Abstract 4095: Development of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for patients with metastatic breast cancer
Authors: Sun Yuliang , Meissner Tobias , Elsey Rachel , Theisen Leah , Jones Jason , Williams Casey 
Published: June 2022

Abstract
Background: Tumor complexity and heterogeneity require matching of actionable genomic alterations with available therapy to increase response rates and prolong survival in patients with cancer. It has been a long-standing challenge for treating oncologists to select an effective patient-specific therapeutic strategy due to the molecular rationale, disease relevance, patient-specific issues, including patient access to treatments. We have developed a set of molecular and clinical evidence-based criteria as an algorithm for ranking therapeutic strategies in order to deliver optimal care and improve outcomes in patients with metastatic malignancies.
Methods: Patients included in the analysis received comprehensive genomic profiling (CGP) for selected biomarkers. CGP results of 50 patients with stage IV tumors were reviewed by our multidisciplinary Molecular Tumor Board (MTB), after which treatment recommendations were generated based on molecular matching only (Cohort 1). CGP results of the other current 29 patients with stage IV breast cancer were reviewed by MTB, and therapeutic recommendations were provided with ranking scores calculated by our molecular and clinical evidence-based algorithm with the criteria not only focusing on molecular matching, but also including disease relevance, patient-specific clinical considerations and treatment availability as weighting factors (Cohort 2). The matching rates from recommendations and treatment outcomes of the two cohorts were then assessed.
Results: In Cohort 1, of the 50 patients, 34 patients (68%) were initiated with personalized therapeutic plans based on molecular matching that were recommended by our MTB. The other 16 patients were not treated with molecular matching therapeutic plans recommended by MTB, as the results of treating oncologists’ choices, treatment availability or patient preference. Patients were followed and outcomes were then evaluated. Thirteen patients (38.2% of 34 patients) achieved progression-free survival (PFS) at 12-week time point, and 6 patients achieved PFS (including stable disease, N=4 and partial response, N=2) at 6-month time point. The other 21 patients (61.8% of 34 patients) could not be assessed due to disease progression, treatment termination per drug toxicity or death before the follow-up time point. Cohort 2 is ongoing, the results of which will be presented in the meeting.
Conclusion: Our novel molecular and clinical evidence-based algorithm may be used to support oncologists decision-making to utilize the most clinically appropriate and effective therapeutic options. Additional studies with larger sample sizes in different type of solid tumors are planned in order to determine a clinically and statistically relevant range of score for the treatment recommendations with optimal clinical outcomes.
Citation Format: Yuliang Sun, Tobias Meissner, Rachel Elsey, Leah Theisen, Jason Jones, Casey Williams. Development of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for patients with metastatic breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4095.