J Breast Cancer.  2019 Dec;22(4):548-561. 10.4048/jbc.2019.22.e55.

Prognostic Role of KRAS mRNA Expression in Breast Cancer

• Hwang KT
• Kim BH
• Oh S
• Park SY
• Jung J
• Kim J
• Choi IS
• Jeon SY
• Kim WY

• KMID: 2470892
• DOI: http://doi.org/10.4048/jbc.2019.22.e55

Abstract

PURPOSE
We investigated the prognostic role of KRAS mRNA expression in breast cancer using The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases.
METHODS
Clinical and biological data of 1,093 breast cancers from TCGA database and 1,904 breast cancers from METABRIC database were analyzed. Overall survival (OS) and breast cancer-specific survival (BCSS) were determined.
RESULTS
The group with high KRAS mRNA expression showed worse survival than the group with low KRAS mRNA expression regarding both OS (p = 0.012 in TCGA, p < 0.001 in METABRIC) and BCSS (p = 0.001 in METABRIC). According to multivariate analysis, the level of KRAS mRNA expression was an independent prognostic factor in both TCGA (hazard ratio [HR], 1.570; 95% confidence interval [CI], 1.026-2.403; p = 0.038) and METABRIC (HR, 1.254; 95% CI, 1.087-1.446; p = 0.002) databases. The prognostic impact of mRNA expression was effective only for luminal A subtype (p < 0.001 in METABRIC). Positive correlation was observed between mRNA expression and copy number alteration (CNA) (r = 0.577, p < 0.001 in TCGA; ρ = 0.343, p < 0.001 in METABRIC). Methylation showed negative correlations with both mRNA expression and CNA (r = −0.272, p < 0.001 in TCGA). The expression of mRNA had little association with the mutation status in breast cancers, having a mutation frequency of approximately 0.6%.
CONCLUSION
KRAS mRNA expression was significantly associated with breast cancer prognosis. It was found to be an independent prognostic factor for breast cancer. Prognostic role of KRAS mRNA expression was effective only in luminal A subtype. Further studies are needed to validate the prognostic role of KRAS mRNA expression in breast cancer, thus paving a way for clinical application of KRAS in practice.

Keyword

Breast neoplasms; Prognosis; ras Proteins; RNA

MeSH Terms

Breast Neoplasms*
Breast*
Classification
Genome
Methylation
Multivariate Analysis
Mutation Rate
Phenobarbital
Prognosis
ras Proteins
RNA
RNA, Messenger*
Phenobarbital
RNA
RNA, Messenger
ras Proteins

Figure

• 

  Figure 1 Survival curves according to the expression level of KRAS mRNA using TCGA and METABRIC databases. OS curves according to RNA seq median value (A) and RNA seq z-score (B) in TCGA database. OS curves (C) and BCSS curves (D) according to RNA mic in METABRIC database. OS = overall survival; TCGA = The Cancer Genome Atlas; METABRIC = Molecular Taxonomy of Breast Cancer International Consortium; RNA seq = RNA sequencing; BCSS = breast cancer-specific survival; RNA mic = RNA microarray.

• 

  Figure 2 OS curves according to the expression level of KRAS mRNA in each subtype of breast cancer using METABRIC database. OS curves in luminal A (A), luminal B (B), HER2 (C), and basal (D) subtypes. OS = overall survival; METABRIC, Molecular Taxonomy of Breast Cancer International Consortium; HER2 = human epidermal growth factor receptor 2; RNA mic, RNA microarray.

• 

  Figure 3 Boxplots and scatter plots for correlation between mRNA expression and CNA of KRAS. Boxplots depicting the correlation between RNA seq and nonlinear data of CNA (A), and scatter plot showing the correlation between RNA seq and linear data of CNA (B) using TCGA database. Boxplots depicting the correlation between RNA mic and nonlinear data of CNA (C), and scatter plot showing the correlation between RNA mic and nonlinear data of CNA (D) using METABRIC database. CNA = copy number alteration; RNA seq = RNA sequencing; TCGA = The Cancer Genome Atlas; RNA mic = RNA microarray; METABRIC = Molecular Taxonomy of Breast Cancer International Consortium; CNA_lin = copy number alteration linear; CNA non = copy number alteration nonlinear; GISTIC = Genomic Identification of Significant Targets in Cancer; RSEM = RNA sequencing by expectation maximization. *p values by t-test between CNA = −2 and the other groups were 0.890 (CNA = −1), 0.133 (CNA = 0), 0.039 (CNA = 1), and < 0.001 (CNA = 2); †p values by t-test between CNA = −2 and the other groups were 0.513 (CNA = −1), 0.218 (CNA = 0), 0.044 (CNA = 1), and 0.069 (CNA = 2).

• 

  Figure 4 Scatter plot showing correlation between mRNA expression and methylation of KRAS using TCGA database. TCGA = The Cancer Genome Atlas; RNA seq = RNA sequencing; RSEM = RNA sequencing by expectation maximization; CNA non = copy number alteration nonlinear.

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