Bean, G. R. | bioRxiv Science

bioRxiv2025

Generative AI Enables Breast Cancer Genomic Subtype Prediction from Histology Images

Breast cancer subtyping is essential for precision oncology, influencing prognosis, treatment selection, and clinical trial design. The Integrative Subtype Classification (IC) categorizes breast tumors into groups with distinct long-term outcomes based on genomic and correlated transcriptomic features. This method relies on sequencing data, which, despite decreasing costs, is not always available in research or clinical settings. Here we introduce PATH-IC, a computational pathology model that predicts ER+ breast cancer IC subtype risk of relapse categories from routine histology data. We enhance the current state-of-the-art computational pathology approach with BERGERON, which leverages generative AI to correct class imbalance and reduce overfitting, showing that synthetic data improves PATH-ICs performance by the equivalent of 41% more real training samples. PATH-IC achieves a testing AUROC of 0.814, with predictions correlating to Oncotype DX scores and long-term relapse risk. Using attention-based model interpretation and CRAWFORD, a novel embedding-to-image foundation model, we demonstrate that PATH-IC identifies expected tumor microenvironment patterns for IC subtypes and highlights heterochromatin condensation as a key feature of high-risk tumors. Matched single-cell spatial transcriptomics confirm IC subtype-specific gene expression patterns identified by PATH-IC, including active metabolic, proliferative, and proteostasis pathways in the high-risk group. PATH-IC advances computational pathology through generative AI, enabling subtype inference from histopathology data.

cancer biology↗

bioRxiv2021

mSWI/SNF interacts with the ribosome and its inhibition/mutations alter translation and sensitize to mTOR/PI3K inhibitors

The chromatin remodelers mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) subunits are mutated, deleted or amplified in more than 40% of cancers. Understanding their functions in normal cells and the consequences of cancers alterations will lead to path toward new targeted therapies. Canonically, mSWI/SNF complexes regulate the structure of chromatin, however they likely have additional functions which could be relevant in carcinogenesis. Here, we highlight the substantial alteration of mSWI/SNF subunits expression in both the nucleus and cytoplasm in breast cancer cases. We demonstrate mSWI/SNF cytoplasmic localization and interaction with the translation initiation machinery. Short-term inhibition and depletion of specific subunits alter protein synthesis, implicating a direct role for these factors in translation. Inhibition and depletion of specific subunits increase sensitivity to mTOR-PI3K inhibitors, suggesting a potential therapeutic opportunity for diseases harboring mutations in these complexes. Indeed, SMARCA4 pathogenic mutations decrease protein synthesis. Furthermore, taking advantage of the DepMap studies, we demonstrate cancer cells harboring mutations of specific mSWI/SNF subunits exhibit a genetic dependency on translation factors and are particularly sensitive to translation pathway inhibitors. In conclusion, we report an unexpected cytoplasmic role for mSWI/SNF in protein synthesis, suggesting potential new therapeutic opportunities for patients afflicted by cancers demonstrating alterations in its subunits. Statement of significanceThis study establishes direct functions for mSWI/SNF in protein synthesis. mSWI/SNF inhibition, depletion and cancer mutations alter translation and increase sensitivity to translation pathway inhibitors, illustrating the potential for new therapeutic strategies.

cancer biology↗