Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer
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...
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| Format: | Article |
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MDPI AG
2023-12-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/25/1/35 |
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| author | Sasagu Kurozumi Naohiko Seki Eriko Narusawa Chikako Honda Shoko Tokuda Yuko Nakazawa Takehiko Yokobori Ayaka Katayama Nigel P. Mongan Emad A. Rakha Tetsunari Oyama Takaaki Fujii Ken Shirabe Jun Horiguchi |
| author_facet | Sasagu Kurozumi Naohiko Seki Eriko Narusawa Chikako Honda Shoko Tokuda Yuko Nakazawa Takehiko Yokobori Ayaka Katayama Nigel P. Mongan Emad A. Rakha Tetsunari Oyama Takaaki Fujii Ken Shirabe Jun Horiguchi |
| author_sort | Sasagu Kurozumi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T15:06:50Z |
| format | Article |
| id | doaj.art-e65fda22e5d64172a45719880f053973 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-08T15:06:50Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-e65fda22e5d64172a45719880f0539732024-01-10T14:57:54ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-12-012513510.3390/ijms25010035Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast CancerSasagu Kurozumi0Naohiko Seki1Eriko Narusawa2Chikako Honda3Shoko Tokuda4Yuko Nakazawa5Takehiko Yokobori6Ayaka Katayama7Nigel P. Mongan8Emad A. Rakha9Tetsunari Oyama10Takaaki Fujii11Ken Shirabe12Jun Horiguchi13Department of Breast Surgery, International University of Health and Welfare, Chiba 286-8520, JapanDepartment of Functional Genomics, Chiba University Graduate School of Medicine, Chiba 260-8670, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanInitiative for Advanced Research, Gunma University, Gunma 371-8511, JapanDepartment of Diagnostic Pathology, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanBiodiscovery Institute, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham NG7 2RD, UKAcademic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UKDepartment of Diagnostic Pathology, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of General Surgical Science, Gunma University Graduate School of Medicine, Gunma 371-8511, JapanDepartment of Breast Surgery, International University of Health and Welfare, Chiba 286-8520, JapanThis 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.https://www.mdpi.com/1422-0067/25/1/35invasive breast cancerhistological grademicroRNA |
| spellingShingle | Sasagu Kurozumi Naohiko Seki Eriko Narusawa Chikako Honda Shoko Tokuda Yuko Nakazawa Takehiko Yokobori Ayaka Katayama Nigel P. Mongan Emad A. Rakha Tetsunari Oyama Takaaki Fujii Ken Shirabe Jun Horiguchi Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer International Journal of Molecular Sciences invasive breast cancer histological grade microRNA |
| title | Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer |
| title_full | Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer |
| title_fullStr | Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer |
| title_full_unstemmed | Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer |
| title_short | Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer |
| title_sort | identification of micrornas associated with histological grade in early stage invasive breast cancer |
| topic | invasive breast cancer histological grade microRNA |
| url | https://www.mdpi.com/1422-0067/25/1/35 |
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