Core Insights - Breast cancer is the most prevalent cancer among women globally, with nearly 70% of patients diagnosed with luminal-type breast cancer [1] - Chinese medical experts have utilized an AI model to identify precise treatment targets for immune-regulatory and RTK-driven luminal-type breast cancer patients, significantly improving treatment efficacy [1] Group 1: Research Findings - The research led by Professor Shao Zhimin was published in the renowned journal "Cancer Cell" and categorized luminal-type breast cancer into four subtypes: classic luminal (SNF1), immune-regulatory (SNF2), proliferative (SNF3), and RTK-driven (SNF4) [1] - The study, named LINUX, is a multi-center, randomized, controlled Phase II clinical trial focusing on treatment challenges for advanced luminal-type breast cancer patients who have developed resistance [1] Group 2: AI Model Application - The AI molecular model, described as a "super brain," integrates vast amounts of microscopic information and can produce molecular typing results within five minutes, significantly lowering the barriers and costs for precision diagnosis [2] - The clinical research demonstrated that for immune-regulatory and RTK-driven luminal-type breast cancer patients, different precision treatment strategies increased objective response rates from 30% to 65% and from 20% to 70%, respectively, with median progression-free survival more than doubling for both subtypes [2] Group 3: Future Plans - The research team plans to conduct a multi-center, randomized controlled Phase III clinical trial targeting precision treatment strategies for immune-regulatory (SNF2) and RTK-driven (SNF4) patients to validate their effectiveness and superiority in a larger patient population [2]