Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer

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 (P<sub>Interaction</sub> = 0.04). AIMMeR may help reduce pathologist workload and streamline diagnostics in CRC.

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Publication Details

Journal
Cell Reports Medicine
Published
2024-09-01
DOI
https://doi.org/10.1016/j.xcrm.2024.101727
Citations
7
Primary Topic
Genetic factors in colorectal cancer
Type
article
Field-Weighted Citation Impact
2.97

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article

Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer

Ann‐Katrin Rodewald, Rachel Kerr, Marta Nowak, Faiz Jabbar et al.
7 citations
Cell Reports Medicine
Genetic factors in colorectal cancer
2.97
article

Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer

Ann‐Katrin Rodewald, Rachel Kerr, Marta Nowak, Faiz Jabbar, Luciana Gneo, Andrea Harkin, David Kerr, Francesco Pezzella, Mark Saunders, Timothy Iveson, Caroline Kelly, Owen J. Sansom, Joanne Edwards, Jennifer Hay, Noori Maka, Alistair Easton, Enric Domingo, Karin Oein, Tijana Tomasevic, Ian Tomlinson
article en
7 citations

Abstract

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 (P<sub>Interaction</sub> = 0.04). AIMMeR may help reduce pathologist workload and streamline diagnostics in CRC.

Cell Reports MedicineVol. 5(9)
Centre for Human Genetics (GB), University of Zurich (CH), University of Oxford (GB), Life Science Zurich (CH), Center for Pediatric Endocrinology Zurich (CH), The Christie NHS Foundation Trust (GB), Cancer Research UK Scotland Institute (GB), Oxford BioMedica (United Kingdom) (GB), Queen Elizabeth University Hospital (GB), University of Southampton (GB), University of Glasgow (GB)
Cancer Research UK, National Institute for Health and Care Research, University of Glasgow, Promedica Stiftung, NIHR Oxford Biomedical Research Centre
Good health and well-being
Openalex Percentile: Top 9%
Genetic factors in colorectal cancer
2.97
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