Δευτέρα 4 Ιουνίου 2018

Comparison of tumor-infiltrating lymphocytes of breast cancer in core needle biopsies and resected specimens: a retrospective analysis

Abstract

Purpose

Neoadjuvant chemotherapy (NAC) is being increasingly used to treat locally advanced breast cancer and to conserve the breast. In triple-negative breast cancer and HER2-positive breast cancer, a high density of tumor-infiltrating lymphocytes (TILs) is an important predictor of NAC response. Thus far, it remains unclear whether the TIL scores in core needle biopsies (CNBs) are closely representative of those in the whole tumor section in resected specimens. This study aimed to evaluate the concordance between the TIL scores of CNBs and resected specimens of breast cancer.

Methods

A total of 220 matched pairs of CNBs and resected specimens of breast cancer were included. Stromal TILs were scored on slides stained with hematoxylin and eosin. Clinicopathologic parameters and the agreement of the TIL scores between CNBs and resected specimens were statistically analyzed.

Results

The average TIL score was approximately 4.4% higher for the resected specimens than for the CNBs. When the tumors were divided into two groups according to a 60% TIL score cut-off (low and intermediate TIL vs. high TIL), 8.2% showed discordance between the CNB and resected specimen. The overall intraclass correlation coefficient (ICC) value of the TIL score was 0.895 (95% confidence interval, 0.864–0.920, P < 0.001), and all molecular subtypes showed ICC values over 0.8 (P < 0.001). The ICC values were > 0.9 when ≥ 5 cores were included in the CNBs. Tumors with discordant TILs were characterized by histologic grade III, ER negativity, high proliferative index, and HER2 and triple-negative subtypes. A high proliferative index was an independent risk factor for TIL discordance.

Conclusions

The TIL score in CNB specimens is a reliable value that reflects the TIL status of the entire tumor in resected specimens of breast cancer. More than five CNB cores may accurately predict the TIL score of the entire tumor.



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