Cell Reports Medicine (Sep 2024)
Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer
- Marta Nowak,
- Faiz Jabbar,
- Ann-Katrin Rodewald,
- Luciana Gneo,
- Tijana Tomasevic,
- Andrea Harkin,
- Tim Iveson,
- Mark Saunders,
- Rachel Kerr,
- Karin Oein,
- Noori Maka,
- Jennifer Hay,
- Joanne Edwards,
- Ian Tomlinson,
- Owen Sansom,
- Caroline Kelly,
- Francesco Pezzella,
- David Kerr,
- Alistair Easton,
- Enric Domingo,
- Viktor H. Koelzer,
- David N. Church,
- Bengt Glimelius,
- Ismail Gogenur,
- Emma Jaeger,
- Hannah Morgan,
- Clare Orange,
- Claire Palles,
- Campbell Roxburgh
Affiliations
- Marta Nowak
- Department of Pathology and Molecular Pathology, Zurich, Zurich, Switzerland
- Faiz Jabbar
- Cancer Genomics and Immunology Group, The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
- Ann-Katrin Rodewald
- Department of Pathology and Molecular Pathology, Zurich, Zurich, Switzerland
- Luciana Gneo
- Cancer Genomics and Immunology Group, The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
- Tijana Tomasevic
- Cancer Genomics and Immunology Group, The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
- Andrea Harkin
- CRUK Glasgow Clinical Trials Unit, University of Glasgow, Glasgow, UK
- Tim Iveson
- University of Southampton, Southampton, UK
- Mark Saunders
- The Christie NHS Foundation Trust, Manchester, UK
- Rachel Kerr
- Department of Oncology, University of Oxford, Oxford, UK
- Karin Oein
- Glasgow Tissue Research Facility, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, UK
- Noori Maka
- Glasgow Tissue Research Facility, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, UK
- Jennifer Hay
- Glasgow Tissue Research Facility, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, UK
- Joanne Edwards
- School of Cancer Sciences, University of Glasgow, Glasgow, UK
- Ian Tomlinson
- Department of Oncology, University of Oxford, Oxford, UK
- Owen Sansom
- CRUK Beatson Institute of Cancer Research, Garscube Estate, Glasgow, UK
- Caroline Kelly
- CRUK Glasgow Clinical Trials Unit, University of Glasgow, Glasgow, UK
- Francesco Pezzella
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- David Kerr
- Nuffield Department of Clinical and Laboratory Sciences, University of Oxford, Oxford, UK
- Alistair Easton
- Department of Oncology, University of Oxford, Oxford, UK
- Enric Domingo
- Department of Oncology, University of Oxford, Oxford, UK
- Viktor H. Koelzer
- Department of Pathology and Molecular Pathology, Zurich, Zurich, Switzerland; Department of Oncology, University of Oxford, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Oxford, UK; Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
- David N. Church
- Cancer Genomics and Immunology Group, The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Oxford NIHR Comprehensive Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Corresponding author
- Bengt Glimelius
- Ismail Gogenur
- Emma Jaeger
- Hannah Morgan
- Clare Orange
- Claire Palles
- Campbell Roxburgh
- Journal volume & issue
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Vol. 5,
no. 9
p. 101727
Abstract
Summary: Testing for DNA mismatch repair deficiency (MMRd) is recommended for all colorectal cancers (CRCs). Automating this would enable precision medicine, particularly if providing information on etiology not captured by deep learning (DL) methods. We present AIMMeR, an AI-based method for determination of mismatch repair (MMR) protein expression at a single-cell level in routine pathology samples. AIMMeR shows an area under the receiver-operator curve (AUROC) of 0.98, and specificity of ≥75% at 98% sensitivity against pathologist ground truth in stage II/III in two trial cohorts, with positive predictive value of ≥98% for the commonest pattern of somatic MMRd. Lower agreement with microsatellite instability (MSI) testing (AUROC 0.86) reflects discordance between MMR and MSI PCR rather than AIMMeR misclassification. Analysis of the SCOT trial confirms MMRd prognostic value in oxaliplatin-treated patients; while MMRd does not predict differential benefit of chemotherapy duration, it correlates with difference in relapse by regimen (PInteraction = 0.04). AIMMeR may help reduce pathologist workload and streamline diagnostics in CRC.
