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Ranghiero A, Frascarelli C, Cursano G, Pescia C, Ivanova M, Vacirca D, Rappa A, Taormina SV, Barberis M, Fusco N, Rocco EG, Venetis K. Circulating tumour DNA testing in metastatic breast cancer: Integration with tissue testing. Cytopathology 2023; 34:519-529. [PMID: 37640801 DOI: 10.1111/cyt.13295] [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: 06/16/2023] [Revised: 07/26/2023] [Accepted: 08/14/2023] [Indexed: 08/31/2023]
Abstract
Breast cancer biomarker profiling predominantly relies on tissue testing (surgical and/or biopsy samples). However, the field of liquid biopsy, particularly the analysis of circulating tumour DNA (ctDNA), has witnessed remarkable progress and continues to evolve rapidly. The incorporation of ctDNA-based testing into clinical practice is creating new opportunities for patients with metastatic breast cancer (MBC). ctDNA offers advantages over conventional tissue analyses, as it reflects tumour heterogeneity and enables multiple serial biopsies in a minimally invasive manner. Thus, it serves as a valuable complement to standard tumour tissues and, in certain instances, may even present a potential alternative approach. In the context of MBC, ctDNA testing proves highly informative in the detection of disease progression, monitoring treatment response, assessing actionable biomarkers, and identifying mechanisms of resistance. Nevertheless, ctDNA does exhibit inherent limitations, including its generally low abundance, necessitating timely blood samplings and rigorous management of the pre-analytical phase. The development of highly sensitive assays and robust bioinformatic tools has paved the way for reliable ctDNA analyses. The time has now come to establish how ctDNA and tissue analyses can be effectively integrated into the diagnostic workflow of MBC to provide patients with the most comprehensive and accurate profiling. In this manuscript, we comprehensively analyse the current methodologies employed in ctDNA analysis and explore the potential benefits arising from the integration of tissue and ctDNA testing for patients diagnosed with MBC.
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Affiliation(s)
- Alberto Ranghiero
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Chiara Frascarelli
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Giulia Cursano
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Carlo Pescia
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
- School of Pathology, University of Milan, Milan, Italy
| | - Mariia Ivanova
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Davide Vacirca
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Alessandra Rappa
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | | | - Massimo Barberis
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Nicola Fusco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Elena Guerini Rocco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
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Hockings H, Lakatos E, Huang W, Mossner M, Khan MA, Metcalf S, Nicolini F, Smith K, Baker AM, Graham TA, Lockley M. Adaptive therapy achieves long-term control of chemotherapy resistance in high grade ovarian cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.549688. [PMID: 37546942 PMCID: PMC10401956 DOI: 10.1101/2023.07.21.549688] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Drug resistance results in poor outcomes for most patients with metastatic cancer. Adaptive Therapy (AT) proposes to address this by exploiting presumed fitness costs incurred by drug-resistant cells when drug is absent, and prescribing dose reductions to allow fitter, sensitive cells to re-grow and re-sensitise the tumour. However, empirical evidence for treatment-induced fitness change is lacking. We show that fitness costs in chemotherapy-resistant ovarian cancer cause selective decline and apoptosis of resistant populations in low-resource conditions. Moreover, carboplatin AT caused fluctuations in sensitive/resistant tumour population size in vitro and significantly extended survival of tumour-bearing mice. In sequential blood-derived cell-free DNA and tumour samples obtained longitudinally from ovarian cancer patients during treatment, we inferred resistant cancer cell population size through therapy and observed it correlated strongly with disease burden. These data have enabled us to launch a multicentre, phase 2 randomised controlled trial (ACTOv) to evaluate AT in ovarian cancer.
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Affiliation(s)
- Helen Hockings
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Eszter Lakatos
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Weini Huang
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Maximilian Mossner
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Mohammed Ateeb Khan
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Stephen Metcalf
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Francesco Nicolini
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Kane Smith
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Ann-Marie Baker
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Trevor A. Graham
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Michelle Lockley
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
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5
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Abbosh C, Frankell AM, Harrison T, Kisistok J, Garnett A, Johnson L, Veeriah S, Moreau M, Chesh A, Chaunzwa TL, Weiss J, Schroeder MR, Ward S, Grigoriadis K, Shahpurwalla A, Litchfield K, Puttick C, Biswas D, Karasaki T, Black JRM, Martínez-Ruiz C, Bakir MA, Pich O, Watkins TBK, Lim EL, Huebner A, Moore DA, Godin-Heymann N, L'Hernault A, Bye H, Odell A, Roberts P, Gomes F, Patel AJ, Manzano E, Hiley CT, Carey N, Riley J, Cook DE, Hodgson D, Stetson D, Barrett JC, Kortlever RM, Evan GI, Hackshaw A, Daber RD, Shaw JA, Aerts HJWL, Licon A, Stahl J, Jamal-Hanjani M, Birkbak NJ, McGranahan N, Swanton C. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA. Nature 2023; 616:553-562. [PMID: 37055640 PMCID: PMC7614605 DOI: 10.1038/s41586-023-05776-4] [Citation(s) in RCA: 89] [Impact Index Per Article: 89.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 01/30/2023] [Indexed: 04/15/2023]
Abstract
Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.
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Affiliation(s)
- Christopher Abbosh
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
| | - Alexander M Frankell
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | | | - Judit Kisistok
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | | | | | - Selvaraju Veeriah
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | | | | | - Tafadzwa L Chaunzwa
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Jakob Weiss
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Freiburg University Hospital, Freiburg, Germany
| | | | - Sophia Ward
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Advanced Sequencing Facility, The Francis Crick Institute, London, UK
| | - Kristiana Grigoriadis
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | | | - Kevin Litchfield
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Tumour Immunogenomics and Immunosurveillance Laboratory, University College London Cancer Institute, London, UK
| | - Clare Puttick
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Dhruva Biswas
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK
| | - Takahiro Karasaki
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Metastasis Laboratory, University College London Cancer Institute, London, UK
| | - James R M Black
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Carlos Martínez-Ruiz
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Maise Al Bakir
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Oriol Pich
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Thomas B K Watkins
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Emilia L Lim
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Ariana Huebner
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - David A Moore
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Department of Cellular Pathology, University College London Hospitals, London, UK
| | | | | | | | | | | | - Fabio Gomes
- The Christie NHS Foundation Trust, Manchester, UK
| | - Akshay J Patel
- University Hospital Birmingham NHS Foundation Trust, Birmingham, UK
| | - Elizabeth Manzano
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Crispin T Hiley
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Nicolas Carey
- Cancer Research Centre, University of Leicester, Leicester, UK
| | - Joan Riley
- Cancer Research Centre, University of Leicester, Leicester, UK
| | - Daniel E Cook
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | | | | | | | | | - Gerard I Evan
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Allan Hackshaw
- Cancer Research UK & UCL Cancer Trials Centre, London, UK
| | | | - Jacqui A Shaw
- Cancer Research Centre, University of Leicester, Leicester, UK
| | - Hugo J W L Aerts
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands
| | | | | | - Mariam Jamal-Hanjani
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Metastasis Laboratory, University College London Cancer Institute, London, UK
- Department of Oncology, University College London Hospitals, London, UK
| | - Nicolai J Birkbak
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Nicholas McGranahan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
- Department of Oncology, University College London Hospitals, London, UK.
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