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Fűr GM, Nemes K, Magó É, Benő AÁ, Topolcsányi P, Moldvay J, Pongor LS. Applied models and molecular characteristics of small cell lung cancer. Pathol Oncol Res 2024; 30:1611743. [PMID: 38711976 PMCID: PMC11070512 DOI: 10.3389/pore.2024.1611743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 04/03/2024] [Indexed: 05/08/2024]
Abstract
Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.
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Affiliation(s)
- Gabriella Mihalekné Fűr
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Kolos Nemes
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Éva Magó
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
- Genome Integrity and DNA Repair Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Alexandra Á. Benő
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Petronella Topolcsányi
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Judit Moldvay
- Department of Pulmonology, Szeged University Szent-Gyorgyi Albert Medical School, Szeged, Hungary
- 1st Department of Pulmonology, National Koranyi Institute of Pulmonology, Budapest, Hungary
| | - Lőrinc S. Pongor
- Cancer Genomics and Epigenetics Core Group, Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
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2
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Lê H, Deforges J, Cutolo P, Lamarque A, Hua G, Lindner V, Jain S, Balloul JM, Benkirane-Jessel N, Quéméneur E. Patient-derived tumoroids and proteomic signatures: tools for early drug discovery. Front Immunol 2024; 15:1379613. [PMID: 38698850 PMCID: PMC11063793 DOI: 10.3389/fimmu.2024.1379613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 03/14/2024] [Indexed: 05/05/2024] Open
Abstract
Onco-virotherapy is an emergent treatment for cancer based on viral vectors. The therapeutic activity is based on two different mechanisms including tumor-specific oncolysis and immunostimulatory properties. In this study, we evaluated onco-virotherapy in vitro responses on immunocompetent non-small cell lung cancer (NSCLC) patient-derived tumoroids (PDTs) and healthy organoids. PDTs are accurate tools to predict patient's clinical responses at the in vitro stage. We showed that onco-virotherapy could exert specific antitumoral effects by producing a higher number of viral particles in PDTs than in healthy organoids. In the present work, we used multiplex protein screening, based on proximity extension assay to highlight different response profiles. Our results pointed to the increase of proteins implied in T cell activation, such as IFN-γ following onco-virotherapy treatment. Based on our observation, oncolytic viruses-based therapy responders are dependent on several factors: a high PD-L1 expression, which is a biomarker of greater immune response under immunotherapies, and the number of viral particles present in tumor tissue, which is dependent to the metabolic state of tumoral cells. Herein, we highlight the use of PDTs as an alternative in vitro model to assess patient-specific responses to onco-virotherapy at the early stage of the preclinical phases.
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Affiliation(s)
- Hélène Lê
- Transgene S.A., Illkirch–Graffenstaden, France
- INSERM UMR1260, Regenerative Nanomedicine, Strasbourg, France
| | | | | | | | - Guoqiang Hua
- INSERM UMR1260, Regenerative Nanomedicine, Strasbourg, France
| | - Véronique Lindner
- INSERM UMR1260, Regenerative Nanomedicine, Strasbourg, France
- Department of Pathology, Hopitaux Universitaires de Strasbourg, Strasbourg, France
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3
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Yan S, He Y, Zhu Y, Ye W, Chen Y, Zhu C, Zhan F, Ma Z. Human patient derived organoids: an emerging precision medicine model for gastrointestinal cancer research. Front Cell Dev Biol 2024; 12:1384450. [PMID: 38638528 PMCID: PMC11024315 DOI: 10.3389/fcell.2024.1384450] [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: 02/09/2024] [Accepted: 03/22/2024] [Indexed: 04/20/2024] Open
Abstract
Gastrointestinal cancers account for approximately one-third of the total global cancer incidence and mortality with a poor prognosis. It is one of the leading causes of cancer-related deaths worldwide. Most of these diseases lack effective treatment, occurring as a result of inappropriate models to develop safe and potent therapies. As a novel preclinical model, tumor patient-derived organoids (PDOs), can be established from patients' tumor tissue and cultured in the laboratory in 3D architectures. This 3D model can not only highly simulate and preserve key biological characteristics of the source tumor tissue in vitro but also reproduce the in vivo tumor microenvironment through co-culture. Our review provided an overview of the different in vitro models in current tumor research, the derivation of cells in PDO models, and the application of PDO model technology in gastrointestinal cancers, particularly the applications in combination with CRISPR/Cas9 gene editing technology, tumor microenvironment simulation, drug screening, drug development, and personalized medicine. It also elucidates the ethical status quo of organoid research and the current challenges encountered in clinical research, and offers a forward-looking assessment of the potential paths for clinical organoid research advancement.
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Affiliation(s)
- Sicheng Yan
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yuxuan He
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yuehong Zhu
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Wangfang Ye
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yan Chen
- Department of Colorectal Surgery, Huzhou Central Hospital, The Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China
| | - Cong Zhu
- Department of Colorectal Surgery, Huzhou Central Hospital, The Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China
| | - Fuyuan Zhan
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhihong Ma
- Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, The Affiliated Central Hospital of Huzhou University, Huzhou, China
- School of Basic Medicine College, Zhejiang Chinese Medical University, Hangzhou, China
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4
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Luan Q, Pulido I, Isagirre A, Carretero J, Zhou J, Shimamura T, Papautsky I. Deciphering fibroblast-induced drug resistance in non-small cell lung carcinoma through patient-derived organoids in agarose microwells. LAB ON A CHIP 2024; 24:2025-2038. [PMID: 38410967 DOI: 10.1039/d3lc01044a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Patient-derived organoids (PDOs) serve as invaluable 3D tumor models, retaining the histological complexity and genetic heterogeneity found in primary tumors. However, the limitation of small sample volumes and the lack of tailored platforms have hindered the research using PDOs. Within the tumor microenvironment, cancer-associated fibroblasts play a pivotal role in influencing drug sensitivity. In this study, we introduce an agarose microwell platform designed for PDO-based tumor and tumor microenvironment models, enabling rapid drug screening and resistance studies with small sample volumes. These microwells, constructed using 3D printing molds, feature a U-shaped bottom and 200 μm diameter. We successfully generated co-culture spheroids of non-small cell lung carcinoma (NSCLC) cells, including NCI-H358 or A549, and NSCLC PDOs F231 or F671 with fibroblast cell line, WI-38. Our results demonstrate the production of uniformly-sized spheroids (coefficient of variation <30%), high viability (>80% after 1 week), and fibroblast-induced drug resistance. The PDOs maintained their viability (>81% after 2 weeks) and continued to proliferate. Notably, when exposed to adagrasib, a KRASG12C inhibitor, we observed reduced cytotoxicity in KRASG12C-mutant spheroids when co-cultured with fibroblasts or their supernatant. The fibroblast supernatant sustained proliferative signals in tumor models. Taking into account the physical features, viability, and drug resistance acquired through supernatants from the fibroblasts, our platform emerges as a suitable platform for in vitro tumor modeling and the evaluation of drug efficacy using patient-derived tissues.
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Affiliation(s)
- Qiyue Luan
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, 851 S. Morgan Street, 218 SEO, Chicago, IL 60607, USA.
| | - Ines Pulido
- Department of Surgery, University of Illinois Chicago, Chicago, IL 60612, USA
- University of Illinois Cancer Center, Chicago, IL 60612, USA
| | - Angelique Isagirre
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, 851 S. Morgan Street, 218 SEO, Chicago, IL 60607, USA.
| | - Julian Carretero
- Departament de Fisiologia, Facultat de Farmacia, Universitat de Valencia, Burjassot, 46010, Spain
| | - Jian Zhou
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, 851 S. Morgan Street, 218 SEO, Chicago, IL 60607, USA.
- University of Illinois Cancer Center, Chicago, IL 60612, USA
| | - Takeshi Shimamura
- Department of Surgery, University of Illinois Chicago, Chicago, IL 60612, USA
- University of Illinois Cancer Center, Chicago, IL 60612, USA
| | - Ian Papautsky
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, 851 S. Morgan Street, 218 SEO, Chicago, IL 60607, USA.
- University of Illinois Cancer Center, Chicago, IL 60612, USA
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5
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Yang X, Yang C, Zhang S, Geng H, Zhu AX, Bernards R, Qin W, Fan J, Wang C, Gao Q. Precision treatment in advanced hepatocellular carcinoma. Cancer Cell 2024; 42:180-197. [PMID: 38350421 DOI: 10.1016/j.ccell.2024.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/01/2023] [Accepted: 01/17/2024] [Indexed: 02/15/2024]
Abstract
The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.
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Affiliation(s)
- Xupeng Yang
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Chen Yang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Shu Zhang
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Haigang Geng
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Andrew X Zhu
- I-Mab Biopharma, Shanghai, China; Jiahui International Cancer Center, Jiahui Health, Shanghai, China
| | - René Bernards
- Division of Molecular Carcinogenesis, Oncode Institute, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Wenxin Qin
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jia Fan
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Cun Wang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
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6
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Vaishnavi A, Kinsey CG, McMahon M. Preclinical Modeling of Pathway-Targeted Therapy of Human Lung Cancer in the Mouse. Cold Spring Harb Perspect Med 2024; 14:a041385. [PMID: 37788883 PMCID: PMC10760064 DOI: 10.1101/cshperspect.a041385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Animal models, particularly genetically engineered mouse models (GEMMs), continue to have a transformative impact on our understanding of the initiation and progression of hematological malignancies and solid tumors. Furthermore, GEMMs have been employed in the design and optimization of potent anticancer therapies. Increasingly, drug responses are assessed in mouse models either prior, or in parallel, to the implementation of precision medical oncology, in which groups of patients with genetically stratified cancers are treated with drugs that target the relevant oncoprotein such that mechanisms of drug sensitivity or resistance may be identified. Subsequently, this has led to the design and preclinical testing of combination therapies designed to forestall the onset of drug resistance. Indeed, mouse models of human lung cancer represent a paradigm for how a wide variety of GEMMs, driven by a variety of oncogenic drivers, have been generated to study initiation, progression, and maintenance of this disease as well as response to drugs. These studies have now expanded beyond targeted therapy to include immunotherapy. We highlight key aspects of the relationship between mouse models and the evolution of therapeutic approaches, including oncogene-targeted therapies, immunotherapies, acquired drug resistance, and ways in which successful antitumor strategies improve on efficiently translating preclinical approaches into successful antitumor strategies in patients.
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Affiliation(s)
- Aria Vaishnavi
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah 84112, USA
| | - Conan G Kinsey
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah 84112, USA
- Department of Internal Medicine, University of Utah, Salt Lake City, Utah 84112, USA
| | - Martin McMahon
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah 84112, USA
- Department of Dermatology, University of Utah, Salt Lake City, Utah 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, Utah 84112, USA
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7
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Zou J, Shah O, Chiu YC, Ma T, Atkinson JM, Oesterreich S, Lee AV, Tseng GC. Systems approach for congruence and selection of cancer models towards precision medicine. PLoS Comput Biol 2024; 20:e1011754. [PMID: 38198519 PMCID: PMC10805322 DOI: 10.1371/journal.pcbi.1011754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 01/23/2024] [Accepted: 12/12/2023] [Indexed: 01/12/2024] Open
Abstract
Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.
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Affiliation(s)
- Jian Zou
- Department of Statistics, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Osama Shah
- Women’s Cancer Research Center, UPMC Hillman Cancer Center (HCC), Pittsburgh, Pennsylvania, United States of America
- Magee-Womens Research Institute, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Yu-Chiao Chiu
- Cancer Therapeutics Program, UPMC Hillman Cancer Center (HCC), Pittsburgh, Pennsylvania, United States of America
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, Maryland, United States of America
| | - Jennifer M. Atkinson
- Women’s Cancer Research Center, UPMC Hillman Cancer Center (HCC), Pittsburgh, Pennsylvania, United States of America
- Magee-Womens Research Institute, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Steffi Oesterreich
- Women’s Cancer Research Center, UPMC Hillman Cancer Center (HCC), Pittsburgh, Pennsylvania, United States of America
- Magee-Womens Research Institute, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Adrian V. Lee
- Women’s Cancer Research Center, UPMC Hillman Cancer Center (HCC), Pittsburgh, Pennsylvania, United States of America
- Magee-Womens Research Institute, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - George C. Tseng
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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Yu Y, Zhou T, Cao L. Use and application of organ-on-a-chip platforms in cancer research. J Cell Commun Signal 2023:10.1007/s12079-023-00790-7. [PMID: 38032444 DOI: 10.1007/s12079-023-00790-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
Tumors are a major cause of death worldwide, and much effort has been made to develop appropriate anti-tumor therapies. Existing in vitro and in vivo tumor models cannot reflect the critical features of cancer. The development of organ-on-a-chip models has enabled the integration of organoids, microfluidics, tissue engineering, biomaterials research, and microfabrication, offering conditions that mimic tumor physiology. Three-dimensional in vitro human tumor models that have been established as organ-on-a-chip models contain multiple cell types and a structure that is similar to the primary tumor. These models can be applied to various foci of oncology research. Moreover, the high-throughput features of microfluidic organ-on-a-chip models offer new opportunities for achieving large-scale drug screening and developing more personalized treatments. In this review of the literature, we explore the development of organ-on-a-chip technology and discuss its use as an innovative tool in basic and clinical applications and summarize its advancement of cancer research.
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Affiliation(s)
- Yifan Yu
- Department of Hepatobiliary and Transplant Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - TingTing Zhou
- The College of Basic Medical Science, Health Sciences Institute, Key Laboratory of Cell Biology of Ministry of Public Health, Key Laboratory of Medical Cell Biology of Ministry of Education, Liaoning Province Collaborative Innovation Center of Aging Related Disease Diagnosis and Treatment and Prevention, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, China
| | - Liu Cao
- The College of Basic Medical Science, Health Sciences Institute, Key Laboratory of Cell Biology of Ministry of Public Health, Key Laboratory of Medical Cell Biology of Ministry of Education, Liaoning Province Collaborative Innovation Center of Aging Related Disease Diagnosis and Treatment and Prevention, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, China.
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Sulimanov R, Koshelev K, Makarov V, Mezentsev A, Durymanov M, Ismail L, Zahid K, Rumyantsev Y, Laskov I. Mathematical Modeling of Non-Small-Cell Lung Cancer Biology through the Experimental Data on Cell Composition and Growth of Patient-Derived Organoids. Life (Basel) 2023; 13:2228. [PMID: 38004368 PMCID: PMC10672646 DOI: 10.3390/life13112228] [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: 10/05/2023] [Revised: 11/06/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with "omics" approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.
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Affiliation(s)
- Rushan Sulimanov
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
| | - Konstantin Koshelev
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
- Ivannikov Institute for System Programming of the Russian Academy of Science, 109004 Moscow, Russia
| | - Vladimir Makarov
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
| | - Alexandre Mezentsev
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
- School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (L.I.); (K.Z.)
| | - Mikhail Durymanov
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
- School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (L.I.); (K.Z.)
| | - Lilian Ismail
- School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (L.I.); (K.Z.)
| | - Komal Zahid
- School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (L.I.); (K.Z.)
| | - Yegor Rumyantsev
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
| | - Ilya Laskov
- Medical Informatics Laboratory, Yaroslav-the-Wise Novgorod State University, 173003 Veliky Novgorod, Russia; (R.S.); (K.K.); (V.M.); (A.M.); (M.D.); (I.L.)
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10
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Zhu L, Zhang J, Guo Q, Kuang J, Li D, Wu M, Mo Y, Zhang T, Gao X, Tan J. Advanced lung organoids and lung-on-a-chip for cancer research and drug evaluation: a review. Front Bioeng Biotechnol 2023; 11:1299033. [PMID: 38026900 PMCID: PMC10662056 DOI: 10.3389/fbioe.2023.1299033] [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: 09/22/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
Lung cancer has become the primary cause of cancer-related deaths because of its high recurrence rate, ability to metastasise easily, and propensity to develop drug resistance. The wide-ranging heterogeneity of lung cancer subtypes increases the complexity of developing effective therapeutic interventions. Therefore, personalised diagnostic and treatment strategies are required to guide clinical practice. The advent of innovative three-dimensional (3D) culture systems such as organoid and organ-on-a-chip models provides opportunities to address these challenges and revolutionise lung cancer research and drug evaluation. In this review, we introduce the advancements in lung-related 3D culture systems, with a particular focus on lung organoids and lung-on-a-chip, and their latest contributions to lung cancer research and drug evaluation. These developments include various aspects, from authentic simulations and mechanistic enquiries into lung cancer to assessing chemotherapeutic agents and targeted therapeutic interventions. The new 3D culture system can mimic the pathological and physiological microenvironment of the lung, enabling it to supplement or replace existing two-dimensional culture models and animal experimental models and realize the potential for personalised lung cancer treatment.
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Affiliation(s)
- Leqing Zhu
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
- Shenzhen Clinical Medical College, Southern Medical University, Shenzhen, China
| | - Jianhua Zhang
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Quanwei Guo
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Jun Kuang
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Dongfang Li
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Mengxi Wu
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Yijun Mo
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Tao Zhang
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Xinghua Gao
- Materials Genome Institute, Shanghai University, Shanghai, China
| | - Jianfeng Tan
- Department of Thoracic Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
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Jin J, Yoshimura K, Sewastjanow-Silva M, Song S, Ajani JA. Challenges and Prospects of Patient-Derived Xenografts for Cancer Research. Cancers (Basel) 2023; 15:4352. [PMID: 37686627 PMCID: PMC10486659 DOI: 10.3390/cancers15174352] [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: 07/17/2023] [Revised: 08/18/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.
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Affiliation(s)
| | | | | | - Shumei Song
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.J.); (K.Y.); (M.S.-S.)
| | - Jaffer A. Ajani
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.J.); (K.Y.); (M.S.-S.)
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