Serial multiomic analysis in advanced breast cancer: A novel platform to inform therapeutic decisions

e13001 Background: We designed and implemented a platform wherein patients with metastatic treatment-refractory cancer would receive individually tailored treatment informed by multi-omic data and iteratively adapted in real-time. Here we describe the workflow of this platform and quantify operational characteristics for a metastatic breast cancer cohort. Methods: Participants with metastatic breast cancer progressing after standard-of-care therapy were enrolled. Sites demonstrating disease progression were targeted for biopsy. Resultant tissue was analyzed by a next-generation sequencing (NGS) solid tumor panel, whole exome sequencing, whole transcriptomic sequencing, multiplex protein analysis of a panel of cancer-relevant proteins and phosphoproteins, and focused immunohistochemistry (IHC) and fluorescence in-situ hybridization (FISH) analysis. Results: Between 1/1/2017 to 12/31/2021, 74 participants were consented and 55 were enrolled. Median age at enrollment was 54 years, most were ECOG 0-1, and received a median of 2 lines of therapy in the metastatic setting. There were 95 biopsies collected from 55 individual participants and analytics were successfully generated in 94% of the cases. At the provider’s request, an integrated clinical, molecular, and cancer biology tumor board (TB) was convened for 25 participants. A total of 21 participants received matched therapy based on clinical parameters coupled to a consideration of biologically informed therapeutic vulnerabilities and 6 had a PFS2/PFS1 > 1.3. Twenty-one participants had a median of 2 repeat progression biopsies (range 2-5) and new alterations with potential therapeutic implications were identified. Repeat biopsies could have led to a new treatment in 11 of the participants, though only 3 received a therapy recommended by the tumor board owing to either rapid disease progression, clinical deterioration, or lack of access to drug. Conclusions: We demonstrated the practical feasibility and initial operating characteristics of a platform designed to comprehensively understand and integrate the clinical and molecular characteristics of a cohort with metastatic progressive breast cancer as they evolve on therapy and to use this information to deliver iteratively tailored therapy in real time. Further, clinical responses were observed in a subset of participants. These findings suggest an opportunity to incorporate this platform earlier in a disease course or to design adaptive clinical trials with access to therapies aimed at targeting new biological alteration.