Preoperative prediction nomogram based on primary tumor miRNAs signature and clinical‐related features for axillary lymph node metastasis in early‐stage invasive breast cancer

• Published in: International journal of cancer Vol. 142; no. 9; pp. 1901 - 1910
• Main Authors: Xie, Xinhua, Tan, Weige, Chen, Bo, Huang, Xiaojia, Peng, Cheng, Yan, Shumei, Yang, Lu, Song, Cailu, Wang, Jianwei, Zheng, Wenbo, Tang, Hailin, Xie, Xiaoming
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.05.2018
• Subjects: Algorithms; ALN; AUS; Biopsy; Breast cancer; Breast Neoplasms - genetics; Breast Neoplasms - pathology; Cancer; Cohort Studies; Humans; Invasiveness; Lymph; Lymph nodes; Lymph Nodes - pathology; Lymphatic Metastasis; Lymphatic system; Medical research; Metastases; Metastasis; MicroRNAs - genetics; Middle Aged; miRNA; miRNAs signature; Neoplasm Invasiveness; Neoplasm Staging; Nomograms; Paraffin Embedding; Polymerase chain reaction; Random Allocation; Retrospective Studies; Surgery; Ultrasound; miRNAs signature; breast cancer; ALN; AUS
• ISSN: 0020-7136; 1097-0215; 1097-0215
• DOI: 10.1002/ijc.31208

More than half patients who undergo axillary lymph node (ALN) surgery are ALN negative in early‐stage invasive breast cancer (EIBC). Thus, to avoid excessive treatment, we aim to establish and validate a novel nomogram model for the preoperative diagnosis of ALN status in patients with EIBC. In total, 864 patients with EIBC from two independent centers were enrolled in our study. For the discovery set, miRNAs expression profiling with functional roles in ALN metastasis was discovered by microarray analysis and validated by quantitative polymerase chain reaction (PCR). For the training and validation cohorts, we used PCR to quantify miRNAs expression in a model development cohort and assessed miRNAs signature in an internal validation cohort and external independent validation cohort. Multivariable logistic regression analyses were used to establish a nomogram model for the likelihood of ALN metastasis from miRNAs signature and clinical variables. A signature of nine‐miRNA was significantly associated with ALN status. The predictive ability of our nomogram that included miRNAs signature and clinical‐related variables (age, tumor size, tumor location and axillary ultrasound‐reported ALN status) was significantly greater than a model that only considered clinical‐related factors (concordance index: 0.856, 0.796) and also performed well in the two validation cohorts (concordance index: 0.841, 0.747). Our nomogram is a reliable prediction method that can be conveniently used to preoperatively predict ALN status in patients with EIBC. Therefore, after further confirmation in prospective and multicenter clinical trial, omission of axillary surgery may be feasible for some patients with EIBC in the future. What's new? Surgical staging of axillary lymph node (ALN) involvement informs decisions regarding the clinical management of breast cancer. In patients with early‐stage disease, however, surgical staging of the axilla can have lasting adverse effects, including arm numbness and shoulder motion impairment. Here, a nomogram model incorporating miRNA signatures relevant to ALN metastasis was developed to predict ALN status in patients with early‐stage invasive breast cancer. Combining miRNA signatures with clinically relevant risk factors successfully predicted ALN status preoperatively. In identifying patients with very low risk of ALN metastasis, the novel model can potentially facilitate treatment optimization and help prevent unnecessary procedures.