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. 2019 May;8(5):2303-2312.
doi: 10.1002/cam4.2065. Epub 2019 Mar 18.

SNP mutation-related genes in breast cancer for monitoring and prognosis of patients: A study based on the TCGA database

Chundi Gao  1 , Jing Zhuang  2   3 , Chao Zhou  2   3 , Huayao Li  1 , Cun Liu  4 , Lijuan Liu  2   3 , Fubin Feng  2   3 , Ruijuan Liu  2   3 , Changgang Sun  2   3
Affiliations

SNP mutation-related genes in breast cancer for monitoring and prognosis of patients: A study based on the TCGA database

Chundi Gao et al. Cancer Med. 2019 May.

Abstract

Advances in cancer biology have allowed early diagnosis and more comprehensive treatment of breast cancer (BC). However, it remains the most common cause of cancer death in women worldwide because of its strong invasiveness and metastasis. In-depth study of the molecular pathogenesis of BC and of relevant prognostic markers would improve the quality of life and prognosis of patients. In this study, bioinformatics analysis of SNP-related data from BC patients provided in the TCGA database revealed that six mutant genes (NCOR1, GATA3, CDH1, ATM, AKT1, and PTEN) were significantly associated with the corresponding expression levels of the proteins. The proteins were involved in multiple pathways related to the development of cancer, including the PI3K-Akt signaling pathway, pertinent microRNAs, and the MAPK signaling pathway. In addition, overall survival and recurrence-free survival analysis revealed the close associations of the expression of GATA3, NCOR1, CDH1, and ATM with survival of BC patients. Therefore, detecting these gene mutations and exploring their corresponding expression could be valuable in predicting the prognosis of patients. The results of the high-throughput data mining provide important fundamental bioinformatics information and a relevant theoretical basis for further exploring the molecular pathogenesis of BC and assessing the prognosis of patients.

Keywords: bioinformatics analysis; biomarkers; breast cancer; prognosis; single nucleotide polymorphisms.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
A waterfall map of 20 genes that mutated in more than 50 samples. (A)mutated gene, (B)tanslational effect, and (C)mutation type
Figure 2
Figure 2
The volcano diagram about differentially expresses mRNAs. Red dots represent up‐regulated mRNA and green dots represent down‐regulated mRNA
Figure 3
Figure 3
Pathways enrichment map of 517 mutant genes. The top 20 terms with the lowest P value were selected. Count: the number of enriched genes in each term
Figure 4
Figure 4
The PPI network of the 517 mutant genes in breast cancer
Figure 5
Figure 5
The relationship between mutation and expression about six genes
Figure 6
Figure 6
The relationship between mutation sites and corresponding gene expression of AKT1, CDH1, and GATA3
Figure 7
Figure 7
Kaplan‐Meier survival curves of the mutant genes. (A‐D) The OS curves of the mutant genes, (E‐H) The RFS curves of the mutant genes
See this image and copyright information in PMC

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