Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

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Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete response (pCR) to neoadjuvant therapy in breast cancer. The first stage learns the transcriptome from histopathology using 8,742 patients across 32 cancer types, corroborated by pathologist review and spatial agreement with measured expression. This simplifies the second stage to predicting pCR from inferred expression and clinical variables. Devel

Source: ArXiv AI