4.6 Article

A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer

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FRONTIERS IN ONCOLOGY
卷 11, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.746763

关键词

triple-negative breast cancer; distant metastasis; prognostic biomarker; modeling; transcriptomics

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资金

  1. National Natural Science Foundation of China [81902684]
  2. Shanghai three year action plan for Traditional Chinese Medicine [ZY(2018-2020)-CCCX-2005-04]

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This study established clinical prognostic model, seven-gene signature, and combined model for predicting distant metastasis risk in lymph node-negative TNBC patients. The seven-gene signature showed significant differentiation of distant metastasis risk in both training and validation sets. The composite clinical and gene signature demonstrated improved prognostic accuracy compared to the clinical signature.
Background The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment. Methods We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model. Results A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size. Conclusions The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.

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