Identification of Key Biomarkers and Candidate Molecules in Non-Small-Cell Lung Cancer by Integrated Bioinformatics Analysis

被引:8
作者
Yu, Liyan [1 ]
Liang, Xuemei [2 ]
Wang, Jianwei [3 ]
Ding, Guangxiang [3 ]
Tang, Jinhai [3 ]
Xue, Juan [3 ]
He, Xin [2 ]
Ge, Jingxuan [2 ]
Jin, Xianzhang [2 ]
Yang, Zhiyi [2 ]
Li, Xianwei [2 ]
Yao, Hehuan [2 ]
Yin, Hongtao [2 ]
Liu, Wu [2 ]
Yin, Shengchen [2 ]
Sun, Bing [2 ]
Sheng, Junxiu [3 ]
机构
[1] Dalian Med Univ, Affiliated Hosp 1, Dept Resp, Dalian 116044, Liaoning, Peoples R China
[2] Dalian Med Univ, Affiliated Hosp 1, Dept Thorac Surg, Dalian 116044, Peoples R China
[3] Dalian Med Univ, Affiliated Hosp 1, Dept Radiat Oncol, Dalian 116044, Peoples R China
关键词
PD-L1; EXPRESSION; GENE-EXPRESSION; IMMUNE ESCAPE; UP-REGULATION; WEB SERVER; PATHWAY; COMBINATION; P85-ALPHA; MIR-146A; SURVIVAL;
D O I
10.1155/2023/6782732
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background. Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis. Methods. From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools. Results. We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis P < 0.05. We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis P < 0.05. On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients P < 0.05. Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma. Conclusions. The results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.
引用
收藏
页数:19
相关论文
共 85 条
  • [1] IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer
    Abiko, K.
    Matsumura, N.
    Hamanishi, J.
    Horikawa, N.
    Murakami, R.
    Yamaguchi, K.
    Yoshioka, Y.
    Baba, T.
    Konishi, I.
    Mandai, M.
    [J]. BRITISH JOURNAL OF CANCER, 2015, 112 (09) : 1501 - 1509
  • [2] Involvement of TIMP-1 in PECAM-1-mediated tumor dissemination
    Abraham, Valsamma
    Cao, Gaoyuan
    Parambath, Andrew
    Lawal, Fareedah
    Handumrongkul, Chakkrapong
    Debs, Robert
    Delisser, Horace M.
    [J]. INTERNATIONAL JOURNAL OF ONCOLOGY, 2018, 53 (02) : 488 - 502
  • [3] OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs
    Anaya, Jordan
    [J]. PEERJ COMPUTER SCIENCE, 2016,
  • [4] Assidi Mourad, 2019, Tumour Biol, V41, p1010428319863627, DOI 10.1177/1010428319863627
  • [5] PD-L1 up-regulation in melanoma increases disease aggressiveness and is mediated through miR-17-5p
    Audrito, Valentina
    Serra, Sara
    Stingi, Aureliano
    Orso, Francesca
    Gaudino, Federica
    Bologna, Cinzia
    Neri, Francesco
    Garaffo, Giulia
    Nassini, Romina
    Baroni, Gianna
    Rulli, Eliana
    Massi, Daniela
    Oliviero, Salvatore
    Piva, Roberto
    Taverna, Daniela
    Mandala, Mario
    Deaglio, Silvia
    [J]. ONCOTARGET, 2017, 8 (09) : 15894 - 15911
  • [6] NCBI GEO: archive for functional genomics data sets-update
    Barrett, Tanya
    Wilhite, Stephen E.
    Ledoux, Pierre
    Evangelista, Carlos
    Kim, Irene F.
    Tomashevsky, Maxim
    Marshall, Kimberly A.
    Phillippy, Katherine H.
    Sherman, Patti M.
    Holko, Michelle
    Yefanov, Andrey
    Lee, Hyeseung
    Zhang, Naigong
    Robertson, Cynthia L.
    Serova, Nadezhda
    Davis, Sean
    Soboleva, Alexandra
    [J]. NUCLEIC ACIDS RESEARCH, 2013, 41 (D1) : D991 - D995
  • [7] Global Epidemiology of Lung Cancer
    Barta, Julie A.
    Powell, Charles A.
    Wisnivesky, Juan P.
    [J]. ANNALS OF GLOBAL HEALTH, 2019, 85 (01):
  • [8] ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks
    Bindea, Gabriela
    Mlecnik, Bernhard
    Hackl, Hubert
    Charoentong, Pornpimol
    Tosolini, Marie
    Kirilovsky, Amos
    Fridman, Wolf-Herman
    Pages, Franck
    Trajanoski, Zlatko
    Galon, Jerome
    [J]. BIOINFORMATICS, 2009, 25 (08) : 1091 - 1093
  • [9] The Evolution of Therapies in Non-Small Cell Lung Cancer
    Boolell, Vishal
    Alamgeer, Muhammad
    Watkins, David N.
    Ganju, Vinod
    [J]. CANCERS, 2015, 7 (03) : 1815 - 1846
  • [10] [Anonymous], 2020, CA Cancer J Clin, V70, P313, DOI [10.3322/caac.21492, 10.3322/caac.21609]