Back

m6A RNA methylation regulators contribute to progression and impact the prognosis of breast cancer

Wenjie, J.; Minglong, D.; Zebin, H.; Kaidi, W.; Han, W.

2020-10-16 health informatics
10.1101/2020.10.13.20212332
Show abstract

N6-methyladenosine (m6A) is the most commonly modified form of mRNA. M6A RNA methylation regulators are proved to be expressed clearly in some cancers by plenty of studies. Moreover, they also are proved to be indirectly involved in the growth of cancers. However, it remains unclear that the role of m6A RNA methylation regulator in the prognosis of breast cancer (BRCA). The data that we used in this study is the mRNA expression data obtained from the corresponding clinical information and the Tumor Genome Atlas (TCGA) database. And the goal we used the Wilcoxon rank-sum test was to evaluate the difference in the expression of m6A RNA methylation regulators in the normal group and the tumor group, and analyze the correlation between m6A RNA methylation regulators. We identified two subgroups of BRCA (cluster1 and 2) by using the K-mean algorithm and analyzing the correlation between clinic information and subgroups. The LASSO regression model then was used to figure out three m6A RNA methylation regulators, namely YTHDF3, ZC3H13, and HNRNPC. The riskScore of each patient was calculated according to the regression coefficients of the three m6A RNA methylation regulators. Base on the riskScore, we divided the patients into two groups, the high-risk group, and the low-risk group. After analyzing, we found that the overall survival rate (OS) of the low-risk group was higher than that of the other group. We conducted a univariate and multi-factor independent prognostic analysis of riskScore and three m6A RNA methylation regulators, and found that riskScore has a significant correlation with BRCA. In conclusion, the m6A RNA methylation regulator is closely related to the development of BRCA, and the prognostic factor riskScore obtained from the regression of the expression of the three m6A RNA methylation regulators in the human body are likely to guide the individualization of BRCA patients A useful prognostic biomarker for treatment.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
PLOS ONE
based on 1737 papers
Top 44%
11.5%
2
Scientific Reports
based on 701 papers
Top 21%
7.8%
3
BMC Medical Genomics
based on 12 papers
Top 0.1%
7.8%
4
Cancers
based on 57 papers
Top 3%
5.2%
5
Biomedicines
based on 21 papers
Top 0.3%
3.1%
6
iScience
based on 74 papers
Top 0.8%
3.1%
7
Journal of Personalized Medicine
based on 17 papers
Top 0.2%
2.9%
8
Frontiers in Oncology
based on 34 papers
Top 3%
2.5%
9
Journal of Biomedical Informatics
based on 37 papers
Top 3%
2.5%
10
BMC Medical Informatics and Decision Making
based on 36 papers
Top 4%
2.5%
11
Aging
based on 18 papers
Top 0.9%
2.5%
50% of probability mass above
12
Computers in Biology and Medicine
based on 39 papers
Top 3%
2.4%
13
eLife
based on 262 papers
Top 17%
1.6%
14
Heliyon
based on 57 papers
Top 7%
1.4%
15
JAMIA Open
based on 35 papers
Top 5%
1.4%
16
Genomics, Proteomics & Bioinformatics
based on 10 papers
Top 1%
1.4%
17
Communications Biology
based on 36 papers
Top 2%
1.4%
18
Briefings in Bioinformatics
based on 11 papers
Top 0.4%
1.2%
19
Cancer Medicine
based on 17 papers
Top 3%
1.2%
20
JCO Clinical Cancer Informatics
based on 14 papers
Top 3%
0.9%
21
Medicine
based on 29 papers
Top 7%
0.8%
22
Informatics in Medicine Unlocked
based on 11 papers
Top 2%
0.8%
23
Frontiers in Cardiovascular Medicine
based on 33 papers
Top 6%
0.8%
24
Frontiers in Artificial Intelligence
based on 11 papers
Top 2%
0.8%
25
Frontiers in Pharmacology
based on 27 papers
Top 4%
0.8%
26
JMIR Medical Informatics
based on 16 papers
Top 4%
0.8%
27
PLOS Genetics
based on 39 papers
Top 5%
0.8%
28
British Journal of Cancer
based on 22 papers
Top 4%
0.8%
29
Nature Communications
based on 483 papers
Top 40%
0.8%
30
Frontiers in Immunology
based on 140 papers
Top 7%
0.8%