Cedars-Sinai researchers have developed a new artificial intelligence tool, named BRIDGE, that could transform how doctors select presurgical treatments for breast cancer patients. The tool, detailed in the journal Annals of Oncology alongside early validation data, reads genetic signals inside a tumor to identify which subtypes are present, rather than forcing the whole mass into one category.
Breast cancer is not a single disease; it comprises multiple subtypes that respond differently to treatments. Traditionally, pathologists classify tumors based on overall characteristics, but this can miss within-tumor heterogeneity. BRIDGE (Breast cancer molecular subtype classification using deep learning) leverages deep learning to analyze gene expression data at a finer resolution, potentially uncovering mixed subtypes that could influence treatment response.
According to the press release, BRIDGE could change how doctors pick the most suitable presurgical therapy, also known as neoadjuvant therapy. By more accurately identifying subtypes, the tool may help tailor treatments to the specific biology of each patient's tumor, potentially improving outcomes and reducing unnecessary side effects.
The development at Cedars-Sinai builds on other advances in the fight against cancer being made by numerous companies, such as Calidi Biotherapeutics Inc. (NASDAQ: CLDI), which focuses on developing novel stem cell-based platforms for cancer treatment. However, the BRIDGE tool specifically addresses the challenge of tumor heterogeneity in breast cancer.
Early validation data, as reported in the press release, suggest that BRIDGE can effectively classify breast cancer subtypes from gene expression data. While the tool is still in the research phase, its potential impact on clinical decision-making is significant. If validated in larger studies, BRIDGE could become a standard part of the diagnostic workflow, helping oncologists choose the most effective presurgical treatments.
For patients, this could mean more personalized care, with treatments selected based on the precise molecular makeup of their tumors. For the healthcare industry, it represents a step toward precision oncology, where AI tools augment human expertise to improve outcomes.
The researchers at Cedars-Sinai are continuing to refine BRIDGE and plan further studies to validate its clinical utility. The tool is part of a broader trend where AI is increasingly used to analyze complex biological data, offering new insights into cancer biology and treatment.
