Automated mRNA-Based Detection of ER, PR, HER2, and Ki-67 in Breast Cancer Tissue and Cytology Samples in Resource-Limited Settings.
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.
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.
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.
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.
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.
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.
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.
Authors
Basu Basu, Talukdar Talukdar, Mukherjee Mukherjee, Muwonge Muwonge, Lucas Lucas, Deka Deka, Bal Bal, Gautam Gautam, Rohilla Rohilla, Bansal Bansal, Singla Singla, Khare Khare, Carvalho Carvalho, Gadgil Gadgil, Kannan Kannan, Srinivasan Srinivasan
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