Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients

PLoS One. 2020 Dec 30;15(12):e0244693. doi: 10.1371/journal.pone.0244693. eCollection 2020.

Abstract

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What's more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Breast Neoplasms / genetics*
  • Breast Neoplasms / pathology
  • Cell Cycle Proteins / genetics
  • Databases, Genetic
  • Female
  • Golgi Matrix Proteins / genetics
  • Humans
  • Interleukin-8 / genetics
  • Likelihood Functions
  • Lung Neoplasms / genetics*
  • Lung Neoplasms / secondary
  • Membrane Proteins / genetics
  • Mixed Function Oxygenases / genetics
  • Nomograms*
  • Prognosis
  • Repressor Proteins / genetics
  • Risk Assessment
  • Tetraspanins / genetics
  • Tumor Suppressor Proteins / genetics

Substances

  • Cell Cycle Proteins
  • Golgi Matrix Proteins
  • Interleukin-8
  • MCM5 protein, human
  • Membrane Proteins
  • Repressor Proteins
  • TMEM158 protein, human
  • TSPAN31 protein, human
  • Tetraspanins
  • Tumor Suppressor Proteins
  • macrogolgin
  • Mixed Function Oxygenases
  • HIF1AN protein, human

Grants and funding

This research was supported by National Natural Science Foundation of China (31860311 to Q.L., http://www.nsfc.gov.cn/english/site_1/index.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.