or favorable growth characteristics. To better characterize and improve selection of cell lines, we compared 60 melanoma cell lines profiled by the Cancer Cell Line Encyclopedia and 472 cutaneous melanoma tumors profiled by The Cancer Genome Atlas by DNA sequence and copy number alterations. All samples were scored for stromal and immune cell composition by the ESTIMATE algorithm, and 412 tumors with ≥ 60% tumor cell fraction were compared to cell lines. Uncharacterized early passage cell lines that lacked BRAF, NRAS, or NF1 mutations had near zero mean Pearson correlation of copy number alterations per gene to tumors and also tended to have higher stromal scores. The Comet Exact Test was applied to tumors and cell lines identifying three pairs of genes mutated in a mutually exclusive pattern in tumors but not cell lines: BRAF and NRAS, BRAF and NF1, as well as NRAS and PTEN. Additionally, 31 genes were more frequently mutated in cell lines than tumors. Avoiding cell lines with co-occurring mutually exclusive mutations and the fewest differentially mutated genes within a known distribution of genetic similarity to tumors by copy number alterations may optimize selection.

Modeling phenotypes of malignant gliomas

Malignant gliomas are primary tumors of the central nervous system characterized by diffuse infiltration into the brain and a high recurrence rate. Advances in comprehensive genomic studies have provided unprecedented insight into the genetic and molecular heterogeneity of these tumors and refined our understanding of their evolution from low to high grade. However, similar levels of phenotypic characterization are indispensable to understanding the complexity of malignant gliomas. Experimental glioma models have also achieved great progress in recent years. Advances in transgenic technologies and cell culture have allowed the establishment of mouse models that mirror the human disease with increasing fidelity and which support single-cell resolution for phenotypic analyses. Here we review the major types of preclinical glioma models, with an emphasis on how recent developments in experimental modeling have shed new light on two fundamental aspects of glioma phenotype, their cell of origin and their invasive potential.

Species-specific real-time RT-PCR analysis of expression of stromal cell genes in a tumor xenotransplantation model in mice

Human tumor xenografts in mice together with the species-specific analysis of expressed genes allow to study the molecular processes driving tumor growth and progression in vivo and help to develop and evaluate anticancer therapies. In the present work, we designed and validated species-specific real-time RT-PCR assays for discrimination and quantitation of expression of human and mouse transcripts in cancer and stromal cells including dipeptidyl peptidase (DPP) 4, DPP8, DPP9, fibroblast activation protein (FAP) and CXC chemokine receptor 4 in mixed human-mouse biological samples. Using single species RNA samples and mixed human-mouse RNA samples, we formulated and characterized two-step real-time RT-PCR assays to quantitate expression of the indicated transcripts and described analytical performance of the assays. We also demonstrated the applicability of these assays for species-specific quantitation of transcriptional expression of mouse stromal cell genes including Dpp4, Dpp8, Dpp9, Fap and Cxcr4 in mixed human-mouse RNA samples from human glioma cell-derived tumor xenografts growing in mouse brain.