Identification of Differentially Expressed Genes as Potential Therapeutic and Prognostic Targets for Breast Cancer Based on Bioinformatics

被引:1
|
作者
Ma, Yan [1 ]
Peng, Yingge [2 ]
Li, Xin [3 ]
Huo, Xiaoguang [1 ]
Xu, Wenzhe [1 ]
Zhao, Wei [1 ]
Wang, Yingnan [4 ]
机构
[1] Zibo Cent Hosp, Dept Ultrasound, Zibo 255000, Shandong, Peoples R China
[2] Zibo Tradit Chinese Med Hosp, Hlth Management Ctr, Zibo 255000, Shandong, Peoples R China
[3] Zibo Cent Hosp, Dept Clin Lab, Zibo 255000, Shandong, Peoples R China
[4] Zibo Tradit Chinese Med Hosp, Dept Surg, Zibo 255000, Shandong, Peoples R China
关键词
breast cancer; hub gene; biomarker; prognosis;
D O I
10.23812/j.biol.regul.homeost.agents.20233711.605
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Breast cancer (BC) is one of the most common malignant tumors in women. There is an urgent need to explore the key genes responsible for the prognosis of BC. The aim of this study was to screen out differentially expressed genes (DEGs) in BC and to provide reliable prognosis prediction. DEGs related to prognosis of BC were identified and verified as markers for predicting BC prognosis.Methods: Two data sets GSE22820 and GSE29431 were selected from the Gene Expression Omnibus (GEO) database and the DEGs were screened by the online tool of GEO2R and visualized by the volcano maps. The bioinformatics software of database for annotation, visualization, and integrated discovery (DAVID) was used to annotate associated functions of DEGs. Search tool for the retrieval of interacting genes/proteins (STRING) was used to construct the protein-protein interaction (PPI) networks which were visualized by Cytoscape software. Afterward, the data from The Cancer Genome Atlas (TCGA) were used for multivari-ate Cox regression analysis and Kaplan-Meier (K-M) survival analysis was used to identify prognosis-related key genes. The immortalized breast epithelial cell line MCF10A and BC cell line MCF7 were purchased and exploited to verify the differential expression of selected hub genes through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and western blot. The expressions of prognostic-related genes were regulated through transfecting MCF7 cells, followed by exploring the effects of prognosis-related genes. The cell proliferation was determined by assays of colony formation. The cell counting kit (CCK)-8 and the cell migration were evaluated by the tests of transwell and cell scratch. The flow cytometry of Annexin V-PE and 7-AAD double stained cells was used for measuring cell apoptosis. Results: The bioinformatics analysis indicated that 969 DEGs were found in GSE22820, out of which 421 genes were over-expressed and 548 genes were under-expressed. In GSE29431, 724 DEGs were found, out of which 109 genes were over-expressed and 615 genes were under-expressed. GSE22820, GSE29431, and Co-DEGs are involved in mitotic nuclear division, regulation of angiogenesis, connective tissue development, muscle organ development, glucose metabolic process, and hexose metabolic process. Genes of peroxisome proliferator-activated receptor alpha (PPARA), peroxisome proliferator-activated receptor gamma (PPARG), lipoprotein lipase (LPL), leptin (LEP), insulin like growth factor 1 (IGF1), type I collagen alpha 1 (COL1A1), Fibronectin (FN)1, and anillin (ANLN) were identified as hub genes, and ANLN, PPARA, PPARG, and LPL were verified for having effect on prognosis of BC. The upregulation of PPARA and PPARG, and the downregulation of ANLN and LPL restrained both proliferation and migration and induced apoptosis of BC cells.Conclusions: PPARA, PPARG, LPL, LEP, IGF1, COL1A1, FN1, and ANLN were identified as hub genes and ANLN, PPARA, PPARG, and LPL could affect the development of BC by inhibiting proliferation and migration and promoting apoptosis of cancer cells.
引用
收藏
页码:6375 / 6388
页数:14
相关论文
共 50 条
  • [41] Promoter Methylation-Regulated Differentially Expressed Genes in Breast Cancer
    Sindi, Samar
    Hamdi, Norah
    Hassan, Sabah
    Ganash, Magdah
    Alharbi, Mona
    Alburae, Najla
    Azhari, Sheren
    Alkhayyat, Shadi
    Linjawi, Ayman
    Alkhatabi, Heba
    Elaimi, Aisha
    Alrefaei, Ghadeer
    Alsubhi, Nouf
    Alrafiah, Aziza
    Alhazmi, Safiah
    BREAST CANCER-TARGETS AND THERAPY, 2023, 15 : 435 - 450
  • [42] Identification of therapeutic targets of breast cancer
    Yang, Yang
    Chen, Lu
    Xu, Xinyue
    Fan, Zhenlin
    Li, Wenjing
    Niu, Chunfeng
    INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2016, 9 (08): : 15447 - 15456
  • [43] Identification of genes related to ribosomal proteins in colorectal cancer: exploring their potential as biomarkers, prognostic indicators, and therapeutic targets
    Salehinia, Negin
    Al-Mosawi, Aseel Kamil Mohammad
    Al-Moussawi, Duaa Kamel
    Sadeghi, Ensieh Sagheb
    Zamani, Atefeh
    Mahdevar, Mohammad
    MOLECULAR BIOLOGY REPORTS, 2024, 51 (01)
  • [44] Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer
    Xu, Tiankai
    Chu, Chu
    Xue, Shuyu
    Jiang, Tongchao
    Wang, Ying
    Xia, Wen
    Lin, Huanxin
    JOURNAL OF TRANSLATIONAL MEDICINE, 2025, 23 (01)
  • [45] Identification of Differentially Expressed Genes and Biological Pathways in Sanguinarine-treated Ovarian Cancer by Integrated Bioinformatics Analysis
    Yu, Haiting
    Touna, Abdelkerim Barh
    Yin, Xueqin
    Zhang, Qin
    Leng, Tianyan
    Yang, Lihua
    PHARMACOGNOSY MAGAZINE, 2021, 17 (73) : 106 - 111
  • [46] Identification of differentially expressed genes between mucinous adenocarcinoma and other adenocarcinoma of colorectal cancer using bioinformatics analysis
    Zhang, Xue
    Zuo, Jing
    Wang, Long
    Han, Jing
    Feng, Li
    Wang, Yudong
    Fan, Zhisong
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2020, 48 (08)
  • [47] Identification of potential hub genes and therapeutic drugs in ovarian cancer via bioinformatics analysis
    Zhou, Xinyue
    Song, Zuofei
    Chen, Jia
    Wang, Dongxue
    Sun, Jingli
    ALL LIFE, 2023, 16 (01)
  • [48] Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment
    Cui, Hongtu
    Ma, Ruilin
    Hu, Tao
    Xiao, Gary Guishan
    Wu, Chengjun
    FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY, 2022, 12
  • [49] Identification of Prognostic Biomarkers and Molecular Targets Among JAK Family in Breast Cancer
    Liu, Fangteng
    Wu, Hengyu
    JOURNAL OF INFLAMMATION RESEARCH, 2021, 14 : 97 - 114
  • [50] Differentially expressed genes associated with the metastatic phenotype in breast cancer
    Kirschmann, DA
    Seftor, EA
    Nieva, DRC
    Mariano, EA
    Hendrix, MJC
    BREAST CANCER RESEARCH AND TREATMENT, 1999, 55 (02) : 127 - 136