Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), , and mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to predict tumor status. In this systematic review, we evaluated the role of AI in predicting MSI status, , and mutations in colorectal cancer.
View Article and Find Full Text PDFAccurate testing for epidermal growth factor receptor () variants is essential for informing treatment decisions in non-small cell lung cancer (NSCLC). Automated diagnostic workflows may allow more streamlined initiation of targeted treatments, where appropriate, while comprehensive variant analysis is ongoing. FACILITATE, a real-world, prospective, multicenter, European study, evaluated performance and analytical turnaround time of the Idylla™ EGFR Mutation Test compared with local reference methods.
View Article and Find Full Text PDFBackground: Low miR-31-3p expression was identified as predictive of anti-EGFR efficacy in RAS-wt mCRC. Primary tumor side was also proposed as a predictive factor of anti-EGFR benefit. This retrospective multicentric study evaluated the predictive role of miR-31-3p in right-sided RAS-wt mCRC patients treated with first-line CT+anti-EGFR or CT+bevacizumab (Beva).
View Article and Find Full Text PDF