Sperm Autoantigenic Protein 17 Predicts the Prognosis and the Immunotherapy Response of Cancers: A Pan-Cancer Analysis

被引:12
|
作者
Tu, Zewei [1 ,2 ,3 ,4 ]
Peng, Jie [5 ]
Long, Xiaoyan [6 ]
Li, Jingying [7 ]
Wu, Lei [1 ,2 ,3 ,4 ]
Huang, Kai [1 ,2 ,3 ,4 ]
Zhu, Xingen [1 ,2 ,3 ,4 ]
机构
[1] Nanchang Univ, Dept Neurosurg, Affiliated Hosp 2, Nanchang, Peoples R China
[2] Jiangxi Key Lab Neurol Tumors & Cerebrovascular D, Nanchang, Peoples R China
[3] Nanchang Univ, Inst Neurosci, Nanchang, Peoples R China
[4] Jiangxi Hlth Commiss JXHC Key Lab Neurol Med, Nanchang, Peoples R China
[5] Nanchang Univ, Clin Med Coll 2, Nanchang, Peoples R China
[6] East China Inst Digital Med Engn, Shangrao, Peoples R China
[7] Nanchang Univ, Dept Comprehens Intens Care Unit, Affiliated Hosp 2, Nanchang, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2022年 / 13卷
关键词
sperm autoantigenic protein 17 (SPA17); pan-cancer; prognostic biomarker; immunotherapy response; CMap; SP17; EXPRESSION; ANTIGEN; INHIBITORS; ANTI-PD-1; PD-1;
D O I
10.3389/fimmu.2022.844736
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundSperm autoantigen protein 17 (SPA17) is a highly conserved mammalian protein that participates in the acrosome reaction during fertilization and is a recently reported member of the cancer-testicular antigen (CTA) family. It has been reported that the SPA17 expression is limited in adult somatic tissues and re-expressed in tumor tissues. Recently, studies have found that SPA17 regulates the progression of various cancers, but its role in cancer immunotherapy is not clear. MethodsThe pan-cancer and normal tissue transcriptional data were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. We explored the SPA17 pan-cancer genomic alteration analysis in the cBioPortal webtool. The Human Protein Atlas (HPA) and ComPPI websites were used to mine the SPA17 protein information. We performed a western blotting assay to validate the upregulated SPA17 expression in clinical glioblastoma (GBM) samples. The univariate Cox regression and Kaplan-Meier method were used to assess the prognostic role of SPA17 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was used to search the associated cancer hallmarks with SPA17 expression in each cancer type. TIMER2.0 was the main platform to investigate the immune cell infiltrations related to SPA17 in pan-cancer. The associations between SPA17 and immunotherapy biomarkers were performed by Spearman correlation analysis. The drug sensitivity information from the Connectivity Map (CMap) dataset was downloaded to perform SAP17-specific inhibitor sensitivity analysis. FindingsSPA17 was aberrantly expressed in most cancer types and exhibited prognosis predictive ability in various cancers. In addition, our results also show that SPA17 was significantly correlated with immune-activated hallmarks (including pathways and biological processes), immune cell infiltrations, and immunoregulator expressions. The most exciting finding was that SPA17 could significantly predict anti-PDL1 and anti-PD1 therapy responses in cancer patients. Finally, specific inhibitors, like irinotecan and puromycin, which correlate with SPA17 expression in different cancer types, were also screened using Connectivity Map (CMap). ConclusionsOur results reveal that SPA17 was abnormally expressed in cancer tissues, and this expression pattern could be associated with immune cell infiltrations in tumor microenvironments. Clinically, SPA17 not only acted as a potent prognostic factor to predict the clinical outcomes of cancer patients but was also a promising immunotherapy predictive biomarker for cancer patients treated with immune-checkpoint inhibitors (ICIs).
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Spindle component 25 predicts the prognosis and the immunotherapy response of cancers: a pan-cancer analysis
    Xia, Fengjuan
    Yang, Haixia
    Wu, Huangjian
    Zhao, Bo
    SCIENTIFIC REPORTS, 2024, 14 (01)
  • [2] 4-Hydroxyphenylpyruvate Dioxygenase-Like predicts the prognosis and the immunotherapy response of cancers: a pan-cancer analysis
    Li, Huimin
    Liu, Junzhi
    Wang, Shurui
    Xu, Yue
    Tang, Qiang
    Ying, Guoguang
    AGING-US, 2024, 16 (05): : 4327 - 4347
  • [3] A comprehensive analysis of PANoptosome to prognosis and immunotherapy response in pan-cancer
    Zhuang, Lingling
    Sun, Qiran
    Huang, Shenglan
    Hu, Lanyan
    Chen, Qi
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [4] A comprehensive analysis of PANoptosome to prognosis and immunotherapy response in pan-cancer
    Lingling Zhuang
    Qiran Sun
    Shenglan Huang
    Lanyan Hu
    Qi Chen
    Scientific Reports, 13
  • [5] AMP-dependent protein kinase alpha 1 predicts cancer prognosis and immunotherapy response: from pan-cancer analysis to experimental validation
    Yong, Tao
    Wei, Qiu-Ya
    Liu, Jie
    Wang, Yun-Peng
    Huang, Wei-Peng
    Lu, Yu
    Wang, Chen
    Fan, Yong
    AMERICAN JOURNAL OF CANCER RESEARCH, 2024, 14 (10): : 5079 - 5094
  • [6] Roles of HMGBs in Prognosis and Immunotherapy: A Pan-Cancer Analysis
    Lin, Tong
    Zhang, Yingzhao
    Lin, Zhimei
    Peng, Lisheng
    FRONTIERS IN GENETICS, 2021, 12
  • [7] Comprehensive Pan-Cancer Analysis of Senescence With Cancer Prognosis and Immunotherapy
    Zhao, Qinfei
    Hu, Weiquan
    Xu, Jing
    Zeng, Shaoying
    Xi, Xuxiang
    Chen, Jing
    Wu, Xiangsheng
    Hu, Suping
    Zhong, Tianyu
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2022, 9
  • [8] Pan-cancer analysis of ADAMs: A promising biomarker for prognosis and response to chemotherapy and immunotherapy
    Ma, Bo
    Yu, Riyue
    FRONTIERS IN GENETICS, 2023, 14
  • [9] A pan-cancer cuproptosis signature predicting immunotherapy response and prognosis
    Zhu, Xiaojing
    Zhang, Zixin
    Xiao, Yanqi
    Wang, Hao
    Zhang, Jiaxing
    Wang, Mingwei
    Jiang, Minghui
    Xu, Yan
    HELIYON, 2024, 10 (15)
  • [10] Thyroid hormone receptor interacting protein 13 is associated with prognosis and immunotherapy efficacy in human cancers: a pan-cancer analysis
    ShengYao Zheng
    HongYi Wang
    Yingyi Wang
    Discover Oncology, 16 (1)