Abstract:
This study investigates the prevalence of genomic alterations in Xerna tumor microenvironment (TME) subtypes in triple-negative breast cancer (TNBC) patients, utilizing the Xerna TME Panel. The panel uses RNA sequencing data and machine learning to classify tumors into four subtypes: Immune Active (IA), Immune Suppressed (IS), Immune Desert (ID), and Angiogenic (A). Analysis of 203 TNBC samples revealed that 49.3% were classified as IA or IS, suggesting potential responsiveness to immune checkpoint inhibitors (ICI). Additionally, 56.2% of tumors harbored actionable alterations, indicating potential for targeted therapies. Further study and clinical validation are warranted.

Published at SABCS 2023.