Evidence map›Paper›PMID 38601669›Full record

ArticleHeliyon2024

Identification of cuproptosis-related miRNAs in triple-negative breast cancer and analysis of the miRNA-mRNA regulatory network.

Yitao Wang, Jundan Wang, Jing Jiang, Wei Zhang, Long Sun, Qidong Ge, Chao Li, Xinlin Li, Xujun Li, Shenghong Shi

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Elucidating the evolving role of cuproptosis in breast cancer progression.International journal of biological sciences · 2024
    Review
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

10 authors at 2 institutions in 1 country.

Yitao WangHealth Science Center, Ningbo University, Ningbo, 315211, China.
Jundan WangHealth Science Center, Ningbo University, Ningbo, 315211, China.
Jing JiangDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Wei ZhangDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Long SunDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Qidong GeDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Chao LiDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Xinlin LiDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Xujun LiDepartment of Breast Surgery, Ningbo No.2 Hospital, Ningbo, 315010, China.
Shenghong ShiHealth Science Center, Ningbo University, Ningbo, 315211, China.
Ningbo No. 2 Hospital · CNNingbo University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The close association between cuproptosis and tumor immunity in triple-negative breast cancer (TNBC) allows its monitoring for predicting the prognosis of patients with TNBC. Nevertheless, the biological function and prognostic value of cuproptosis-related miRNAs and their target genes have not been reported. Purpose: To construct the miRNA and mRNA-based risk models associated with cuproptosis for patients with TNBC. Methods: Comparison of expression levels for genes associated with cuproptosis was executed between patients in the normal individuals and the TCGA-TNBC cohort. Conducting differential analysis resulted in the identification of differentially expressed miRNA (DE-miRNAs) and differentially expressed genes (DEGs) between the TNBC and Control samples. Screening for prognostic miRNAs and biomarkers involved employing univariate Cox analysis and least absolute shrinkage and selection operator regression analyses. These methods were utilized to construct risk models aimed at predicting the survival of patients with TNBC. Based on the median value of risk scores, patients were then stratified into low- and high-risk groups. Functional enrichment analysis was employed to explore the potential function and pathways of prognostic genes. Additionally, independent prognostic analysis was performed through univariate and multivariate Cox regression. Immune infiltration analysis was performed to examine disparities in the infiltration of immune cells between the two risk groups. Finally, the prognostic gene expression was mined in key cell types of TNBC. Results: We obtained 5213 DEGs and 204 DE-miRNAs related to cuproptosis between TNBC and Control samples. Five prognostic miRNAs (miR-203a-3p, miR-1277-3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were closely associated with TNBC. Significant differences in the functions of prognostic genes between the two risk groups were observed, encompassing adipogenesis, inflammatory response, and hormone metabolic process. The prognostic gene regulatory network revealed that miR200C-3p regulated ZFPM2 and CFL2, and miR-1277-3p regulated BMP2 and RORA. A nomogram was created based on riskScore, cancer status, and pathologic stage to predict 1/3/5-year survival of patients with TNBC. Immune infiltration analysis indicated that the immune microenvironment may be associated with the progression of TNBC. Interestingly, prognostic genes exhibited higher expression levels in T cells, fibroblasts, endothelial cells, and monocytes compared to other cells. Conclusions: Five prognostic miRNA (miR-203a-3p, miR-1277-3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were significantly associated with TNBC, it provides new therapeutic targets for the treatment and prognosis of TNBC.

Indexed as

BioinformaticsBiomarkerCuproptosis-related genesPrognosisSingle-cell RNA sequencing

Identifiers

PMID38601669
PMCPMC11004712
OpenAlexW4393238060

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.