Abstract PO2-27-05: Composite biomarkers for the prediction of progression-free survival with CDK4/6 inhibitors in metastatic HR+/HER2- breast cancer

Abstract

Abstract CDK4/6 inhibitors are widely used in combination with endocrine therapy in the treatment of HR+/HER2- metastatic breast cancer. Generally the CDK4/6 inhibitors lead to a doubling of progression-free survival (PFS) over single agent endocrine therapy. In spite of a known mechanism of action, biomarkers to define the duration of response to CDK4/6 inhibitors with either aromatase inhibitors (AI) or fulvestrant (FUL) remain lacking. A cohort of over 300 patients receiving standard of care CDK4/6 inhibitor combination therapy for metastatic disease were consented for participation (NCT04526587). The duration of PFS in both AI and FUL treated sub-groups were comparable to that observed in randomized clinical trials. In this cohort progesterone receptor-status (HR 0.70, p=0.0123), visceral disease (HR 1.55, p=0.0013), prior endocrine therapy (HR 2.34, p< 0.001), and type of endocrine therapy (HR 2.16, p< 0.001) were associated with duration of PFS. To develop biomarkers, gene expression analyses was performed on 313 tumor samples representing over 200 individual patients. Focusing on the pre-treatment metastatic biopsy, established signatures associated with prognosis in HR+/HER2- breast cancer were employed to determine association with response to combination therapy in the metastatic setting. Proliferation-associated signatures were associated with shorter PFS. For example, an established RB loss signature was associated with PFS in both AI (HR 1.9, p=0.009) and FUL (HR 2.8, p=0.007) treated patients. Clinically employed signatures (e.g. OncotypeDx and Mammaprint) harbored variable associations with outcomes. Random Survival Forest feature selection was applied to individual and combined prognostic signatures. This approach resulted in a potent classifier for progression-free survival (HR 10, p< 1E-20). To enable applicability to different manifestations of disease, significant clinical pathological variables were incorporated into the model so that there was equivalent performance in AI and FUL treated patients for prediction of PFS. This predictive algorithm was also strongly associated with overall survival (HR 4.6, p=2.7E-8). Ongoing studies are evaluating the algorithms prospectively in NCT04526587. Citation Format: Agnieszka Witkiewicz, Jianxin Wang, Erik Knudsen, Ellis Levine, Tracey O'Connor. Composite biomarkers for the prediction of progression-free survival with CDK4/6 inhibitors in metastatic HR+/HER2- breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-27-05.