Evidence map›Paper›PMID 35116451›Full record

ArticleTranslational cancer research2021

An integrated bioinformatics analysis to investigate the targets of miR-133a-1 in breast cancer.

Yanchun Meng, Hao Tang, Zhiguo Luo, Wenlong Tan, Lin Chen, Yiqun Du, Zhonghua Tao, Mingzhu Huang, Wenhua Li, Jun Cao and 8 more

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Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

18 authors.

Yanchun Meng *Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Hao Tang *Department of Urology, Nanjing Jinling Hospital, Nanjing, China.
Zhiguo Luo *Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Wenlong TanDepartment of Biotechnology, Beijing Institute of Radiation Medicine, Beijing, China.
Lin ChenDepartments of Colorectal Surgery and General Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Yiqun DuDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhonghua TaoDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Mingzhu HuangDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Wenhua LiDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Jun CaoDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Leiping WangDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Ting LiDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Xin LiuDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Fangfang LvDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiaojian LiuDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Jian ZhangDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Lei ZhengCentral Laboratory, Harrison International Peace Hospital, Hengshui, China.
Xichun HuDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe microRNA (miRNA) miR-133a-1 has been identified as a tumor suppressor in breast cancer. However, the underlying mechanisms of miR-133a-1 in breast cancer have not been fully elucidated. This study aimed to explore the targets of miR-133a-1 in breast cancer using an integrated bioinformatics approach.

methodsHuman SKBR3 breast cancer cells were transfected with miR-133a-1 or a miRNA negative control (miRNA-NC) for 48 hours. The RNA-seq sequencing technique was performed to identify the differential expression of genes induced by miR-133a-1 overexpression. Functional enrichment analysis was conducted to determine the target genes and pathways involved in breast cancer.

resultsBreast cancer patients with high levels of miR-133a-1 expression commonly showed longer overall survival compared to patients with a low level of miR-133a-1 expression. Using Cuffdiff, we identified 1,216 differentially expressed genes induced by miR-133a-1 overexpression, including 653 upregulated and 563 downregulated genes.

conclusionsThis report provides useful insights for understanding the underlying mechanisms in the pathogenesis of breast cancer.

Indexed as

bioinformatics analysisbreast cancermiR-133a-1sex-determining region Y-box 9 (SOX9)

Identifiers

PMID35116451
PMCPMC8799015

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