The pan-cancer multi-omics landscape of key genes of sialylation combined with RNA-sequencing validation

被引:5
|
作者
Wu, Zhixuan [2 ]
Wang, Ziqiong [2 ]
Wu, Haodong [2 ]
Zheng, Na [1 ]
Huang, Dongdong [1 ]
Huang, Zhipeng [1 ]
Han, Hui [2 ]
Bao, Jingxia [2 ]
Xu, Hongjie [2 ]
Zhang, Rongrong [2 ]
Du, Zhou [1 ]
Wu, Dazhou [1 ]
机构
[1] Wenzhou Med Univ, Affiliated Hosp 1, Dept Hernia & Abdominal Wall Surg, Wenzhou 325015, Zhejiang, Peoples R China
[2] Wenzhou Med Univ, Affiliated Hosp 1, Wenzhou 325015, Zhejiang, Peoples R China
关键词
Sialylation; Pan-cancer; Multi-omics; Tumor microenvironment; Immunotherapy; IMMUNE CHECKPOINT; DNA METHYLATION; SIALYLTRANSFERASE; PPGALNAC-T13; EXPRESSION; RESPONSES;
D O I
10.1016/j.compbiomed.2023.107556
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Sialylation, the process of salivary acid glycan synthesis, plays a pivotal function in tumor growth, immune escape, tumor metastasis, and resistance to drugs. However, the association between sialylation and prognosis, tumor microenvironment (TME), and treatment response in a variety of cancers remains unclear. Methods: A comprehensive survey of the expression profile, prognostic value, and genetic and epigenetic alterations of sialylation-related genes was performed in pan-cancer. Subsequently, the single-sample gene set enrichment analysis (ssGSEA) algorithm was used to compute sialylation pathway scores in pan-cancer. Correlations of sialylation pathway scores with clinical features, prognosis, and TME were evaluated using multiple algorithms. Finally, the efficacy of the sialylation pathway score in determining the effect of immunotherapy was evaluated. The expression of sialylation-related genes were verified by RNA-sequencing.Results: Significant differences were observed in sialylation-related genes expression between tumors and adjacent normal tissues for most cancer types. Sialylation pathway scores differed according to the type of tumor, where the poor prognosis was correlated with high sialylation pathway scores in uveal melanoma (UVM) and pancreatic adenocarcinoma (PAAD). In addition, sialylation pathway scores were positively associated with the ImmuneScore, StromalScore and immune-related pathways. Moreover, the level of immune cells infiltration was higher in tumors with higher sialylation pathway scores. Finally, patients with high sialylation pathway scores were more sensitive to immunotherapy.Conclusion: Sialylation-related genes are essential in pan-cancer. The sialylation pathway score may be used as a biomarker in oncology patients.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Glutamine Metabolism Regulators Associated with Cancer Development and the Tumor Microenvironment: A Pan-Cancer Multi-Omics Analysis
    Zou, Jingwen
    Du, Kunpeng
    Li, Shaohua
    Lu, Lianghe
    Mei, Jie
    Lin, Wenping
    Deng, Min
    Wei, Wei
    Guo, Rongping
    GENES, 2021, 12 (09)
  • [32] TCGAplot: an R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data
    Chenqi Liao
    Xiong Wang
    BMC Bioinformatics, 24
  • [33] The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer
    Wang, Cong
    Zhang, Mengyan
    Zhao, Jiyun
    Li, Bin
    Xiao, Xingjun
    Zhang, Yan
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 163
  • [34] Pan-cancer analysis from multi-omics data reveals AAMP as an unfavourable prognostic marker
    Wang, Yang
    Liu, Ting
    Zhang, Ke
    Huang, Rong-hai
    Jiang, Li
    EUROPEAN JOURNAL OF MEDICAL RESEARCH, 2023, 28 (01)
  • [35] Tissue-specific identification of multi-omics features for pan-cancer drug response prediction
    Zhao, Zhi
    Wang, Shixiong
    Zucknick, Manuela
    Aittokallio, Tero
    ISCIENCE, 2022, 25 (08)
  • [36] Multi-omics analysis reveals the panoramic picture of necroptosis-related regulators in pan-cancer
    Li, Guanghao
    Wang, Xiaoxuan
    Liu, Yongheng
    Li, Huikai
    Mu, Han
    Zhang, Yanting
    Li, Qiang
    AGING-US, 2022, 14 (12): : 5034 - 5058
  • [37] TCGAplot: an R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data
    Liao, Chenqi
    Wang, Xiong
    BMC BIOINFORMATICS, 2023, 24 (01)
  • [38] Pan-cancer analysis from multi-omics data reveals AAMP as an unfavourable prognostic marker
    Yang Wang
    Ting Liu
    Ke Zhang
    Rong-hai Huang
    Li Jiang
    European Journal of Medical Research, 28
  • [39] Genetic mechanisms underlying oncogenic metabolic switch revealed by pan-cancer multi-omics analysis
    McClure, Marni B.
    Saito, Yuki
    Kogure, Yasunori
    Kataoke, Keisuke
    CANCER SCIENCE, 2021, 112 : 308 - 308
  • [40] Pan-Cancer Multi-Omics Analysis of Minichromosome Maintenance Proteins (MCMs) Expression in Human Cancers
    Wang, Lulu
    Liu, Xiaowei
    FRONTIERS IN BIOSCIENCE-LANDMARK, 2023, 28 (09):