Abstract B08: Identifying high-risk triple negative breast cancer patients using a novel cycling kinetics metric

Abstract

Abstract Background Ki67 Index (KI) and Mitotic Index (MI) are proliferation markers with established prognostic value in breast cancer. These indices are evaluated individually and on disparate measurement scales; they thereforefail to capture information about cell cycling kinetics of proliferating cells. Within the triple negative (TNBC) subtype , we rationally integrate the two markers to identify high-risk patients whose proliferative cells exhibit fast cycling kinetics. Methods Pathology reports of breast cancer patients (n=10,504 from Northside Hospital, Atlanta and n=1560 from Nottingham Hospital, UK) were retrospectively analyzed for mitotic scores, KI and clinical outcomes. Mitotic counts in 267 H&E-stained breast carcinoma samples were evaluated by two pathologists to transform mitotic scores into %MI based on cellularity. %MI: %KI ratio was defined as the Ki67-Adjusted Mitotic Score (KAMS), which reflects cycling kinetics of proliferative cells. Ability of KAMS to stratify triplenegative breast cancers (TNBCs) was tested in three cohorts who received only adjuvant chemotherapy (n=478 from Northside Hospital, USA; n=322 from Nottingham Hospital, UK, and n=108 from OlabisiOnabanjo University, Nigeria). Stratification of KAMS, KI and MI were performed onthe thresholdsthat produced the lowest AIC (best model fit).Slow-cycling and fast-cycling TNBC subgroups from Nottingham Hospital were analyzed for biomarker expression. Results Kaplan-Meier survival analyses, AIC andc2 values showed that KAMS-based stratification of TNBCs into two subgroups was superior to that by either KI or MI, regardless of hospital, and KAMS retained its significance in multivariate analyses, controlling for stage and age. Fast-cycling TNBCs have poorer prognosis than slow-cycling TNBCs, perhaps due to higher intratumoral heterogeneity in fast cycling tumors. Fast-cycling TNBCs showed high expression of proteins implicated in DNA damage response, sumoylation, EGFR signaling and metastasis. By contrast, slow-cycling TNBCs showed extensive chromatin modification. Conclusion KAMS quantifies cell cycling kinetics, stratifies TNBCs and yields new risk-predictive information that is not revealed by either KI or MI. KAMS reveals the underlying heterogeneity in cycling kinetics among TNBCs and helps identify TNBCs who might benefit from treatments that target the cell cycle machinery. Citation Format: Sergey Klimov, Guanhao Wei, Andrew Green, Mohammed Aleskandarany, Emad Rakha, Ian Ellis, Guilherme Cantuaria, Ayodeji O. Agboola, Michelle Reid, Li Xiaoxian, Rida C. G. Padmashree, Remus Osan, Ritu Aneja. Identifying high-risk triple negative breast cancer patients using a novel cycling kinetics metric. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B08.