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Breast Cancer Treatment Studies / Medical Imaging Techniques and Applications / HER2/EGFR in Cancer Research · Journal article
BMC Cancer · August 11, 2026
Encouraging direction, but not yet definitive.
This single-center retrospective study of 644 breast cancer patients reveals that ER, PR, and HER2 undergo conversion in 13.4%, 17.7%, and 12.0% of cases after neoadjuvant therapy, with HER2 loss predominating. Bidirectional ER remodeling and baseline molecular subtype independently predict pathological complete response, whereas post-treatment AR changes show limited independent predictive value. Findings suggest post-NAT biomarker reassessment may refine molecular classification and guide individualized post-treatment planning, but require prospective external validation.
Retrospective cohort study. 644 patients with breast cancer treated with neoadjuvant therapy followed by surgery at a single center; specific eligibility criteria and patient demographics not detailed in source.. Intervention: Neoadjuvant therapy followed by surgery; specific chemotherapy regimens, hormonal therapies, or targeted therapies not detailed in source.. Compared with: Pre- and post-neoadjuvant therapy biomarker assessment (paired analysis); no separate control arm.. n = 644. Single-center study; specific country or institution not named in source text..
ER, PR, and HER2 conversion rates were 13.4%, 17.7%, and 12.0%, respectively HER2 change was predominantly loss-driven (9.1% loss vs. 2.9% gain) Ki-67 and AR significantly decreased after NAT (P < 0.001 and P = 0.017)
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Clinicians should consider post-neoadjuvant biomarker reassessment to refine molecular subtype classification and individualize post-treatment decisions, with particular attention to ER remodeling patterns and Ki-67 decline in residual disease. However, baseline AR assessment appears to have limited independent value for predicting treatment response.
Real-world retrospective analysis of 644 patients showing biomarker dynamics after neoadjuvant therapy with clear statistical associations and pathological outcomes, but limited by single-center design and lack of prospective validation or clinical outcome follow-up.
As stated by the source record.
Quoted from the source exactly as published.
Clinicians should consider post-neoadjuvant biomarker reassessment to refine molecular subtype classification and individualize post-treatment decisions, with particular attention to ER remodeling patterns and Ki-67 decline in residual disease. However, baseline AR assessment appears to have limited independent value for predicting treatment response.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Biomarker dynamics after neoadjuvant therapy (NAT) may affect molecular subtype classification and treatment decisions. Although previous studies have described receptor conversion after NAT, the clinical significance of integrated biomarker remodeling, including ER, PR, HER2, Ki-67, and AR, particularly in relation to multiple pathological response indicators in real-world clinical practice, remains incompletely understood. We retrospectively analyzed 644 patients with breast cancer who received neoadjuvant therapy followed by surgery. Changes in ER, PR, HER2, Ki-67, and AR were evaluated using McNemar’s test and the Wilcoxon signed-rank test. Multivariable logistic regression was used to assess associations between biomarker evolution and treatment response, including pCR, Miller–Payne grade, ypT stage, and ypN status, with emphasis on residual disease. Exploratory analyses also evaluated biomarker-change patterns according to pretreatment Nottingham grade. A sensitivity analysis was performed using the more stringent pCR definition of ypT0 ypN0. ER, PR, and HER2 conversion rates were 13.4%, 17.7%, and 12.0%, respectively. HER2 change was predominantly loss-driven (9.1% vs. 2.9% gain). Directional analysis showed that bidirectional ER remodeling was associated with improved pathological response, while PR and HER2 conversion were mainly related to baseline subtype and MP grade. Ki-67 and AR significantly decreased after NAT ( P < 0.001 and P = 0.017). Baseline molecular subtype and Ki-67 independently predicted pCR, whereas AR was not significantly associated ( P = 0.882). Applying the more stringent ypT0 ypN0 definition reduced the pCR rate from 37.6% to 36.5% but did not materially alter the multivariable results. In patients with residual invasive breast carcinoma, the magnitude of Ki-67 decline differed across ypT groups ( P = 0.034) and was smaller in Grade III than in Grade I–II tumors ( P = 0.010). Biomarker remodeling after NAT may reflect therapy-associated biological changes, although the underlying mechanisms remain to be elucidated. HER2 changes are predominantly loss-driven, and ER shows response-associated bidirectional remodeling. Post-NAT biomarker reassessment may provide complementary information for molecular stratification and individualized post-neoadjuvant treatment planning. Dynamic changes in Ki-67 may provide additional information for pathological-response stratification in patients with residual disease, whereas baseline AR showed limited independent predictive value.
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