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

Shristi Bhattarai; Manali Rupji; Hsueh-Ping Chao; Qi Xu; Geetanjali Saini; Padmashree Rida; Mohammed A Aleskandarany; Andrew R Green; Ian O Ellis; Emiel A Janssen; Kristin Jonsdottir; Emad Rakha; Jeanne Kowalski; Ritu Aneja

doi:10.1038/s44276-024-00097-z

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

BJC Rep. 2024 Nov 13;2(1):87. doi: 10.1038/s44276-024-00097-z.

Authors

Shristi Bhattarai^{1

2}, Manali Rupji³, Hsueh-Ping Chao⁴, Qi Xu⁴, Geetanjali Saini⁵, Padmashree Rida⁶, Mohammed A Aleskandarany⁷, Andrew R Green⁸, Ian O Ellis⁸, Emiel A Janssen⁹, Kristin Jonsdottir⁹, Emad Rakha¹⁰, Jeanne Kowalski¹¹, Ritu Aneja^{12

13}

Affiliations

¹ Department of Molecular and Cellular Biology, Kennesaw State University, Kennesaw, GA, USA.
² Department of Biology, Georgia State University, Atlanta, GA, USA.
³ Biostatistics Shared Resource, Winship Cancer Institute, Emory University, Atlanta, GA, USA.
⁴ Department of Oncology and Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX, USA.
⁵ Department of Nutrition Sciences, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, USA.
⁶ Novazoi Theranostics, Salt Lake City, UT, USA.
⁷ Division of Biomedical and Forensic Sciences, School of Human Science, University of Derby, Derby, UK.
⁸ Nottingham Breast Cancer Research Centre, Academic Unit for Translational Medical Sciences, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK.
⁹ Department of Pathology, Stavanger University Hospital, Stavanger, Norway.
¹⁰ Nottingham Breast Cancer Research Centre, Academic Unit for Translational Medical Sciences, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK. [email protected].
¹¹ Department of Oncology and Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX, USA. [email protected].
¹² Department of Biology, Georgia State University, Atlanta, GA, USA. [email protected].
¹³ Department of Nutrition Sciences, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, USA. [email protected].

Abstract

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 < 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.

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.

Grants and funding

R01CA239120/National Cancer Institutes of Health