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Related Concept Videos

Metastasis02:30

Metastasis

Metastasis is the spread of cancer cells from the original site to distant locations in the body. Cancer cells can spread via blood vessels (hematogenous) as well as lymph vessels in the body.
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...

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Related Experiment Video

Updated: Jun 16, 2026

Neutrophil Extracellular Traps Generated by Low Density Neutrophils Obtained from Peritoneal Lavage Fluid Mediate Tumor Cell Growth and Attachment
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Identification of neutrophil extracellular traps (NETs)-related molecular clusters in prostate cancer: Implications

Wen-Cai Zheng1, Fei Lin1, Qian-Ren-Shun Qiu1

  • 1Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.

International Immunopharmacology
|December 29, 2024
PubMed
Summary

This study identifies neutrophil extracellular trap (NETs)-related gene clusters and develops a prognostic model to predict biochemical recurrence in prostate cancer (PCa). The model accurately identifies high-risk patients and suggests chemotherapy benefits for low-risk individuals.

Keywords:
Biochemical recurrenceNeutrophil extracellular trapsProstate cancerTumor immune microenvironment

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Area of Science:

  • Oncology
  • Immunology
  • Genomics

Background:

  • Neutrophil extracellular traps (NETs) play a role in cancer progression.
  • Predictive biomarkers for prostate cancer (PCa) recurrence are crucial for treatment decisions.

Purpose of the Study:

  • To identify NETs-related molecular clusters in PCa.
  • To develop a novel gene signature for predicting biochemical recurrence in PCa.
  • To evaluate the clinical utility of the prognostic model.

Main Methods:

  • Consensus clustering of transcriptome data from TCGA and GEO databases.
  • Univariate Cox and Lasso regression for prognostic model construction.
  • Internal and external validation of the model, including preliminary experimental validation of ANXA3.

Main Results:

  • Two distinct NETs-related clusters were identified with significant differences in clinical features and recurrence.
  • A novel NETs-related prognostic model demonstrated strong predictive performance across multiple cohorts (AUCs ranging from 0.696 to 0.827).
  • The model identified high-risk patients and suggested potential chemotherapy benefits for low-risk patients; ANXA3 inhibition reduced PCa cell invasion, migration, and proliferation.

Conclusions:

  • A novel NETs-related prognostic model for PCa has been developed.
  • This model exhibits excellent predictive performance for biochemical recurrence and chemotherapy efficacy.
  • The findings offer potential for improved risk stratification and personalized treatment strategies in PCa.