Prat Aleix, Guarneri Valentina, Pascual Tomás, Brasó-Maristany Fara, Sanfeliu Esther, Paré Laia, Schettini Francesco, Martínez Débora, Jares Pedro, Griguolo Gaia, Dieci Maria Vittoria, Cortés Javier, Llombart-Cussac Antonio, Conte Benedetta, Marín-Aguilera Mercedes, Chic Nuria, Puig-Butillé Joan Anton, Martínez Antonio, Galván Patricia, Tsai Yi-Hsuan, González-Farré Blanca, Mira Aurea, Vivancos Ana, Villagrasa Patricia, Parker Joel S, Conte Pierfranco, Perou Charles M
Translational Genomics and Targeted Therapies in Solid Tumors, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Department of Medical Oncology, Hospital Clinic of Barcelona, Spain; SOLTI cooperative group, Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain; Institute of Oncology (IOB)-Hospital Quirónsalud, Barcelona, Spain.
Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy; Medical Oncology 2, Istituto Oncologico Veneto, IRCCS, Padova, Italy.
EBioMedicine. 2022 Jan;75:103801. doi: 10.1016/j.ebiom.2021.103801. Epub 2022 Jan 3.
Both clinical and genomic data independently predict survival and treatment response in early-stage HER2-positive breast cancer. Here we present the development and validation of a new HER2DX risk score, and a new HER2DX pathological complete response (pCR) score, both based on a 27-gene expression plus clinical feature-based classifier.
HER2DX is a supervised learning algorithm incorporating tumour size, nodal staging, and 4 gene expression signatures tracking immune infiltration, tumour cell proliferation, luminal differentiation, and the expression of the HER2 amplicon, into a single score. 434 HER2-positive tumours from the Short-HER trial were used to train a prognostic risk model; 268 cases from an independent cohort were used to verify the accuracy of the HER2DX risk score. In addition, 116 cases treated with neoadjuvant anti-HER2-based chemotherapy were used to train a predictive model of pathological complete response (pCR); two independent cohorts of 91 and 67 cases were used to verify the accuracy of the HER2DX pCR likelihood score. Five publicly available independent datasets with >1,000 patients with early-stage HER2-positive disease were also analysed.
In Short-HER, HER2DX variables were associated with good risk outcomes (i.e., immune, and luminal) and poor risk outcomes (i.e., proliferation, and tumour and nodal staging). In an independent cohort, continuous HER2DX risk score was significantly associated with disease-free survival (DFS) (p=0·002); the 5-year DFS in the low-risk group was 97·4% (94·4-100·0%). For the neoadjuvant pCR predictor training cohort, HER2DX variables were associated with pCR (i.e., immune, proliferation and HER2 amplicon) and non-pCR (i.e., luminal, and tumour and nodal staging). In both independent test set cohorts, continuous HER2DX pCR likelihood score was significantly associated with pCR (p<0·0001). A weak negative correlation was found between the HER2DX risk score versus the pCR score (correlation coefficient -0·19).
The two HER2DX tests provide accurate estimates of the risk of recurrence, and the likelihood to achieve a pCR, in early-stage HER2-positive breast cancer.
This study received funding from Reveal Genomics, IDIBAPS and the University of Padova.
临床数据和基因组数据均可独立预测早期HER2阳性乳腺癌的生存率和治疗反应。在此，我们展示了一种基于27个基因表达加上临床特征的分类器开发并验证的新HER2DX风险评分和新HER2DX病理完全缓解（pCR）评分。
HER2DX是一种监督学习算法，将肿瘤大小、淋巴结分期以及追踪免疫浸润、肿瘤细胞增殖、管腔分化和HER2扩增子表达的4个基因表达特征整合为一个单一评分。来自Short-HER试验的434例HER2阳性肿瘤用于训练一个预后风险模型；来自一个独立队列的268例病例用于验证HER2DX风险评分的准确性。此外，116例接受基于新辅助抗HER2化疗的病例用于训练病理完全缓解（pCR）的预测模型；两个分别包含91例和67例病例的独立队列用于验证HER2DX pCR可能性评分的准确性。还分析了5个公开可用的、包含超过1000例早期HER2阳性疾病患者的独立数据集。
在Short-HER试验中，HER2DX变量与良好风险结果（即免疫和管腔）以及不良风险结果（即增殖、肿瘤和淋巴结分期）相关。在一个独立队列中，连续的HER2DX风险评分与无病生存期（DFS）显著相关（p = 0·002）；低风险组的5年DFS为97·4%（94·4 - 100·0%）。对于新辅助pCR预测训练队列，HER2DX变量与pCR（即免疫、增殖和HER2扩增子）以及非pCR（即管腔、肿瘤和淋巴结分期）相关。在两个独立测试集队列中，连续的HER2DX pCR可能性评分与pCR显著相关（p < 0·0001）。发现HER2DX风险评分与pCR评分之间存在弱负相关（相关系数 -0·19）。
这两种HER2DX检测为早期HER2阳性乳腺癌的复发风险和实现pCR的可能性提供了准确估计。
本研究获得了Reveal Genomics、IDIBAPS和帕多瓦大学的资助。
