Prognostic value and molecular mechanisms of OAS1 in lung adenocarcinoma

被引:0
作者
Wang, Lei [1 ]
Gao, Linlu [1 ]
Ding, Fei [2 ]
Gao, Kun [1 ]
Liu, Qian [3 ]
Yin, Xiaoling [4 ]
机构
[1] Zibo Hosp Integrated Tradit Chinese & Western Med, Oncol Dept, Zibo 255022, Shandong, Peoples R China
[2] Zibo First Hosp, Oncol Dept, Zibo 255022, Shandong, Peoples R China
[3] Zibo City Hosp Integrated Chinese & Western Med, Oncol Dept, Zibo 255000, Shandong, Peoples R China
[4] Zibo Hosp Integrated Tradit Chinese & Western Med, Resp Dept, 8 Jinjing Ave, Zibo 255022, Shandong, Peoples R China
来源
BMC PULMONARY MEDICINE | 2024年 / 24卷 / 01期
关键词
Lung adenocarcinoma; OAS1; Prognosis; Function and pathway; Transcription regulatory network; SURVIVAL; IDENTIFICATION; PREDICTION; STAT3;
D O I
10.1186/s12890-024-03206-3
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
Background The expression of 2'-5'-oligoadenylate synthetase 1 (OAS1) in lung cancer has been validated in numerous studies. However, the prognostic value of OAS1 expression in lung adenocarcinoma (LUAD) still remains unclear. This study aimed to reveal the prognostic value and associated molecular mechanisms of OAS1 expression in LUAD. Methods Gene expression data of LUAD were extracted from online databases. Gene and protein expression levels of OAS1 in LUAD and normal samples were revealed, followed by prognostic analysis of OAS1. Next, we conducted a thorough bioinformatics analysis to examine the enrichment of key functional and biological signaling pathways and their correlation with the abundance of immune cells. The independent prognoses, drug responses, and PPI networks associated with OAS1 were analyzed. OAS1 expression was evaluated in LUAD tissues and cell lines. OAS1 was knocked down by siRNA transfection, followed by CCK8, colony formation, and wound-healing assays. Results Gene and protein expression levels of OAS1 in LUAD samples were significantly higher than those in normal samples (all P < 0.05). OAS1 stimulation were correlated with poor prognosis, lymph node metastasis, advanced tumor stage, immune cells, and immunomodulators. The prognostic value of OAS1 in LUAD was determined via univariate regression analysis. In total, 10 OAS1-associated genes were revealed via PPI analysis of OAS1, which were primarily enriched in functions, such as the negative regulation of viral genome replication. Transcriptional analysis revealed several OAS1-related interactions, including STAT3-miR-21-OAS1. STAT3 was overexpressed and miR-21 was expressed in LUAD cells. Upregulation of OAS1 protein was determined in LUAD tissues and cell lines. OAS1 knockdown significantly reduced proliferation and migration of LUAD cells. Conclusions OAS1 overexpression influenced survival and immune cell infiltration in patients with LUAD, which might be a potential prognostic gene for LUAD. Moreover, OAS1 contributed to LUAD progression by participating in STAT3-miR-21-OAS1 axis.
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页数:15
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共 51 条
  • [1] Statistics notes - Survival probabilities (the Kaplan-Meier method)
    Bland, JM
    Altman, DG
    [J]. BRITISH MEDICAL JOURNAL, 1998, 317 (7172) : 1572 - 1572
  • [2] Updates in grading and invasion assessment in lung adenocarcinoma
    Borczuk, Alain C.
    [J]. MODERN PATHOLOGY, 2022, 35 (SUPPL 1) : 28 - 35
  • [3] Chen BB, 2018, METHODS MOL BIOL, V1711, P243, DOI 10.1007/978-1-4939-7493-1_12
  • [4] DAVID: Database for annotation, visualization, and integrated discovery
    Dennis, G
    Sherman, BT
    Hosack, DA
    Yang, J
    Gao, W
    Lane, HC
    Lempicki, RA
    [J]. GENOME BIOLOGY, 2003, 4 (09)
  • [5] Dutta Pranabananda, 2014, JAKSTAT, V3, pe999503, DOI 10.1080/21623996.2014.999503
  • [6] miRWalk2.0: a comprehensive atlas of microRNA-target interactions
    Dweep, Harsh
    Gretz, Norbert
    [J]. NATURE METHODS, 2015, 12 (08) : 697 - 697
  • [7] Gao L, 2019, AM J TRANSL RES, V11, P7503
  • [8] pRRophetic: An R Package for Prediction of Clinical Chemotherapeutic Response from Tumor Gene Expression Levels
    Geeleher, Paul
    Cox, Nancy
    Huang, R. Stephanie
    [J]. PLOS ONE, 2014, 9 (09):
  • [9] Visualizing and interpreting cancer genomics data via the Xena platform
    Goldman, Mary J.
    Craft, Brian
    Hastie, Mim
    Repecka, Kristupas
    McDade, Fran
    Kamath, Akhil
    Banerjee, Ayan
    Luo, Yunhai
    Rogers, Dave
    Brooks, Angela N.
    Zhu, Jingchun
    Haussler, David
    [J]. NATURE BIOTECHNOLOGY, 2020, 38 (06) : 675 - 678
  • [10] GSVA: gene set variation analysis for microarray and RNA-Seq data
    Haenzelmann, Sonja
    Castelo, Robert
    Guinney, Justin
    [J]. BMC BIOINFORMATICS, 2013, 14