Evidence map›Paper›PMID 39981438›Full record

ArticleFrontiers in molecular biosciences2025

Construction of a circadian rhythm-related gene signature for predicting the prognosis and immune infiltration of breast cancer.

Lin Ni, He Li, Yanqi Cui, Wanqiu Xiong, Shuming Chen, Hancong Huang, Zhiwei Wang, Hu Zhao, Bing Wang

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lin Ni *Department of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
He Li *Department of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Yanqi Cui *Department of Cardiothoracic surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Wanqiu XiongDepartment of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Shuming ChenDepartment of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Hancong HuangDepartment of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Zhiwei WangDepartment of General Surgery, Fuzhou General Teaching Hospital, Fujian University of Traditional Chinese Medicine, 900TH Hospital of Joint Logistics Support Force, Fuzhou, China.
Hu ZhaoDepartment of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.
Bing WangDepartment of General Surgery, Fuzong Clinical Medical College of Fujian Medical University, 900TH Hospital of Joint Logistics Support Force, PLA, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: In this study, we constructed a model based on circadian rhythm associated genes (CRRGs) to predict prognosis and immune infiltration in patients with breast cancer (BC). Materials and methods: By using TCGA and CGDB databases, we conducted a comprehensive analysis of circadian rhythm gene expression and clinicopathological data. Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. On this basis, a circadian gene prediction model about BC prognosis was constructed and validated. We also evaluated the association of the model's risk score with immune cells and immune checkpoint genes, and analyzed prognostic genes and drug sensitivity in this model. Results: We screened 62 DEGs, including 30 upregulated genes and 32 downregulated genes, and performed GO and KEGG analysis on them. The above 62 DEGs were included in Cox analysis, LASSO regression, Random Forest and SVMV-RFE, respectively, and then the intersection was used to obtain 5 prognostic related characteristic genes (SUV39H2, OPN4, RORB, FBXL6 and SIAH2). The Risk Score of each sample was calculated according to the expression level and risk coefficient of 5 genes, Risk Score= (SUV39H2 expression level ×0.0436) + (OPN4 expression level ×1.4270) + (RORB expression level ×0.1917) + (FBXL6 expression level ×0.3190) + (SIAH2 expression level × -0.1984). Conclusion: SUV39H2, OPN4, RORB and FBXL6 were positively correlated with Risk Score, while SIAH2 was negatively correlated with Risk Score. The above five circadian rhythm genes can construct a risk model for predicting the prognosis and immune invasion of BC.

Indexed as

a risk modelbreast cancercircadian rhythmmachine learningpredict prognosis

Identifiers

PMID39981438
PMCPMC11839441

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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.