SCRUM-Japan genesis virtual sequencing (VSQ) project: A novel algorithm combining deep learning (DL) with pathological diagnostics to enable the prediction of BRAF mutations and microsatellite instability (MSI) in advanced colorectal cancer (CRC).

Abstract

112 Background: Numerous genetic and epigenetic abnormalities may lead to various morphologies of cancer. However, exactly which gene abnormality causes which morphology is unknown. The VSQ Project aims at investigating a novel algorithm by synergistically fusing DL technology and pathological diagnostics for the prediction of cancer genome abnormalities. This was achieved by elucidating the association between the morphological findings and genetic abnormalities, including BRAF V600E mutations and MSI status directly linked to the therapeutic strategies for advanced CRC patients (pts). Methods: Clinicopathological-genomic integrated DB derived from SCRUM-Japan GI-SCREEN, a nation-wide cancer genome screening project including CRC, were used. A total of 1,657 images of thin sections (one representative image per pt) cut from formalin-fixed and paraffin-embedded (FFPE) tissue specimens from primary or metastatic tumors with genetic abnormalities confirmed by next-generation sequencing (NGS) were investigated; 1,234 and 423 images (one per pt) were used for training and validation cohorts, respectively. First, we developed image-prediction models based on the morphological features precisely annotated by the single central pathologist, and then constructed the DL algorithms (gene-prediction models) that enabled the prediction of gene abnormalities by using images filtered by the image-prediction models. Results: We achieved high accuracy of AUC > 0.90 for 12 features among the 33 morphological features analyzed. Next, we created several DL algorithms that enabled the prediction of BRAF mutations and MSI. The prediction level reached a high accuracy of AUC = 0.955 for the BRAF mutations and AUC = 0.857 for MSI in the training cohort. We verified the AUCs in the validation cohort and achieved AUC = 0.831 and 0.883 for BRAF mutations and MSI, respectively. Conclusions: Our findings suggest that VSQ can appropriately predict BRAF mutation and MSI status in advanced CRC, potentially without performing NGS tests. VSQ may also enable prompt initiation of systemic treatments in CRC patients as well as establish an unprecedented next-generation pathology in the near future.