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
  • [1] Pan-cancer and multi-omics analysis: NDUFA1 is a potential therapeutic target and prognostic marker for esophageal cancer
    Yin, Rui
    Zhou, Gai
    Liu, Guanqi
    Hou, Xiaoting
    Yang, Haifeng
    Ge, Jianxin
    Ying, Jie
    CELL BIOLOGY AND TOXICOLOGY, 2025, 41 (01)
  • [2] Integration of multi-omics and clinical treatment data reveals bladder cancer therapeutic vulnerability gene combinations and prognostic risks
    Xu, Yan
    Sun, Xiaoyu
    Liu, Guangxu
    Li, Hongze
    Yu, Meng
    Zhu, Yuyan
    FRONTIERS IN IMMUNOLOGY, 2024, 14
  • [3] Current advances on single or multi-omics analysis of esophageal cancer
    Kasimu, Kaidirina
    Cui, Wenwen
    Wang, Yihan
    Li, Xin
    Wang, Hongbo
    Yu, Xiaotong
    Ren, Fu
    ADVANCEMENTS IN LIFE SCIENCES, 2024, 11 (02): : 296 - 304
  • [4] Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis
    Kim, Hyung-Yong
    Choi, Hee-Joo
    Lee, Jeong-Yeon
    Kong, Gu
    BRIEFINGS IN BIOINFORMATICS, 2020, 21 (02) : 663 - 675
  • [5] Therapeutic and prognostic potential of GPCRs in prostate cancer from multi-omics landscape
    Li, Shiqi
    Chen, Jianfang
    Chen, Xin
    Yu, Jin
    Guo, Yanzhi
    Li, Menglong
    Pu, Xuemei
    FRONTIERS IN PHARMACOLOGY, 2022, 13
  • [6] Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes
    Sharma, Abhibhav
    Debik, Julia
    Naume, Bjorn
    Ohnstad, Hege Oma
    Bathen, Tone F.
    Giskeodegard, Guro F.
    ONCOGENESIS, 2024, 13 (01):
  • [7] Multi-omics analysis reveals CLIC1 as a therapeutic vulnerability of gliomas
    Wang, Chengcheng
    He, Zheng
    FRONTIERS IN PHARMACOLOGY, 2023, 14
  • [8] 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)
  • [9] 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
  • [10] Multi-omics analysis of the prognostic and biological role of cuproptosis-related gene in gastric cancer
    Zhang, Ruopeng
    Zhang, Feiyang
    Liu, Zekun
    Huang, Yuqian
    Li, Yinghe
    Zhao, Baiwei
    Chen, Wanqi
    JOURNAL OF GASTROINTESTINAL ONCOLOGY, 2024, 15 (03) : 946 - 962