Patient-derived tumoroid models of pulmonary large-cell neuroendocrine carcinoma: a promising tool for personalized medicine and developing novel therapeutic strategies

Pulmonary large-cell neuroendocrine carcinoma (LCNEC), a disease with poor prognosis, is classified as pulmonary high-grade neuroendocrine carcinoma, along with small-cell lung cancer. However, given its infrequent occurrence, only a limited number of preclinical models have been established. Here, we established three LCNEC tumoroids for long-term culture. Whole-exome sequencing revealed that these tumoroids inherited genetic mutations from their parental tumors; two were classified as small-cell carcinoma (S-LCNEC) and one as non-small cell carcinoma (N-LCNEC). Xenografts from these tumoroids in immunodeficient mice mimicked the pathology of the parent LCNEC, and one reproduced the mixed-tissue types of combined LCNEC with a component of adenocarcinoma. Drug sensitivity tests using these LCNEC tumoroids enabled the evaluation of therapeutic agent efficacy. Based on translational research, we found that a CDK4/6 inhibitor might be effective for N-LCNEC and that Aurora A kinase inhibitors might be suitable for S-LCNEC or LCNEC with MYC amplification. These results highlight the value of preclinical tumoroid models in understanding the pathogenesis of rare cancers and developing treatments. LCNEC showed a high success rate in tumoroid establishment, indicating its potential application in personalized medicine.

Establishment and characterization of canine mammary tumoroids for translational research

BACKGROUND

Cancer heterogeneity is a main obstacle for the development of effective therapies, as its replication in in vitro preclinical models is challenging. Around 96% of developed drugs are estimated to fail from discovery to the clinical trial phase probably because of the unsuitability and unreliability of current preclinical models (Front Pharmacol 9:6, 2018; Nat Rev Cancer 8: 147-56, 2008) in replicating the overall biology of tumors, for instance the tumor microenvironment. Breast cancer is the most frequent cancer among women causing the greatest number of cancer-related deaths. Breast cancer can typically be modeled in vitro through the use of tumoroids; however, current approaches using mouse tumoroids fail to reproduce crucial aspect of human breast cancer, while access to human cells is limited and the focus of ethical concerns. New models of breast cancer, such as companion dogs, have emerged given the resemblance of developed spontaneous mammary tumors to human breast cancer in many clinical and molecular aspects; however, they have so far failed to replicate the tumor microenvironment. The present work aimed at developing a robust canine mammary tumor model in the form of tumoroids which recapitulate the tumor diversity and heterogeneity.

RESULTS

We conducted a complete characterization of canine mammary tumoroids through histologic, molecular, and proteomic analysis, demonstrating their strong similarity to the primary tumor. We demonstrated that these tumoroids can be used as a drug screening model. In fact, we showed that paclitaxel, a human chemotherapeutic, could kill canine tumoroids with the same efficacy as human tumoroids with 0.1 to 1 μM of drug needed to kill 50% of the cells. Due to easy tissue availability, canine tumoroids can be produced at larger scale and cryopreserved to constitute a biobank. We have demonstrated that cryopreserved tumoroids keep the same histologic and molecular features (ER, PR, and HER2 expression) as fresh tumoroids. Furthermore, two cryopreservation techniques were compared from a proteomic point of view which showed that tumoroids made from frozen material allowed to maintain the same molecular diversity as from freshly dissociated tumor.

CONCLUSIONS

These findings revealed that canine mammary tumoroids can be easily generated and may provide an adequate and more reliable preclinical model to investigate tumorigenesis mechanisms and develop new treatments for both veterinary and human medicine.

Comprehensive Method for Exosome Isolation and Proteome Analysis for Detection of CCN Factors in/on Exosomes

Cellular Communication Network (CCN) proteins are secretory growth factors often associated with extracellular matrix (ECM) and extracellular vesicles (EVs) such as exosomes or matrix-coated vesicles. CCN factors and fragments loaded on/in EVs may play key roles in cell communication networks in cancer biology, bone and cartilage metabolism, wound healing, and tissue regeneration. CCN proteins and EVs/exosomes are found in body fluids, such as blood, urine, milk, and supernatants of the two-dimensionally (2D) cultured cells and three-dimensionally (3D) cultured tissues, such as spheroids or organoids. More than ten methods to isolate exosomes or EVs have been developed with different properties. Here, we introduce comprehensive protocols for polymer-based precipitation, affinity purification, ultracentrifugation methods combined with the ultrafiltration method for isolating CCN-loaded exosomes/EVs from 2D and 3D cultured tissues, and proteome analysis using mass spectrometry for comprehensive analysis of CCN proteins.

Ameloblastoma modifies tumor microenvironment for enhancing invasiveness by altering collagen alignment

Tumor progression is profoundly affected by crosstalk between cancer cells and their stroma. In the past decades, the development of bioinformatics and the establishment of organoid model systems have allowed extensive investigation of the relationship between tumor cells and the tumor microenvironment (TME). However, the interaction between tumor cells and the extracellular matrix (ECM) in odontogenic epithelial neoplasms and the ECM remodeling mechanism remain unclear. In the present study, transcriptomic comparison and histopathologic analysis revealed that TME-related genes were upregulated in ameloblastoma compared to in odontogenic keratocysts. Tumoroid analysis indicated that type I collagen is required for ameloblastoma progression. Furthermore, ameloblastoma shows the capacity to remodel the ECM independently of cancer-associated fibroblasts. In conclusion, ameloblastoma-mediated ECM remodeling contributes to the formation of an invasive collagen architecture during tumor progression.

3D Culture of Primary Patient-Derived Hepatoblastoma Tumoroids

Hepatoblastoma, the most common primary liver malignancy in children, remains poorly understood due in part to a relative lack of methods to expand tumor cells in culture and a paucity of robust experimental models. Here, we describe a method to obtain primary tumor cells from patients with hepatoblastoma and to propagate the cells in 3D culture as tumor organoids, or "tumoroids". We further detail methods to prepare the tumoroids for whole-mount and cross-sectional imaging as well as to perform lentiviral transduction.

An alternative approach to tracing the volumic proliferation development of an entire tumor spheroid in 3D through a mini-Opto tomography platform

Microscopy, which is listed among the major in-situ imaging applications, allows to derive information from a biological sample on the existing architectural structures of cells and tissues and their changes over time. Large biological samples such as tumor spheroids cannot be imaged within one field of view, regional imaging in different areas and subsequent stitching are required to attain the full picture. Microscopy is not typically used to produce full-size visualization of tumor spheroids measuring a few millimeters in size. In this study, we propose a 3D volume imaging technique for tracing the growth of an entire tumor spheroid measuring up to 10 mm using a miniaturized optical (mini-Opto) tomography platform. We performed a primary analysis of the 3D imaging for the MIA PaCa-2 pancreatic tumoroid employing its 2D images produced with the mini-Opto tomography from different angles ranging from -25 ° to +25 ° at six different three-day-apart time points of consecutive image acquisition. These 2D images were reconstructed by using a 3D image reconstruction algorithm that we developed based on the algebraic reconstruction technique (ART). We were able to reconstruct the 3D images of the tumoroid to achieve 800 × 800-pixel 50-layer images at resolutions of 5-25 μm. We also created its 3D visuals to understand more clearly how its volume changed and how it looked over weeks. The volume of the tumor was calculated to be 6.761 mm³ at the first imaging time point and 46.899 mm³ 15 days after the first (at the sixth time point), which is 6.94 times larger in volume. The mini-Opto tomography can be considered more advantageous than commercial microscopy because it is portable, more cost-effective, and easier to use, and enables full-size visualization of biological samples measuring a few millimeters in size.

Molecular insights of metastasis and cancer progression derived using 3D cancer spheroid co-culture in vitro platform

The multistep metastasis process is carried out by the combinatorial effect of the stromal cells and the cancerous cells and plays vital role in the cancer progression. The scaffold/physical cues aided 3D cancer spheroid imitates the spatiotemporal organization and physiological properties of the tumor. Understanding the role of the key players in different stages of metastasis, the molecular cross-talk between the stromal cells and the cancer cells contributing in the advancement of the metastasis through 3D cancer spheroid co-culture in vitro platform is the center of discussion in the present review. This state-of-art in vitro platform utilized to study the cancer cell host defence and the role of exosomes in the cross talk leading to cancer progression has been critically examined here. 3D cancer spheroid co-culture technique is the promising next-generation in vitro approach for exploring potent treatments and personalized medicines to combat cancer metastasis leading to cancer progression.

Evaluating the transcriptional fidelity of cancer models

BACKGROUND

Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors.

METHODS

We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence.

RESULTS

We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity.

CONCLUSIONS

CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Role of cellulose family in fibril organization of collagen for forming 3D cancer spheroids: In vitro and in silico approach

Introduction: Cell aggregation of three-dimensional (3D) culture systems (the so-called spheroids) are designed as in vitro platform to represent more accurately the in vivo environment for drug discovery by using semi-solid media. The uniform multicellular tumor spheroids can be generated based on the interaction of cells with extracellular matrix (ECM) macromolecules such as collagen and integrin. This study aimed to investigate the possible interactions between the cellulose family and collagen using both in vitro and in silico approaches. Methods: The 3D microtissue of JIMT-1 cells was generated using hanging drop method to study the effects of charge and viscosity of the medium containing cellulose family. To determine the mode of interaction between cellulose derivatives (CDs) and collagen-integrin, docking analysis and molecular simulation were further performed using open source web servers and chemical simulations (GROMACS), respectively. Results: The results confirmed that the addition of CDs into the 3D medium can promote the formation of solid spheroids, where methylcellulose (MC) yielded uniform spheroids compared to carboxymethyl cellulose (CMC). Moreover, the computational analysis showed that MC interacted with both integrin and collagen, while sodium carboxymethyl cellulose (NaCMC) only interacted with collagen residues. The stated different behaviors in the 3D culture formation and collagen interaction were found in the physicochemical properties of CDs. Conclusion: Based on in vitro and in silico findings, MC is suggested as an important ECM-mimicking entity that can support the semi-solid medium and promote the formation of the uniform spheroid in the 3D culture.

Concise Review: Current Status of Three-Dimensional Organoids as Preclinical Models

Three-dimensional (3D) cultures use the property of some cells to self-organize in matrices and generate structures that can be programmed to represent an organ or a pathology. Organoid cultures are the 3D cultivation of source tissue (ranging from cells to tissue fragments) in a support matrix and specialized media that nearly resembles the physiological environment. Depending on the source tissue, growth factors, and inhibitors provided, organoids can be programmed to recapitulate the biology of a system and progression of pathology. Organoids are genetically stable, and genetically amenable, making them very suitable tools to study tissue homeostasis and cancer. In this Review, we focus on providing recent technical advances from published literature to efficiently use organoids as a tool for disease modeling and therapeutics. Also, we discuss stem cell biology principles used to generate multiple organoids and their characteristics, with a brief description of methodology. A major theme of this review is to expand organoid applications to the study disease progression and drug response in different cancers. We also discuss shortcomings, limitations, and advantages of developed 3D cultures, with the rationale behind the methodology. Stem Cells 2018;36:1329-1340.