Literature DB >> 28791371

Comprehensive analysis of aberrantly expressed microRNA profiles reveals potential biomarkers of human lung adenocarcinoma progression.

Jing Sui1, Ru-Song Yang2, Si-Yi Xu1, Yan-Qiu Zhang1, Cheng-Yun Li1, Sheng Yang1, Li-Hong Yin1, Yue-Pu Pu1, Ge-Yu Liang1.   

Abstract

Lung adenocarcinoma (LUAD) is a complex disease that poses challenges for diagnosis and treatment. The aim of the present study is to investigate LUAD-specific key microRNAs (miRNAs) from large-scale samples in The Cancer Genome Atlas (TCGA) database. We used an integrative computational method to identify LUAD-specific key miRNAs related to TNM stage and lymphatic metastasis from the TCGA database. Twenty-five LUAD-specific key miRNAs (fold change >2, p<0.05) from the TCGA database were investigated, and 15 were found to be aberrantly expressed with respect to clinical features. Three miRNAs were correlated with overall survival (log-rank p<0.05). Then, 5 miRNAs were randomly selected for verification of expression in 53 LUAD patient tissues using qRT-PCR. Diagnostic value of these above 5 miRNAs was determined by areas under receiver operating characteristic curves (ROC). Finally, the LUAD-related miRNA miR-30a-3p was selected for verification of biologic function in A549 cells. The results of tests for cell proliferation, apoptosis, and target genes suggested that miR-30a-3p decreases cell proliferation and promotes apoptosis through targeting AKT3. Therefore, miR-30a-3p may be a promising biomarker for the early screening of high-risk populations and early diagnosis of LUAD. Our studies provide insights into identifying novel potential biomarkers for diagnosis and prognosis of LUAD.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28791371     DOI: 10.3892/or.2017.5880

Source DB:  PubMed          Journal:  Oncol Rep        ISSN: 1021-335X            Impact factor:   3.906


  7 in total

1.  MiR-30a-3p Suppresses the Growth and Development of Lung Adenocarcinoma Cells Through Modulating GOLM1/JAK-STAT Signaling.

Authors:  Dongxiao Ding; Yunqiang Zhang; Xuede Zhang; Ke Shi; Wenjun Shang; Junjie Ying; Li Wang; Zhongjie Chen; Haihua Hong
Journal:  Mol Biotechnol       Date:  2022-04-19       Impact factor: 2.860

2.  Differential microRNA expression profiles between young and old lung adenocarcinoma patients.

Authors:  Mirella Giordano; Laura Boldrini; Adele Servadio; Cristina Niccoli; Franca Melfi; Marco Lucchi; Alfredo Mussi; Gabriella Fontanini
Journal:  Am J Transl Res       Date:  2018-03-15       Impact factor: 4.060

3.  Identification of nine microRNAs as potential biomarkers for lung adenocarcinoma.

Authors:  Zhi-Peng Ren; Xiao-Bin Hou; Xiao-Dong Tian; Jun-Tang Guo; Lian-Bin Zhang; Zhi-Qiang Xue; Jian-Qing Deng; Shao-Wei Zhang; Jun-Yi Pan; Xiang-Yang Chu
Journal:  FEBS Open Bio       Date:  2019-01-09       Impact factor: 2.693

4.  Nonnegative matrix factorization-based bioinformatics analysis reveals that TPX2 and SELENBP1 are two predictors of the inner sub-consensuses of lung adenocarcinoma.

Authors:  Haiwei Wang; Xinrui Wang; Liangpu Xu; Hua Cao; Ji Zhang
Journal:  Cancer Med       Date:  2021-11-03       Impact factor: 4.452

5.  Characterization of plasma exosomal microRNAs in responding to radiotherapy of human esophageal squamous cell carcinoma.

Authors:  Nan Miao; Wenjie Cai; Sijia Ding; Yajuan Liu; Wanhua Chen; Tao Sun
Journal:  Mol Med Rep       Date:  2022-07-27       Impact factor: 3.423

6.  A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma.

Authors:  Omar Abdelwahab; Nourelislam Awad; Menattallah Elserafy; Eman Badr
Journal:  PLoS One       Date:  2022-09-06       Impact factor: 3.752

7.  SKA3 promotes lung adenocarcinoma metastasis through the EGFR-PI3K-Akt axis.

Authors:  Dan-Dan Hu; Hai-Ling Chen; Li-Ming Lou; Hong Zhang; Guo-Liang Yang
Journal:  Biosci Rep       Date:  2020-02-28       Impact factor: 3.840

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.