The Prognostic Value and Immunotherapeutic Characteristics of GFPT2 in Pan-cancer.

IF 1.6 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Yiyi Zhou, Yuchao Dong
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引用次数: 0

Abstract

Purpose: The purpose of this study is to investigate the underlying relationship of diagnosis and therapy between glutamine-fructose-6-phosphate transaminase 2 (GFPT2) and various cancers.

Methods: The Cancer Genome Atlas (TCGA) database was utilized to get gene expression RNAseq and clinical data for 33 tumors. The immunotherapeutic cohorts, including GSE35640, GSE78220, GSE67501, GSE181815, and IMvigor210, were derived from the Gene Expression Omnibus database (GEO) and a previously released article. Differential expression analysis of GFPT2 was performed using several clinical factors, and prognostic analysis was performed using Cox proportional hazard regression. In addition, the Cell type Identification By Estimating Relative Subsets Of RNA transcripts (CIBERSORT) and the Estimation of STromal and Immune cells in MAlignant Tumor tissues utilizing Expression data (ESTIMATE) algorithms were used to investigate the connection between GFPT2 and the tumor microenvironment. This approach additionally incorporated dynamic immunological indicators, such as tumor mutational burden (TMB) and microsatellite instability (MSI). In addition, a correlation between GFPT2 expression and the effectiveness of anticancer drugs was plotted for discussion.

Results: GFPT2 expression significantly differed in 11 out of 33 cancers. Although the distinct correlation between GFPT2 expression and clinical parameters had no wide distribution in pan-cancer, it demonstrated the potential prognostic validity of gene expression. GFPT2 demonstrated a strong correlation with immune infiltration, immune modulators, and immunerelated biomarkers. Furthermore, a variance analysis demonstrated a significant relationship between GFPT2 and the efficacy of immunotherapy. In addition, GFPT2 was associated with increased sensitivity of drugs such as Olaparib and Lenvatinib and decreased sensitivity of drugs such as Nilotinib.

Conclusion: Collectively, GFPT2 is potentially useful as a biomarker for prognostic prediction and immune infiltration in a variety of malignancies ,and could lead to exciting new approaches to personalized oncotherapy.

泛癌症中 GFPT2 的预后价值和免疫治疗特征
目的:本研究旨在探讨谷氨酰胺-6-磷酸果糖转氨酶2(GFPT2)与各种癌症的诊断和治疗之间的潜在关系:方法:利用癌症基因组图谱(TCGA)数据库获取33种肿瘤的基因表达RNAseq和临床数据。免疫治疗队列(包括 GSE35640、GSE78220、GSE67501、GSE181815 和 IMvigor210)来自基因表达总库数据库(GEO)和之前发布的一篇文章。利用几种临床因素对 GFPT2 进行了差异表达分析,并利用 Cox 比例危险回归进行了预后分析。此外,研究人员还使用了 "通过估算RNA转录本相对子集进行细胞类型鉴定(CIBERSORT)"和 "利用表达数据估算恶性肿瘤组织中的STromal和免疫细胞(ESTIMATE)"算法来研究GFPT2与肿瘤微环境之间的联系。这种方法还纳入了动态免疫学指标,如肿瘤突变负荷(TMB)和微卫星不稳定性(MSI)。此外,还绘制了 GFPT2 表达与抗癌药物疗效之间的相关性图,以供讨论:结果:33 种癌症中有 11 种癌症的 GFPT2 表达存在明显差异。尽管 GFPT2 表达与临床参数之间的明显相关性在泛癌症中并没有广泛分布,但它显示了基因表达对预后的潜在有效性。GFPT2 与免疫浸润、免疫调节剂和免疫相关生物标记物有很强的相关性。此外,一项方差分析显示,GFPT2 与免疫疗法的疗效有显著关系。此外,GFPT2还与奥拉帕利(Olaparib)和伦伐替尼(Lenvatinib)等药物的敏感性增加以及尼罗替尼(Nilotinib)等药物的敏感性降低有关:总之,GFPT2有可能成为多种恶性肿瘤预后预测和免疫渗透的生物标志物,并可能为个性化肿瘤治疗带来令人兴奋的新方法。
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来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
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