Bioinformatics Analysis Screening and Identification of Key Biomarkers and Drug Targets in Human Glioblastoma

被引:0
|
作者
Wang, Chunlei [1 ,2 ]
Beylerli, Ozal [3 ]
Gu, Yan [1 ,2 ]
Xu, Shancai [1 ,2 ]
Ji, Zhiyong [1 ,2 ]
Ilyasova, Tatiana [3 ]
Gareev, Ilgiz [3 ]
Chekhonin, Vladimir [4 ,5 ,6 ]
机构
[1] Harbin Med Univ, Affiliated Hosp 1, Dept Neurosurg, Harbin, Heilongjiang, Peoples R China
[2] Harbin Med Univ, Inst Brain Sci, Harbin, Heilongjiang, Peoples R China
[3] Bashkir State Med Univ, Ufa 450008, Russia
[4] Pirogov Russian Natl Res Med Univ, Minist Healthcare Russian Federat, Moscow, Russia
[5] Minist Healthcare Russian Federat, Serbsky Fed Med Res Ctr Psychiat & Narcol, Moscow, Russia
[6] Natl Med Res Ctr Endocrinol, Moscow, Russia
关键词
Glioblastoma; bioinformatics analysis; diagnosis; therapeutic strategies; cancer progression; drugs; GENE-EXPRESSION OMNIBUS; TERT PROMOTER MUTATIONS; PROGNOSTIC SIGNATURE; PANCREATIC-CANCER; COPY NUMBER; MGMT GENE; GEMCITABINE; BRAIN; SPINDLE; GLIOMA;
D O I
10.2174/0109298673316883240829073901
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background Glioblastoma is the most common type of brain cancer, with a prognosis that is unfortunately poor. Despite considerable progress in the field, the intricate molecular basis of this cancer remains elusive.Aim The aim of this study was to identify genetic indicators of glioblastoma and reveal the processes behind its development.Objective The advent and integration of supercomputing technology have led to a significant advancement in gene expression analysis platforms. Microarray analysis has gained recognition for its pivotal role in oncology, crucial for the molecular categorization of tumors, diagnosis, prognosis, stratification of patients, forecasting tumor responses, and pinpointing new targets for drug discovery. Numerous databases dedicated to cancer research, including the Gene Expression Omnibus (GEO) database, have been established. Identifying differentially expressed genes (DEGs) and key genes deepens our understanding of the initiation of glioblastoma, potentially unveiling novel markers for diagnosis and prognosis, as well as targets for the treatment of glioblastoma.Methods This research sought to discover genes implicated in the development and progression of glioblastoma by analyzing microarray datasets GSE13276, GSE14805, and GSE109857 from the GEO database. DEGs were identified, and a function enrichment analysis was performed. Additionally, a protein-protein interaction network (PPI) was constructed, followed by module analysis using the tools STRING and Cytoscape.Results The analysis yielded 88 DEGs, consisting of 66 upregulated and 22 downregulated genes. These genes' functions and pathways primarily involved microtubule activity, mitotic cytokinesis, cerebral cortex development, localization of proteins to the kinetochore, and the condensation of chromosomes during mitosis. A group of 27 pivotal genes was pinpointed, with biological process analysis indicating significant enrichment in activities, such as division of the nucleus during mitosis, cell division, maintaining cohesion between sister chromatids, segregation of sister chromatids during mitosis, and cytokinesis. The survival analysis indicated that certain genes, including PCNA clamp-associated factor (PCLAF), ribonucleoside-diphosphate reductase subunit M2 (RRM2), nucleolar and spindle-associated protein 1 (NUSAP1), and kinesin family member 23 (KIF23), could be instrumental in the development, invasion, or recurrence of glioblastoma.Conclusion The identification of DEGs and key genes in this study advances our comprehension of the molecular pathways that contribute to the oncogenesis and progression of glioblastoma. This research provides valuable insights into potential diagnostic and therapeutic targets for glioblastoma.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
    Fee Faysal Ahmed
    Arnob Dip Das
    Mst. Joynab Sumi
    Md. Zohurul Islam
    Md. Shahedur Rahman
    Md. Harun Rashid
    Salem A. Alyami
    Naif Alotaibi
    A. K. M. Azad
    Mohammad Ali Moni
    Scientific Reports, 13
  • [32] Identification of key biomarkers and potential molecular mechanisms in lung cancer by bioinformatics analysis
    Li, Zhenhua
    Sang, Meixiang
    Tian, Ziqiang
    Liu, Zhao
    Lv, Jian
    Zhang, Fan
    Shan, Baoen
    ONCOLOGY LETTERS, 2019, 18 (05) : 4429 - 4440
  • [33] Identification of key biomarkers in neonatal sepsis by integrated bioinformatics analysis and clinical validation
    Yan, Rui
    Zhou, Tao
    HELIYON, 2022, 8 (11)
  • [34] Identification of key biomarkers in breast cancer based on bioinformatics analysis and experimental verification
    Huan, Yu
    She, Ping
    Cai, Xushan
    Qi, Jiehua
    Zhang, Chunli
    JOURNAL OF THE EGYPTIAN NATIONAL CANCER INSTITUTE, 2025, 37 (01)
  • [35] Identification of key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis
    Cai, Weisong
    Li, Haohuan
    Zhang, Yubiao
    Han, Guangtao
    PEERJ, 2020, 8
  • [36] Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis
    Chen, Chengyong
    Sun, Chong
    Tang, Dong
    Yang, Guangcheng
    Zhou, Xuanjun
    Wang, Donghai
    ONCOLOGY LETTERS, 2016, 11 (06) : 3999 - 4007
  • [37] Bioinformatics analysis of key biomarkers for bladder cancer
    Liu, Wentao
    Xu, Yuxin
    Bai, Shengbin
    Liao, Libin
    BIOMEDICAL REPORTS, 2023, 18 (02)
  • [38] Integrative Bioinformatics Approaches for Identification of Drug Targets in Hypertension
    Hemerich, Daiane
    van Setten, Jessica
    Tragante, Vinicius
    Asselbergs, Folkert W.
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2018, 5
  • [39] Screening and identification of key gene in sepsis development Evidence from bioinformatics analysis
    Fu, Qinghui
    Yu, Wenqiao
    Fu, Shuiqiao
    Chen, Enjiang
    Zhang, Shaoyang
    Liang, Ting-bo
    MEDICINE, 2020, 99 (27) : E20759
  • [40] Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
    Chen, Kegong
    Bai, Long
    Ji, Lin
    Wu, Libo
    Li, Guanghua
    MEDICINE, 2021, 100 (24) : E26271