Multi-Omics Analysis Reveals the IFI6 Gene as a Prognostic Indicator and Therapeutic Target in Esophageal Cancer

被引:3
|
作者
Viet-Nhi, Nguyen-Kieu [1 ]
Quan, Tran Minh [2 ]
Truc, Vu Cong [3 ]
Bich, Tran Anh [4 ]
Nam, Pham Hoang [4 ]
Le, Nguyen Quoc Khanh [5 ,6 ,7 ,8 ]
Chen, Po-Yueh [9 ,10 ]
Hung, Shih-Han [1 ,9 ,10 ]
机构
[1] Taipei Med Univ, Coll Med, Int Master Ph D Program Med, Taipei 110, Taiwan
[2] Cho Ray Hosp, Dept Thorac Surg, Ho Chi Minh City 700000, Vietnam
[3] Univ Med & Pharm Ho Chi Minh City, Fac Med, Dept Otolaryngol, Ho Chi Minh City 700000, Vietnam
[4] Cho Ray Hosp, Dept Otolaryngol, Ho Chi Minh City 700000, Vietnam
[5] Taipei Med Univ, Coll Med, Profess Master Program Artificial Intelligence Med, Taipei 110, Taiwan
[6] Taipei Med Univ, AIBioMed Res Grp, Taipei 110, Taiwan
[7] Taipei Med Univ, Res Ctr Artificial Intelligence Med, Taipei 110, Taiwan
[8] Taipei Med Univ Hosp, Translat Imaging Res Ctr, Taipei 110, Taiwan
[9] Taipei Med Univ, Wan Fang Hosp, Dept Otolaryngol, Taipei 110, Taiwan
[10] Taipei Med Univ, Coll Med, Sch Med, Dept Otolaryngol, Taipei 110, Taiwan
关键词
IFI6; esophageal cancer; prognostic indicators; gene expression; bioinformatics; multi-omics analysis; VIRUS-INFECTION; HEPATITIS-C; SURVIVAL; APOPTOSIS; SUBGROUP; G1P3; RISK;
D O I
10.3390/ijms25052691
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
The role of the IFI6 gene has been described in several cancers, but its involvement in esophageal cancer (ESCA) remains unclear. This study aimed to identify novel prognostic indicators for ESCA-targeted therapy by investigating IFI6's expression, epigenetic mechanisms, and signaling activities. We utilized public data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) to analyze IFI6's expression, clinical characteristics, gene function, pathways, and correlation with different immune cells in ESCA. The TIMER2.0 database was employed to assess the pan-cancer expression of IFI6, while UALCAN was used to examine its expression across tumor stages and histology subtypes. Additionally, the KEGG database helped identify related pathways. Our findings revealed 95 genes positively correlated and 15 genes negatively correlated with IFI6 in ESCA. IFI6 was over-expressed in ESCA and other cancers, impacting patient survival and showing higher expression in tumor tissues than normal tissues. IFI6 was also correlated with CD4+ T cells and B cell receptors (BCRs), both essential in immune response. GO Biological Process (GO BP) enrichment analysis indicated that IFI6 was primarily associated with the Type I interferon signaling pathway and the defense response to viruses. Intriguingly, KEGG pathway analysis demonstrated that IFI6 and its positively correlated genes in ESCA were mostly linked to the Cytosolic DNA-sensing pathway, which plays a crucial role in innate immunity and viral defense, and the RIG-I-like receptor (RLR) signaling pathway, which detects viral infections and activates immune responses. Pathways related to various viral infections were also identified. It is important to note that our study relied on online databases. Given that ESCA consists of two distinct subgroups (ESCC and EAC), most databases combine them into a single category. Future research should focus on evaluating IFI6 expression and its impact on each subgroup to gain more specific insights. In conclusion, inhibiting IFI6 using targeted therapy could be an effective strategy for treating ESCA considering its potential as a biomarker and correlation with immune cell factors.
引用
收藏
页数:16
相关论文
共 50 条
  • [21] Multi-omics analysis reveals the prognostic and tumor micro-environmental value of lumican in multiple cancer types
    Guo, Zehuai
    Li, Zeyun
    Chen, Ming
    Qi, Xiangjun
    Sun, Zhe
    Wu, Siqi
    Hou, Xuenan
    Qiu, Mengli
    Cao, Yang
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2023, 10
  • [22] Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease
    Wei, Lan
    Gao, Jingjing
    Wang, Liangzhi
    Tao, Qianru
    Tu, Chao
    HUMAN MOLECULAR GENETICS, 2024, 33 (02) : 122 - 137
  • [23] Viewpoint Multi-omics analysis of metastatic pancreatic cancer reveals an immunosuppressive landscape
    Steele, Nina G.
    Hartway, Kailee M.
    MED, 2023, 4 (10): : 657 - 659
  • [24] Multi-Omics Analysis of Primary Prostate Cancer Datasets Reveals Novel Biomarkers
    Tuncer, Melis
    Karabekmez, Muhammed Erkan
    Collak, Filiz Kisaayak
    BIOCHEMICAL GENETICS, 2024,
  • [25] Systemic Multi-Omics Analysis Reveals Amplified P4HA1 Gene Associated With Prognostic and Hypoxic Regulation in Breast Cancer
    Murugesan, Manikandan
    Premkumar, Kumpati
    FRONTIERS IN GENETICS, 2021, 12
  • [26] Multi-omics analysis reveals the role of the autophagy-related gene AGT in chemotherapy resistance in colorectal cancer and the therapeutic potential of its inhibitors
    Cai, Wenjiao
    Xiang, Tao
    Liu, Xiaoli
    Fu, Chong
    DISCOVER ONCOLOGY, 2024, 15 (01)
  • [27] Integrated Analysis of Multi-Omics Data to Identify Prognostic Genes for Pancreatic Cancer
    Jiang, Feng
    Huang, Xiaolu
    Zhang, Fan
    Pan, Jingjing
    Wang, Junjun
    Hu, Lijuan
    Chen, Jie
    Wang, Yumin
    DNA AND CELL BIOLOGY, 2022, 41 (03) : 305 - 318
  • [28] Multi-omics analysis of expression and prognostic value of NSUN members in prostate cancer
    Sun, Guangyu
    Ma, Shenfei
    Zheng, Zhiwen
    Wang, Xiaohua
    Chen, Shuaiqi
    Chang, Taihao
    Liang, Zhengxin
    Jiang, Yuchen
    Xu, Shengxian
    Liu, Ranlu
    FRONTIERS IN ONCOLOGY, 2022, 12
  • [29] Multi-omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple-negative breast cancer
    Xie, Jindong
    Deng, Xinpei
    Xie, Yi
    Zhu, Hongbo
    Liu, Peng
    Deng, Wei
    Ning, Li
    Tang, Yuhui
    Sun, Yuying
    Tang, Hailin
    Cai, Manbo
    Xie, Xiaoming
    Zou, Yutian
    MEDCOMM, 2024, 5 (03):
  • [30] Research on radiotherapy related genes and prognostic target identification of rectal cancer based on multi-omics
    Liu, Yi
    Yang, Yanguang
    Ni, Feng
    Tai, Guomei
    Yu, Cenming
    Jiang, Xiaohui
    Wang, Ding
    JOURNAL OF TRANSLATIONAL MEDICINE, 2023, 21 (01)