Identification of uridine phosphatase 1 as a potential therapeutic target in gastric cancer by integrated bioinformatics analysis and experimental validation.

IF 2.2 4区 医学 Q3 ONCOLOGY
Yongfeng Wang, Yichen Feng, Chengzhang Zhu, Ling Guan, Shengfeng Wang, Anqi Zou, Miao Yu, Yuan Yuan, Hui Cai
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引用次数: 0

Abstract

Gastric cancer remains a major global health challenge, and its early diagnosis and prognosis prediction pose significant challenges to the current clinical treatment of gastric cancer. Finding gastric cancer biomarkers is essential to comprehending its pathophysiology and creating novel targeted treatments. Following the acquisition and processing of the gastric cancer sample, the single-cell RNA sequencing data, monocyte subpopulation characterization, and cell type identification were performed. Key gene modules linked to gastric-cancer-related monocytes were identified using high-dimensional weighted gene co-expression network analysis. Machine-learning diagnostic models were created utilizing the discovered gastric-cancer-related monocyte-related genes (GCRMORGs). A prognostic model was developed with the uridine phosphatase 1 (UPP1)-related risk scores and verified in separate cohorts, and multiple immunological analyses were performed. Finally, using various experimental assays, we thoroughly investigated the function of the UPP1 gene in gastric cancer. Gastric cancer samples showed a distinct immune milieu topography with an abundance of monocytes. Eventually, 32 GCRMORGs were identified. Diagnostic models demonstrated a high degree of efficacy in differentiating between patients with gastric cancer and the control group. The prognostic model showed significant predictive value for gastric cancer patients' survival. At the same time, we have confirmed from experimental perspectives that a poor prognosis for patients is indicated by a high expression of UPP1 in gastric cancer tissue. Important monocyte subpopulations associated with gastric cancer samples were detected in our investigation. The prognosis of patients with gastric cancer can be predicted using a predictive model based on 32 GCRMORGs. In addition, focusing on UPP1 in gastric cancer may yield novel therapeutic targets and approaches.

尿苷磷酸酶1作为胃癌潜在治疗靶点的综合生物信息学分析和实验验证。
胃癌仍然是全球健康面临的重大挑战,其早期诊断和预后预测对当前胃癌的临床治疗提出了重大挑战。发现胃癌生物标志物对于理解其病理生理学和创造新的靶向治疗方法至关重要。在获取和处理胃癌样本后,进行单细胞RNA测序数据、单核细胞亚群表征和细胞类型鉴定。使用高维加权基因共表达网络分析确定了与胃癌相关单核细胞相关的关键基因模块。利用发现的胃癌相关单核细胞相关基因(GCRMORGs)创建机器学习诊断模型。利用尿苷磷酸酶1 (UPP1)相关风险评分建立预后模型,并在单独的队列中进行验证,并进行多项免疫学分析。最后,通过各种实验分析,我们深入研究了UPP1基因在胃癌中的功能。胃癌标本表现出独特的免疫环境地形和丰富的单核细胞。最终鉴定出32个GCRMORGs。诊断模型在鉴别胃癌患者和对照组方面显示出高度的有效性。该预后模型对胃癌患者的生存有显著的预测价值。同时,我们从实验角度证实,胃癌组织中UPP1的高表达预示着患者预后不良。在我们的研究中发现了与胃癌样本相关的重要单核细胞亚群。基于32个GCRMORGs的预测模型可以预测胃癌患者的预后。此外,关注胃癌中的UPP1可能会产生新的治疗靶点和方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Anti-Cancer Drugs
Anti-Cancer Drugs 医学-药学
CiteScore
3.80
自引率
0.00%
发文量
244
审稿时长
3 months
期刊介绍: Anti-Cancer Drugs reports both clinical and experimental results related to anti-cancer drugs, and welcomes contributions on anti-cancer drug design, drug delivery, pharmacology, hormonal and biological modalities and chemotherapy evaluation. An internationally refereed journal devoted to the fast publication of innovative investigations on therapeutic agents against cancer, Anti-Cancer Drugs aims to stimulate and report research on both toxic and non-toxic anti-cancer agents. Consequently, the scope on the journal will cover both conventional cytotoxic chemotherapy and hormonal or biological response modalities such as interleukins and immunotherapy. Submitted articles undergo a preliminary review by the editor. Some articles may be returned to authors without further consideration. Those being considered for publication will undergo further assessment and peer-review by the editors and those invited to do so from a reviewer pool.
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