PO.EN01.01 · 内分泌肿瘤
用芳香化酶抑制剂序贯新辅助治疗ER阳性/HER2阴性乳腺癌:Ki67动态变化与生物学转变
Neoadjuvant treatment of ER-positive/HER2-negative breast cancer with aromatase inhibitors in sequence: Ki67 dynamics and biology shifts
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景。新辅助内分泌治疗(NET)用于经严格筛选的局部晚期激素受体(HR)阳性、HER-2阴性乳腺癌患者。芳香化酶抑制剂(AI)是此情形下的首选方案。尽管有人提出NET对某些患者与新辅助化疗(NCT)疗效相似,但目前尚无可靠标志物指导术后决策。新辅助治疗前后Ki67水平的变化及多基因阵列(MGA)提供的结果被认为是有前景且具临床相关性的进一步决策标志物。
方法。NEOLETEXE试验是一项开放标签、患者内交叉试验,纳入局部晚期HR阳性、HER2阴性乳腺癌患者。患者按1:1随机分配至来曲唑或依西美坦NET治疗3个月,随后进行患者内交叉至另一种治疗方案再持续3个月。在新辅助治疗前及治疗期间的多个时间点进行了广泛的生物样本库采集。在一部分患者中,使用Prosigna®(PAM50)检测对诊断性活检和最终手术标本进行了基因表达谱分析。在基线时获取的粗针活检和手术时收集的切除标本中评估了免疫组化Ki67表达。
结果。共84例患者纳入意向治疗分析。中位年龄为76岁。病理完全缓解(pCR)发生率为6%(n=5)。中位随访时间为6.3年。随访期间仅九例患者(10.7%)复发。对基线时(Ki67b)和手术时(Ki67s)的Ki67进行了分析,将Ki67水平10%或更高分类为Ki67high。Kaplan-Meier分析显示,手术时Ki67水平低(<10%)的患者与Ki67 high组相比,无复发生存期(RFS)显著更佳(HR 0.07,CI 0.02-0.31,p < 0.001)。在20例患者队列中于基线和手术时进行了Prosigna检测。基线时,Prosigna队列中35%(n = 7)分类为Luminal A,57.9%(n = 11)为Luminal B,一例患者被鉴定为HER2富集型。手术时,大多数肿瘤分类为Luminal A(80%,n = 16),两例患者归类为HER2富集型,仅一例患者仍为Luminal B型。
结论。我们的试验有力地强调,以AI作为单药治疗局部晚期HR阳性乳腺癌的NET,对于经严格筛选的患者是NCT一种务实且有效的替代方案。手术时的Ki67表达数据和MGA数据被证明是有前景的标志物,可能指导新辅助治疗后的决策,应在未来的临床试验中加以验证。
查看英文原文 English abstract
Background. Neoadjuvant endocrine treatment (NET) is used for locally advanced hormone receptor (HR)-positive, HER-2-negative breast cancer in highly selected patients. Aromatase inhibitors (AI) are the preferred option in this setting. Although NET has been proposed to be similarly effective as neoadjuvant chemotherapy (NCT) for certain patients, there are no reliable markers currently available to guide post-surgery decisions. Changes in Ki67 levels and results provided by multi-gene arrays (MGA) before and after neoadjuvant treatment have been suggested to be promising and clinically relevant markers for further decision making.
Methods. The NEOLETEXE trial was an open-label, intrapatient cross-over trial including patients with locally advanced HR-positive, HER2-negative breast cancer. Patients were randomized 1:1 to NET with either letrozole or exemestane for 3 months, followed by an intrapatient cross-over to the alternative treatment for another 3 months. Extensive biobanking was performed at multiple time points before and during neoadjuvant therapy. In a subset of patients, gene expression profiling was performed using the Prosigna® (PAM50) assay on both the diagnostic biopsy and the final surgical specimen. Immunohistochemical Ki67 expression was assessed in core biopsies obtained at baseline and in excision specimens collected at the time of surgery.
Results. A total of 84 patients were included in the intention-to-treat analysis. The median age was 76 years. Pathological complete responses (pCR) occurred in 6% (n=5). The median follow-up time was 6,3 years. Only nine patients (10,7%) relapsed during the follow-up period. An analysis of Ki67 at baseline (Ki67b) and at the time of surgery (Ki67s) was performed, with levels of Ki67 10% or higher classified as Ki67high. Kaplan-Meier analysis showed that patients with low Ki67 levels at surgery (<10%) experienced significantly better recurrence-free survival (RFS) compared to the Ki67 high group (HR 0,07, CI 0.02-0.31, p < 0.001).Prosigna testing was performed at baseline and at the time of surgery in a cohort of 20 patients. At baseline, 35% (n = 7) of the Prosigna cohort were classified as Luminal A, 57,9% (n = 11) as Luminal B, and one patient was identified as HER2-enriched. At the time of surgery, most tumors were classified as Luminal A (80%, n = 16), two patients were categorized as HER2-enriched, and only one patient remained in the Luminal B category.
Conclusions. Our trial strongly underlines that NET involving AI as monotherapy for locally advanced HR-positive breast cancer is a pragmatic and effective alternative to NCT in highly selected patients. Ki67 expression data and MGA data at surgery turned out to be promising markers to potentially guide post-neoadjuvant decision-making and should be tested in future clinical trials.
利益披露 Disclosure
K. Fjermeros, None..
J. J. G. Hettich, None..
S. B. Geisler, None..
U. Buvarp, None..
H. P. Ødegård, None..
E. S. Agustsdottir, None..
L. C. Reitsma, None..
N. Bahrami, None..
X. Tekpli, None..
T. Lüders, None..
A. Tahiri, None..
M. Seyedzadeh, None..
T. Sauer, None..
S. Mathiassen, None..
S. Ranestad, None..
C. Hammarstrøm, None..
J. Geisler, None.