Triple-negative, basal-like, and quintuple-negative breast cancers: better prediction model for survival

Author:

Choi Yoon-La,Oh Ensel,Park Sarah,Kim Yeonju,Park Yeon-Hee,Song Kyoung,Cho Eun Yoon,Hong Yun-Chul,Choi Jong Sun,Lee Jeong Eon,Kim Jung Han,Nam Seok Jin,Im Young-Hyuck,Yang Jung-Hyun,Shin Young Kee

Abstract

Abstract Background Triple-negative breast cancers (TNBCs) and basal-like breast cancers (BLBCs) are known as poor outcome subtypes with a lack of targeted therapy. Previous studies have shown conflicting results regarding the difference of prognostic significance between TNBCs and BLBCs. In this study, we aimed to characterize the prognostic features of TNBCs, in view of BLBCs and quintuple-negative breast cancers (QNBC/5NPs). Methods Using tissue microarray-based immunohistochemical analysis, we categorized 951 primary breast cancers into four or five subtypes according to the expression of ER, PR, HER2, and basal markers (CK5/6, EGFR). Results The results of this study showed that both TNBCs and BLBCs were associated with high histological and/or nuclear grades. When the TNBCs are divided into two subtypes by the presence of basal markers, the clinicopathologic characteristics of TNBCs were mainly maintained in the BLBCs. The 5-subgrouping was the better prediction model for both disease free and overall survival in breast cancers than the 4-subgrouping. After multivariate analysis of TNBCs, the BLBCs did not have a worse prognosis than the QNBC/5NPs. Interestingly, the patients with BLBCs showed significant adjuvant chemotherapy benefit. In addition, QNBC/5NPs comprised about 6~8% of breast cancers in publicly available breast cancer datasets Conclusion The QNBC/5NP subtype is a worse prognostic subgroup of TNBCs, especially in higher stage and this result may be related to adjuvant chemotherapy benefit of BLBCs, calling for caution in the identification of subgroups of patients for therapeutic classification.

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

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