Evidence map›Paper›PMID 40390494›Full record

ArticleJournal, genetic engineering & biotechnology2025

TIMELESS as a prognostic biomarker and therapeutic target in gastric cancer.

Xiangrong Meng, Qi Sun, Zhongshuang Liu, Shenqi Cao, Chunyang Xu, Longjiang Di, Yan Wu, Wenjing Zhang

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Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiangrong MengDepartment of Laboratory Diagnosis, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Qi SunDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Heilong Jiang University of Chinese Medicine, Harbin, China.
Zhongshuang LiuDepartment of Stomatology, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen, China.
Shenqi CaoAnesthesiology, Harbin Medical University, Harbin, China.
Chunyang XuDepartment of Laboratory Diagnosis, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Longjiang DiSchool of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China.
Yan WuDepartment of Ultrasound, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Wenjing ZhangDepartment of Laboratory Diagnosis, the Second Affiliated Hospital of Harbin Medical University, Harbin, China. Electronic address: wenjingzhang@hrbmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastric cancer (GC), one of the most prevalent malignancies worldwide, is characterized by complex etiological and pathological mechanisms. Emerging evidence on the dysregulation of circadian clock genes has revealed promising opportunities for improving the diagnosis, treatment, and prognosis of patients with GC.

methodsThis study utilized a multifaceted approach combining machine learning algorithms, gene set enrichment analysis, immune infiltration profiling, survival prognosis analysis, drug sensitivity testing, and in vitro experiments to investigate the functional roles of core clock genes in GC.

resultsBy integrating data from The Cancer Genome Atlas, Gene Expression Omnibus datasets, and the National Center for Biotechnology Information database, we identified 29 differentially expressed clock genes in GC. Among these, the application of four distinct machine learning algorithms highlighted TIMELESS (TIM) and BHLHE41 as pivotal genes, with TIM demonstrating notable diagnostic performance (area under the receiver operating characteristic curve = 0.802). Elevated TIM expression was strongly associated with poor clinical prognosis and increased infiltration of immune cells in tumor tissues. Notably, a specific interaction was identified between TIM and the pyroptosis-associated molecule CASP8, indicating a potential synergistic role in GC pathogenesis. Additionally, bortezomib emerged as a potential targeted therapeutic agent capable of modulating TIM activity in GC.

conclusionTIM is identified as a promising diagnostic biomarker and therapeutic target in GC, offering valuable implications for improving patient prognosis and guiding personalized treatment strategies.

Indexed as

Clock geneGastric cancerMachine learningPrognosisPyroptosisTIMELESSTumor-infiltrating

Identifiers

PMID40390494
PMCPMC12433785

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