Concordance of the molecular subtype classification between core needle biopsy and surgical specimen in primary breast cancer.

BACKGROUND

Molecular profiling of breast cancer (BC) classifies several intrinsic subtypes based on different patterns of gene expression. Multigene assays estimate the risk of recurrence and help to select high-risk patients for adjuvant chemotherapy. However, these tests are associated with significant costs. Immunohistochemistry (IHC) offers a surrogate classification for molecular subtypes by determining estrogen (ER) and progesterone receptors (PR), human epidermal growth factor (Her2neu), as well as the proliferation marker Ki67. Core needle biopsy (CNB) is well established in BC diagnosis and allows a pre-operative assessment of biomarkers. The aim of this study was to analyze the concordance of these markers between CNB and surgical specimens to assess whether re-testing of the surgical specimen is mandatory.

MATERIALS AND METHODS

Within a 3-year period, patients with primary BC and paired samples of CNB and surgical specimens were analyzed retrospectively. Concordance rates of ER, PR, Her2neu, Ki67, and the surrogate classification for molecular subtypes were calculated using the Landis and Koch agreement grades.

RESULTS

Out of 2254 patients with primary breast cancer, 1307 paired specimens without pre-operative treatment were available for analysis Concordance rates for ER, PR, Her2neu, and Ki67 status showed substantial-to-almost perfect agreement grades (κ = 0.91, 0.75, 0.89, and 0.61, respectively). Though substantial concordance was also found for the subtype classification (κ = 0.70), the molecular subtype changed in 18.5% of patients based on the testing of the surgical specimen, mainly from luminal A-like to luminal B-like.

CONCLUSIONS

Though the concordance rates for single markers were convincing, a significant proportion of the molecular subtypes differed between CNB and the surgical specimen. Re-testing of PR and Ki67 is mandatory to ensure optimal treatment decisions. Further research is necessary to define safe, efficient, and cost-effective predictive models in adjuvant breast cancer therapy.