Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides.

Mismatch Repair Deficiency (dMMR)/Microsatellite Instability (MSI) is a key biomarker in colorectal cancer (CRC). Universal screening of CRC patients for MSI status is now recommended, but contributes to increased workload for pathologists and delayed therapeutic decisions. Deep learning has the potential to ease dMMR/MSI testing and accelerate oncologist decision making in clinical practice, yet no comprehensive validation of a clinically approved tool has been conducted. We developed MSIntuit, a clinically approved artificial intelligence (AI) based pre-screening tool for MSI detection from haematoxylin-eosin (H&E) stained slides. After training on samples from The Cancer Genome Atlas (TCGA), a blind validation is performed on an independent dataset of 600 consecutive CRC patients. Inter-scanner reliability is studied by digitising each slide using two different scanners. MSIntuit yields a sensitivity of 0.96-0.98, a specificity of 0.47-0.46, and an excellent inter-scanner agreement (Cohen's κ: 0.82). By reaching high sensitivity comparable to gold standard methods while ruling out almost half of the non-MSI population, we show that MSIntuit can effectively serve as a pre-screening tool to alleviate MSI testing burden in clinical practice.

Drastic Reduction of Turnaround Time After Implementation of a Fully Automated Assay for RAS-BRAF Mutations in Colorectal Cancer: A Pilot Prospective Study in Real-life Conditions.

In some situations, there is a need for rapid mutation tests for guiding clinical decisions and starting targeted therapies with minimal delays. In this study we evaluated the turnaround time before and after the implementation of a fully automated multiplex assay for KRAS and NRAS/BRAF mutation tests (Idylla™ platform, Biocartis) in metastatic colorectal cancer. The objective of this project was to compare the turnaround times in 2017-2018 with the fully automated multiplex assay to the 2016 results with previous methods. Centers with a number of tests for metastatic colorectal cancer > 100 yearly and a usual turnaround time ≥ 3 weeks for mutation detection were selected. Results of 505 KRAS tests and 369 NRAS/BRAF tests were transmitted by 10 centers. The mean turnaround time from test prescription to reception of results was reduced from 25.8 days in 2016 to 4.5 days in 2017-2018. In conclusion, this pilot project shows that the Idylla™ platform for testing KRAS and NRAS/BRAF mutations allows an optimized turnaround time from test prescription to reception of results.

[Detection of RAS genes mutation using the Cobas® method in a private laboratory of pathology: Medical and economical study in comparison to a public platform of molecular biology of cancer]. / Analyse des mutations des gènes RAS par technique Cobas® au sein d'une structure de pathologie libérale : étude médico-économique et moléculaire comparative avec une plateforme labellisée INCa.

In France, determination of the mutation status of RAS genes for predictive response to anti-EGFR targeted treatments is carried out by public platforms of molecular biology of cancer created by the French National Cancer Institute. This study aims to demonstrate the feasibility of these analyses by a private pathology laboratory (MEDIPATH) as per the requirements of accreditation. We retrospectively studied the mutation status of KRAS and NRAS genes in 163 cases of colorectal metastatic cancer using the Cobas® technique. We compared our results to those prospectively obtained through pyrosequencing and allelic discrimination by the genetic laboratory of solid tumors at the Nice University Hospital (PACA-EST regional platform). The results of both series were identical: 98.7% positive correlation; negative correlation of 93.1%; overall correlation of 95.7% (Kappa=0.92). This study demonstrates the feasibility of molecular analysis in a private pathology laboratory. As this practice requires a high level of guarantee, its accreditation, according to the NF-EN-ISO15189 quality compliance French standard, is essential. Conducting molecular analysis in this context avoids the steps of routing the sample and the result between the pathology laboratory and the platform, which reduces the overall time of rendering the result. In conclusion, the transfer of some analysis from these platforms to private pathology laboratories would allow the platforms to be discharged from a part of routine testing and therefore concentrate their efforts to the development of new analyses constantly required to access personalized medicine.