1
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Liu Y, Wu W, Cai C, Zhang H, Shen H, Han Y. Patient-derived xenograft models in cancer therapy: technologies and applications. Signal Transduct Target Ther 2023; 8:160. [PMID: 37045827 PMCID: PMC10097874 DOI: 10.1038/s41392-023-01419-2] [Citation(s) in RCA: 47] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 03/21/2023] [Indexed: 04/14/2023] Open
Abstract
Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.
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Affiliation(s)
- Yihan Liu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, P.R. China
| | - Wantao Wu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, P.R. China
| | - Changjing Cai
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, P.R. China
| | - Hao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Hong Shen
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, P.R. China.
| | - Ying Han
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, P.R. China.
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2
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DasGupta R, Yap A, Yaqing EY, Chia S. Evolution of precision oncology-guided treatment paradigms. WIREs Mech Dis 2023; 15:e1585. [PMID: 36168283 DOI: 10.1002/wsbm.1585] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/30/2022] [Accepted: 07/11/2022] [Indexed: 01/31/2023]
Abstract
Cancer treatment is gradually evolving from the classical use of nonspecific cytotoxic drugs targeting generic mechanisms of cell growth and proliferation. Instead, new "patient-specific treatment paradigms" that are based on an individual patient's tumor-specific molecular features are emerging, and these include "druggable" genomic alterations such as oncogenic driver mutations, downstream activities of cancer-signaling pathways, and the expression of specific genes involved in tumorigenesis and cancer progression. This evolving landscape of making evidence-based treatment decisions forms the foundation of precision oncology, which aims to deliver "the right drug, to the right patient and at the right time". The long-term vision for this approach is to maximize the treatment efficacy while minimizing exposure to ineffective therapy and reducing co-morbidity-related side effects. Successful clinical translation and implementation of this vision have the potential to revolutionize treatment paradigms from predominantly reactive, to more evidence-based, proactive and predictive care. In this article, we review the past and current approaches in precision oncology, and describe their remarkable power and limitations. We also speculate on the evolution of newly emerging methodologies of the future that can be used to address some of the key challenges associated with the existing paradigms. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics Cancer > Molecular and Cellular Physiology Cancer > Computational Models.
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Affiliation(s)
- Ramanuj DasGupta
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore.,Cancer Science Institute, National University of Singapore, Singapore, Singapore
| | - Aixin Yap
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Elena Yong Yaqing
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Shumei Chia
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
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3
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Kuiken HJ, Dhakal S, Selfors LM, Friend CM, Zhang T, Callari M, Schackmann RCJ, Gray GK, Crowdis J, Bhang HEC, Baslan T, Stegmeier F, Gygi SP, Caldas C, Brugge JS. Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts. Oncogene 2022; 41:112-124. [PMID: 34703030 PMCID: PMC8727509 DOI: 10.1038/s41388-021-02075-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 10/01/2021] [Accepted: 10/11/2021] [Indexed: 11/09/2022]
Abstract
Intratumoral heterogeneity has been described for various tumor types and models of human cancer, and can have profound effects on tumor progression and drug resistance. This study describes an in-depth analysis of molecular and functional heterogeneity among subclonal populations (SCPs) derived from a single triple-negative breast cancer cell line, including copy number analysis, whole-exome and RNA sequencing, proteome analysis, and barcode analysis of clonal dynamics, as well as functional assays. The SCPs were found to have multiple unique genetic alterations and displayed significant variation in anchorage independent growth and tumor forming ability. Analyses of clonal dynamics in SCP mixtures using DNA barcode technology revealed selection for distinct clonal populations in different in vitro and in vivo environmental contexts, demonstrating that in vitro propagation of cancer cell lines using different culture conditions can contribute to the establishment of unique strains. These analyses also revealed strong enrichment of a single SCP during the development of xenograft tumors in immune-compromised mice. This SCP displayed attenuated interferon signaling in vivo and reduced sensitivity to the antiproliferative effects of type I interferons. Reduction in interferon signaling was found to provide a selective advantage within the xenograft microenvironment specifically. In concordance with the previously described role of interferon signaling as tumor suppressor, these findings suggest that similar selective pressures may be operative in human cancer and patient-derived xenograft models.
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Affiliation(s)
- Hendrik J Kuiken
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, 1066 CX, the Netherlands
| | - Sabin Dhakal
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
- Inzen Therapeutics, Cambridge, MA, 02142, USA
| | - Laura M Selfors
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
| | - Chandler M Friend
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
| | - Tian Zhang
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Maurizio Callari
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
| | - Ron C J Schackmann
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
- Merus, Utrecht, 3584 CM, the Netherlands
| | - G Kenneth Gray
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
| | - Jett Crowdis
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
- Ludwig Center at Harvard, Boston, MA, 02115, USA
- Broad Institute, Cambridge, MA, 02142, USA
| | - Hyo-Eun C Bhang
- Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, 02139, USA
- Civetta Therapeutics, Cambridge, MA, 02142, USA
| | - Timour Baslan
- Cancer Biology and Genetics Program, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA
| | - Frank Stegmeier
- Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, 02139, USA
- KSQ Therapeutics, Inc., Cambridge, MA, 02139, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Carlos Caldas
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
| | - Joan S Brugge
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA.
- Ludwig Center at Harvard, Boston, MA, 02115, USA.
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4
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Honkala A, Malhotra SV, Kummar S, Junttila MR. Harnessing the predictive power of preclinical models for oncology drug development. Nat Rev Drug Discov 2021; 21:99-114. [PMID: 34702990 DOI: 10.1038/s41573-021-00301-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/27/2021] [Indexed: 12/21/2022]
Abstract
Recent progress in understanding the molecular basis of cellular processes, identification of promising therapeutic targets and evolution of the regulatory landscape makes this an exciting and unprecedented time to be in the field of oncology drug development. However, high costs, long development timelines and steep rates of attrition continue to afflict the drug development process. Lack of predictive preclinical models is considered one of the key reasons for the high rate of attrition in oncology. Generating meaningful and predictive results preclinically requires a firm grasp of the relevant biological questions and alignment of the model systems that mirror the patient context. In doing so, the ability to conduct both forward translation, the process of implementing basic research discoveries into practice, as well as reverse translation, the process of elucidating the mechanistic basis of clinical observations, greatly enhances our ability to develop effective anticancer treatments. In this Review, we outline issues in preclinical-to-clinical translatability of molecularly targeted cancer therapies, present concepts and examples of successful reverse translation, and highlight the need to better align tumour biology in patients with preclinical model systems including tracking of strengths and weaknesses of preclinical models throughout programme development.
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Affiliation(s)
- Alexander Honkala
- Department of Cell Development & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
| | - Sanjay V Malhotra
- Department of Cell Development & Cancer Biology, Oregon Health & Science University, Portland, OR, USA.,Center for Experimental Therapeutics, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Shivaani Kummar
- Center for Experimental Therapeutics, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA. .,Division of Hematology & Medical Oncology, Oregon Health & Science University, Portland, OR, USA.
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5
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Chen J, Jin Y, Li S, Qiao C, Peng X, Li Y, Gu Y, Wang W, You Y, Yin J, Shan Y, Wang YX, Qin M, Li H, Cai Y, Dong Y, Peng S, Pan L. Patient-Derived Xenografts Are a Reliable Preclinical Model for the Personalized Treatment of Epithelial Ovarian Cancer. Front Oncol 2021; 11:744256. [PMID: 34671560 PMCID: PMC8522495 DOI: 10.3389/fonc.2021.744256] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/09/2021] [Indexed: 11/13/2022] Open
Abstract
To generate robust patient-derived xenograft (PDX) models for epithelial ovarian cancer (EOC), analyze the resemblance of PDX models to the original tumors, and explore factors affecting engraftment rates, fresh cancer tissues from a consecutive cohort of 158 patients with EOC were collected to construct subcutaneous PDX models. Paired samples of original tumors and PDX tumors were compared at the genome, transcriptome, protein levels, and the platinum-based chemotherapy response was evaluated to ensure the reliability of the PDXs. Univariate and multivariate analyses were used to determine the factors affecting the engraftment rates. The engraftment success rate was 58.23% (92/158) over 3–6 months. The Ki-67 index and receiving neoadjuvant chemotherapy can affect the engraftment rate in primary patients. The PDX models generated in this study were found to retain the histomorphology, protein expression, and genetic alteration patterns of the original tumors, despite the transcriptomic differences observed. Clinically, the PDX models demonstrated a high degree of similarity with patients in terms of the chemotherapy response and could predict prognosis. Thus, the PDX model can be considered a promising and reliable preclinical tool for personalized and precise treatment.
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Affiliation(s)
- Jiayu Chen
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Ying Jin
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Siyi Li
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Cui Qiao
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China.,Beijing IDMO Co., Ltd., Beijing, China
| | - Xinxin Peng
- The Bioinformatics Department, Precision Scientific (Beijing) Co., Ltd., Beijing, China
| | - Yan Li
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Yu Gu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Wei Wang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Yan You
- Department of Pathology, Peking Union Medical College Hospital, Beijing, China
| | - Jie Yin
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Ying Shan
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Yong-Xue Wang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Meng Qin
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Hongyue Li
- The Bioinformatics Department, Precision Scientific (Beijing) Co., Ltd., Beijing, China
| | - Yan Cai
- Department of Obstetrics and Gynecology, Beijing Cancer Hospital, Beijing, China
| | - Yu Dong
- The Medical Department, Precision Scientific (Beijing) Co., Ltd., Beijing, China
| | | | - Lingya Pan
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
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6
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Woo XY, Giordano J, Srivastava A, Zhao ZM, Lloyd MW, de Bruijn R, Suh YS, Patidar R, Chen L, Scherer S, Bailey MH, Yang CH, Cortes-Sanchez E, Xi Y, Wang J, Wickramasinghe J, Kossenkov AV, Rebecca VW, Sun H, Mashl RJ, Davies SR, Jeon R, Frech C, Randjelovic J, Rosains J, Galimi F, Bertotti A, Lafferty A, O’Farrell AC, Modave E, Lambrechts D, ter Brugge P, Serra V, Marangoni E, El Botty R, Kim H, Kim JI, Yang HK, Lee C, Dean DA, Davis-Dusenbery B, Evrard YA, Doroshow JH, Welm AL, Welm BE, Lewis MT, Fang B, Roth JA, Meric-Bernstam F, Herlyn M, Davies MA, Ding L, Li S, Govindan R, Isella C, Moscow JA, Trusolino L, Byrne AT, Jonkers J, Bult CJ, Medico E, Chuang JH. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts. Nat Genet 2021; 53:86-99. [PMID: 33414553 PMCID: PMC7808565 DOI: 10.1038/s41588-020-00750-6] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Accepted: 11/18/2020] [Indexed: 02/03/2023]
Abstract
Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.
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Grants
- NC/T001267/1 National Centre for the Replacement, Refinement and Reduction of Animals in Research
- P30 CA016672 NCI NIH HHS
- 29567 Cancer Research UK
- U54 CA233223 NCI NIH HHS
- P30 CA034196 NCI NIH HHS
- P01 CA114046 NCI NIH HHS
- HHSN261201400008C NCI NIH HHS
- P30 CA091842 NCI NIH HHS
- U24 CA224067 NCI NIH HHS
- P50 CA196510 NCI NIH HHS
- U54 CA224070 NCI NIH HHS
- U54 CA224076 NCI NIH HHS
- U54 CA224065 NCI NIH HHS
- U54 CA233306 NCI NIH HHS
- P30 CA010815 NCI NIH HHS
- U24 CA204781 NCI NIH HHS
- U54 CA224083 NCI NIH HHS
- HHSN261201500003C NCI NIH HHS
- HHSN261200800001C NCI NIH HHS
- T32 HG008962 NHGRI NIH HHS
- R50 CA211199 NCI NIH HHS
- P30 CA125123 NCI NIH HHS
- P50 CA070907 NCI NIH HHS
- HHSN261201500003I NCI NIH HHS
- HHSN261200800001E NCI NIH HHS
- P30 CA042014 NCI NIH HHS
- U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
- KWF Kankerbestrijding (Dutch Cancer Society)
- Oncode Institute
- Fondazione AIRC under 5 per Mille 2018 - ID. 21091 EU H2020 Research and Innovation Programme, grant agreement no. 731105 European Research Council Consolidator Grant 724748
- EU H2020 Research and Innovation Programme, grant Agreement No. 754923
- EU H2020 Research and Innovation Programme, grant agreement no. 731105 ISCIII - Miguel Servet program CP14/00228 GHD-Pink/FERO Foundation grant
- Fondazione Piemontese per la Ricerca sul Cancro-ONLUS 5 per mille Ministero della Salute 2015
- Korean Health Industry Development Institute HI13C2148
- Korean Health Industry Development Institute HI13C2148 The First Affiliated Hospital of Xi’an Jiaotong University Ewha Womans University Research Grant
- CPRIT RP170691
- SCU | Ignatian Center for Jesuit Education, Santa Clara University
- Breast Cancer Research Foundation (BCRF)
- Fashion Footwear Charitable Foundation of New York The Foundation for Barnes-Jewish Hospital’s Cancer Frontier Fund
- My First AIRC Grant 19047
- Fondazione AIRC under 5 per Mille 2018 - ID. 21091 AIRC Investigator Grants 18532 and 20697 AIRC/CRUK/FC AECC Accelerator Award 22795 Fondazione Piemontese per la Ricerca sul Cancro-ONLUS 5 per mille Ministero della Salute 2015, 2014, 2016 EU H2020 Research and Innovation Programme, grant Agreement No. 754923 EU H2020 Research and Innovation Programme, grant agreement no. 731105
- Science Foundation Ireland (SFI)
- EU H2020 Research and Innovation Programme, grant agreement no. 731105 EU H2020 Research and Innovation Programme, grant Agreement No. 754923 Irish Health Research Board grant ILP-POR-2019-066
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research)
- EU H2020 Research and Innovation Programme, grant agreement no. 731105 European Research Council (ERC) Synergy project CombatCancer Oncode Institute
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Affiliation(s)
- Xing Yi Woo
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - Jessica Giordano
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Anuj Srivastava
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - Zi-Ming Zhao
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - Michael W. Lloyd
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME USA
| | - Roebi de Bruijn
- grid.430814.aNetherlands Cancer Institute, Amsterdam, the Netherlands
| | - Yun-Suhk Suh
- grid.31501.360000 0004 0470 5905College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Rajesh Patidar
- grid.418021.e0000 0004 0535 8394Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - Li Chen
- grid.418021.e0000 0004 0535 8394Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - Sandra Scherer
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA
| | - Matthew H. Bailey
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA ,grid.223827.e0000 0001 2193 0096Department of Human Genetics, University of Utah, Salt Lake City, UT USA
| | - Chieh-Hsiang Yang
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA
| | - Emilio Cortes-Sanchez
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA
| | - Yuanxin Xi
- grid.240145.60000 0001 2291 4776Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Jing Wang
- grid.240145.60000 0001 2291 4776Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | | | | | - Vito W. Rebecca
- grid.251075.40000 0001 1956 6678The Wistar Institute, Philadelphia, PA USA
| | - Hua Sun
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - R. Jay Mashl
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - Sherri R. Davies
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - Ryan Jeon
- grid.492568.4Seven Bridges Genomics, Charlestown, MA USA
| | | | | | | | - Francesco Galimi
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Andrea Bertotti
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Adam Lafferty
- grid.4912.e0000 0004 0488 7120Department of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Alice C. O’Farrell
- grid.4912.e0000 0004 0488 7120Department of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Elodie Modave
- grid.5596.f0000 0001 0668 7884Center for Cancer Biology, VIB, Leuven, Belgium ,grid.5596.f0000 0001 0668 7884Laboratory of Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Diether Lambrechts
- grid.5596.f0000 0001 0668 7884Center for Cancer Biology, VIB, Leuven, Belgium ,grid.5596.f0000 0001 0668 7884Laboratory of Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Petra ter Brugge
- grid.430814.aNetherlands Cancer Institute, Amsterdam, the Netherlands
| | - Violeta Serra
- grid.411083.f0000 0001 0675 8654Vall d´Hebron Institute of Oncology, Barcelona, Spain
| | - Elisabetta Marangoni
- grid.418596.70000 0004 0639 6384Department of Translational Research, Institut Curie, PSL Research University, Paris, France
| | - Rania El Botty
- grid.418596.70000 0004 0639 6384Department of Translational Research, Institut Curie, PSL Research University, Paris, France
| | - Hyunsoo Kim
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - Jong-Il Kim
- grid.31501.360000 0004 0470 5905College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Han-Kwang Yang
- grid.31501.360000 0004 0470 5905College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Charles Lee
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA ,grid.452438.cPrecision Medicine Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, People’s Republic of China ,grid.255649.90000 0001 2171 7754Department of Life Sciences, Ewha Womans University, Seoul, Republic of Korea
| | - Dennis A. Dean
- grid.492568.4Seven Bridges Genomics, Charlestown, MA USA
| | | | - Yvonne A. Evrard
- grid.418021.e0000 0004 0535 8394Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - James H. Doroshow
- grid.48336.3a0000 0004 1936 8075Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD USA
| | - Alana L. Welm
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA
| | - Bryan E. Welm
- grid.223827.e0000 0001 2193 0096Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA ,grid.223827.e0000 0001 2193 0096Department of Surgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT USA
| | - Michael T. Lewis
- grid.39382.330000 0001 2160 926XLester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX USA
| | - Bingliang Fang
- grid.240145.60000 0001 2291 4776Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Jack A. Roth
- grid.240145.60000 0001 2291 4776Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Funda Meric-Bernstam
- grid.240145.60000 0001 2291 4776Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Meenhard Herlyn
- grid.251075.40000 0001 1956 6678The Wistar Institute, Philadelphia, PA USA
| | - Michael A. Davies
- grid.240145.60000 0001 2291 4776Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Li Ding
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - Shunqiang Li
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - Ramaswamy Govindan
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO USA
| | - Claudio Isella
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Jeffrey A. Moscow
- grid.48336.3a0000 0004 1936 8075Investigational Drug Branch, National Cancer Institute, Bethesda, MD USA
| | - Livio Trusolino
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Annette T. Byrne
- grid.4912.e0000 0004 0488 7120Department of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Jos Jonkers
- grid.430814.aNetherlands Cancer Institute, Amsterdam, the Netherlands
| | - Carol J. Bult
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME USA
| | - Enzo Medico
- grid.7605.40000 0001 2336 6580Department of Oncology, University of Turin, Turin, Italy ,grid.419555.90000 0004 1759 7675Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Jeffrey H. Chuang
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
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7
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Dhanasekaran R. Deciphering Tumor Heterogeneity in Hepatocellular Carcinoma (HCC)-Multi-Omic and Singulomic Approaches. Semin Liver Dis 2021; 41:9-18. [PMID: 33764481 PMCID: PMC8136683 DOI: 10.1055/s-0040-1722261] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Tumor heterogeneity, a key hallmark of hepatocellular carcinomas (HCCs), poses a significant challenge to developing effective therapies or predicting clinical outcomes in HCC. Recent advances in next-generation sequencing-based multi-omic and single cell analysis technologies have enabled us to develop high-resolution atlases of tumors and pull back the curtain on tumor heterogeneity. By combining multiregion targeting sampling strategies with deep sequencing of the genome, transcriptome, epigenome, and proteome, several studies have revealed novel mechanistic insights into tumor initiation and progression in HCC. Advances in multiparametric immune cell profiling have facilitated a deeper dive into the biological complexity of HCC, which is crucial in this era of immunotherapy. Moreover, studies using liquid biopsy have demonstrated their potential to circumvent the need for tissue sampling to investigate heterogeneity. In this review, we discuss how multi-omic and single-cell sequencing technologies have advanced our understanding of tumor heterogeneity in HCC.
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Affiliation(s)
- Renumathy Dhanasekaran
- Department of Medicine, Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California
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8
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Niida A, Hasegawa T, Innan H, Shibata T, Mimori K, Miyano S. A unified simulation model for understanding the diversity of cancer evolution. PeerJ 2020; 8:e8842. [PMID: 32296600 PMCID: PMC7150545 DOI: 10.7717/peerj.8842] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 03/02/2020] [Indexed: 01/24/2023] Open
Abstract
Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.
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Affiliation(s)
- Atsushi Niida
- Laboratory of Molecular Medicine, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Takanori Hasegawa
- Division of Health Medical Data Science, Health Intelligence Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Hideki Innan
- SOKENDAI, The Graduate University for Advanced Studies, Hayama, Japan
| | - Tatsuhiro Shibata
- Laboratory of Molecular Medicine, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Division of Cancer Genomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Koshi Mimori
- Department of Surgery, Kyushu University Beppu Hospita, Beppu, Japan
| | - Satoru Miyano
- Laboratory of DNA Information Analysis, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
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9
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Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies. Cancers (Basel) 2020; 12:cancers12020444. [PMID: 32074948 PMCID: PMC7072242 DOI: 10.3390/cancers12020444] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 02/05/2020] [Accepted: 02/10/2020] [Indexed: 12/20/2022] Open
Abstract
The vast majority of mortality in breast cancer results from distant metastasis. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Pre-clinical animal models that reliably reflect the biology of breast cancer brain metastasis are needed to develop and test new treatments for this deadly condition. The patient-derived xenograft (PDX) model maintains many features of a donor tumor, such as intra-tumor heterogeneity, and permits the testing of individualized treatments. However, the establishment of orthotopic PDXs of brain metastasis is procedurally difficult. We have developed a method for generating such PDXs with high tumor engraftment and growth rates. Here, we describe this method and identify variables that affect its outcomes. We also compare the brain-orthotopic PDXs with ectopic PDXs grown in mammary pads of mice, and show that the responsiveness of PDXs to chemotherapeutic reagents can be dramatically affected by the site that they are in.
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10
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Shi J, Li Y, Jia R, Fan X. The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance. Int J Cancer 2019; 146:2078-2088. [PMID: 31479514 DOI: 10.1002/ijc.32662] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 08/29/2019] [Indexed: 12/14/2022]
Abstract
Patient-derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next-generation preclinical models.
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Affiliation(s)
- Jiahao Shi
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, People's Republic of China
| | - Yongyun Li
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, People's Republic of China
| | - Renbing Jia
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Xianqun Fan
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
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