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Nulsen J, Hussain N, Al-Deka A, Yap J, Uddin K, Yau C, Ahmed AA. Completing a genomic characterisation of microscopic tumour samples with copy number. BMC Bioinformatics 2023; 24:453. [PMID: 38036971 PMCID: PMC10688092 DOI: 10.1186/s12859-023-05576-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Genomic insights in settings where tumour sample sizes are limited to just hundreds or even tens of cells hold great clinical potential, but also present significant technical challenges. We previously developed the DigiPico sequencing platform to accurately identify somatic mutations from such samples. RESULTS Here, we complete this genomic characterisation with copy number. We present a novel protocol, PicoCNV, to call allele-specific somatic copy number alterations from picogram quantities of tumour DNA. We find that PicoCNV provides exactly accurate copy number in 84% of the genome for even the smallest samples, and demonstrate its clinical potential in maintenance therapy. CONCLUSIONS PicoCNV complements our existing platform, allowing for accurate and comprehensive genomic characterisations of cancers in settings where only microscopic samples are available.
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Affiliation(s)
- Joel Nulsen
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Nosheen Hussain
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Aws Al-Deka
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Jason Yap
- University of Birmingham, Birmingham, UK
| | | | - Christopher Yau
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Health Data Research UK, London, UK
| | - Ahmed Ashour Ahmed
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK.
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK.
- Singula Bio Ltd., Oxford, UK.
- Oxford Biomedical Research Centre, National Institute of Health Research, Oxford, UK.
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2
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Asada K, Kaneko S, Takasawa K, Machino H, Takahashi S, Shinkai N, Shimoyama R, Komatsu M, Hamamoto R. Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology. Front Oncol 2021; 11:666937. [PMID: 34055633 PMCID: PMC8149908 DOI: 10.3389/fonc.2021.666937] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 04/26/2021] [Indexed: 12/17/2022] Open
Abstract
With the completion of the International Human Genome Project, we have entered what is known as the post-genome era, and efforts to apply genomic information to medicine have become more active. In particular, with the announcement of the Precision Medicine Initiative by U.S. President Barack Obama in his State of the Union address at the beginning of 2015, "precision medicine," which aims to divide patients and potential patients into subgroups with respect to disease susceptibility, has become the focus of worldwide attention. The field of oncology is also actively adopting the precision oncology approach, which is based on molecular profiling, such as genomic information, to select the appropriate treatment. However, the current precision oncology is dominated by a method called targeted-gene panel (TGP), which uses next-generation sequencing (NGS) to analyze a limited number of specific cancer-related genes and suggest optimal treatments, but this method causes the problem that the number of patients who benefit from it is limited. In order to steadily develop precision oncology, it is necessary to integrate and analyze more detailed omics data, such as whole genome data and epigenome data. On the other hand, with the advancement of analysis technologies such as NGS, the amount of data obtained by omics analysis has become enormous, and artificial intelligence (AI) technologies, mainly machine learning (ML) technologies, are being actively used to make more efficient and accurate predictions. In this review, we will focus on whole genome sequencing (WGS) analysis and epigenome analysis, introduce the latest results of omics analysis using ML technologies for the development of precision oncology, and discuss the future prospects.
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Affiliation(s)
- Ken Asada
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Syuzo Kaneko
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Ken Takasawa
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Hidenori Machino
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Satoshi Takahashi
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Norio Shinkai
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ryo Shimoyama
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Masaaki Komatsu
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Ryuji Hamamoto
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
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Morotti M, Albukhari A, Alsaadi A, Artibani M, Brenton JD, Curbishley SM, Dong T, Dustin ML, Hu Z, McGranahan N, Miller ML, Santana-Gonzalez L, Seymour LW, Shi T, Van Loo P, Yau C, White H, Wietek N, Church DN, Wedge DC, Ahmed AA. Promises and challenges of adoptive T-cell therapies for solid tumours. Br J Cancer 2021; 124:1759-1776. [PMID: 33782566 PMCID: PMC8144577 DOI: 10.1038/s41416-021-01353-6] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/22/2021] [Accepted: 03/04/2021] [Indexed: 12/11/2022] Open
Abstract
Cancer is a leading cause of death worldwide and, despite new targeted therapies and immunotherapies, many patients with advanced-stage- or high-risk cancers still die, owing to metastatic disease. Adoptive T-cell therapy, involving the autologous or allogeneic transplant of tumour-infiltrating lymphocytes or genetically modified T cells expressing novel T-cell receptors or chimeric antigen receptors, has shown promise in the treatment of cancer patients, leading to durable responses and, in some cases, cure. Technological advances in genomics, computational biology, immunology and cell manufacturing have brought the aspiration of individualised therapies for cancer patients closer to reality. This new era of cell-based individualised therapeutics challenges the traditional standards of therapeutic interventions and provides opportunities for a paradigm shift in our approach to cancer therapy. Invited speakers at a 2020 symposium discussed three areas-cancer genomics, cancer immunology and cell-therapy manufacturing-that are essential to the effective translation of T-cell therapies in the treatment of solid malignancies. Key advances have been made in understanding genetic intratumour heterogeneity, and strategies to accurately identify neoantigens, overcome T-cell exhaustion and circumvent tumour immunosuppression after cell-therapy infusion are being developed. Advances are being made in cell-manufacturing approaches that have the potential to establish cell-therapies as credible therapeutic options. T-cell therapies face many challenges but hold great promise for improving clinical outcomes for patients with solid tumours.
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Affiliation(s)
- Matteo Morotti
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Ashwag Albukhari
- Biochemistry Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Abdulkhaliq Alsaadi
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Mara Artibani
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - James D Brenton
- Functional Genomics of Ovarian Cancer Laboratory, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Stuart M Curbishley
- Advanced Therapies Facility and National Institute for Health Research (NIHR) Biomedical Research Centre, University of Birmingham, Birmingham, UK
| | - Tao Dong
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, University of Oxford, Oxford, UK
| | - Michael L Dustin
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Zhiyuan Hu
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Nicholas McGranahan
- Cancer Genome Evolution Research Group, University College London Cancer Institute, London, UK
| | - Martin L Miller
- Cancer System Biology Group, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Laura Santana-Gonzalez
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Leonard W Seymour
- Gene Therapy Group, Department of Oncology, University of Oxford, Oxford, UK
| | - Tingyan Shi
- Department of Gynecological Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Peter Van Loo
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Christopher Yau
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
- The Alan Turing Institute, London, UK
| | - Helen White
- Patient Representative, Endometrial Cancer Genomics England Clinical Interpretation Partnership (GeCIP) Domain, London, UK
| | - Nina Wietek
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - David N Church
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
- Oxford NIHR Biomedical Research Centre, Oxford, UK.
| | - David C Wedge
- Oxford NIHR Biomedical Research Centre, Oxford, UK.
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK.
| | - Ahmed A Ahmed
- Ovarian Cancer Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
- Oxford NIHR Biomedical Research Centre, Oxford, UK.
- Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
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4
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Bley N, Schott A, Müller S, Misiak D, Lederer M, Fuchs T, Aßmann C, Glaß M, Ihling C, Sinz A, Pazaitis N, Wickenhauser C, Vetter M, Ungurs O, Strauss HG, Thomssen C, Hüttelmaier S. IGF2BP1 is a targetable SRC/MAPK-dependent driver of invasive growth in ovarian cancer. RNA Biol 2020; 18:391-403. [PMID: 32876513 PMCID: PMC7951963 DOI: 10.1080/15476286.2020.1812894] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Epithelial-to-mesenchymal transition (EMT) is a hallmark of aggressive, mesenchymal-like high-grade serous ovarian carcinoma (HGSOC). The SRC kinase is a key driver of cancer-associated EMT promoting adherens junction (AJ) disassembly by phosphorylation-driven internalization and degradation of AJ proteins. Here, we show that the IGF2 mRNA-binding protein 1 (IGF2BP1) is up-regulated in mesenchymal-like HGSOC and promotes SRC activation by a previously unknown protein-ligand-induced, but RNA-independent mechanism. IGF2BP1-driven invasive growth of ovarian cancer cells essentially relies on the SRC-dependent disassembly of AJs. Concomitantly, IGF2BP1 enhances ERK2 expression in an RNA-binding dependent manner. Together this reveals a post-transcriptional mechanism of interconnected stimulation of SRC/ERK signalling in ovarian cancer cells. The IGF2BP1-SRC/ERK2 axis is targetable by the SRC-inhibitor saracatinib and MEK-inhibitor selumetinib. However, due to IGF2BP1-directed stimulation, only combinatorial treatment effectively overcomes the IGF2BP1-promoted invasive growth in 3D culture conditions as well as intraperitoneal mouse models. In conclusion, we reveal an unexpected role of IGF2BP1 in enhancing SRC/MAPK-driven invasive growth of ovarian cancer cells. This provides a rationale for the therapeutic benefit of combinatorial SRC/MEK inhibition in mesenchymal-like HGSOC.
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Affiliation(s)
- Nadine Bley
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Annekatrin Schott
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Simon Müller
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Danny Misiak
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Marcell Lederer
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Tommy Fuchs
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Chris Aßmann
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Markus Glaß
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Christian Ihling
- Dept. of Pharmaceutical Chemistry & Bioanalytics, Inst. of Pharmacy, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Andrea Sinz
- Dept. of Pharmaceutical Chemistry & Bioanalytics, Inst. of Pharmacy, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Nikolaos Pazaitis
- Inst. of Pathology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Claudia Wickenhauser
- Inst. of Pathology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Martina Vetter
- Clinics for Gynecology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Olga Ungurs
- Clinics for Gynecology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Hans-Georg Strauss
- Clinics for Gynecology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Christoph Thomssen
- Clinics for Gynecology, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Stefan Hüttelmaier
- Sect. Molecular Cell Biology, Inst. of Molecular Medicine, Charles Tanford Protein Center, Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
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5
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Abstract
Mutations that allow tumors to evolve and become resistant to treatment can be readily identified with a new sequencing approach.
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Affiliation(s)
- Nadine Bley
- Department of Molecular Cell Biology, Martin Luther University Halle-Wittenberg, Halle, Germany.,Institute of Molecular Medicine, Martin Luther University Halle-Wittenberg, Halle, Germany
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