ArticleBJC reports2024
Cell cycle traverse rate predicts long-term outcomes in a multi-institutional cohort of patients with triple-negative breast cancer.
Article in BJC reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
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Who cites it
3 citing papers in PubMed.
- Patient-specific modeling of G2/M cell cycle dynamics reveals prognostic dynamical regimes driven by copy number alterations.NPJ systems biology and applications · 2026Article
- Article
- Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images.Cancers · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
backgroundKi67 index (KI) and mitotic index (MI) are proliferation markers with established prognostic value in breast carcinomas. While KI is evaluated immunohistochemically and reported as a percentage, MI is determined visually and reflects total mitotic cells in 10 high-power fields. Our objective was to integrate KI and MI into a novel metric; the cell cycle traverse rate (CCTR). Given the lack of prognostic and predictive biomarkers in TNBC, we sought to assess the potential of CCTR as a risk-stratification tool for chemotherapy-treated TNBC patients from two independent cohorts: the Nottingham group (n = 124) and the Norway group (n = 71).
methodsWe evaluated the ability of CCTR to predict survival after adjuvant chemotherapy for TNBC patients (n = 195) in two independent cohorts. Using immunohistochemistry and RNA sequencing, we determined the differences in immunohistochemical biomarkers, gene ontologies, molecular pathways and immune cell fractions based on CCTR.
resultsTNBC shows a significantly lower median CCTR compared to luminal A (p < 0.01), luminal B (p < 0.01), and HER2+ samples (p < 0.01). CCTR outperformed both KI and MI in effectively risk-stratifying TNBC patients suggesting that combining KI and MI into a single metric, namely CCTR, could serve as a superior prognostic marker for Breast Cancer Specific Survival (BCSS) (p = 0.041). CCTR-high group exhibited enriched expression of various oncogenic signatures, including angiogenesis, epithelial-to-mesenchymal transition (EMT), Hedgehog signaling, hypoxia, Notch signaling, PI3K-AKT-mTOR signaling, TGFβ signaling, p53 signaling, and TNFα signaling via NFκB. These findings suggest the potential involvement of these pathways in the aggressiveness and clinical outcomes of TNBC patients.
conclusionsCollectively, these findings suggest that CCTR offers superior predictive information compared to KI and MI alone with respect to long-term outcomes from adjuvant chemotherapy in patients with TNBC that may guide treatment decision making.
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Registered trials
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