4.7 Article

Integrative 3′ Untranslated Region-Based Model to Identify Patients with Low Risk of Axillary Lymph Node Metastasis in Operable Triple-Negative Breast Cancer

期刊

ONCOLOGIST
卷 24, 期 1, 页码 22-30

出版社

OXFORD UNIV PRESS
DOI: 10.1634/theoncologist.2017-0609

关键词

Prediction modeling; 3 ' untranslated region; Alternative polyadenylation; Triple-negative breast cancer; Lymph node

类别

资金

  1. National Natural Science Foundation of China [81602316, 81672601, 31671380, 81572583]
  2. Shanghai Committee of Science and Technology Funds [15410724000]
  3. Ministry of Science and Technology of China (National Key R&D Program of China) [MOST2016YFC0900300]
  4. Research Fund for the Doctoral Program of Higher Education of China [20130071110057]

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Background Sentinel lymph node biopsy is the standard surgical staging approach for operable triple-negative breast cancer (TNBC) with clinically negative axillae. In this study, we sought to develop a model to predict TNBC patients with negative nodal involvement, who would benefit from the exemption of the axillary staging surgery. Materials and Methods We evaluated 3 ' untranslated region (3 ' UTR) profiles using microarray data of TNBC from two Gene Expression Omnibus datasets. Samples from GSE31519 were divided into training set (n = 164) and validation set (n = 163), and GSE76275 was used to construct testing set (n = 164). We built a six-member 3 ' UTR panel (ADD2, COL1A1, APOL2, IL21R, PKP2, and EIF4G3) using an elastic net model to estimate the risk of lymph node metastasis (LNM). Receiver operating characteristic and logistic analyses were used to assess the association between the panel and LNM status. Results The six-member 3 ' UTR-panel showed a high distinguishing power with an area under the curve of 0.712, 0.729, and 0.708 in the training, validation, and testing sets, respectively. After adjustment by tumor size, the 3 ' UTR panel retained significant predictive power in the training, validation, and testing sets (odds ratio = 4.93, 4.58, and 3.59, respectively; p < .05 for all). A combinatorial analysis of the 3 ' UTR panel and tumor size yielded an accuracy of 97.2%, 100%, and 100% in training, validation, and testing set, respectively. Conclusion This study established an integrative 3 ' UTR-based model as a promising predictor for nodal negativity in operable TNBC. Although a prospective study is needed to validate the model, our results may permit a no axillary surgery option for selected patients. Implications for Practice Currently, sentinel lymph node biopsy is the standard approach for surgical staging in breast cancer patients with negative axillae. Prediction estimation for lymph node metastasis of breast cancer relies on clinicopathological characteristics, which is unreliable, especially in triple-negative breast cancer (TNBC)-a highly heterogeneous disease. The authors developed and validated an effective prediction model for the lymph node status of patients with TNBC, which integrates 3 ' UTR markers and tumor size. This is the first 3 ' UTR-based model that will help identify TNBC patients with low risk of nodal involvement who are most likely to benefit from exemption axillary surgery.

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