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Preclinical Models of Solid Malignancies

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A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 33187

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Prof. Dr. Sebastian Schölch

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Guest Editor

1. NWG-KKE Translational Surgical Oncology, German Cancer Research Center, Heidelberg, Germany
2. Department of Surgery, Faculty of Medicine Mannheim, University of Heidelberg, Heidelberg, Germany
Interests: circulating tumor cells; preclinical models of cancer; minimal residual disease; gastrointestinal cancer; lung cancer; surgical oncology; gastrointestinal surgery; thoracic surgery; pleural malignancy

Prof. Dr. Christian Pilarsky

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Co-Guest Editor

Department of Surgery, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
Interests: pancreatic cancer; CRISPR/Cas; diagnosis; therapy; Kras; apoptosis
Special Issues, Collections and Topics in MDPI journals

Dr. Georg Flügen

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Co-Guest Editor

Department of Surgery, University Hospital Düsseldorf, University of Düsseldorf, 40225 Düsseldorf, Germany
Interests: dormancy; latency; diseminated tumor cells; minimal residual disease; chorioallantoic membrane model; CAM; preclinical models of cancer; metastasis; colorectal cancer; gastrointestinal cancer; surgical oncology; gastrointestinal surgery

Special Issue Information

Dear Colleagues,

Model systems are indispensable research tools in natural sciences. In cancer research, cell lines and xenograft mouse models have been the gold standard for many decades. However, the astonishingly low clinical approval rate of preclinically active compounds has made it clear that traditional, cell-line based tumor models are unable to accurately simulate the complex human disease.
In consequence, a multitude of novel tumor models have been developed in the past decade,; ranging from novel cell culture methods such as organoid culture or ex -vivo perfusion of tissue slices to avian chorioallantoic membrane (CAM) and sophisticated new animal models. Novel genetically engineered mouse models (GEMMs) of solid malignancies have been introduced in the past years and allow new insights into tumor biology as well as treatment experiments. While for the majority of solid tumors, GEMMs are now available, more tailored models for specific cancer subtypes are often still lacking. Moreover, in other malignancies (e.g., esophageal cancer), genetically engineered mouse models are still to be introduced.
Each tumor model has specific advantages and limitations, and some models are more suitable for clinical translation in a precision medicine setting than others. However, if carefully selected, novel tumor models enable cancer researchers to address their scientific questions with high accuracy and predictive power. This Special Issue will highlight the current state of the art, covering all aspects of preclinical tumor modeling in order to advance our understanding of solid tumors and their treatment.

Prof. Sebastian Schölch
Prof. Dr. Christian Pilarsky
Dr. Georg Flügen
Guest Editors

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Keywords

preclinical tumor models
organoids
3D cell culture
CAM model
genetically engineered mouse models
animal model
solid malignancy
orthotopic mouse model

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Published Papers (9 papers)

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Research

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19 pages, 3090 KiB

Open AccessArticle

Prolonged Exposure to Oxaliplatin during HIPEC Improves Effectiveness in a Preclinical Micrometastasis Model

by Nick Seyfried, Can Yurttas, Markus Burkard, Benedikt Oswald, Alexander Tolios, Franziska Herster, Joseph Kauer, Tarkan Jäger, Ingmar Königsrainer, Karolin Thiel, Markus Quante, Hans-Georg Rammensee, Sascha Venturelli, Matthias Schwab, Alfred Königsrainer, Stefan Beckert and Markus W. Löffler

Cancers 2022, 14(5), 1158; https://doi.org/10.3390/cancers14051158 - 24 Feb 2022

Cited by 6 | Viewed by 2873

Abstract

Cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy (HIPEC) was considered a promising treatment for patients with peritoneal metastasis from colorectal cancer. However, the recently published randomized controlled PRODIGE 7 trial failed to demonstrate survival benefits through the addition of short-term oxaliplatin-based HIPEC. Constituting a complex multifactorial treatment, we investigated HIPEC in a preclinical model concerning the elimination of minimal tumor residues, thereby aiming to better understand the size of effects and respective clinical trial results. Patient samples of peritoneal perfusates obtained during HIPEC treatments and oxaliplatin-containing solutions at clinically relevant dosages, conforming with established HIPEC protocols, were assessed regarding their ability to eliminate modelled ~100 µm thickness cancer cell layers. Impedance-based real-time cell analysis and classical end-point assays were used. Flow cytometry was employed to determine the effect of different HIPEC drug solvents on tumor cell properties. Effectiveness of peritoneal perfusate patient samples and defined oxaliplatin-containing solutions proved limited but reproducible. HIPEC simulations for 30 min reduced the normalized cell index below 50% with peritoneal perfusates from merely 3 out of 9 patients within 72 h, indicating full-thickness cytotoxic effects. Instead, prolonging HIPEC to 1 h enhanced these effects and comprised 7 patients’ samples, while continuous drug exposure invariably resulted in complete cell death. Further, frequently used drug diluents caused approximately 25% cell size reduction within 30 min. Prolonging oxaliplatin exposure improved effectiveness of HIPEC to eliminate micrometastases in our preclinical model. Accordingly, insufficient penetration depth, short exposure time, and the physicochemical impact of drug solvents may constitute critical factors. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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16 pages, 3893 KiB

Open AccessArticle

CRISPR-Cas9 Screen Identifies DYRK1A as a Target for Radiotherapy Sensitization in Pancreatic Cancer

by Bin Lan, Siyuan Zeng, Shuman Zhang, Xiaofan Ren, Yuming Xing, Isabella Kutschick, Susanne Pfeffer, Benjamin Frey, Nathalie Britzen-Laurent, Robert Grützmann, Nils Cordes and Christian Pilarsky

Cancers 2022, 14(2), 326; https://doi.org/10.3390/cancers14020326 - 10 Jan 2022

Cited by 12 | Viewed by 4513

Abstract

Although radiation therapy has recently made great advances in cancer treatment, the majority of patients diagnosed with pancreatic cancer (PC) cannot achieve satisfactory outcomes due to intrinsic and acquired radioresistance. Identifying the molecular mechanisms that impair the efficacy of radiotherapy and targeting these pathways are essential to improve the radiation response of PC patients. Our goal is to identify sensitive targets for pancreatic cancer radiotherapy (RT) using the kinome-wide CRISPR-Cas9 loss-of-function screen and enhance the therapeutic effect through the development and application of targeted inhibitors combined with radiotherapy. We transduced pancreatic cancer cells with a protein kinase library; 2D and 3D library cells were irradiated daily with a single dose of up to 2 Gy for 4 weeks for a total of 40 Gy using an X-ray generator. Sufficient DNA was collected for next-generation deep sequencing to identify candidate genes. In this study, we identified several cell cycle checkpoint kinases and DNA damage related kinases in 2D- and 3D-cultivated cells, including DYRK1A, whose loss of function sensitizes cells to radiotherapy. Additionally, we demonstrated that the harmine-targeted suppression of DYRK1A used in conjunction with radiotherapy increases DNA double-strand breaks (DSBs) and impairs homologous repair (HR), resulting in more cancer cell death. Our results support the use of CRISPR-Cas9 screening to identify new therapeutic targets, develop radiosensitizers, and provide novel strategies for overcoming the tolerance of pancreatic cancer to radiotherapy. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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22 pages, 5755 KiB

Open AccessArticle

Patient-Derived Xenografts of High-Grade Serous Ovarian Cancer Subtype as a Powerful Tool in Pre-Clinical Research

by Magdalena Cybula, Lin Wang, Luyao Wang, Ana Luiza Drumond-Bock, Katherine M. Moxley, Doris M. Benbrook, Camille Gunderson-Jackson, Maria J. Ruiz-Echevarria, Resham Bhattacharya, Priyabrata Mukherjee and Magdalena Bieniasz

Cancers 2021, 13(24), 6288; https://doi.org/10.3390/cancers13246288 - 15 Dec 2021

Cited by 18 | Viewed by 3279

Abstract

(1) Background. PDX models have become the preferred tool in research laboratories seeking to improve development and pre-clinical testing of new drugs. PDXs have been shown to capture the cellular and molecular characteristics of human tumors better than simpler cell line-based models. More recently, however, hints that PDXs may change their characteristics over time have begun to emerge, emphasizing the need for comprehensive analysis of PDX evolution. (2) Methods. We established a panel of high-grade serous ovarian carcinoma (HGSOC) PDXs and developed and validated a 300-SNP signature that can be successfully utilized to assess genetic drift across PDX passages and detect PDX contamination with lymphoproliferative tissues. In addition, we performed a detailed histological characterization and functional assessment of multiple PDX passages. (3) Results. Our data show that the PDXs remain largely stable throughout propagation, with marginal genetic drift at the time of PDX initiation and adaptation to mouse host. Importantly, our PDX lines retained the major histological characteristics of the original patients’ tumors even after multiple passages in mice, demonstrating a strong concordance with the clinical responses of their corresponding patients. (4) Conclusions. Our data underline the value of defined HGSOC PDXs as a pre-clinical tumor model. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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16 pages, 3082 KiB

Open AccessArticle

Deep Learning Based Automated Orthotopic Lung Tumor Segmentation in Whole-Body Mouse CT-Scans

by Wouter R. P. H. van de Worp, Brent van der Heyden, Georgios Lappas, Ardy van Helvoort, Jan Theys, Annemie M. W. J. Schols, Frank Verhaegen and Ramon C. J. Langen

Cancers 2021, 13(18), 4585; https://doi.org/10.3390/cancers13184585 - 13 Sep 2021

Cited by 13 | Viewed by 3020

Abstract

Lung cancer is the leading cause of cancer related deaths worldwide. The development of orthotopic mouse models of lung cancer, which recapitulates the disease more realistically compared to the widely used subcutaneous tumor models, is expected to critically aid the development of novel therapies to battle lung cancer or related comorbidities such as cachexia. However, follow-up of tumor take, tumor growth and detection of therapeutic effects is difficult, time consuming and requires a vast number of animals in orthotopic models. Here, we describe a solution for the fully automatic segmentation and quantification of orthotopic lung tumor volume and mass in whole-body mouse computed tomography (CT) scans. The goal is to drastically enhance the efficiency of the research process by replacing time-consuming manual procedures with fast, automated ones. A deep learning algorithm was trained on 60 unique manually delineated lung tumors and evaluated by four-fold cross validation. Quantitative performance metrics demonstrated high accuracy and robustness of the deep learning algorithm for automated tumor volume analyses (mean dice similarity coefficient of 0.80), and superior processing time (69 times faster) compared to manual segmentation. Moreover, manual delineations of the tumor volume by three independent annotators was sensitive to bias in human interpretation while the algorithm was less vulnerable to bias. In addition, we showed that besides longitudinal quantification of tumor development, the deep learning algorithm can also be used in parallel with the previously published method for muscle mass quantification and to optimize the experimental design reducing the number of animals needed in preclinical studies. In conclusion, we implemented a method for fast and highly accurate tumor quantification with minimal operator involvement in data analysis. This deep learning algorithm provides a helpful tool for the noninvasive detection and analysis of tumor take, tumor growth and therapeutic effects in mouse orthotopic lung cancer models. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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14 pages, 4344 KiB

Open AccessArticle

Nrf2/Keap1-Pathway Activation and Reduced Susceptibility to Chemotherapy Treatment by Acidification in Esophageal Adenocarcinoma Cells

by Lucie Storz, Philipp Walther, Olga Chemnitzer, Orestis Lyros, Stefan Niebisch, Matthias Mehdorn, Boris Jansen-Winkeln, Yusef Moulla, Thomas Büch, Ines Gockel and René Thieme

Cancers 2021, 13(11), 2806; https://doi.org/10.3390/cancers13112806 - 4 Jun 2021

Cited by 6 | Viewed by 2725

Abstract

Chronic acid reflux causes cellular damage and inflammation in the lower esophagus. Due to these irritating insults, the squamous epithelium is replaced by metaplastic epithelium, which is a risk factor for the development of esophageal adenocarcinoma (EAC). In this study, we investigated the acid susceptibility in a Barrett’s cell culture in vitro model, using six cell lines, derived from squamous epithelium (EPC1 and EPC2), metaplasia (CP-A), dysplasia (CP-B), and EAC (OE33 and OE19) cells. Cells exposed to acidic pH showed a decreased viability dependent on time, pH, and progression status in the Barrett’s sequence, with the highest acid susceptibility in the squamous epithelium (EPC1 and EPC2), and the lowest in EAC cells. Acid pulsing was accompanied with an activation of the Nrf2/Keap1- and the NFκB-pathway, resulting in an increased expression of HO1—independent of the cellular context. OE33 showed a decreased responsiveness towards 5-FU, when the cells were grown in acidic conditions (pH 6 and pH 5.5). Our findings suggest a strong damage of squamous epithelium by gastroesophageal reflux, while Barrett’s dysplasia and EAC cells apparently exert acid-protective features, which lead to a cellular resistance against acid reflux. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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15 pages, 2919 KiB

Open AccessArticle

Differential Effects of Trp53 Alterations in Murine Colorectal Cancer

by Alexander M. Betzler, Lahiri K. Nanduri, Barbara Hissa, Linda Blickensdörfer, Michael H. Muders, Janine Roy, Moritz Jesinghaus, Katja Steiger, Wilko Weichert, Matthias Kloor, Barbara Klink, Michael Schroeder, Massimiliano Mazzone, Jürgen Weitz, Christoph Reissfelder, Nuh N. Rahbari and Sebastian Schölch

Cancers 2021, 13(4), 808; https://doi.org/10.3390/cancers13040808 - 15 Feb 2021

Cited by 5 | Viewed by 3502

Abstract

Background: Colorectal cancer (CRC) development is a multi-step process resulting in the accumulation of genetic alterations. Despite its high incidence, there are currently no mouse models that accurately recapitulate this process and mimic sporadic CRC. We aimed to develop and characterize a genetically engineered mouse model (GEMM) of Apc/Kras/Trp53 mutant CRC, the most frequent genetic subtype of CRC. Methods: Tumors were induced in mice with conditional mutations or knockouts in Apc, Kras, and Trp53 by a segmental adeno-cre viral infection, monitored via colonoscopy and characterized on multiple levels via immunohistochemistry and next-generation sequencing. Results: The model accurately recapitulates human colorectal carcinogenesis clinically, histologically and genetically. The Trp53 R172H hotspot mutation leads to significantly increased metastatic capacity. The effects of Trp53 alterations, as well as the response to treatment of this model, are similar to human CRC. Exome sequencing revealed spontaneous protein-modifying alterations in multiple CRC-related genes and oncogenic pathways, resulting in a genetic landscape resembling human CRC. Conclusions: This model realistically mimics human CRC in many aspects, allows new insights into the role of TP53 in CRC, enables highly predictive preclinical studies and demonstrates the value of GEMMs in current translational cancer research and drug development. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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16 pages, 3130 KiB

Open AccessArticle

GAS2L1 Is a Potential Biomarker of Circulating Tumor Cells in Pancreatic Cancer

by Lei Zhu, Ke-Jia Kan, Johanna L. Grün, Barbara Hissa, Cui Yang, Balázs Győrffy, Sonja Loges, Christoph Reißfelder and Sebastian Schölch

Cancers 2020, 12(12), 3774; https://doi.org/10.3390/cancers12123774 - 15 Dec 2020

Cited by 12 | Viewed by 3534

Abstract

Pancreatic cancer is a malignant disease with high mortality and a dismal prognosis. Circulating tumor cell (CTC) detection and characterization have emerged as essential techniques for early detection, prognostication, and liquid biopsy in many solid malignancies. Unfortunately, due to the low EPCAM expression in pancreatic cancer CTCs, no specific marker is available to identify and isolate this rare cell population. This study analyzed single-cell RNA sequencing profiles of pancreatic CTCs from a genetically engineered mouse model (GEMM) and pancreatic cancer patients. Through dimensionality reduction analysis, murine pancreatic CTCs were grouped into three clusters with different biological functions. CLIC4 and GAS2L1 were shown to be overexpressed in pancreatic CTCs in comparison with peripheral blood mononuclear cells (PBMCs). Further analyses of PBMCs and RNA-sequencing datasets of enriched pancreatic CTCs were used to validate the overexpression of GAS2L1 in pancreatic CTCs. A combinatorial approach using both GAS2L1 and EPCAM expression leads to an increased detection rate of CTCs in PDAC in both GEMM and patient samples. GAS2L1 is thus proposed as a novel biomarker of pancreatic cancer CTCs. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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Review

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30 pages, 4422 KiB

Open AccessReview

In Vitro, In Vivo, and In Silico Models of Lymphangiogenesis in Solid Malignancies

by Sophie Bekisz, Louis Baudin, Florence Buntinx, Agnès Noël and Liesbet Geris

Cancers 2022, 14(6), 1525; https://doi.org/10.3390/cancers14061525 - 16 Mar 2022

Cited by 4 | Viewed by 3980

Abstract

Lymphangiogenesis (LA) is the formation of new lymphatic vessels by lymphatic endothelial cells (LECs) sprouting from pre-existing lymphatic vessels. It is increasingly recognized as being involved in many diseases, such as in cancer and secondary lymphedema, which most often results from cancer treatments. For some cancers, excessive LA is associated with cancer progression and metastatic dissemination to the lymph nodes (LNs) through lymphatic vessels. The study of LA through in vitro, in vivo, and, more recently, in silico models is of paramount importance in providing novel insights and identifying the key molecular actors in the biological dysregulation of this process under pathological conditions. In this review, the different biological (in vitro and in vivo) models of LA, especially in a cancer context, are explained and discussed, highlighting their principal modeled features as well as their advantages and drawbacks. Imaging techniques of the lymphatics, complementary or even essential to in vivo models, are also clarified and allow the establishment of the link with computational approaches. In silico models are introduced, theoretically described, and illustrated with examples specific to the lymphatic system and the LA. Together, these models constitute a toolbox allowing the LA research to be brought to the next level. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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19 pages, 690 KiB

Open AccessReview

Organoid Models for Cancer Research—From Bed to Bench Side and Back

by Carolin Kastner, Anne Hendricks, Hanna Deinlein, Mohammed Hankir, Christoph-Thomas Germer, Stefanie Schmidt and Armin Wiegering

Cancers 2021, 13(19), 4812; https://doi.org/10.3390/cancers13194812 - 26 Sep 2021

Cited by 11 | Viewed by 4242

Abstract

Organoids are a new 3D ex vivo culture system that have been applied in various fields of biomedical research. First isolated from the murine small intestine, they have since been established from a wide range of organs and tissues, both in healthy and diseased states. Organoids genetically, functionally and phenotypically retain the characteristics of their tissue of origin even after multiple passages, making them a valuable tool in studying various physiologic and pathophysiologic processes. The finding that organoids can also be established from tumor tissue or can be engineered to recapitulate tumor tissue has dramatically increased their use in cancer research. In this review, we discuss the potential of organoids to close the gap between preclinical in vitro and in vivo models as well as clinical trials in cancer research focusing on drug investigation and development. Full article

(This article belongs to the Special Issue Preclinical Models of Solid Malignancies)

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