Cancer medicine
Automated mRNA-Based Detection of ER, PR, HER2, and Ki-67 in Breast Cancer Tissue and Cytology Samples in Resource-Limited Settings
By Basu P, Talukdar A, Mukherjee P and 13 others.
Abstract
Background
Accurate detection of estrogen and progesterone receptors (ER/PR), HER2, and Ki-67 is essential for molecular classification of breast cancer and in deciding upon tailored treatment. In many low- and middle-income countries (LMICs), access to histopathology and immunohistochemistry (IHC) is limited. STRAT4, an automated RT-qPCR assay performed on the widely available GeneXpert platform, offers a potential alternative. We evaluated the performance of STRAT4 on core biopsy, unstained smear of fine-needle aspiration biopsy (FNAB-US), and cellblock samples compared with conventional IHC in 178 histopathology-confirmed breast cancer patients.
Methods
Matched core biopsy, cellblock, and FNAB-US samples were analyzed using STRAT4. Concordance with IHC for ER, PR, HER2, and Ki-67 was assessed using percentage agreement and kappa statistics. The effect of alternative dCt cut-offs used in an earlier study was also examined. Molecular subtype classification derived from STRAT4 was compared with IHC-based classification.