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Toh SY, Leong HS, Chong FT, Rodrigues-Junior DM, Ren MJ, Kwang XL, Lau DPX, Lee PH, Vettore AL, Teh BT, Tan DSW, Iyer NG. Therapeutic application of extracellular vesicular EGFR isoform D as a co-drug to target squamous cell cancers with tyrosine kinase inhibitors. Dev Cell 2024; 59:2189-2202.e8. [PMID: 39089249 DOI: 10.1016/j.devcel.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 05/31/2024] [Accepted: 07/09/2024] [Indexed: 08/03/2024]
Abstract
Targeting wild-type epidermal growth factor receptor (EGFR) using tyrosine kinase inhibitors (TKIs) never achieved its purported success in cancers such as head and neck squamous cell carcinoma, which are largely EGFR-dependent. We had previously shown that exceptional responders to TKIs have a genetic aberration that results in overexpression of an EGFR splice variant, isoform D (IsoD). IsoD lacks an integral transmembrane and kinase domain and is secreted in extracellular vesicles (EVs) in TKI-sensitive patient-derived cultures. Remarkably, the exquisite sensitivity to TKIs could be transferred to TKI-resistant tumor cells, and IsoD protein in the EV is necessary and sufficient to transfer the phenotype in vitro and in vivo across multiple models and drugs. This drug response requires an intact endocytic mechanism, binding to full-length EGFR, and signaling through Src-phosphorylation within the endosomal compartment. We propose a therapeutic strategy using EVs containing EGFR IsoD as a co-drug to expand the use of TKI therapy to EGFR-driven cancers.
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Affiliation(s)
- Shen Yon Toh
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore
| | - Hui Sun Leong
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore
| | - Fui Teen Chong
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore
| | - Dorival Mendes Rodrigues-Junior
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Biomedical Center, Uppsala University, Uppsala, Sweden
| | - Meng Jie Ren
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore
| | - Xue Lin Kwang
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Dawn P X Lau
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Po-Hsien Lee
- Laboratory of Cancer Epigenome, National Cancer Centre Singapore, Singapore, Singapore
| | - Andre Luiz Vettore
- Department of Biological Sciences, Universidade Federal de São Paulo, Diadema, Brazil
| | - Bin Tean Teh
- Laboratory of Cancer Epigenome, National Cancer Centre Singapore, Singapore, Singapore
| | - Daniel S W Tan
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - N Gopalakrishna Iyer
- Cancer Therapeutics Research Laboratory, National Cancer Centre Singapore, Singapore, Singapore; Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore; Department of Head and Neck Surgery, National Cancer Centre Singapore, Singapore, Singapore.
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2
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Tostado CP, Da Ong LX, Heng JJW, Miccolis C, Chia S, Seow JJW, Toh Y, DasGupta R. An AI-assisted integrated, scalable, single-cell phenomic-transcriptomic platform to elucidate intratumor heterogeneity against immune response. Bioeng Transl Med 2024; 9:e10628. [PMID: 38435825 PMCID: PMC10905538 DOI: 10.1002/btm2.10628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 11/16/2023] [Indexed: 03/05/2024] Open
Abstract
We present a novel framework combining single-cell phenotypic data with single-cell transcriptomic analysis to identify factors underpinning heterogeneity in antitumor immune response. We developed a pairwise, tumor-immune discretized interaction assay between natural killer (NK-92MI) cells and patient-derived head and neck squamous cell carcinoma (HNSCC) cell lines on a microfluidic cell-trapping platform. Furthermore we generated a deep-learning computer vision algorithm that is capable of automating the acquisition and analysis of a large, live-cell imaging data set (>1 million) of paired tumor-immune interactions spanning a time course of 24 h across multiple HNSCC lines (n = 10). Finally, we combined the response data measured by Kaplan-Meier survival analysis against NK-mediated killing with downstream single-cell transcriptomic analysis to interrogate molecular signatures associated with NK-effector response. As proof-of-concept for the proposed framework, we efficiently identified MHC class I-driven cytotoxic resistance as a key mechanism for immune evasion in nonresponders, while enhanced expression of cell adhesion molecules was found to be correlated with sensitivity against NK-mediated cytotoxicity. We conclude that this integrated, data-driven phenotypic approach holds tremendous promise in advancing the rapid identification of new mechanisms and therapeutic targets related to immune evasion and response.
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Affiliation(s)
- Christopher P. Tostado
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
- Institute for Health Innovation and Technology (iHealthtech), National University of SingaporeSingaporeSingapore
| | - Lucas Xian Da Ong
- Institute for Health Innovation and Technology (iHealthtech), National University of SingaporeSingaporeSingapore
| | - Joel Jia Wei Heng
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
| | - Carlo Miccolis
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
| | - Shumei Chia
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
| | - Justine Jia Wen Seow
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
| | - Yi‐Chin Toh
- Institute for Health Innovation and Technology (iHealthtech), National University of SingaporeSingaporeSingapore
- School of Mechanical, Medical and Process EngineeringQueensland University of TechnologyBrisbaneAustralia
- Centre for Biomedical TechnologiesQueensland University of TechnologyBrisbaneAustralia
| | - Ramanuj DasGupta
- Genome Institute of Singapore, Laboratory of Precision Oncology and Cancer EvolutionSingaporeSingapore
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3
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Dehkordi SR, Wong ITL, Ni J, Luebeck J, Zhu K, Prasad G, Krockenberger L, Xu G, Chowdhury B, Rajkumar U, Caplin A, Muliaditan D, Coruh C, Jin Q, Turner K, Teo SX, Pang AWC, Alexandrov LB, Chua CEL, Furnari FB, Paulson TG, Law JA, Chang HY, Yue F, DasGupta R, Zhao J, Mischel PS, Bafna V. Breakage fusion bridge cycles drive high oncogene copy number, but not intratumoral genetic heterogeneity or rapid cancer genome change. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571349. [PMID: 38168210 PMCID: PMC10760206 DOI: 10.1101/2023.12.12.571349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Oncogene amplification is a major driver of cancer pathogenesis. Breakage fusion bridge (BFB) cycles, like extrachromosomal DNA (ecDNA), can lead to high copy numbers of oncogenes, but their impact on intratumoral heterogeneity, treatment response, and patient survival are not well understood due to difficulty in detecting them by DNA sequencing. We describe a novel algorithm that detects and reconstructs BFB amplifications using optical genome maps (OGMs), called OM2BFB. OM2BFB showed high precision (>93%) and recall (92%) in detecting BFB amplifications in cancer cell lines, PDX models and primary tumors. OM-based comparisons demonstrated that short-read BFB detection using our AmpliconSuite (AS) toolkit also achieved high precision, albeit with reduced sensitivity. We detected 371 BFB events using whole genome sequences from 2,557 primary tumors and cancer lines. BFB amplifications were preferentially found in cervical, head and neck, lung, and esophageal cancers, but rarely in brain cancers. BFB amplified genes show lower variance of gene expression, with fewer options for regulatory rewiring relative to ecDNA amplified genes. BFB positive (BFB (+)) tumors showed reduced heterogeneity of amplicon structures, and delayed onset of resistance, relative to ecDNA(+) tumors. EcDNA and BFB amplifications represent contrasting mechanisms to increase the copy numbers of oncogene with markedly different characteristics that suggest different routes for intervention.
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Affiliation(s)
- Siavash Raeisi Dehkordi
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Ivy Tsz-Lo Wong
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Jing Ni
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215 USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115 USA
| | - Jens Luebeck
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, San Diego, CA, USA
| | - Kaiyuan Zhu
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Gino Prasad
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Lena Krockenberger
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Guanghui Xu
- Plant Molecular and Cellular Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Biswanath Chowdhury
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Utkrisht Rajkumar
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Ann Caplin
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Daniel Muliaditan
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Ceyda Coruh
- Plant Molecular and Cellular Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- ClearNote Health, San Diego, CA 92121 USA
| | - Qiushi Jin
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine Northwestern University, Chicago, IL, USA
| | | | - Shu Xian Teo
- Singapore Nuclear Research and Safety Initiative, National University of Singapore
| | | | - Ludmil B Alexandrov
- Moores Cancer Center, UC San Diego Health, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California at San Diego, La Jolla, CA, USA
| | | | - Frank B Furnari
- Department of Medicine, University of California at San Diego, La Jolla, CA, USA
| | - Thomas G Paulson
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Julie A Law
- Plant Molecular and Cellular Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, USA
| | - Ramanuj DasGupta
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Jean Zhao
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215 USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115 USA
| | - Paul S Mischel
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Vineet Bafna
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
- Halıcıoğlu Data Science Institute, University of California at San Diego, La Jolla, CA, USA
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4
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Pellecchia S, Viscido G, Franchini M, Gambardella G. Predicting drug response from single-cell expression profiles of tumours. BMC Med 2023; 21:476. [PMID: 38041118 PMCID: PMC10693176 DOI: 10.1186/s12916-023-03182-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Intra-tumour heterogeneity (ITH) presents a significant obstacle in formulating effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) has evolved as a powerful instrument for probing ITH at the transcriptional level, offering an unparalleled opportunity for therapeutic intervention. RESULTS Drug response prediction at the single-cell level is an emerging field of research that aims to improve the efficacy and precision of cancer treatments. Here, we introduce DREEP (Drug Response Estimation from single-cell Expression Profiles), a computational method that leverages publicly available pharmacogenomic screens from GDSC2, CTRP2, and PRISM and functional enrichment analysis to predict single-cell drug sensitivity from transcriptomic data. We validated DREEP extensively in vitro using several independent single-cell datasets with over 200 cancer cell lines and showed its accuracy and robustness. Additionally, we also applied DREEP to molecularly barcoded breast cancer cells and identified drugs that can selectively target specific cell populations. CONCLUSIONS DREEP provides an in silico framework to prioritize drugs from single-cell transcriptional profiles of tumours and thus helps in designing personalized treatment strategies and accelerating drug repurposing studies. DREEP is available at https://github.com/gambalab/DREEP .
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Affiliation(s)
- Simona Pellecchia
- Telethon Institute of Genetics and Medicine, Naples, Italy
- Genomics and Experimental Medicine Program, Scuola Superiore Meridionale, Naples, Italy
| | - Gaetano Viscido
- Telethon Institute of Genetics and Medicine, Naples, Italy
- Department of Chemical, Materials and Industrial Engineering, University of Naples Federico II, Naples, Italy
| | - Melania Franchini
- Telethon Institute of Genetics and Medicine, Naples, Italy
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
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5
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Liu DD, Muliaditan D, Viswanathan R, Cui X, Cheow LF. Melt-Encoded-Tags for Expanded Optical Readout in Digital PCR (METEOR-dPCR) Enables Highly Multiplexed Quantitative Gene Panel Profiling. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301630. [PMID: 37485651 PMCID: PMC10520687 DOI: 10.1002/advs.202301630] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/27/2023] [Indexed: 07/25/2023]
Abstract
Digital PCR (dPCR) is an important tool for precise nucleic acid quantification in clinical setting, but the limited multiplexing capability restricts its applications for quantitative gene panel profiling. Here, this work describes melt-encoded-tags for expanded optical readout in digital PCR (METEOR-dPCR), a simple two-step assay that enables simultaneous quantification of a large panel of arbitrary genes in a dPCR platform. Target genes are quantitatively converted into DNA tags with unique melting temperatures through a ligation approach. These tags are then counted and distinguished by their melt-curve profiles on a dPCR platform. A multiplexing capacity of M^N, where M is the number of resolvable melting temperature and N is the number of fluorescence channel, can be achieved. This work validates METEOR-dPCR with simultaneous DNA copy number profiling of 60 targets using dPCR in cancer cells, and demonstrates its sensitivity for estimating tumor fraction in mixed tumor and normal DNA samples. The rapid, quantitative, and highly multiplexed METEOR-dPCR assay will have wide appeal for many clinical applications.
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Affiliation(s)
- Dong Dong Liu
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
| | - Daniel Muliaditan
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
- Genome institute of SingaporeAgency for ScienceTechnology and ResearchSingapore138672Singapore
| | - Ramya Viswanathan
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Xu Cui
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Lih Feng Cheow
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
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6
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Quah HS, Cao EY, Suteja L, Li CH, Leong HS, Chong FT, Gupta S, Arcinas C, Ouyang JF, Ang V, Celhar T, Zhao Y, Tay HC, Chan J, Takahashi T, Tan DSW, Biswas SK, Rackham OJL, Iyer NG. Single cell analysis in head and neck cancer reveals potential immune evasion mechanisms during early metastasis. Nat Commun 2023; 14:1680. [PMID: 36973261 PMCID: PMC10042873 DOI: 10.1038/s41467-023-37379-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/15/2023] [Indexed: 03/29/2023] Open
Abstract
Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures. Furthermore, scRNAseq analyses of tumor-infiltrating CD8 + T-lymphocytes show two distinct trajectories to T-cell dysfunction, corroborated by their clonal architecture based on single-cell T-cell receptor sequencing. By determining key modulators of these trajectories, followed by validation using external datasets and functional experiments, we uncover a role for SOX4 in mediating T-cell exhaustion. Finally, interactome analyses between pre-metastatic tumor cells and CD8 + T-lymphocytes uncover a putative role for the Midkine pathway in immune-modulation and this is confirmed by scRNAseq of tumors from humanized mice. Aside from specific findings, this study demonstrates the importance of tumor heterogeneity analyses in identifying key vulnerabilities during early metastasis.
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Affiliation(s)
- Hong Sheng Quah
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
- Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore
| | - Elaine Yiqun Cao
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Lisda Suteja
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
| | - Constance H Li
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
- Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore
| | - Hui Sun Leong
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
| | - Fui Teen Chong
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
| | - Shilpi Gupta
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Camille Arcinas
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
- Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore
| | - John F Ouyang
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Vivian Ang
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Teja Celhar
- HuNIT platform, Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Yunqian Zhao
- HuNIT platform, Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Hui Chen Tay
- HuNIT platform, Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Jerry Chan
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore
| | - Takeshi Takahashi
- Laboratory Animal Research Department, Central Institute for Experimental Animals (CIEA), Kawasaki, Japan
| | - Daniel S W Tan
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore
- Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore
- Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
| | - Subhra K Biswas
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Owen J L Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
- School of Biological Sciences, University of Southampton, Southampton, United Kingdom
- The Alan Turing Institute, The British Library, London, United Kingdom
| | - N Gopalakrishna Iyer
- Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore.
- Academic Clinical Program in Oncology, Duke-NUS Medical School, Singapore, Singapore.
- Department of Head and Neck Surgery, National Cancer Centre, Singapore, Singapore.
- Division of Medical Sciences, National Cancer Centre, Singapore, Singapore.
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7
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Ex Vivo Functional Assay for Evaluating Treatment Response in Tumor Tissue of Head and Neck Squamous Cell Carcinoma. Cancers (Basel) 2023; 15:cancers15020478. [PMID: 36672427 PMCID: PMC9856585 DOI: 10.3390/cancers15020478] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Head and neck squamous cell carcinoma (HNSCC) displays a large heterogeneity in treatment response, and consequently in patient prognosis. Despite extensive efforts, no clinically validated model is available to predict tumor response. Here we describe a functional test for predicting tumor response to radiation and chemotherapy on the level of the individual patient. METHODS Resection material of 17 primary HNSCC patients was cultured ex vivo, irradiated or cisplatin-treated, after which the effect on tumor cell vitality was analyzed several days after treatment. RESULTS Ionizing radiation (IR) affected tumor cell growth and viability with a clear dose-response relationship, and marked heterogeneity between tumors was observed. After a single dose of 5Gy, proliferation in IR-sensitive tumors dropped below 30% of the untreated level, while IR-resistant tumors maintained at least 60% of proliferation. IR-sensitive tumors showed on average a twofold increase in apoptosis, as well as an increased number and size of DNA damage foci after treatment. No differences in the homologous recombination (HR) proficiency between IR-sensitive and -resistant tumors were detected. Cisplatin caused a decrease in proliferation, as well as induction of apoptosis, again with marked variation between the samples. CONCLUSIONS Our functional ex vivo assay discriminated between IR-sensitive and IR-resistant HNSCC tumors, and may also be suitable for predicting response to cisplatin. Its predictive value is currently under investigation in a prospective clinical study.
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8
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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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9
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Lv W, Chen T, Wang S, Li C, Zhang B, Wang L, Xv F, Cao F, Wang J, Chen L, Liao C, Li N, Liu H. Feasibility of high-throughput drug sensitivity screening (HDS)-guided treatment for children with refractory or relapsed acute myeloid leukemia. Front Pediatr 2023; 11:1117988. [PMID: 36873635 PMCID: PMC9982438 DOI: 10.3389/fped.2023.1117988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 01/23/2023] [Indexed: 02/19/2023] Open
Abstract
Relapsed/refractory (rel/ref) acute myeloid leukemia (AML) has a very high mortality rate. At present, hematopoietic stem cell transplantation (HSCT) is the most effective treatment for rel/ref AML. The remission of the primary disease before HSCT is crucial for the transplantation to be effective. Therefore, it is critical to choose a suitable type of chemotherapy before HSCT. Here, we recorded the outcomes of high-throughput drug sensitivity screening (HDS) in children with rel/ref AML. Thirty-seven pediatric rel/ref AML patients who received HDS from September 2017 until July 2021 were analyzed retrospectively. Most of the patients (24 patients, 64.9%) had adverse cytogenetics. Two patients had rel/ref AML with central nervous system leukemia. The complete remission (CR) rate was 67.6%. Eight patients developed IV grade bone marrow suppression. Twenty-three patients (62.2%) underwent HSCT. The 3-year overall survival (OS) and EFS rates were 45.9% and 43.2%, respectively. Infection in the myelosuppression stage was the main cause of death. The outcome of HDS was superior to the commonly reported rates. These results suggest that HDS may be a novel treatment option for pediatric patients with rel/ref AML, and it is a promising transitional regimen prior to HSCT.
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Affiliation(s)
- Wenxiu Lv
- Department of Hematology and Oncology, Anhui Provincial Children's Hospital (Anhui Hospital, Pediatric Hospital of Fudan University), Hefei, Anhui, China.,Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Tianping Chen
- Department of Hematology and Oncology, Anhui Provincial Children's Hospital (Anhui Hospital, Pediatric Hospital of Fudan University), Hefei, Anhui, China
| | - Shen Wang
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Chun Li
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Bo Zhang
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Liang Wang
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Fang Xv
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Fang Cao
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Jing Wang
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Li Chen
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Chenglin Liao
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Na Li
- Department of Pediatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Hongjun Liu
- Department of Hematology and Oncology, Anhui Provincial Children's Hospital (Anhui Hospital, Pediatric Hospital of Fudan University), Hefei, Anhui, China
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10
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Goh J, De Mel S, Hoppe MM, Mohd Abdul Rashid MB, Zhang XY, Jaynes P, Ka Yan Ng E, Rahmat NDB, Jayalakshmi, Liu CX, Poon L, Chan E, Lee J, Chee YL, Koh LP, Tan LK, Soh TG, Yuen YC, Loi HY, Ng SB, Goh X, Eu D, Loh S, Ng S, Tan D, Cheah DMZ, Pang WL, Huang D, Ong SY, Nagarajan C, Chan JY, Ha JCH, Khoo LP, Somasundaram N, Tang T, Ong CK, Chng WJ, Lim ST, Chow EK, Jeyasekharan AD. An ex vivo platform to guide drug combination treatment in relapsed/refractory lymphoma. Sci Transl Med 2022; 14:eabn7824. [PMID: 36260690 DOI: 10.1126/scitranslmed.abn7824] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin's lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options (n = 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo-guided combination therapy in RR-NHL.
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Affiliation(s)
- Jasmine Goh
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Sanjay De Mel
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Michal M Hoppe
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | | | - Xi Yun Zhang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Patrick Jaynes
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Esther Ka Yan Ng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | | | - Jayalakshmi
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Clementine Xin Liu
- Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Limei Poon
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Esther Chan
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Joanne Lee
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Yen Lin Chee
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Liang Piu Koh
- Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore
| | - Lip Kun Tan
- Department of Laboratory Medicine, National University Hospital, Singapore 119074, Singapore
| | - Teck Guan Soh
- Department of Laboratory Medicine, National University Hospital, Singapore 119074, Singapore
| | - Yi Ching Yuen
- Department of Pharmacy, National University Health System, Singapore 119074, Singapore
| | - Hoi-Yin Loi
- Department of Diagnostic Imaging, National University Hospital, Singapore 119074, Singapore
| | - Siok-Bian Ng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Xueying Goh
- Department of Otolaryngology, National University Hospital, Singapore 119074, Singapore
| | - Donovan Eu
- Department of Otolaryngology, National University Hospital, Singapore 119074, Singapore
| | - Stanley Loh
- Department of Diagnostic Imaging, National University Hospital, Singapore 119074, Singapore
| | - Sheldon Ng
- Department of Diagnostic Imaging, National University Hospital, Singapore 119074, Singapore
| | - Daryl Tan
- Mount Elizabeth Novena Hospital, Singapore 329563, Singapore.,Department of Haematology, Singapore General Hospital, Singapore 169608, Singapore
| | - Daryl Ming Zhe Cheah
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Wan Lu Pang
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Dachuan Huang
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Shin Yeu Ong
- Department of Haematology, Singapore General Hospital, Singapore 169608, Singapore
| | | | - Jason Yongsheng Chan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore.,SingHealth Duke-NUS Blood Cancer Centre, Singapore 168582, Singapore
| | - Jeslin Chian Hung Ha
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Lay Poh Khoo
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Nagavalli Somasundaram
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Tiffany Tang
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Choon Kiat Ong
- Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore 169610, Singapore.,Programme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore.,Genome Institute of Singapore, A*STAR, Singapore 138672, Singapore
| | - Wee-Joo Chng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Soon Thye Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore.,SingHealth Duke-NUS Blood Cancer Centre, Singapore 168582, Singapore.,Office of Education, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Edward K Chow
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.,N.1 Institute for Health, National University of Singapore, Singapore 117456, Singapore.,Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Anand D Jeyasekharan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University Singapore, Singapore 117599, Singapore.,Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Health System, Singapore 119074, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
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11
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Ong LJY, Chia S, Wong SQR, Zhang X, Chua H, Loo JM, Chua WY, Chua C, Tan E, Hentze H, Tan IB, DasGupta R, Toh YC. A comparative study of tumour-on-chip models with patient-derived xenografts for predicting chemotherapy efficacy in colorectal cancer patients. Front Bioeng Biotechnol 2022; 10:952726. [PMID: 36147524 PMCID: PMC9488115 DOI: 10.3389/fbioe.2022.952726] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/19/2022] [Indexed: 11/24/2022] Open
Abstract
Inter-patient and intra-tumour heterogeneity (ITH) have prompted the need for a more personalised approach to cancer therapy. Although patient-derived xenograft (PDX) models can generate drug response specific to patients, they are not sustainable in terms of cost and time and have limited scalability. Tumour Organ-on-Chip (OoC) models are in vitro alternatives that can recapitulate some aspects of the 3D tumour microenvironment and can be scaled up for drug screening. While many tumour OoC systems have been developed to date, there have been limited validation studies to ascertain whether drug responses obtained from tumour OoCs are comparable to those predicted from patient-derived xenograft (PDX) models. In this study, we established a multiplexed tumour OoC device, that consists of an 8 × 4 array (32-plex) of culture chamber coupled to a concentration gradient generator. The device enabled perfusion culture of primary PDX-derived tumour spheroids to obtain dose-dependent response of 5 distinct standard-of-care (SOC) chemotherapeutic drugs for 3 colorectal cancer (CRC) patients. The in vitro efficacies of the chemotherapeutic drugs were rank-ordered for individual patients and compared to the in vivo efficacy obtained from matched PDX models. We show that quantitative correlation analysis between the drug efficacies predicted via the microfluidic perfusion culture is predictive of response in animal PDX models. This is a first study showing a comparative framework to quantitatively correlate the drug response predictions made by a microfluidic tumour organ-on-chip (OoC) model with that of PDX animal models.
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Affiliation(s)
- Louis Jun Ye Ong
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QL, Australia
- Centre for Biomedical Technologies, Queensland University of Technology (QUT), Brisbane, QL, Australia
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
| | - Shumei Chia
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Stephen Qi Rong Wong
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Biological Resource Centre, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Samuel Oschin Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Xiaoqian Zhang
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Huiwen Chua
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Jia Min Loo
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Wei Yong Chua
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Clarinda Chua
- National Cancer Centre Singapore, Singapore, Singapore
| | - Emile Tan
- Singapore General Hospital, Singapore, Singapore
| | - Hannes Hentze
- Experimental, Drug Development Centre, A*STAR, Singapore, Singapore
| | - Iain Beehuat Tan
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
- National Cancer Centre Singapore, Singapore, Singapore
- Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Ramanuj DasGupta
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore, A*STAR, Singapore, Singapore
- *Correspondence: Ramanuj DasGupta, ; Yi-Chin Toh,
| | - Yi-Chin Toh
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QL, Australia
- Centre for Biomedical Technologies, Queensland University of Technology (QUT), Brisbane, QL, Australia
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- *Correspondence: Ramanuj DasGupta, ; Yi-Chin Toh,
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12
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Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches. J Pers Med 2022; 12:jpm12060854. [PMID: 35743639 PMCID: PMC9224778 DOI: 10.3390/jpm12060854] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/11/2022] [Accepted: 05/19/2022] [Indexed: 02/07/2023] Open
Abstract
Head and neck cancers (HNCs) represent the sixth most widespread malignancy worldwide. Surgery, radiotherapy, chemotherapeutic and immunotherapeutic drugs represent the main clinical approaches for HNC patients. Moreover, HNCs are characterised by an elevated mutational load; however, specific genetic mutations or biomarkers have not yet been found. In this scenario, personalised medicine is showing its efficacy. To study the reliability and the effects of personalised treatments, preclinical research can take advantage of next-generation sequencing and innovative technologies that have been developed to obtain genomic and multi-omic profiles to drive personalised treatments. The crosstalk between malignant and healthy components, as well as interactions with extracellular matrices, are important features which are responsible for treatment failure. Preclinical research has constantly implemented in vitro and in vivo models to mimic the natural tumour microenvironment. Among them, 3D systems have been developed to reproduce the tumour mass architecture, such as biomimetic scaffolds and organoids. In addition, in vivo models have been changed over the last decades to overcome problems such as animal management complexity and time-consuming experiments. In this review, we will explore the new approaches aimed to improve preclinical tools to study and apply precision medicine as a therapeutic option for patients affected by HNCs.
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13
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Ramazzotti D, Angaroni F, Maspero D, Ascolani G, Castiglioni I, Piazza R, Antoniotti M, Graudenzi A. Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines. Nat Commun 2022; 13:2718. [PMID: 35551450 PMCID: PMC9098403 DOI: 10.1038/s41467-022-30230-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 04/06/2022] [Indexed: 12/30/2022] Open
Affiliation(s)
| | - Fabrizio Angaroni
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | - Davide Maspero
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.,Inst. of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Segrate, Milan, Italy
| | - Gianluca Ascolani
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | | | - Rocco Piazza
- Dept. of Medicine and Surgery, Univ. of Milan-Bicocca, Monza, Italy.,Bicocca Bioinformatics, Biostatistics and Bioimaging Centre - B4, Milan, Italy
| | - Marco Antoniotti
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.,Bicocca Bioinformatics, Biostatistics and Bioimaging Centre - B4, Milan, Italy
| | - Alex Graudenzi
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy. .,Inst. of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Segrate, Milan, Italy. .,Bicocca Bioinformatics, Biostatistics and Bioimaging Centre - B4, Milan, Italy.
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14
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Xiang W, Lam YH, Periyasamy G, Chuah C. Application of High Throughput Technologies in the Development of Acute Myeloid Leukemia Therapy: Challenges and Progress. Int J Mol Sci 2022; 23:ijms23052863. [PMID: 35270002 PMCID: PMC8910862 DOI: 10.3390/ijms23052863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/26/2022] [Accepted: 02/28/2022] [Indexed: 11/27/2022] Open
Abstract
Acute myeloid leukemia (AML) is a complex hematological malignancy characterized by extensive heterogeneity in genetics, response to therapy and long-term outcomes, making it a prototype example of development for personalized medicine. Given the accessibility to hematologic malignancy patient samples and recent advances in high-throughput technologies, large amounts of biological data that are clinically relevant for diagnosis, risk stratification and targeted drug development have been generated. Recent studies highlight the potential of implementing genomic-based and phenotypic-based screens in clinics to improve survival in patients with refractory AML. In this review, we will discuss successful applications as well as challenges of most up-to-date high-throughput technologies, including artificial intelligence (AI) approaches, in the development of personalized medicine for AML, and recent clinical studies for evaluating the utility of integrating genomics-guided and drug sensitivity testing-guided treatment approaches for AML patients.
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Affiliation(s)
- Wei Xiang
- Department of Haematology, Singapore General Hospital, Singapore 169608, Singapore; (W.X.); (Y.H.L.)
| | - Yi Hui Lam
- Department of Haematology, Singapore General Hospital, Singapore 169608, Singapore; (W.X.); (Y.H.L.)
| | - Giridharan Periyasamy
- High Throughput Phenomics Platform, Experimental Drug Development Centre, Agency for Science, Technology and Research (A*STAR), Singapore 139632, Singapore;
| | - Charles Chuah
- Department of Haematology, Singapore General Hospital, Singapore 169608, Singapore; (W.X.); (Y.H.L.)
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore 169857, Singapore
- Correspondence:
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15
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Functional Therapeutic Target Validation Using Pediatric Zebrafish Xenograft Models. Cancers (Basel) 2022; 14:cancers14030849. [PMID: 35159116 PMCID: PMC8834194 DOI: 10.3390/cancers14030849] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/29/2022] [Accepted: 02/03/2022] [Indexed: 12/14/2022] Open
Abstract
Simple Summary Despite the major progress of precision and personalized oncology, a significant therapeutic benefit is only achieved in cases with directly druggable genetic alterations. This highlights the need for additional methods that reliably predict each individual patient’s response in a clinically meaningful time, e.g., through ex vivo functional drug screen profiling. Moreover, patient-derived xenograft (PDX) models are more predictive than cell culture studies, as they reconstruct cell–cell and cell–extracellular matrix (ECM) interactions and consider the tumor microenvironment, drug metabolism and toxicities. Zebrafish PDXs (zPDX) are nowadays emerging as a fast model allowing for multiple drugs to be tested at the same time in a clinically relevant time window. Here, we show that functional drug response profiling of zPDX from primary material obtained through the INdividualized Therapy FOr Relapsed Malignancies in Childhood (INFORM) pediatric precision oncology pipeline provides additional key information for personalized precision oncology. Abstract The survival rate among children with relapsed tumors remains poor, due to tumor heterogeneity, lack of directly actionable tumor drivers and multidrug resistance. Novel personalized medicine approaches tailored to each tumor are urgently needed to improve cancer treatment. Current pediatric precision oncology platforms, such as the INFORM (INdividualized Therapy FOr Relapsed Malignancies in Childhood) study, reveal that molecular profiling of tumor tissue identifies targets associated with clinical benefit in a subgroup of patients only and should be complemented with functional drug testing. In such an approach, patient-derived tumor cells are exposed to a library of approved oncological drugs in a physiological setting, e.g., in the form of animal avatars injected with patient tumor cells. We used molecularly fully characterized tumor samples from the INFORM study to compare drug screen results of individual patient-derived cell models in functional assays: (i) patient-derived spheroid cultures within a few days after tumor dissociation; (ii) tumor cells reisolated from the corresponding mouse PDX; (iii) corresponding long-term organoid-like cultures and (iv) drug evaluation with the corresponding zebrafish PDX (zPDX) model. Each model had its advantage and complemented the others for drug hit and drug combination selection. Our results provide evidence that in vivo zPDX drug screening is a promising add-on to current functional drug screening in precision medicine platforms.
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16
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Ahmad US, Parkinson EK, Wan H. Desmoglein-3 induces YAP phosphorylation and inactivation during collective migration of oral carcinoma cells. Mol Oncol 2022; 16:1625-1649. [PMID: 35000271 PMCID: PMC9019900 DOI: 10.1002/1878-0261.13177] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 12/08/2021] [Accepted: 01/06/2022] [Indexed: 11/07/2022] Open
Abstract
Alterations of the Hippo-YAP pathway are potential targets for oral squamous cell carcinoma (OSCC) therapy, but heterogeneity in this pathway could be responsible for therapeutic resistance. We analysed the Hippo-YAP signatures in a cohort of characterised keratinocyte cell lines derived from the mouth floor and buccal mucosa from different stages of OSCC tumour progression and focused on the specific role of YAP on invasive and metastatic potential. We confirmed heterogeneity in the Hippo-YAP pathway in OSCC lines, including overexpression of YAP1, WWTR1 (often referred to as TAZ) and the major Hippo signalling components, as well as the variations in the genes encoding the intercellular anchoring junctional proteins, which could potentially regulate the Hippo pathway. Specifically, desmoglein-3 (DSG3) exhibits a unique and mutually exclusive regulation of YAP via YAP phosphorylation during the collective migration of OSCC cells. Mechanistically, such regulation is associated with inhibition of phosphorylation of epidermal growth factor receptor (EGFR) (S695/Y1086) and its downstream effectors heat shock protein beta-1 (Hsp27) (S78/S82) and transcription factor AP-1 (c-Jun) (S63), leading to YAP phosphorylation coupled with its cytoplasmic translocation and inactivation. Additionally, OSCC lines display distinct phenotypes of YAP dependency or a mixed YAP and TAZ dependency for cell migration, and present distinct patterns in YAP abundance and activity, with the latter being associated with YAP nuclear localisation. In conclusion, this study has provided evidence for a newly identified paradigm in the Hippo-YAP pathway and suggests a new regulation mechanism involved in the control of collective migration in OSCC cells.
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Affiliation(s)
- Usama Sharif Ahmad
- Centre for Oral Immunobiology and Regenerative Medicine, Institute of Dentistry, School of Medicine and Dentistry, Barts and The London, London, UK
| | - Eric Kenneth Parkinson
- Centre for Oral Immunobiology and Regenerative Medicine, Institute of Dentistry, School of Medicine and Dentistry, Barts and The London, London, UK
| | - Hong Wan
- Centre for Oral Immunobiology and Regenerative Medicine, Institute of Dentistry, School of Medicine and Dentistry, Barts and The London, London, UK
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17
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den bossche VV, Zaryouh H, Vara-Messler M, Vignau J, Machiels JP, Wouters A, Schmitz S, Corbet C. Microenvironment-driven intratumoral heterogeneity in head and neck cancers: clinical challenges and opportunities for precision medicine. Drug Resist Updat 2022; 60:100806. [DOI: 10.1016/j.drup.2022.100806] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 02/06/2023]
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18
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Suphavilai C, Chia S, Sharma A, Tu L, Da Silva RP, Mongia A, DasGupta R, Nagarajan N. Predicting heterogeneity in clone-specific therapeutic vulnerabilities using single-cell transcriptomic signatures. Genome Med 2021; 13:189. [PMID: 34915921 PMCID: PMC8680165 DOI: 10.1186/s13073-021-01000-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 11/02/2021] [Indexed: 12/22/2022] Open
Abstract
While understanding molecular heterogeneity across patients underpins precision oncology, there is increasing appreciation for taking intra-tumor heterogeneity into account. Based on large-scale analysis of cancer omics datasets, we highlight the importance of intra-tumor transcriptomic heterogeneity (ITTH) for predicting clinical outcomes. Leveraging single-cell RNA-seq (scRNA-seq) with a recommender system (CaDRReS-Sc), we show that heterogeneous gene-expression signatures can predict drug response with high accuracy (80%). Using patient-proximal cell lines, we established the validity of CaDRReS-Sc's monotherapy (Pearson r>0.6) and combinatorial predictions targeting clone-specific vulnerabilities (>10% improvement). Applying CaDRReS-Sc to rapidly expanding scRNA-seq compendiums can serve as in silico screen to accelerate drug-repurposing studies. Availability: https://github.com/CSB5/CaDRReS-Sc .
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Affiliation(s)
| | - Shumei Chia
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Ankur Sharma
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Lorna Tu
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rafael Peres Da Silva
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- School of Computing, National University of Singapore, Singapore, Singapore
| | - Aanchal Mongia
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Department of Computer Science and Engineering, Indraprastha Institute of Information Technology, Delhi, India
| | | | - Niranjan Nagarajan
- Genome Institute of Singapore, A*STAR, Singapore, Singapore.
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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19
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Fong ELS, Iyer NG. Next generation in vitro tumor models guiding cancer therapy. Adv Drug Deliv Rev 2021; 179:114047. [PMID: 34763000 DOI: 10.1016/j.addr.2021.114047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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20
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Chen J, Cheng J, Zhao C, Zhao B, Mi J, Li W. The Hippo pathway: a renewed insight in the craniofacial diseases and hard tissue remodeling. Int J Biol Sci 2021; 17:4060-4072. [PMID: 34671220 PMCID: PMC8495397 DOI: 10.7150/ijbs.63305] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 09/20/2021] [Indexed: 12/13/2022] Open
Abstract
The Hippo pathway plays an important role in many pathophysiological processes, including cell proliferation and differentiation, cell death, cell migration and invasion. Because of its extensive functions, Hippo pathway is closely related to not only growth and development, but also many diseases, including inflammation and cancer. In this study, the role of Hippo pathway in craniofacial diseases and hard tissue remodeling was reviewed, in attempting to find new research directions.
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Affiliation(s)
- Jun Chen
- Xiangya School of Stomatology, Central South University, Changsha 410008, China.,Xiangya Stomatological Hospital, Central South University, Changsha 410008, China.,Hunan Key Laboratory of Oral Health Research, Hunan 3D Printing Engineering Research Center of Oral Care, Hunan Clinical Research Center of Oral Major Diseases and Oral Health, Central South University, Changsha 410008, China
| | - Jingyi Cheng
- Xiangya School of Stomatology, Central South University, Changsha 410008, China
| | - Cong Zhao
- Xiangya School of Stomatology, Central South University, Changsha 410008, China
| | - Boxuan Zhao
- Xiangya School of Stomatology, Central South University, Changsha 410008, China
| | - Jia Mi
- Xiangya School of Stomatology, Central South University, Changsha 410008, China
| | - Wenjie Li
- Xiangya School of Stomatology, Central South University, Changsha 410008, China.,Xiangya Stomatological Hospital, Central South University, Changsha 410008, China.,Hunan Key Laboratory of Oral Health Research, Hunan 3D Printing Engineering Research Center of Oral Care, Hunan Clinical Research Center of Oral Major Diseases and Oral Health, Central South University, Changsha 410008, China.,National Key Laboratory of Science and Technology on High-strength Structural Materials, Central South University, Changsha 410083, China.,State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, China
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21
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Saddawi-Konefka R, Simon AB, Sumner W, Sharabi A, Mell LK, Cohen EEW. Defining the Role of Immunotherapy in the Curative Treatment of Locoregionally Advanced Head and Neck Cancer: Promises, Challenges, and Opportunities. Front Oncol 2021; 11:738626. [PMID: 34621678 PMCID: PMC8490924 DOI: 10.3389/fonc.2021.738626] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/01/2021] [Indexed: 12/30/2022] Open
Abstract
Recent advancements in the development of immunotherapies have raised the hope for patients with locally-advanced HNSCC (LA-HNSCC) to achieve improved oncologic outcomes without the heavy burden of treatment-related morbidity. While there are several ongoing late phase clinical trials that seek to determine whether immunotherapy can be effectively employed in the definitive setting, initial results from concurrent immuno-radiotherapy therapy trials have not shown strong evidence of benefit. Encouragingly, evidence from preclinical studies and early-phase neoadjuvant studies have begun to show potential pathways forward, with therapeutic combinations and sequences that intentionally spare tumor draining lymphatics in order to maximize the synergy between definitive local therapy and immunotherapy. The intent of this review is to summarize the scientific rationale and current clinical evidence for employing immunotherapy for LA-HNSCC as well as the ongoing efforts and challenges to determine how to optimally deliver and sequence immunotherapy alongside traditional therapeutics. In both the preclinical and clinical settings, we will discuss the application of immunotherapies to both surgical and radiotherapeutic management of HNSCC.
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Affiliation(s)
- Robert Saddawi-Konefka
- Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA, United States
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
| | - Aaron B. Simon
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
- Department of Radiation Oncology, UC Irvine School of Medicine, Irvine, CA, United States
| | - Whitney Sumner
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
- Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, San Diego, CA, United States
| | - Andrew Sharabi
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
- Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, San Diego, CA, United States
| | - Loren K. Mell
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
- Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, San Diego, CA, United States
| | - Ezra E. W. Cohen
- Moores Cancer Center, UC San Diego, La Jolla, CA, United States
- Department of Medicine, Division of Hematology-Oncology, UC San Diego School of Medicine, San Diego, CA, United States
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22
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Li H, Jiang H, Huang Z, Chen Z, Chen N. Prognostic Value of an m 5C RNA Methylation Regulator-Related Signature for Clear Cell Renal Cell Carcinoma. Cancer Manag Res 2021; 13:6673-6687. [PMID: 34471382 PMCID: PMC8404088 DOI: 10.2147/cmar.s323072] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 08/02/2021] [Indexed: 12/27/2022] Open
Abstract
Purpose Clear cell renal cell carcinoma (ccRCC) is highly heterogeneous and is one of the most lethal types of cancer within the urinary system. Aberrant expression of 5-methylcytosine (m5C) RNA methylation regulators has been shown to result in occurrence and progression of tumors. However, the role of these regulators in ccRCC remains unclear. Materials and Methods We extracted RNA sequencing expression data with corresponding clinical information of patients with ccRCC from The Cancer Genome Atlas (TCGA) database. We then compared the expression profiles of m5C RNA methylation regulators between normal and ccRCC tissues, and determined different subtypes through consensus clustering analysis. In addition, we constructed a prognostic signature and evaluated it using a range of bioinformatics approaches. The expression of signature-related genes was subsequently verified in the clinical samples using qRT-PCR. Results We identified 12 differentially expressed m5C RNA methylation regulators between cancer and normal control samples. Two clusters of patients with ccRCC and diverse clinicopathological characteristics and prognoses were then determined through consensus clustering analysis. Functional annotations revealed that m5C RNA regulators were significantly correlated with the ccRCC progression. Moreover, we constructed a four-gene risk score signature (comprised of NOP2, NSUN4, NSUN6, and TET2) and divided the patients with ccRCC into high- and low-risk groups based on the median risk score. The risk score was associated with clinicopathological features and was an independent prognostic indicator of ccRCC. Our stratified analysis results suggest that the signature has high prognostic value. Based on qRT-PCR results, the NOP2 and NSUN4 mRNA expressions were higher and those of NSUN6 and TET2 were lower in ccRCC tissues than in normal tissues. Conclusion Our results demonstrate that m5C RNA methylation regulators may affect ccRCC progression and could be exploited for diagnostic and prognostic purposes.
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Affiliation(s)
- Hanrong Li
- Department of Extracorporeal Shock Wave Lithotripsy, Meizhou People's Hospital (Huangtang Hospital), Meizhou, Guangdong, People's Republic of China
| | - Huiming Jiang
- Department of Urology, Meizhou People's Hospital (Huangtang Hospital), Meizhou, Guangdong, People's Republic of China
| | - Zhicheng Huang
- Department of Urology, Meizhou People's Hospital (Huangtang Hospital), Meizhou, Guangdong, People's Republic of China
| | - Zhilin Chen
- Department of Urology, Meizhou People's Hospital (Huangtang Hospital), Meizhou, Guangdong, People's Republic of China
| | - Nanhui Chen
- Department of Urology, Meizhou People's Hospital (Huangtang Hospital), Meizhou, Guangdong, People's Republic of China
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23
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Wang B, Warden AR, Ding X. The optimization of combinatorial drug therapies: Strategies and laboratorial platforms. Drug Discov Today 2021; 26:2646-2659. [PMID: 34332097 DOI: 10.1016/j.drudis.2021.07.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/19/2021] [Accepted: 07/14/2021] [Indexed: 12/26/2022]
Abstract
Designing optimal combinatorial drug therapies is challenging, because the drug interactions depend not only on the drugs involved, but also on their doses. With recent advances, combinatorial drug therapy is closer than ever to clinical application. Herein, we summarize approaches and advances over the past decade for identifying and optimizing drug combination therapies, with innovations across research fields, covering physical laboratory platforms for combination screening to computational models and algorithms designed for synergism prediction and optimization. By comparing different types of approach, we detail a three-step workflow that could maximize the overall optimization efficiency, thus enabling the application of personalized optimization of combinatorial drug therapy.
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Affiliation(s)
- Boqian Wang
- Institute for Personalized Medicine, State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China
| | - Antony R Warden
- Institute for Personalized Medicine, State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China
| | - Xianting Ding
- Institute for Personalized Medicine, State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China.
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24
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van Harten AM, Brakenhoff RH. Targeted Treatment of Head and Neck (Pre)Cancer: Preclinical Target Identification and Development of Novel Therapeutic Applications. Cancers (Basel) 2021; 13:2774. [PMID: 34204886 PMCID: PMC8199752 DOI: 10.3390/cancers13112774] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 12/14/2022] Open
Abstract
Head and neck squamous cell carcinomas (HNSCC) develop in the mucosal lining of the upper-aerodigestive tract. In carcinogen-induced HNSCC, tumors emerge from premalignant mucosal changes characterized by tumor-associated genetic alterations, also coined as 'fields' that are occasionally visible as leukoplakia or erythroplakia lesions but are mostly invisible. Consequently, HNSCC is generally diagnosed de novo at more advanced stages in about 70% of new diagnosis. Despite intense multimodality treatment protocols, the overall 5-years survival rate is 50-60% for patients with advanced stage of disease and seems to have reached a plateau. Of notable concern is the lack of further improvement in prognosis despite advances in treatment. This can be attributed to the late clinical presentation, failure of advanced HNSCC to respond to treatment, the deficit of effective targeted therapies to eradicate tumors and precancerous changes, and the lack of suitable markers for screening and personalized therapy. The molecular landscape of head and neck cancer has been elucidated in great detail, but the absence of oncogenic mutations hampers the identification of druggable targets for therapy to improve outcome of HNSCC. Currently, functional genomic approaches are being explored to identify potential therapeutic targets. Identification and validation of essential genes for both HNSCC and oral premalignancies, accompanied with biomarkers for therapy response, are being investigated. Attentive diagnosis and targeted therapy of the preceding oral premalignant (preHNSCC) changes may prevent the development of tumors. As classic oncogene addiction through activating mutations is not a realistic concept for treatment of HNSCC, synthetic lethality and collateral lethality need to be exploited, next to immune therapies. In recent studies it was shown that cell cycle regulation and DNA damage response pathways become significantly altered in HNSCC causing replication stress, which is an avenue that deserves further exploitation as an HNSCC vulnerability for treatment. The focus of this review is to summarize the current literature on the preclinical identification of potential druggable targets for therapy of (pre)HNSCC, emerging from the variety of gene knockdown and knockout strategies, and the testing of targeted inhibitors. We will conclude with a future perspective on targeted therapy of HNSCC and premalignant changes.
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Affiliation(s)
- Anne M. van Harten
- Cancer Center Amsterdam, Otolaryngology-Head and Neck Surgery, Tumor Biology & Immunology Section, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands; or
- Sidney Kimmel Cancer Center, Department of Cancer Biology, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Ruud H. Brakenhoff
- Cancer Center Amsterdam, Otolaryngology-Head and Neck Surgery, Tumor Biology & Immunology Section, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands; or
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25
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Abstract
Overcoming the challenges of understanding and treating cancer requires reliable patient-derived models of cancer (PDMCs). For decades, cancer research and therapeutic development relied primarily on cancer cell lines because of their prevalence, reproducibility, and simplicity to maintain. However, findings from research conducted in cell lines are rarely recapitulated in vivo and seldom directly translatable to patients. The tumor microenvironment (TME), tumor-stromal interactions, and associations with host immune cells produce profound changes in tumor phenotype and complexity not captured in traditional monolayer cell culture. In this chapter, we present various cancer explant models and discuss their applicability based on specific research aims. We discuss the appropriateness of these models for basic science questions, drug screening/development, and for personalized, precision medicine. We also consider logistical factors such as resource cost, technical difficulty, and accessibility. We finish this chapter with a practical guide intended to help the reader select the cancer explant model system(s) that best address their research aims.
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26
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Saidak Z, Lailler C, Testelin S, Chauffert B, Clatot F, Galmiche A. Contribution of Genomics to the Surgical Management and Study of Oral Cancer. Ann Surg Oncol 2021; 28:5842-5854. [PMID: 33846893 PMCID: PMC8460589 DOI: 10.1245/s10434-021-09904-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/07/2021] [Indexed: 02/06/2023]
Abstract
Background Oral squamous cell carcinoma (OSCC) is the most frequent type of tumor arising from the oral cavity. Surgery is the cornerstone of the treatment of these cancers. Tumor biology has long been overlooked as an important contributor to the outcome of surgical procedures, but recent studies are challenging this concept. Molecular analyses of tumor DNA or RNA provide a rich source of information about the biology of OSCC. Methods We searched for relevant articles using PubMed. We examined in particular the prospect of applying molecular methods for minimally invasive exploration of OSCC biology. Results We examined five potential applications of genomics to the surgical management and study of OSCC: i) assessing oral potentially malignant lesions; ii) tumor staging prior to surgery; iii) predicting postoperative risk in locally advanced tumors; iv) measuring minimal residual disease and optimizing the longitudinal monitoring of OSCC; and v) predicting the efficacy of medical treatment. Conclusions Genomic information can be harnessed in order to identify new biomarkers that could improve the staging, choice of therapy and management of OSCC. The identification of new biomarkers is awaited for better personalization of the surgical treatment of OSCC.
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Affiliation(s)
- Zuzana Saidak
- UR7516 "CHIMERE, Université de Picardie Jules Verne", Amiens, France. .,Centre de Biologie Humaine, CHU Amiens, Amiens, France.
| | - Claire Lailler
- UR7516 "CHIMERE, Université de Picardie Jules Verne", Amiens, France.,Centre de Biologie Humaine, CHU Amiens, Amiens, France
| | - Sylvie Testelin
- UR7516 "CHIMERE, Université de Picardie Jules Verne", Amiens, France.,Department of Maxillofacial Surgery, CHU Amiens, Amiens, France
| | - Bruno Chauffert
- UR7516 "CHIMERE, Université de Picardie Jules Verne", Amiens, France.,Department of Oncology, CHU Amiens, Amiens, France
| | - Florian Clatot
- Centre Henri Becquerel, Rouen, France.,INSERM U1245/Team IRON, Rouen, France
| | - Antoine Galmiche
- UR7516 "CHIMERE, Université de Picardie Jules Verne", Amiens, France.,Centre de Biologie Humaine, CHU Amiens, Amiens, France
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27
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Skanderup AJ, DasGupta R. Targeting the developmental origins of cancer. NATURE CANCER 2021; 2:256-257. [PMID: 35121958 DOI: 10.1038/s43018-021-00186-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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28
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Oh JW, Oh YJ, Han S, Her NG, Nam DH. High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma. Cancers (Basel) 2021; 13:cancers13030372. [PMID: 33498427 PMCID: PMC7864197 DOI: 10.3390/cancers13030372] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/16/2021] [Accepted: 01/17/2021] [Indexed: 12/23/2022] Open
Abstract
Simple Summary Real-time ex vivo drug testing tailors individual therapeutics based on predicted drug responses. Most technologies to date rely on conventional drug screening that provides low confidence data. Here, we present high-content analysis-based drug testing of glioblastoma patients to identify the right glioblastoma patients for a given drug. This generates multi-parameter biomarker and phenotype readouts providing a better reliability of the assay. Additionally, we showed a high-content drug repurposing screen and defined a new c-Met-inhibiting function of the CDK4/6 inhibitor Abemaciclib. Large-scale high throughput screening results demonstrate that Abemaciclib sensitivity in glioblastoma patients is highly correlated with the c-Met inhibitors sensitivity, further supporting the accuracy of the platform and important new clinical implications regarding multiple functions of Abemaciclib. Abstract (1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.
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Affiliation(s)
- Jeong-Woo Oh
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- Department of Health Sciences & Technology, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul 06351, Korea
| | - Yun Jeong Oh
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
| | - Suji Han
- Research Institute, National Cancer Center, Goyang 10408, Korea;
| | - Nam-Gu Her
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- R&D Center, AIMEDBIO Inc., Seoul 15835, Korea
- Correspondence: (N.-G.H.); (D.-H.N.); Tel.: +82-2-6285-0827
| | - Do-Hyun Nam
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- Department of Health Sciences & Technology, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul 06351, Korea
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University, Seoul 06351, Korea
- Correspondence: (N.-G.H.); (D.-H.N.); Tel.: +82-2-6285-0827
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29
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Lee TW, Lai A, Harms JK, Singleton DC, Dickson BD, Macann AMJ, Hay MP, Jamieson SMF. Patient-Derived Xenograft and Organoid Models for Precision Medicine Targeting of the Tumour Microenvironment in Head and Neck Cancer. Cancers (Basel) 2020; 12:E3743. [PMID: 33322840 PMCID: PMC7763264 DOI: 10.3390/cancers12123743] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 12/10/2020] [Accepted: 12/10/2020] [Indexed: 12/24/2022] Open
Abstract
Patient survival from head and neck squamous cell carcinoma (HNSCC), the seventh most common cause of cancer, has not markedly improved in recent years despite the approval of targeted therapies and immunotherapy agents. Precision medicine approaches that seek to individualise therapy through the use of predictive biomarkers and stratification strategies offer opportunities to improve therapeutic success in HNSCC. To enable precision medicine of HNSCC, an understanding of the microenvironment that influences tumour growth and response to therapy is required alongside research tools that recapitulate the features of human tumours. In this review, we highlight the importance of the tumour microenvironment in HNSCC, with a focus on tumour hypoxia, and discuss the fidelity of patient-derived xenograft and organoids for modelling human HNSCC and response to therapy. We describe the benefits of patient-derived models over alternative preclinical models and their limitations in clinical relevance and how these impact their utility in precision medicine in HNSCC for the discovery of new therapeutic agents, as well as predictive biomarkers to identify patients' most likely to respond to therapy.
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Affiliation(s)
- Tet Woo Lee
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
| | - Amy Lai
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
- Department of Pharmacology and Clinical Pharmacology, University of Auckland, Auckland 1023, New Zealand
| | - Julia K. Harms
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
| | - Dean C. Singleton
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
| | - Benjamin D. Dickson
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
| | - Andrew M. J. Macann
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
- Department of Radiation Oncology, Auckland City Hospital, Auckland 1023, New Zealand
| | - Michael P. Hay
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
| | - Stephen M. F. Jamieson
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand; (T.W.L.); (A.L.); (J.K.H.); (D.C.S.); (B.D.D.); (M.P.H.)
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand;
- Department of Pharmacology and Clinical Pharmacology, University of Auckland, Auckland 1023, New Zealand
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30
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Arora A, Niño JLG, Myaing MZ, Chia S, Arasi B, Ravasio A, Huang RYJ, Dasgupta R, Biro M, Viasnoff V. Two high-yield complementary methods to sort cell populations by their 2D or 3D migration speed. Mol Biol Cell 2020; 31:2779-2790. [PMID: 33085550 PMCID: PMC7851856 DOI: 10.1091/mbc.e20-07-0466] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/07/2020] [Accepted: 10/07/2020] [Indexed: 11/28/2022] Open
Abstract
The potential to migrate is one of the most fundamental functions for various epithelial, mesenchymal, and immune cells. Image analysis of motile cell populations, both primary and cultured, typically reveals an intercellular variability in migration speeds. However, cell migration chromatography, the sorting of large populations of cells based on their migratory characteristics, cannot be easily performed. The lack of such methods has hindered our understanding of the direct correlation between the capacity to migrate and other cellular properties. Here, we report two novel, easily implementable and readily scalable methods to sort millions of live migratory cancer and immune cells based on their spontaneous migration in two-dimensional and three-dimensional microenvironments, respectively. Correlative downstream transcriptomic, molecular and functional tests reveal marked differences between the fast and slow subpopulations in patient-derived cancer cells. We further employ our method to reveal that sorting the most migratory cytotoxic T lymphocytes yields a pool of cells with enhanced cytotoxicity against cancer cells. This phenotypic assay opens new avenues for the precise characterization of the mechanisms underlying hither to unexplained heterogeneities in migratory phenotypes within a cell population, and for the targeted enrichment of the most potent migratory leukocytes in immunotherapies.
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Affiliation(s)
- Aditya Arora
- Mechanobiology Institute, National University of Singapore, Singapore 117411
| | - Jorge Luis Galeano Niño
- EMBL Australia, Single Molecule Science Node, School of Medical Sciences, University of New South Wales 2052, Sydney, Australia
| | - Myint Zu Myaing
- Mechanobiology Institute, National University of Singapore, Singapore 117411
| | - Shumei Chia
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore/A*STAR, Singapore 138632
| | - Bakya Arasi
- Mechanobiology Institute, National University of Singapore, Singapore 117411
| | - Andrea Ravasio
- Mechanobiology Institute, National University of Singapore, Singapore 117411
- Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ruby Yun-Ju Huang
- Cancer Science Institute of Singapore, National University of Singapore, Centre for Translational Medicine, Singapore 117599
| | - Ramanuj Dasgupta
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore/A*STAR, Singapore 138632
| | - Maté Biro
- Laboratory of Precision Oncology and Cancer Evolution, Genome Institute of Singapore/A*STAR, Singapore 138632
| | - Virgile Viasnoff
- Mechanobiology Institute, National University of Singapore, Singapore 117411
- Pontificia Universidad Católica de Chile, Santiago, Chile
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31
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Schuch LF, Silveira FM, Wagner VP, Borgato GB, Rocha GZ, Castilho RM, Vargas PA, Martins MD. Head and neck cancer patient-derived xenograft models - A systematic review. Crit Rev Oncol Hematol 2020; 155:103087. [PMID: 32992152 DOI: 10.1016/j.critrevonc.2020.103087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/12/2020] [Accepted: 08/14/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Patient-derived xenograft (PDX) involve the direct surgical transfer of fresh human tumor samples to immunodeficient mice. This systematic review aimed to identify publications of head and neck cancer PDX (HNC-PDX) models, describing the main methodological characteristics and outcomes. METHODS An electronic search was undertaken in four databases, including publications having used HNC-PDX. Data were analyzed descriptively. RESULTS 63 articles were yielded. The nude mouse was one most commonly animal model used (38.8 %), and squamous cell carcinoma accounted for the majority of HNC-PDX (80.6 %). Tumors were mostly implanted in the flank (86.3 %), and the latency period ranged from 30 to 401 days. The successful rate ranged from 17 % to 100 %. Different drugs and pathways were identified. CONCLUSION HNC-PDX appears to significantly recapitulate the morphology of the original HNC and represents a valuable method in translational research for the assessment of the in vivo effect of novel therapies for HNC.
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Affiliation(s)
- Lauren F Schuch
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Felipe M Silveira
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Vivian P Wagner
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Gabriell B Borgato
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Guilherme Z Rocha
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Rogerio M Castilho
- Laboratory of Epithelial Biology, Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, Ann Arbor, MI, 48109-1078, United States; Comprehensive Cancer Center, University of Michigan, Ann Arbor, MI, 48109, United States
| | - Pablo A Vargas
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil
| | - Manoela D Martins
- Department of Oral Diagnosis, Piracicaba Dental School, Universidade de Campinas, Piracicaba, SP, Brazil; Department of Oral Pathology, School of Dentistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
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32
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Pei H, Yu M, Dong D, Wang Y, Li Q, Li L, Tang B. Phenotype-related drug sensitivity analysis of single CTCs for medicine evaluation. Chem Sci 2020; 11:8895-8900. [PMID: 34123143 PMCID: PMC8163339 DOI: 10.1039/c9sc05566e] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Due to the heterogeneous and variable drug sensitivity of tumor cells, real-time monitoring of a patient's drug response is desirable for implementing personalized and dynamic therapy. Although considerable efforts have been directed at drug screening in living cells, performing repeated drug sensitivity analysis using patient-derived primary tumor cells at the single-cell level remains challenging. Here, we present an efficient approach to assess phenotype-related drug sensitivity at the single-cell level using patient-derived circulating tumor cells (CTCs) based on a drug sensitivity microfluidic chip (DS-Chip). The DS-Chip consists of a drug gradient generator and parallel cell traps, achieving continuous single CTC capture, drug gradient distributions, drug stimulation, fluorescent probe labeling and three-color fluorescence imaging. Based on the established DS-Chip, we investigated the drug sensitivity of single cells by simultaneously monitoring epithelial–mesenchymal transition (EMT) biomarkers and apoptosis in living cells, and verified the correlation between EMT gradients and drug sensitivity. Using the new approach, we further tested the optimal drug response dose in individual CTCs isolated from 5 cancer patients through fluorescence analysis of EMT and apoptosis. The DS-Chip allows noninvasive and real-time measurements of the drug sensitivity of a patient's tumor cells during therapy. This developed approach has practical significance and can effectively guide drug selection and therapeutic evaluation for personalized medicine. Due to the heterogeneous and variable drug sensitivity of tumor cells, real-time monitoring of a patient's drug response is desirable for implementing personalized and dynamic therapy.![]()
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Affiliation(s)
- Haimeng Pei
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
| | - Mei Yu
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
| | - Defang Dong
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
| | - Yiguo Wang
- Shandong Provincial Qianfoshan Hospital, The First Hospital Affiliated with Shandong First Medical University Jinan 250014 P. R. China
| | - Qingling Li
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
| | - Lu Li
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
| | - Bo Tang
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging, Institute of Molecular and Nano Science, Shandong Normal University Jinan 250014 P. R. China
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33
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Ravasio A, Myaing MZ, Chia S, Arora A, Sathe A, Cao EY, Bertocchi C, Sharma A, Arasi B, Chung VY, Greene AC, Tan TZ, Chen Z, Ong HT, Iyer NG, Huang RY, DasGupta R, Groves JT, Viasnoff V. Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity. Commun Biol 2020; 3:429. [PMID: 32764731 PMCID: PMC7411022 DOI: 10.1038/s42003-020-01136-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 06/29/2020] [Indexed: 11/28/2022] Open
Abstract
The Eph family of receptor tyrosine kinases is crucial for assembly and maintenance of healthy tissues. Dysfunction in Eph signaling is causally associated with cancer progression. In breast cancer cells, dysregulated Eph signaling has been linked to alterations in receptor clustering abilities. Here, we implemented a single-cell assay and a scoring scheme to systematically probe the spatial organization of activated EphA receptors in multiple carcinoma cells. We show that cancer cells retain EphA clustering phenotype over several generations, and the degree of clustering reported for migration potential both at population and single-cell levels. Finally, using patient-derived cancer lines, we probed the evolution of EphA signalling in cell populations that underwent metastatic transformation and acquisition of drug resistance. Taken together, our scalable approach provides a reliable scoring scheme for EphA clustering that is consistent over multiple carcinomas and can assay heterogeneity of cancer cell populations in a cost- and time-effective manner. Ravasio et al. develop an assay to quantify the clustering of Eph receptor EphA2 upon ligand binding, based on the scoring of single cells. They discover that clustering phenotype predicts cell and population migration potential in cancer cells and reflects Eph associated gene expression profiles in cancer cell lines.
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Affiliation(s)
- Andrea Ravasio
- National University of Singapore, Singapore, Singapore.,Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | - Shumei Chia
- Genome Institute of Singapore, A-STAR, Singapore, Singapore
| | - Aditya Arora
- National University of Singapore, Singapore, Singapore
| | - Aneesh Sathe
- National University of Singapore, Singapore, Singapore
| | | | - Cristina Bertocchi
- National University of Singapore, Singapore, Singapore.,Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ankur Sharma
- Genome Institute of Singapore, A-STAR, Singapore, Singapore
| | - Bakya Arasi
- National University of Singapore, Singapore, Singapore
| | - Vin Yee Chung
- National University of Singapore, Singapore, Singapore
| | | | - Tuan Zea Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Zhongwen Chen
- National University of Singapore, Singapore, Singapore
| | - Hui Ting Ong
- National University of Singapore, Singapore, Singapore
| | | | - Ruby YunJu Huang
- School of Medicine & Graduate Institute of Oncology, College of Medicine, National Taiwan, Taiwan.,University Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Jay T Groves
- National University of Singapore, Singapore, Singapore.,University of California, Berkeley, CA, USA
| | - Virgile Viasnoff
- National University of Singapore, Singapore, Singapore. .,Centre National de la Recherche Scientifique, Singapore, Singapore.
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34
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Preclinical models of head and neck squamous cell carcinoma for a basic understanding of cancer biology and its translation into efficient therapies. CANCERS OF THE HEAD & NECK 2020; 5:9. [PMID: 32714605 PMCID: PMC7376675 DOI: 10.1186/s41199-020-00056-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 07/15/2020] [Indexed: 12/12/2022]
Abstract
Comprehensive molecular characterization of head and neck squamous cell carcinoma (HNSCC) has led to the identification of distinct molecular subgroups with fundamental differences in biological properties and clinical behavior. Despite improvements in tumor classification and increased understanding about the signaling pathways involved in neoplastic transformation and disease progression, current standard-of-care treatment for HNSCC mostly remains to be based on a stage-dependent strategy whereby all patients at the same stage receive the same treatment. Preclinical models that closely resemble molecular HNSCC subgroups that can be exploited for dissecting the biological function of genetic variants and/or altered gene expression will be highly valuable for translating molecular findings into improved clinical care. In the present review, we merge and discuss existing and new information on established cell lines, primary two- and three-dimensional ex vivo tumor cultures from HNSCC patients, and animal models. We review their value in elucidating the basic biology of HNSCC, molecular mechanisms of treatment resistance and their potential for the development of novel molecularly stratified treatment.
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35
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Ong LJY, Zhu L, Tan GJS, Toh YC. Quantitative Image-Based Cell Viability (QuantICV) Assay for Microfluidic 3D Tissue Culture Applications. MICROMACHINES 2020; 11:mi11070669. [PMID: 32660019 PMCID: PMC7407956 DOI: 10.3390/mi11070669] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/03/2020] [Accepted: 07/07/2020] [Indexed: 01/01/2023]
Abstract
Microfluidic 3D tissue culture systems are attractive for in vitro drug testing applications due to the ability of these platforms to generate 3D tissue models and perform drug testing at a very small scale. However, the minute cell number and liquid volume impose significant technical challenges to perform quantitative cell viability measurements using conventional colorimetric or fluorometric assays, such as MTS or Alamar Blue. Similarly, live-dead staining approaches often utilize metabolic dyes that typically label the cytoplasm of live cells, which makes it difficult to segment and count individual cells in compact 3D tissue cultures. In this paper, we present a quantitative image-based cell viability (QuantICV) assay technique that circumvents current challenges of performing the quantitative cell viability assay in microfluidic 3D tissue cultures. A pair of cell-impermeant nuclear dyes (EthD-1 and DAPI) were used to sequentially label the nuclei of necrotic and total cell populations, respectively. Confocal microscopy and image processing algorithms were employed to visualize and quantify the cell nuclei in the 3D tissue volume. The QuantICV assay was validated and showed good concordance with the conventional bulk MTS assay in static 2D and 3D tumor cell cultures. Finally, the QuantICV assay was employed as an on-chip readout to determine the differential dose responses of parental and metastatic 3D oral squamous cell carcinoma (OSCC) to Gefitinib in a microfluidic 3D culture device. This proposed technique can be useful in microfluidic cell cultures as well as in a situation where conventional cell viability assays are not available.
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Affiliation(s)
- Louis Jun Ye Ong
- Department of Biomedical Engineering, National University of Singapore, 4, Engineering Drive 3, E4-04-10, Singapore 117583, Singapore; (L.J.Y.O.); (L.Z.); (G.J.S.T.)
- Institute for Health Innovation and Technology, National University of Singapore, 14 Medical Drive, #14-01, Singapore 117599, Singapore
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Level 7, O Block, Gardens Point Campus, Brisbane City QLD 4000, Australia
| | - Liang Zhu
- Department of Biomedical Engineering, National University of Singapore, 4, Engineering Drive 3, E4-04-10, Singapore 117583, Singapore; (L.J.Y.O.); (L.Z.); (G.J.S.T.)
- Singapore Institute of Manufacturing Technology, 31 Biopolis Way, #04-10 Nanos, Singapore 138669, Singapore
- The N.1 Institute for Health, 28 Medical Drive, #05-corridor, Singapore 117456, Singapore
| | - Gabriel Jenn Sern Tan
- Department of Biomedical Engineering, National University of Singapore, 4, Engineering Drive 3, E4-04-10, Singapore 117583, Singapore; (L.J.Y.O.); (L.Z.); (G.J.S.T.)
| | - Yi-Chin Toh
- Department of Biomedical Engineering, National University of Singapore, 4, Engineering Drive 3, E4-04-10, Singapore 117583, Singapore; (L.J.Y.O.); (L.Z.); (G.J.S.T.)
- Institute for Health Innovation and Technology, National University of Singapore, 14 Medical Drive, #14-01, Singapore 117599, Singapore
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Level 7, O Block, Gardens Point Campus, Brisbane City QLD 4000, Australia
- The N.1 Institute for Health, 28 Medical Drive, #05-corridor, Singapore 117456, Singapore
- NUS Tissue Engineering Programme, National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore
- Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Q Block-IHBI, 60 Musk Avenue, Kelvin Grove QLD 4059, Australia
- Correspondence:
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36
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Rodrigues-Junior DM, Tan SS, Lim SK, Leong HS, Melendez ME, Ramos CRN, Viana LDS, Tan DSW, Carvalho AL, Iyer NG, Vettore AL. Circulating extracellular vesicle-associated TGFβ3 modulates response to cytotoxic therapy in head and neck squamous cell carcinoma. Carcinogenesis 2020; 40:1452-1461. [PMID: 31436806 DOI: 10.1093/carcin/bgz148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 08/14/2019] [Accepted: 08/20/2019] [Indexed: 01/28/2023] Open
Abstract
Management of locally advanced head and neck squamous cell carcinoma (HNSCC) requires a multi-prong approach comprising surgery, radiation and/or chemotherapy, yet outcomes are limited. This is largely due to a paucity of biomarkers that can predict response to specific treatment modalities. Here, we evaluated TGFβ3 protein levels in extracellular vesicles (EVs) released by HNSCC cells as a predictor for response to chemoradiation therapy (CRT). To this end, specific EV-fractions were isolated from cell lines or HNSCC patient plasma, and TGFβ3 protein was quantified. In patients treated with CRT, TGFβ3 levels were found to be significantly higher in plasma EV-fractions or non-responders compared with responders. High levels of TGFβ3 levels in Annexin V-EVs were associated with the worst progression-free survival. In vitro experiments demonstrated that TGFβ3 silencing sensitized HNSCC cells to cytotoxic therapies, and this phenotype could be rescued by treatment with exogenous. In addition, specific EV-fractions shed by cisplatin-resistant cells were sufficient to transfer the resistant phenotype to sensitive cells through activation of TGFβ-signaling pathway. Therefore, our data show that TGFβ3 transmitted through EV plays a significant role in response to cytotoxic therapy, which can be exploited as a potential biomarker for CRT response in HNSCC patients treated with curative intent.
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Affiliation(s)
- Dorival Mendes Rodrigues-Junior
- Department of Biological Sciences, Universidade Federal de São Paulo, Diadema, Brazil.,Cancer Therapeutics Research Laboratory, National Cancer Centre of Singapore, Singapore
| | - Soon Sim Tan
- Institute of Medical Biology, A*-STAR, Singapore
| | | | - Hui Sun Leong
- Cancer Therapeutics Research Laboratory, National Cancer Centre of Singapore, Singapore
| | | | | | | | - Daniel S W Tan
- Cancer Therapeutics Research Laboratory, National Cancer Centre of Singapore, Singapore.,Division of Medical Oncology, National Cancer Centre of Singapore, Singapore
| | | | - N Gopalakrishna Iyer
- Cancer Therapeutics Research Laboratory, National Cancer Centre of Singapore, Singapore.,Division of Surgical Oncology, National Cancer Centre of Singapore, Singapore
| | - Andre Luiz Vettore
- Department of Biological Sciences, Universidade Federal de São Paulo, Diadema, Brazil
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37
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Ho D, Quake SR, McCabe ERB, Chng WJ, Chow EK, Ding X, Gelb BD, Ginsburg GS, Hassenstab J, Ho CM, Mobley WC, Nolan GP, Rosen ST, Tan P, Yen Y, Zarrinpar A. Enabling Technologies for Personalized and Precision Medicine. Trends Biotechnol 2020; 38:497-518. [PMID: 31980301 PMCID: PMC7924935 DOI: 10.1016/j.tibtech.2019.12.021] [Citation(s) in RCA: 126] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 02/06/2023]
Abstract
Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care.
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Affiliation(s)
- Dean Ho
- The N.1 Institute for Health (N.1), National University of Singapore, Singapore; The Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Department of Biomedical Engineering, NUS Engineering, National University of Singapore, Singapore; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Stephen R Quake
- Department of Bioengineering, Stanford University, CA, USA; Department of Applied Physics, Stanford University, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA
| | | | - Wee Joo Chng
- Department of Haematology and Oncology, National University Cancer Institute, National University Health System, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore
| | - Edward K Chow
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore
| | - Xianting Ding
- Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Bruce D Gelb
- Mindich Child Health and Development Institute, Departments of Pediatrics and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Geoffrey S Ginsburg
- Center for Applied Genomics and Precision Medicine, Duke University, NC, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, MO, USA; Psychological & Brain Sciences, Washington University in St. Louis, MO, USA
| | - Chih-Ming Ho
- Department of Mechanical Engineering, University of California, Los Angeles, CA, USA
| | - William C Mobley
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Garry P Nolan
- Department of Microbiology & Immunology, Stanford University, CA, USA
| | - Steven T Rosen
- Comprehensive Cancer Center and Beckman Research Institute, City of Hope, CA, USA
| | - Patrick Tan
- Duke-NUS Medical School, National University of Singapore, Singapore
| | - Yun Yen
- College of Medical Technology, Center of Cancer Translational Research, Taipei Cancer Center of Taipei Medical University, Taipei, Taiwan
| | - Ali Zarrinpar
- Department of Surgery, Division of Transplantation & Hepatobiliary Surgery, University of Florida, FL, USA
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38
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Application of an ex-vivo drug sensitivity platform towards achieving complete remission in a refractory T-cell lymphoma. Blood Cancer J 2020; 10:9. [PMID: 31988286 PMCID: PMC6985240 DOI: 10.1038/s41408-020-0276-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/05/2020] [Accepted: 01/10/2020] [Indexed: 01/02/2023] Open
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Zebrafish Avatars towards Personalized Medicine-A Comparative Review between Avatar Models. Cells 2020; 9:cells9020293. [PMID: 31991800 PMCID: PMC7072137 DOI: 10.3390/cells9020293] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 01/08/2020] [Accepted: 01/21/2020] [Indexed: 02/06/2023] Open
Abstract
Cancer frequency and prevalence have been increasing in the past decades, with devastating impacts on patients and their families. Despite the great advances in targeted approaches, there is still a lack of methods to predict individual patient responses, and therefore treatments are tailored according to average response rates. “Omics” approaches are used for patient stratification and choice of therapeutic options towards a more precise medicine. These methods, however, do not consider all genetic and non-genetic dynamic interactions that occur upon drug treatment. Therefore, the need to directly challenge patient cells in a personalized manner remains. The present review addresses the state of the art of patient-derived in vitro and in vivo models, from organoids to mouse and zebrafish Avatars. The predictive power of each model based on the retrospective correlation with the patient clinical outcome will be considered. Finally, the review is focused on the emerging zebrafish Avatars and their unique characteristics allowing a fast analysis of local and systemic effects of drug treatments at the single-cell level. We also address the technical challenges that the field has yet to overcome.
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40
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Ntanasis-Stathopoulos I, Gavriatopoulou M, Terpos E. Antibody therapies for multiple myeloma. Expert Opin Biol Ther 2020; 20:295-303. [PMID: 31944131 DOI: 10.1080/14712598.2020.1717464] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Introduction: Multiple myeloma (MM) is characterized by the uncontrollable proliferation of plasma cells and the excessive production of a specific type of immunoglobulin. Immune system is deregulated in MM and, thus, immunotherapy is a promising therapeutic strategy.Areas covered: The first approach is to use monoclonal antibodies that recognize specific antigens on the surface of myeloma cells, such as CD38 and B-cell maturation antigen. Upon binding to their target, monoclonal antibodies activate the immune cells to destroy the malignant cell. Anti-CD38 molecules as part of highly effective combination regimens have been approved in both newly diagnosed and relapsed/refractory patients and have significantly changed the myeloma treatment landscape in the recent years. Another strategy is to use antibodies that bind both to a molecule on the surface of the myeloma cell and another molecule on the surface of a T-cell (bispecific antibodies). Consecutively, the T-cell comes close to and recognizes the myeloma cell. These have shown promising results in heavily pre-treated patients.Expert opinion: Antibody therapy has significantly enhanced the armamentarium against MM. Further research should focus on tailoring the combination regimens based on disease and patient characteristics in order to optimize the efficacy and safety.
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Affiliation(s)
- Ioannis Ntanasis-Stathopoulos
- Department of Clinical Therapeutics, Alexandra General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Gavriatopoulou
- Department of Clinical Therapeutics, Alexandra General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Evangelos Terpos
- Department of Clinical Therapeutics, Alexandra General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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41
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Wang Y, Liao H, Zheng T, Wang J, Guo D, Lu Z, Li Z, Chen Y, Shen L, Zhang Y, Gao J. Conditionally reprogrammed colorectal cancer cells combined with mouse avatars identify synergy between EGFR and MEK or CDK4/6 inhibitors. Am J Cancer Res 2020; 10:249-262. [PMID: 32064165 PMCID: PMC7017732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 12/06/2019] [Indexed: 06/10/2023] Open
Abstract
Preclinical models, including patient-derived xenograft (PDX) and organoid and primary cell culture, are essential for studies of cancer cell biology and facilitate translational research and individualization of therapy. We explored the optimum preclinical model by modifying the conventional conditional reprogramming (CR) system followed by screening effective targeted drug combinations against colorectal cancer (CRC). By modifying the ingredients of the culture medium used in a conventional CR system, a novel individualized CR system (termed i-CR) was established. Tumor samples from CRC patients were collected and PDX models were derived followed by high-throughput i-CR drug screening and validation of the effective targeted drug combinations. The i-CR system selectively expanded tumor cells rather than normal epithelial cells and facilitated high-throughput drug screening when combined with high-content imaging and quantitative analysis of cell proliferation. Using inhibitors targeting multiple signaling pathways identified by high-throughput i-CR drug screening, we discovered that inhibition of the EGFR and MEK or CDK4/6 pathways exerted a synergistic inhibitory effect against CRC, and we noted super-synergistic effects when EGFR, MEK, and CDK4/6 inhibitors were used simultaneously. These data were validated using paired PDX models, which showed marked inhibition of tumor growth. The novel i-CR system combined with PDX models will enable individualization of therapy and drug discovery, and strategies combining EGFR, MEK, and CDK4/6 inhibitors warrant clinical validation.
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Affiliation(s)
- Yanni Wang
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteBeijing, China
| | - Haiyan Liao
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
| | - Tongsen Zheng
- Department of Gastrointestinal Medical Oncology, Harbin Medical University Cancer HospitalHarbin, China
| | - Jingyuan Wang
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteBeijing, China
| | | | - Zhihao Lu
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteBeijing, China
| | - Zhongwu Li
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteBeijing, China
| | | | - Lin Shen
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteBeijing, China
| | - Yanqiao Zhang
- Department of Gastrointestinal Medical Oncology, Harbin Medical University Cancer HospitalHarbin, China
| | - Jing Gao
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116, China
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42
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Wallner J, Schwaiger M, Hochegger K, Gsaxner C, Zemann W, Egger J. A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 182:105102. [PMID: 31610359 DOI: 10.1016/j.cmpb.2019.105102] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 09/09/2019] [Accepted: 09/27/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVES Computer-assisted technologies, such as image-based segmentation, play an important role in the diagnosis and treatment support in cranio-maxillofacial surgery. However, although many segmentation software packages exist, their clinical in-house use is often challenging due to constrained technical, human or financial resources. Especially technological solutions or systematic evaluations of open-source based segmentation approaches are lacking. The aim of this contribution is to assess and review the segmentation quality and the potential clinical use of multiple commonly available and license-free segmentation methods on different medical platforms. METHODS In this contribution, the quality and accuracy of open-source segmentation methods was assessed on different platforms using patient-specific clinical CT-data and reviewed with the literature. The image-based segmentation algorithms GrowCut, Robust Statistics Segmenter, Region Growing 3D, Otsu & Picking, Canny Segmentation and Geodesic Segmenter were investigated in the mandible on the platforms 3D Slicer, MITK and MeVisLab. Comparisons were made between the segmentation algorithms and the ground truth segmentations of the same anatomy performed by two clinical experts (n = 20). Assessment parameters were the Dice Score Coefficient (DSC), the Hausdorff Distance (HD), and Pearsons correlation coefficient (r). RESULTS The segmentation accuracy was highest with the GrowCut (DSC 85.6%, HD 33.5 voxel) and the Canny (DSC 82.1%, HD 8.5 voxel) algorithm. Statistical differences between the assessment parameters were not significant (p < 0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the segmentation methods and the ground truth schemes. Functionally stable and time-saving segmentations were observed. CONCLUSION High quality image-based semi-automatic segmentation was provided by the GrowCut and the Canny segmentation method. In the cranio-maxillofacial complex, these segmentation methods provide algorithmic alternatives for image-based segmentation in the clinical practice for e.g. surgical planning or visualization of treatment results and offer advantages through their open-source availability. This is the first systematic multi-platform comparison that evaluates multiple license-free, open-source segmentation methods based on clinical data for the improvement of algorithms and a potential clinical use in patient-individualized medicine. The results presented are reproducible by others and can be used for clinical and research purposes.
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Affiliation(s)
- Jürgen Wallner
- Medical University of Graz, Department of Oral and Maxillofacial Surgery, Auenbruggerplatz 5/1, Graz 8036, Austria; Computer Algorithms for Medicine Laboratory, Graz 8010, Austria.
| | - Michael Schwaiger
- Medical University of Graz, Department of Oral and Maxillofacial Surgery, Auenbruggerplatz 5/1, Graz 8036, Austria; Computer Algorithms for Medicine Laboratory, Graz 8010, Austria
| | - Kerstin Hochegger
- Computer Algorithms for Medicine Laboratory, Graz 8010, Austria; Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz 8010, Austria
| | - Christina Gsaxner
- Medical University of Graz, Department of Oral and Maxillofacial Surgery, Auenbruggerplatz 5/1, Graz 8036, Austria; Computer Algorithms for Medicine Laboratory, Graz 8010, Austria; Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz 8010, Austria
| | - Wolfgang Zemann
- Medical University of Graz, Department of Oral and Maxillofacial Surgery, Auenbruggerplatz 5/1, Graz 8036, Austria
| | - Jan Egger
- Medical University of Graz, Department of Oral and Maxillofacial Surgery, Auenbruggerplatz 5/1, Graz 8036, Austria; Computer Algorithms for Medicine Laboratory, Graz 8010, Austria; Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz 8010, Austria; Shanghai Jiao Tong University, School of Mechanical Engineering, Dong Chuan Road 800, Shanghai 200240, China
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43
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Meng W, Ou W, Chandwani S, Chen X, Black W, Cai Z. Temporal phenotyping by mining healthcare data to derive lines of therapy for cancer. J Biomed Inform 2019; 100:103335. [PMID: 31689549 DOI: 10.1016/j.jbi.2019.103335] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 10/28/2019] [Accepted: 10/30/2019] [Indexed: 01/29/2023]
Abstract
Lines of therapy (LOT) derived from real-world healthcare data not only depict real-world cancer treatment sequences, but also help define patient phenotypes along the course of disease progression and therapeutic interventions. The sequence of prescribed anticancer therapies can be defined as temporal phenotyping resulting from changes in morphological (tumor staging), biochemical (biomarker testing), physiological (disease progression), and behavioral (physician prescribing and patient adherence) parameters. We introduce a novel methodology that is a two-part approach: 1) create an algorithm to derive patient-level LOT and 2) aggregate LOT information via clustering to derive temporal phenotypes, in conjunction with visualization techniques, within a large insurance claims dataset. We demonstrated the methodology using two examples: metastatic non-small cell lung cancer and metastatic melanoma. First, we generated a longitudinal patient cohort for each cancer type and applied a set of rules to derive patient-level LOT. Then the LOT algorithm outputs for each cancer type were visualized using Sankey plots and K-means clusters based on durations of LOT and of gaps in therapy between LOT. We found differential distribution of temporal phenotypes across clusters. Our approach to identify temporal patient phenotypes can increase the quality and utility of analyses conducted using claims datasets, with the potential for application to multiple oncology disease areas across diverse healthcare data sources. The understanding of LOT as defining patients' temporal phenotypes can contribute to continuous health learning of disease progression and its interaction with different treatment pathways; in addition, this understanding can provide new insights that can be applied by tailoring treatment sequences for the patient phenotypes who will benefit.
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Affiliation(s)
- Weilin Meng
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
| | - Wanmei Ou
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA
| | - Sheenu Chandwani
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA
| | - Xin Chen
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA
| | - Wynona Black
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA
| | - Zhaohui Cai
- Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ 07033, USA
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44
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Lim JJ, Goh J, Rashid MBMA, Chow EK. Maximizing Efficiency of Artificial Intelligence‐Driven Drug Combination Optimization through Minimal Resolution Experimental Design. ADVANCED THERAPEUTICS 2019. [DOI: 10.1002/adtp.201900122] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Jhin Jieh Lim
- Cancer Science Institute of SingaporeYong Loo Lin School of MedicineNational University of Singapore Singapore 117599 Singapore
| | - Jasmine Goh
- Cancer Science Institute of SingaporeYong Loo Lin School of MedicineNational University of Singapore Singapore 117599 Singapore
| | | | - Edward Kai‐Hua Chow
- Cancer Science Institute of Singapore, Yong Loo Lin School of MedicineNational University of Singapore Singapore 117599 Singapore
- Department of Pharmacology, Yong Loo Lin School of MedicineNational University of Singapore Singapore 117599 Singapore
- N.1 Institute for HealthNational University of Singapore Singapore 117599 Singapore
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45
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Marquart J, Chen EY, Prasad V. Estimation of the Percentage of US Patients With Cancer Who Benefit From Genome-Driven Oncology. JAMA Oncol 2019; 4:1093-1098. [PMID: 29710180 DOI: 10.1001/jamaoncol.2018.1660] [Citation(s) in RCA: 212] [Impact Index Per Article: 42.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Importance To date, the benefit of genome-driven cancer therapy has not been quantified. Objective We sought to estimate the annual percentage of patients in the United States with advanced or metastatic cancer who could be eligible for and benefit from US Food and Drug Administration (FDA)-approved genome-driven therapy from 2006 to 2018. Design, Setting, and Participants Retrospective cross-sectional study using publically available data of (1) demographic characteristics of patients with advanced or metastatic cancer; (2) FDA data on cancer drugs approved from January 2006 through January 2018; (3) measures of response and duration of response from drug labels; and (4) published reports estimating the frequency of various genomic aberrations used to estimate what percentage of patients would have been eligible for and would have benefited from genome-driven therapy during the studied period. Main Outcomes and Measures Estimated percentage of US patients with cancer eligible for and benefiting from genome-targeted and genome-informed therapy by year, response rate of genome-informed indications, and duration of response. Results A total of 31 drugs with 38 FDA-approved indications met our inclusion criteria for genome-targeted or genome-informed therapy from January 1, 2006, through January 31, 2018. The estimated number of patients eligible for genome-targeted therapy in 2006 was 28 729 of a total 564 830 patients with metastatic cancer, or 5.09% (95% CI, 5.03%-5.14%). By 2018, this number had increased to 50 811 of 609 640, or 8.33% (95% CI, 8.26%-8.40%). For genome-informed therapy in 2006, the eligible number of patients was 59 301 of 564 830, or 10.50% (95% CI, 10.42%-10.58%). In 2018, genome-informed treatment could be offered to 94 157 of 609 640, or 15.44% (95% CI, 15.35%-15.53%) of patients with metastatic cancer. The percentage of patients with cancer estimated to benefit from genome-targeted therapy in 2006 was 0.70% (95% CI, 0.68%-0.72%), and in 2018, it had increased to 4.90% (95% CI, 4.85%-4.95%). For genome-informed treatment in 2006, the percentage estimated to benefit was 1.31% (95% CI, 1.28%-1.34%), and in 2018, it had increased to 6.62% (95% CI, 6.56%-6.68%). The median overall response rate for all genome-informed drugs through January 2018 was 54%, and the median duration of response was 29.5 months. Conclusions and Relevance Although the number of patients eligible for genome-driven treatment has increased over time, these drugs have helped a minority of patients with advanced cancer. To accelerate progress in precision oncology, novel trial designs of genomic therapies should be developed, and broad portfolios of drug development, including immunotherapeutic and cytotoxic approaches, should be pursued.
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Affiliation(s)
- John Marquart
- School of Medicine, Oregon Health & Science University, Portland
| | - Emerson Y Chen
- Division of Hematology Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland
| | - Vinay Prasad
- Division of Hematology Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland.,Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland.,Center for Health Care Ethics, Oregon Health & Science University, Portland
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46
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Sharma A. Hiding in Plain Sight: Epigenetic Plasticity in Drug-Induced Tumor Evolution. Epigenet Insights 2019; 12:2516865719870760. [PMID: 31453434 PMCID: PMC6696831 DOI: 10.1177/2516865719870760] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 07/29/2019] [Indexed: 12/22/2022] Open
Abstract
Cancer is a heterogeneous disease with key differences at the cellular and molecular levels. Acquisition of these differences during the course of tumor development manifests into functional and phenotypic heterogeneity leading to tumor diversity, also referred to as intra-tumor heterogeneity (ITH). Within a tumor, there are subpopulations of cells capable of tumor initiation and maintenance. These cells often exhibit resistance to standard-of-care anti-cancer drugs. However, the role of various subpopulations (clones) in drug resistance remains to be investigated. Moreover, the jury is still out about whether drug resistance is a result of clonal selection of preexisting cells, or the cells acquire resistance by dynamic re-wiring of their epigenome. Therefore, we investigated the drug-induced tumor evolution in patient-derived primary cells of head and neck squamous cell carcinoma. Our data demonstrated the role of a preexisting poised epigenetic state in drug-induced adaptive evolution of tumor cells. Importantly, the combination of chemotherapy and epigenetic inhibitors can prevent/delay drug-induced tumor evolution.
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Affiliation(s)
- Ankur Sharma
- Program in Precision Oncology, Genome Institute, Singapore
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47
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Aguilar-Mahecha A, Joseph S, Cavallone L, Buchanan M, Krzemien U, Batist G, Basik M. Precision Medicine Tools to Guide Therapy and Monitor Response to Treatment in a HER-2+ Gastric Cancer Patient: Case Report. Front Oncol 2019; 9:698. [PMID: 31448226 PMCID: PMC6691136 DOI: 10.3389/fonc.2019.00698] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/15/2019] [Indexed: 12/18/2022] Open
Abstract
Trastuzumab, has played a major role in improving treatment outcomes in HER-2 positive gastric cancer. However, once there is disease progression there is a paucity of evidence for second line therapy. Patient-derived xenografts (PDXs) in combination with liquid biopsies can help guide individual therapeutic decisions and have now started to be studied. In the present case we established a PDX model from a metastatic HER-2+ gastric cancer patient and after the first engraftment passage we performed a mouse clinical trial to test T-DM1 as an alternative therapy for the patient. The PDX tumor response served as a guide to administer T-DM1 therapy to the patient who responded to treatment before relapsing 6 months later. Throughout out the clinical follow up of the patient, ctDNA levels of HER-2 copy number and a PIK3CA mutation were monitored and we found their correlation with drug response and disease progression to outperform that of CEA levels. This study highlights the utility of applying precision medicine tools combining PDX models to guide therapy with circulating tumor DNA (ctDNA) to monitor treatment response and disease progression.
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Affiliation(s)
| | - Sarah Joseph
- Segal Cancer Center, Jewish General Hospital, Montreal, QC, Canada
| | - Luca Cavallone
- Department of Oncology, Lady Davis Institute, McGill University, Montreal, QC, Canada
| | - Marguerite Buchanan
- Department of Oncology, Lady Davis Institute, McGill University, Montreal, QC, Canada
| | - Urszula Krzemien
- Department of Oncology, Lady Davis Institute, McGill University, Montreal, QC, Canada
| | - Gerald Batist
- Department of Oncology, Lady Davis Institute, McGill University, Montreal, QC, Canada.,Segal Cancer Center, Jewish General Hospital, Montreal, QC, Canada
| | - Mark Basik
- Department of Oncology, Lady Davis Institute, McGill University, Montreal, QC, Canada.,Department of Surgery, Jewish General Hospital, Montreal, QC, Canada
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Ong LJY, Ching T, Chong LH, Arora S, Li H, Hashimoto M, DasGupta R, Yuen PK, Toh YC. Self-aligning Tetris-Like (TILE) modular microfluidic platform for mimicking multi-organ interactions. LAB ON A CHIP 2019; 19:2178-2191. [PMID: 31179467 DOI: 10.1039/c9lc00160c] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Multi-organ perfusion systems offer the unique opportunity to mimic different physiological systemic interactions. However, existing multi-organ culture platforms have limited flexibility in specifying the culture conditions, device architectures, and fluidic connectivity simultaneously. Here, we report a modular microfluidic platform that addresses this limitation by enabling easy conversion of existing microfluidic devices into tissue and fluid control modules with self-aligning magnetic interconnects. This enables a 'stick-n-play' approach to assemble planar perfusion circuits that are amenable to both bioimaging-based and analytical measurements. A myriad of tissue culture and flow control TILE modules were successfully constructed with backward compatibility. Finally, we demonstrate applications in constructing recirculating multi-organ systems to emulate liver-mediated bioactivation of nutraceuticals and prodrugs to modulate their therapeutic efficacies in the context of atherosclerosis and cancer. This platform greatly facilitates the integration of existing organs-on-chip models to provide an intuitive and flexible way for users to configure different multi-organ perfusion systems.
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Affiliation(s)
- Louis Jun Ye Ong
- Department of Biomedical Engineering, National University of Singapore, 4, Engineering Drive 3, E4-04-10, 117583, Singapore.
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Budach V, Tinhofer I. Novel prognostic clinical factors and biomarkers for outcome prediction in head and neck cancer: a systematic review. Lancet Oncol 2019; 20:e313-e326. [DOI: 10.1016/s1470-2045(19)30177-9] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 02/21/2019] [Accepted: 02/25/2019] [Indexed: 01/16/2023]
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50
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Romano D. Relevance of neuroendocrine tumours models assessed by kinomic profiling. ANNALES D'ENDOCRINOLOGIE 2019; 80:144-148. [PMID: 31054767 DOI: 10.1016/j.ando.2019.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Although there is evidence of a significant rise of neuroendocrine tumours (NETs) incidence, current treatments are largely insufficient due to somewhat poor knowledge of these tumours. Despite many efforts achieved to expose driver oncogene mutations in NETs, the genetic landscape of NETs is characterized by relatively few mutations and chromosomal aberrations per tumour compared with other tumour types. In addition, NETs display few actionable mutations providing compelling rationale for targeted therapies. Recent works aiming at characterizing currently used NETs in vitro models at the genomic level raised concerns on their reliability as bona fide tools to study NETs biology. However, the lack of actionable mutation in NETs implies that sole use of genomic is not sufficient to describe these models and establish appropriate therapeutic strategies. Several kinases and kinase-involving signalling pathways have been demonstrated as abnormally regulated in NETs. Yet, kinases have only been investigated regardless of their involvement in large intracellular signalling networks. In order to assess the validity of in vitro NETs models to study NETs biology, "next-generation" high throughput functional technologies based on "kinome-wide activity" will demonstrate the similarities between signalling pathways in NETs models and patients' samples. These approaches will significantly assist in identifying actionable alterations in NETs signalling pathways and guide patient stratification into early-phase clinical trials based on kinase inhibition targeted therapies.
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Affiliation(s)
- David Romano
- Marseille Medical Genetics, MMG, U1251 Inserm, Aix-Marseille université, Marseille, France.
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