Literature DB >> 33378415

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

Lingchen Wang1,2, Wenhua Wang1,2, Shaopeng Zeng3, Huilie Zheng1,2, Quqin Lu1,2.   

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.

Entities:  

Year:  2020        PMID: 33378415      PMCID: PMC7773205          DOI: 10.1371/journal.pone.0244693

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  30 in total

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Authors:  Yixin Wang; Jan G M Klijn; Yi Zhang; Anieta M Sieuwerts; Maxime P Look; Fei Yang; Dmitri Talantov; Mieke Timmermans; Marion E Meijer-van Gelder; Jack Yu; Tim Jatkoe; Els M J J Berns; David Atkins; John A Foekens
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Review 3.  Breast cancer metastasis: markers and models.

Authors:  Britta Weigelt; Johannes L Peterse; Laura J van 't Veer
Journal:  Nat Rev Cancer       Date:  2005-08       Impact factor: 60.716

4.  MicroRNA-10b and minichromosome maintenance complex component 5 gene as prognostic biomarkers in breast cancer.

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Journal:  Tumour Biol       Date:  2015-01-18

5.  Differentially expressed genes associated with the metastatic phenotype in breast cancer.

Authors:  D A Kirschmann; E A Seftor; D R Nieva; E A Mariano; M J Hendrix
Journal:  Breast Cancer Res Treat       Date:  1999-05       Impact factor: 4.872

6.  Restoration of compact Golgi morphology in advanced prostate cancer enhances susceptibility to galectin-1-induced apoptosis by modifying mucin O-glycan synthesis.

Authors:  Armen Petrosyan; Melissa S Holzapfel; David E Muirhead; Pi-Wan Cheng
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Authors:  Andy J Minn; Gaorav P Gupta; David Padua; Paula Bos; Don X Nguyen; Dimitry Nuyten; Bas Kreike; Yi Zhang; Yixin Wang; Hemant Ishwaran; John A Foekens; Marc van de Vijver; Joan Massagué
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-09       Impact factor: 11.205

8.  Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

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9.  IL-25 blockade inhibits metastasis in breast cancer.

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Journal:  Protein Cell       Date:  2016-12-01       Impact factor: 14.870

Review 10.  Prediction of breast cancer metastasis by genomic profiling: where do we stand?

Authors:  Ulrich Pfeffer; Francesco Romeo; Douglas M Noonan; Adriana Albini
Journal:  Clin Exp Metastasis       Date:  2009-03-24       Impact factor: 5.150

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