Abstract PO5-15-10: Plasticity marker FOXC1 expression accurately predicts efficacy of Adjuvant Tamoxifen + Chemotherapy in reducing all-cause mortality in ER+LN- Breast Cancer: Validation in the SCAN-B Prospective Study (NCT02306096)
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引用次数: 0
Abstract
INTRODUCTION: Despite the development and validation of multimarker gene panels like OncotypeDx®, Mammaprint® and EndoPredict®, an affordable and globally accessible biomarker approach that can predict increased risk of all-cause mortality in patients diagnosed with ER+LN- breast cancer, as well as the efficacy of adjuvant endocrine + chemotherapy in mitigating such elevated risk, continues to be an unmet medical need. Lack of such a pragmatic solution continues to be the cause of preventable recurrent/metastatic disease in patients diagnosed with ER+LN- breast cancer in resource-challenged settings around the world. We hypothesized that a predictive biomarker strategy that measures expression of the plasticity marker FOXC1, in combination with clinical parameters like tumor size (TS) and tumor grade (TG), may offer equivalent results to that of the above multimarker gene panels at a significantly lower economic cost without compromising accuracy of prediction results.
METHODS: Pre-treatment tumor RNA data obtained from a training cohort (compendium of gene expression microarray datasets, n=2857) and a single large validation cohort (SCAN-B Prospective Multicenter Observational Study, n=3520) for patients diagnosed with ER+LN- breast cancer were analyzed for FOXC1 expression, tumor size (TS) and tumor grade (TG) and correlated with Recurrence-Free Survival (RFS) and Overall Survival (OS). Optimized biomarker cutoff values based on model area-under-curve were leave-one-out cross validated and Risk-of-Recurrence (ROR) prediction algorithm derived utilizing the (compendium) training dataset. The unmodified strategy was then validated in the independent (SCAN-B) validation dataset.
RESULTS: A predetermined High ROR score calculated using FOXC1 expression, TS and TG (trained using the compendium dataset) predicted efficacy of adjuvant endocrine + chemotherapy over that of adjuvant endocrine therapy alone in ER+LN- patients in terms of statistically significant reduction in all-cause mortality at 8-years post-diagnosis in the SCAN-B validation dataset (4.66% vs 24.06%, n=326, OR=6.48, 95%CI [2.97-14.11], p< 0.0001). OncotypeDx® (5.7% vs 14.4%, n=762, OR=2.79, 95%CI [1.37-5.67], p=0.002), Mammaprint® (5.1% vs 18.4%, n=665, OR= 95%CI [2.04-8.43], p< 0.0001) and Endopredict® (4.8% vs 15.2%, n=923, OR=3.58 95%CI [1.78-7.21], p=0.0002) were also statistically significant predictors of the same.
CONCLUSION: Pre-treatment tumor FOXC1 mRNA or protein expression (assessed using qRT-PCR or routine immunohistochemistry (IHC), respectively, when combined with TS and TG presents a unique and economical alternative solution to multimarker gene panel tests like OncotypeDx®, Mammaprint® or Endopredict®, for guiding therapy of patients diagnosed with ER+LN- breast cancer in resource challenged settings. Such an approach to identify elevated risk of recurrence in patients diagnosed with ER+LN- breast cancer and prevent the same by guiding adjuvant endocrine + chemotherapy decisions, could help to extend recurrence-free and overall survival. Such an approach merits testing in real world ER+LN- patient cohorts in resource-challenged settings to help support implementation of this FOXC1-driven predictive biomarker strategy in the clinic.
Citation Format: Partha Ray, Tania Ray, Clive Taylor, Robert Hussa. Plasticity marker FOXC1 expression accurately predicts efficacy of Adjuvant Tamoxifen + Chemotherapy in reducing all-cause mortality in ER+LN- Breast Cancer: Validation in the SCAN-B Prospective Study (NCT02306096) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-10.
导言:尽管 OncotypeDx®、Mammaprint® 和 EndoPredict® 等多标志物基因面板已得到开发和验证,但一种可预测 ER+LN- 乳腺癌患者全因死亡风险升高以及辅助内分泌+化疗在降低这种升高风险方面的疗效的负担得起且全球通用的生物标志物方法仍是一项尚未满足的医疗需求。在世界各地资源匮乏的环境中,由于缺乏这种实用的解决方案,被确诊为ER+LN-乳腺癌的患者仍会出现可预防的复发/转移性疾病。我们假设,将可塑性标记物 FOXC1 的表达与肿瘤大小(TS)和肿瘤分级(TG)等临床参数结合起来测量的预测性生物标记物策略,可以在不影响预测结果准确性的前提下,以更低的经济成本提供与上述多标记物基因面板相当的结果。方法:对从一个训练队列(基因表达微阵列数据集汇编,n=2857)和一个大型验证队列(SCAN-B 前瞻性多中心观察研究,n=3520)中获得的ER+LN-乳腺癌患者治疗前肿瘤RNA数据进行分析,检测FOXC1表达、肿瘤大小(TS)和肿瘤分级(TG),并将其与无复发生存期(RFS)和总生存期(OS)相关联。根据模型曲线下面积优化生物标志物截断值,并利用(汇编)训练数据集进行一一交叉验证,得出复发风险(ROR)预测算法。然后在独立的(SCAN-B)验证数据集中对未修改的策略进行验证。结果:利用 FOXC1 表达、TS 和 TG 计算出的预设高 ROR 评分(使用汇编数据集进行训练)预测了 ER+LN- 患者辅助内分泌+化疗的疗效,在 SCAN-B 验证数据集中,诊断后 8 年的全因死亡率在统计学上显著降低(4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%,4.66% vs 24.06%)。66% vs 24.06%,n=326,OR=6.48,95%CI [2.97-14.11],p< 0.0001)。OncotypeDx®(5.7% vs 14.4%,n=762,OR=2.79,95%CI [1.37-5.67],p=0.002)、Mammaprint®(5.1% vs 18.4%,n=665,OR= 95%CI [2.04-8.43],p< 0.0001)和 Endopredict®(4.8% vs 15.2%,n=923,OR=3.58 95%CI [1.78-7.21],p=0.0002)也是具有统计学意义的预测因素。结论:治疗前肿瘤 FOXC1 mRNA 或蛋白表达(分别使用 qRT-PCR 或常规免疫组化 (IHC) 评估)与 TS 和 TG 结合使用时,是一种独特而经济的替代方案,可替代 OncotypeDx®、Mammaprint® 或 Endopredict® 等多标志物基因小组检测,为资源有限的环境中确诊为 ER+LN- 乳腺癌的患者提供治疗指导。这种方法可以识别ER+LN-乳腺癌患者的复发风险,并通过指导辅助内分泌+化疗决策来预防复发,有助于延长无复发生存期和总生存期。这种方法值得在资源匮乏的现实环境中对ER+LN-患者队列进行测试,以帮助支持在临床中实施这种FOXC1驱动的预测性生物标志物策略。引用格式:帕尔塔-雷、塔尼亚-雷、克莱夫-泰勒、罗伯特-胡萨可塑性标志物FOXC1表达可准确预测他莫昔芬+化疗辅助治疗对降低ER+LN-乳腺癌全因死亡率的疗效:SCAN-B前瞻性研究(NCT02306096)的验证[摘要]。In:2023年圣安东尼奥乳腺癌研讨会论文集;2023年12月5-9日;德克萨斯州圣安东尼奥。费城(宾夕法尼亚州):AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-10.
期刊介绍:
The Journal of Chemical Health and Safety focuses on news, information, and ideas relating to issues and advances in chemical health and safety. The Journal of Chemical Health and Safety covers up-to-the minute, in-depth views of safety issues ranging from OSHA and EPA regulations to the safe handling of hazardous waste, from the latest innovations in effective chemical hygiene practices to the courts'' most recent rulings on safety-related lawsuits. The Journal of Chemical Health and Safety presents real-world information that health, safety and environmental professionals and others responsible for the safety of their workplaces can put to use right away, identifying potential and developing safety concerns before they do real harm.