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Xu R, Chen R, Tu C, Gong X, Liu Z, Mei L, Ren X, Li Z. 3D Models of Sarcomas: The Next-generation Tool for Personalized Medicine. PHENOMICS (CHAM, SWITZERLAND) 2024; 4:171-186. [PMID: 38884054 PMCID: PMC11169319 DOI: 10.1007/s43657-023-00111-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 05/16/2023] [Accepted: 05/23/2023] [Indexed: 06/18/2024]
Abstract
Sarcoma is a complex and heterogeneous cancer that has been difficult to study in vitro. While two-dimensional (2D) cell cultures and mouse models have been the dominant research tools, three-dimensional (3D) culture systems such as organoids have emerged as promising alternatives. In this review, we discuss recent developments in sarcoma organoid culture, with a focus on their potential as tools for drug screening and biobanking. We also highlight the ways in which sarcoma organoids have been used to investigate the mechanisms of gene regulation, drug resistance, metastasis, and immune interactions. Sarcoma organoids have shown to retain characteristics of in vivo biology within an in vitro system, making them a more representative model for sarcoma research. Our review suggests that sarcoma organoids offer a potential path forward for translational research in this field and may provide a platform for developing personalized therapies for sarcoma patients.
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Affiliation(s)
- Ruiling Xu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Ruiqi Chen
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Xiaofeng Gong
- College of Life Science, Fudan University, Shanghai, 200433 China
| | - Zhongyue Liu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Lin Mei
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Xiaolei Ren
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Zhihong Li
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
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Lu B, Curtius K, Graham TA, Yang Z, Barnes CP. CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples. Genome Biol 2023; 24:144. [PMID: 37340508 DOI: 10.1186/s13059-023-02983-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 06/08/2023] [Indexed: 06/22/2023] Open
Abstract
Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation.
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Affiliation(s)
- Bingxin Lu
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
| | - Kit Curtius
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Trevor A Graham
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
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Tumor organoid biobank-new platform for medical research. Sci Rep 2023; 13:1819. [PMID: 36725963 PMCID: PMC9892604 DOI: 10.1038/s41598-023-29065-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/30/2023] [Indexed: 02/03/2023] Open
Abstract
Organoids are a new type of 3D model for tumor research, which makes up for the shortcomings of cell lines and xenograft models, and promotes the development of personalized precision medicine. Long-term culture, expansion and storage of organoids provide the necessary conditions for the establishment of biobanks. Biobanks standardize the collection and preservation of normal or pathological specimens, as well as related clinical information. The tumor organoid biobank has a good quality control system, which is conducive to the clinical transformation and large-scale application of tumor organoids, such as disease modeling, new drug development and high-throughput drug screening. This article summarized the common tumor types of patient-derived organoid (PDO) biobanks and the necessary information for biobank construction, such as the number of organoids, morphology, success rate of culture and resuscitation, pathological types. In our results, we found that patient-derived tumor organoid (PDTO) biobanks were being established more and more, with the Netherlands, the United States, and China establishing the most. Biobanks of colorectal, pancreas, breast, glioma, and bladder cancers were established more, which reflected the relative maturity of culture techniques for these tumors. In addition, we provided insights on the precautions and future development direction of PDTO biobank building.
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Proietto M, Crippa M, Damiani C, Pasquale V, Sacco E, Vanoni M, Gilardi M. Tumor heterogeneity: preclinical models, emerging technologies, and future applications. Front Oncol 2023; 13:1164535. [PMID: 37188201 PMCID: PMC10175698 DOI: 10.3389/fonc.2023.1164535] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.
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Affiliation(s)
- Marco Proietto
- Next Generation Sequencing Core, The Salk Institute for Biological Studies, La Jolla, CA, United States
- Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States
- NOMIS Center for Immunobiology and Microbial Pathogenesis, The Salk Institute for Biological Studies, La Jolla, CA, United States
| | - Martina Crippa
- Vita-Salute San Raffaele University, Milan, Italy
- Experimental Imaging Center, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, Italy
| | - Chiara Damiani
- Infrastructure Systems Biology Europe /Centre of Systems Biology (ISBE/SYSBIO) Centre of Systems Biology, Milan, Italy
- Department of Biotechnology and Biosciences, School of Sciences, University of Milano-Bicocca, Milan, Italy
| | - Valentina Pasquale
- Infrastructure Systems Biology Europe /Centre of Systems Biology (ISBE/SYSBIO) Centre of Systems Biology, Milan, Italy
- Department of Biotechnology and Biosciences, School of Sciences, University of Milano-Bicocca, Milan, Italy
| | - Elena Sacco
- Infrastructure Systems Biology Europe /Centre of Systems Biology (ISBE/SYSBIO) Centre of Systems Biology, Milan, Italy
- Department of Biotechnology and Biosciences, School of Sciences, University of Milano-Bicocca, Milan, Italy
| | - Marco Vanoni
- Infrastructure Systems Biology Europe /Centre of Systems Biology (ISBE/SYSBIO) Centre of Systems Biology, Milan, Italy
- Department of Biotechnology and Biosciences, School of Sciences, University of Milano-Bicocca, Milan, Italy
- *Correspondence: Marco Vanoni, ; Mara Gilardi,
| | - Mara Gilardi
- NOMIS Center for Immunobiology and Microbial Pathogenesis, The Salk Institute for Biological Studies, La Jolla, CA, United States
- Salk Cancer Center, The Salk Institute for Biological Studies, La Jolla, CA, United States
- *Correspondence: Marco Vanoni, ; Mara Gilardi,
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Guan X, Huang S. Advances in the application of 3D tumor models in precision oncology and drug screening. Front Bioeng Biotechnol 2022; 10:1021966. [PMID: 36246388 PMCID: PMC9555934 DOI: 10.3389/fbioe.2022.1021966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 09/13/2022] [Indexed: 11/29/2022] Open
Abstract
Traditional tumor models cannot perfectly simulate the real state of tumors in vivo, resulting in the termination of many clinical trials. 3D tumor models’ technology provides new in vitro models that bridge the gap between in vitro and in vivo findings, and organoids maintain the properties of the original tissue over a long period of culture, which enables extensive research in this area. In addition, they can be used as a substitute for animal and in vitro models, and organoids can be established from patients’ normal and malignant tissues, with unique advantages in clinical drug development and in guiding individualized therapies. 3D tumor models also provide a promising platform for high-throughput research, drug and toxicity testing, disease modeling, and regenerative medicine. This report summarizes the 3D tumor model, including evidence regarding the 3D tumor cell culture model, 3D tumor slice model, and organoid culture model. In addition, it provides evidence regarding the application of 3D tumor organoid models in precision oncology and drug screening. The aim of this report is to elucidate the value of 3D tumor models in cancer research and provide a preclinical reference for the precise treatment of cancer patients.
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Affiliation(s)
- Xiaoyong Guan
- Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Shigao Huang
- Department of Radiation Oncology, The First Affiliated Hospital, Air Force Medical University, Xi’an, China
- *Correspondence: Shigao Huang,
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van den Bosch T, Vermeulen L, Miedema DM. Quantitative models for the inference of intratumor heterogeneity. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022. [DOI: 10.1002/cso2.1034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Louis Vermeulen
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Daniël M. Miedema
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
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