Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer

Author:

Kurozumi Sasagu12,Seki Naohiko3ORCID,Narusawa Eriko2,Honda Chikako2,Tokuda Shoko2,Nakazawa Yuko2,Yokobori Takehiko4ORCID,Katayama Ayaka5,Mongan Nigel P.6ORCID,Rakha Emad A.78,Oyama Tetsunari5,Fujii Takaaki2,Shirabe Ken2,Horiguchi Jun1

Affiliation:

1. Department of Breast Surgery, International University of Health and Welfare, Chiba 286-8520, Japan

2. Department of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, Japan

3. Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba 260-8670, Japan

4. Initiative for Advanced Research, Gunma University, Gunma 371-8511, Japan

5. Department of Diagnostic Pathology, Gunma University Graduate School of Medicine, Gunma 371-8511, Japan

6. Biodiscovery Institute, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham NG7 2RD, UK

7. Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK

8. Pathology Department, Hamad Medical Corporation, Doha P.O. Box 3050, Qatar

Abstract

This study aimed to identify microRNAs associated with histological grade using comprehensive microRNA analysis data obtained by next-generation sequencing from early-stage invasive breast cancer. RNA-seq data from normal breast and breast cancer samples were compared to identify candidate microRNAs with differential expression using bioinformatics. A total of 108 microRNAs were significantly differentially expressed in normal breast and breast cancer tissues. Using clinicopathological information and microRNA sequencing data of 430 patients with breast cancer from The Cancer Genome Atlas (TCGA), the differences in candidate microRNAs between low- and high-grade tumors were identified. Comparing the expression of the 108 microRNAs between low- and high-grade cases, 25 and 18 microRNAs were significantly upregulated and downregulated, respectively, in high-grade cases. Clustering analysis of the TCGA cohort using these 43 microRNAs identified two groups strongly predictive of histological grade. miR-3677 is a microRNA upregulated in high-grade breast cancer. The outcome analysis revealed that patients with high miR-3677 expression had significantly worse prognosis than those with low miR-3677 expression. This study shows that microRNAs are associated with histological grade in early-stage invasive breast cancer. These findings contribute to the elucidation of a new mechanism of breast cancer growth regulated by specific microRNAs.

Funder

KAKENHI

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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