Genomic Biomarker for Predicting Response in Early Breast Cancer Patients

Explore a 53-minute webinar on genomic biomarkers for predicting response in early breast cancer patients, presented by Dr. Maggie Cheang. Delve into the heterogeneity of human solid tumors, particularly breast cancers, and learn how genomics and biology can advance therapy response prediction and improve patient outcomes. Discover research approaches, artificial intelligence applications, machine learning techniques, and predictor algorithms in cancer research. Examine window opportunity trials, survival analysis, and differential gene expression. Gain insights into immune-related signatures, translational programs, and newly identified molecular subgroups. Participate in a Q&A session and earn PACE credits upon completion. Enhance your understanding of cutting-edge genomic research in breast cancer treatment.

Introduction
Research Approach
Outline
Artificial Intelligence
Machine Learning
Predictor Algorithm
Disclosure
Applications
Window Opportunity Trials
Survival
Why is it important
Methods
Results
Differential expression of genes
Immune related signatures
Summary
translational program
study highlights
new molecular subgroups
ongoing projects
in summary
Q A