Automated mRNA-Based Detection of ER, PR, HER2, and Ki-67 in Breast Cancer Tissue and Cytology Samples in Resource-Limited Settings.

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 dC_t cut-offs used in an earlier study was also examined. Molecular subtype classification derived from STRAT4 was compared with IHC-based classification.

Results: Concordance between STRAT4 and IHC was high for ER across all sample types (κ: 0.78-0.86). PR detection showed substantial agreement for core biopsies (κ = 0.78) and cellblocks (κ = 0.63), but only fair for FNAB-US samples (κ = 0.53). HER2 detection showed moderate agreement (κ = 0.41-0.58), improving with modified cut-offs (κ = 0.57-0.66), especially for FNAB-US. Ki-67 concordance was low (agreement 58.9%-71.0%). Kappa values indicating agreement between molecular subtype classifications using STRAT4 on various samples and routine IHC were as follows: core biopsies = 0.60; cellblocks = 0.61; FNAB-US samples = 0.45.

Conclusion: Detection of ER from FNAB-US, cellblocks, and core biopsies using STRAT4 showed high concordance with IHC. However, the concordance was low to moderate for other markers.