Evidence map›Paper›PMID 41372399›Full record

ArticleScientific reports2025

E2F transcription factors as multimodal biomarkers for pan-cancer management.

Shaobo Yang, Kai Li, Yong Suo, Zhe Zhang, Houyuan Chen, Yuda Lin, Chong Fu, Yunkai Qie, Chong Shen, Hailong Hu

Abstract read
In one paragraph

Article in Scientific reports, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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

10 authors.

Shaobo Yang *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Kai Li *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Yong Suo *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Zhe ZhangDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Houyuan ChenDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Yuda LinDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Chong FuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Yunkai QieDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China.
Chong ShenDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China. shenchong@tmu.edu.cn.
Hailong HuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China. huhailong@tmu.edu.cn.

Funding

Scientific Research Project of Tianjin Municipal Education Commission 2022ZD069
6 · The paper itself

Abstract

Early 2 factor (E2F) genes are transcription factors that interact with many DNAs and proteins. Studies have demonstrated that E2F genes can play an oncogenic role in different cancers, yet fewer have explored their effects on pan-cancers. In this study, E2F expression is systematically characterized in multiple types of cancer and its predictive value is determined. Several public databases (GEO, Cancer Genome Atlas (TCGA), cBioPortal, Kaplan-Meier Plotter and PrognoScan) were used to evaluate E2F genes differentially expressed between normal and tumor tissue in pan-cancer, we then investigated the correlation between expression levels of E2F and prognostic factors, clinicopathologic stage, gene mutation types, functional enrichment, drug sensitivity. This study also examined the relationship between microsatellite instability, tumor mutation burden, tumor microenvironment (TME), tumor-related immune checkpoint genes, and immunotherapy response as well as the expression of E2F. Then, we examined potential signaling pathways by analyzing gene set enrichment analyses (GSEAs). Finally, we performed the real-time PCR expression validation and in vitro functional experiments of E2F5. The expression of E2F was upregulated in most tumor tissues compared to adjacent normal tissues. The expression of E2F family genes was highest in E2F4 and lowest in E2F7 in 33 TCGA cancers. E2F gene expression correlates significantly with prognosis in multiple cancer types, as well as RNA-related stemness score and DNA-related stemness score, immune and stromal scores. The E2F genes expression also related with immune subtype in pan-cancer. There existed a positive correlation between E2F2 expression level and Dasatinib sensitivity, negatively related to drug sensitivity of Nelarabine, XK-469, Cyclophosphamide, etc. Pazopanib, Doxorubicin, and Paclitaxel sensitivity was all positively associated with E2F5 expression. E2F genes high expression group showed significant positive or negative enrichment in multiple tumor- and immune-related pathways. In addition, we also discovered that the expression level of nearly all E2F genes was positively or negatively correlated with objective responses to anti-PD-1/PD-L1 across multiple immunotherapy cohort. The immune infiltration analysis of specific bladder cancer further showed the significant relationships between E2Fs copy number variations or mutation status, and infiltration level of different immune cells. Furthermore, differential expression validation and in vitro phenotypic experiments indicated that E2F5 significantly promoted BCa cells proliferation and migration. According to these analysis and validation results, E2F genes are relevant to the occurrence and progression of various cancers, which may be biomarkers for tumor diagnostics and prognosis. The discovery of new therapeutic targets can lead to reshaping TME to promote tumor-suppressive metastasis rather than tumor-friendly metastasis.

Indexed as

Biomarkers, TumorE2F Transcription FactorsNeoplasmsGene Expression Regulation, NeoplasticHumansMicrosatellite InstabilityMutationPrognosisTumor MicroenvironmentBiomarkers, TumorE2F Transcription FactorsE2F familyImmunotherapy responseMulti-omicsPan-cancerPrognosis

Identifiers

PMID41372399
PMCPMC12800231

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.