Cell cycle traverse rate predicts long-term outcomes in a multi-institutional cohort of patients with triple-negative breast cancer

Background Ki67 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 object...

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Published in:BJC reports 2024-11, Vol.2 (1), p.87-10, Article 87
Main Authors: Bhattarai, Shristi, Rupji, Manali, Chao, Hsueh-ping, Xu, Qi, Saini, Geetanjali, Rida, Padmashree, Aleskandarany, Mohammed A., Green, Andrew R., Ellis, Ian O., Janssen, Emiel A., Jonsdottir, Kristin, Rakha, Emad, Kowalski, Jeanne, Aneja, Ritu
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Biomedical and Life Sciences
Biomedicine
Cancer Research
Oncology
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creator Bhattarai, Shristi
Rupji, Manali
Chao, Hsueh-ping
Xu, Qi
Saini, Geetanjali
Rida, Padmashree
Aleskandarany, Mohammed A.
Green, Andrew R.
Ellis, Ian O.
Janssen, Emiel A.
Jonsdottir, Kristin
Rakha, Emad
Kowalski, Jeanne
Aneja, Ritu
description Background Ki67 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). Methods We 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. Results TNBC shows a significantly lower median CCTR compared to luminal A ( p  
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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). Methods We 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. Results TNBC shows a significantly lower median CCTR compared to luminal A ( p  &lt; 0.01), luminal B ( p  &lt; 0.01), and HER2+ samples ( p  &lt; 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. Conclusions Collectively, 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.</description><identifier>ISSN: 2731-9377</identifier><identifier>EISSN: 2731-9377</identifier><identifier>DOI: 10.1038/s44276-024-00097-z</identifier><identifier>PMID: 39537757</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>Biomedical and Life Sciences ; Biomedicine ; Cancer Research ; Oncology</subject><ispartof>BJC reports, 2024-11, Vol.2 (1), p.87-10, Article 87</ispartof><rights>The Author(s) 2024</rights><rights>2024. 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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). Methods We 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. Results TNBC shows a significantly lower median CCTR compared to luminal A ( p  &lt; 0.01), luminal B ( p  &lt; 0.01), and HER2+ samples ( p  &lt; 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. 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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). Methods We 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. Results TNBC shows a significantly lower median CCTR compared to luminal A ( p  &lt; 0.01), luminal B ( p  &lt; 0.01), and HER2+ samples ( p  &lt; 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. 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subjects Biomedical and Life Sciences
Biomedicine
Cancer Research
Oncology
title Cell cycle traverse rate predicts long-term outcomes in a multi-institutional cohort of patients with triple-negative breast cancer
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