Clarification attempt of the mechanism of late recurrence by micro- and macro-analyses in estrogen receptor-positive breast cancer

Abstract Purpose The mechanism of late recurrence (LR) of estrogen receptor (ER)-positive breast cancer remains unclear. As prediction models for LR of ER-positive breast cancer, 42-gene classifier (42GC), which analyzes “micro-factors (gene expression patterns)” and the Clinical Treatment Score post-5 years (CTS5), which analyzes “macro-factors (clinicopathological factors)”, were developed; however, improving the accuracy of these models is desirable. We aimed to clarify the mechanism and develop a new prediction model by combining 42GC and CTS5. Methods We selected 2,454 patients with ER-positive breast cancer from public microarray databases. We performed recurrence prognostic analysis using 42GC and CTS5. Results In “the basic research” for recurrent patients (n = 347), the 42GC LR and CTS5 low-risk groups tended to have LR. In “the clinical research” for recurrence-free patients 5 years after surgery (n = 671), the 42GC LR and CTS5 high-risk group had a significantly higher LR rate after 5 years (16.9%) than the 42GC non-LR and CTS5 low-risk group (5.41%) ( p = 0.037). Conclusion In “the basic research,” we found that both micro-and macro-factors were associated with the mechanisms of early recurrence and LR. Meanwhile, in “the clinical research,” we found that the mechanistic tendency toward LR (the CTS5 low-risk group) differed from the high rate of LR (the CTS5 high-risk group). Therefore, differentiating between the biological mechanisms elucidated in “the basic research” and the decision-making process concerning extended hormonal therapy in “the clinical research” is necessary. These findings propose the development of a novel prediction model for LR.