ArticleNPJ breast cancer2025
Prognostic value of nuclear features based on tumor-associated collagen signatures in breast cancer.
Article in NPJ breast cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- High-Density Type I Collagen Promotes IFN-γAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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Authors and funding
17 authors.
Funding
Abstract
The prognostic value of nuclear features based on tumor-associated collagen signatures (TCMF2) is still unclear. In this paper, we extracted and quantified the TCMF2 from 941 invasive breast cancer patients in H&E images. The least absolute shrinkage and selection operator regression were used to build a TCMF2-score. The univariate and multivariate Cox proportional hazards regression analyses showed that the TCMF2-score is an independent prognostic factor with an advantage in the prognosis of early-stage invasive breast cancer. When the TCMF2, the microscopic features of TACS-based collagen (TCMF1) and the tumor-associated collagen signatures (TACS) were combined, they showed better accuracy in patient stratification than the clinical model (CLI) or the model based on TACS + TCMF1. Our results identify that TCMF2 improves the performance of the TACS-based prediction model, and the TACS-based full model (TACS + TCMF1 + TCMF2) may help us stratify patients more accurately and provide more appropriate adjuvant therapy.
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Registered trials
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