Evidence map›Paper›PMID 41107976›Full record

ReviewBreast cancer research : BCR2025

The role of NETosis in breast cancer: mechanistic insights and biomarker potential.

Fahimeh Norouzi, Pooya Eini, Safa Tahmasebi

Abstract readReview
In one paragraph

Review in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

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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

3 authors.

Fahimeh Norouzi *Department of Hematology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Pooya Eini *Toxicological Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Safa TahmasebiStudent Research Committee, Department of Immunology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. safa.tahmasebi@sbmu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neutrophil extracellular trap formation (NETosis), previously described as an effector host defense mechanism, is more frequently associated with cancer-driven inflammation and tumor development. In the case of breast cancer, NETosis assists with several oncogenic processes, including epithelial-mesenchymal transition, immune evasion, organotropic metastasis, angiogenesis, and resistance to therapy. The current study summarizes the evidence of the mechanistic role of NETs in breast cancer and their potential to act as a diagnostic, prognostic, or therapeutic biomarker. Like many other promising candidates for novel prognostic or diagnostic biomarkers, citrullinated histone H3 (citH3), myeloperoxidase-DNA (MPO-DNA) complexes, and circulating cell-free DNA (cfDNA) need further validation to be functional. However, there is some evidence suggesting clinical relevance. Like many candidate therapeutic indices, several therapies are exploring targeting NETosis, including deoxyribonuclease I (DNase I) and peptidyl arginine deiminase 4 (PAD4) inhibitors, as a clinical intervention. However, methodological differences across studies and a lack of standardized detection of NETs are likely impeding future findings. Future insight into the efficiency of detection methods and consistency of experimental design will be beneficial for transferring NETosis to the clinic.

Indexed as

Biomarkers, TumorBreast NeoplasmsExtracellular TrapsFemaleHistonesHumansNeutrophilsPeroxidasePrognosisProtein-Arginine Deiminase Type 4Biomarkers, TumorHistonesPADI4 protein, humanPeroxidaseProtein-Arginine Deiminase Type 4BiomarkersBreast cancerMetastasisNeutrophil extracellular traps (NETs)Tumor microenvironment

Identifiers

PMID41107976
PMCPMC12535134

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.