Development of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for patients with ovarian carcinoma (157)

Abstract

<b>Objectives:</b> Genomic sequencing of tumors is done frequently in oncology due to tumor complexity and heterogeneity, which necessitate matching actionable genomic alterations with available therapies for improved outcomes. Molecular rationale, the robustness of disease-specific data, patient-specific supportive care, and access to treatments must all be taken into account in order to select an effective regimen. However, as the molecular proteomics analysis of tumors is performed earlier in the disease course and the number of targeted therapies rises, it becomes increasingly difficult to effectively and efficiently choose the most appropriate treatment. We have developed a set of molecular and clinical evidence-based criteria to rank therapeutic strategies to deliver optimal care and improve outcomes. <b>Methods:</b> Patients included in the analysis received comprehensive genomic profiling (CGP), including blood/tissue DNA sequencing, transcriptome profiling, and immunohistochemistry for selected biomarkers. CGP results of 50 patients (from our clinical database) with previously treated, stage IV solid 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 an additional 50 patients with ovarian carcinoma will be reviewed by MTB, and therapeutic recommendations (including standard of care therapies, clinical trials, and offlabel drugs) will be provided with ranking scores calculated by our 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 will be assessed. <b>Results:</b> In Cohort 1, of the 50 patients, 34 patients (68%) were initiated with personalized, therapeutic plans predominantly based on molecular matching that was recommended by our MTB. The other 16 patients were not treated with molecular matching therapeutic plans recommended by MTB as a result 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) (including stable disease, <i>n</i>=6, and partial response, <i>n</i>=7) at 12 weeks, and six patients achieved PFS (including stable disease, <i>n</i>=4, and partial response, <i>n</i>=2) at six months. 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 at the meeting. <b>Conclusions:</b> Our novel molecular and clinical evidence-based algorithm may be used to support clinicians' decision-making to utilize the most evidence-based and effective therapeutic options. Additional studies with larger sample sizes in different types of solid tumors are planned in order to determine a clinically and statistically relevant range of scores for the treatment recommendations with optimal clinical outcomes.