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Updated: Jul 11, 2025
A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer
Published on: December 26, 2016
Development of lymph node metastasis-related prognostic markers in breast cancer
Yinhua Pan1, Quanqing Zou1, Wu Yin2
1Department of Breast and Thyroid Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, No. 6 Taoyuan Road, Qingxiu District, Nanning 530021, China.
Background:
Lymph node metastasis (LNM) from Breast cancer (BC) is commonly seen in BC progression. Currently, the identification of genes linked with LNM in BC remains in mystery.
Methods:
Genes related to BC LNM were screened, and a risk model was constructed based on LASSO-Cox analysis. Combined with the Kaplan-Meier curve, the ability of riskscore to distinguish different baseline characteristics was evaluated, and model was verified by the receiver operating characteristic (ROC) curve. The expression levels of prognostic marker genes were analyzed by qRT-PCR and western blot (WB).
Results:
A higher survival rate and longer survival time in low-risk BC patients. The 1, 3 and 5 year AUC values of the training set were 0.79, 0.74, and 0.73, respectively. Results for the validation set was similar to the training set. The differentially expressed genes between the high- and low-risk groups were significantly enriched in immune pathways. In addition, the low-risk group had higher levels of immune infiltration. qRT-PCR and WB results showed that in BC, CDH10, SMR3A, POU3F2, and FABP7 were down-regulated, and LHX1 was up-regulated.
Conclusions:
We built a prognostic model of BC based on LNM-related genes, proffering evaluation for prognosis and precise cure of BC.
Significance:
At present, the genes related to lymph node metastasis in BC are still largely unknown and need to be further explored. Searching for potential lymph node metastasis-related genes of BC will provide meaningful biomarkers for BC treatment. Based on TCGA-BRCA data, we established an effective 11-gene prognostic risk model that could predict patient outcomes independently. Our model could classify BC patients and distinguish patients with poor prognosis effectively. Besides, the feature genes we identified might exert a predictive function in immunotherapy. The results of this study provide a new reference for the prognosis and treatment of BC patients with lymph node metastasis.
