Artificial Intelligence for Histology-Based Detection of Microsatellite Instability and Prediction of Response to Immunotherapy in Colorectal Cancer

Abstract

Microsatellite instability (MSI) is a molecular marker of deficient DNA mismatch repair (dMMR) that is found in approximately 15% of colorectal cancer (CRC) patients. Testing all CRC patients for MSI/dMMR is recommended as screening for Lynch Syndrome and, more recently, to determine eligibility for immune checkpoint inhibitors in advanced disease. However, universal testing for MSI/dMMR has not been uniformly implemented because of cost and resource limitations. Artificial intelligence has been used to predict MSI/dMMR directly from hematoxylin and eosin (H&E) stained tissue slides. We review the emerging data regarding the utility of machine learning for MSI classification, focusing on CRC. We also provide the clinician with an introduction to image analysis with machine learning and convolutional neural networks. Machine learning can predict MSI/dMMR with high accuracy in high quality, curated datasets. Accuracy can be significantly decreased when applied to cohorts with different ethnic and/or clinical characteristics, or different tissue preparation protocols. Research is ongoing to determine the optimal machine learning methods for predicting MSI, which will need to be compared to current clinical practices, including next-generation sequencing. Predicting response to immunotherapy remains an unmet need.

Personalized Immunotherapy in Colorectal Cancers: Where Do We Stand?

“…Advances in computational biology tools and integrating information obtained from different omics methods could develop accurate and rapid models to predict tumor behavior and response to treatment (124)(125)(126). Examples of attempts to create virtual tumor models include virtual patient-ModCell and genome-scale metabolic models used in various cancers, including CRC (127)(128)(129).…”

A winning combination in the war against deadly cancers: exploring new opportunities for combining antibody–drug conjugates and cancer immunotherapies

“…Artificial intelligence is also used for Intensity-modulated radiation therapy (IMRT) treatment planning [53] and radiomics in head and neck cancer [54]. Furthermore, artificial intelligence was used to predict microsatellite instability and deficient DNA mismatch repair in hematoxylin and eosin stained colorectal cancer sections with high accuracy in uniform datasets [55]. Artificial intelligence and machine learning have also been used in developing biomarkers for early detection of head and neck cancer by assessing metatranscriptomic data from saliva samples from normal, potentially malignant and malignant oral tissues [56].…”

Status quo and future prospects of artificial neural network from the perspective of gastroenterologists

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