Abstract
5058 Background: Emerging data suggest differences in the tumor genomic profile of AA compared with CA men with aPC. We hypothesized that there will be significant differences in the tumor genomic landscape between AA and Ca pts as detected by cfDNA CGP. Methods: Pts with aPC and available cfDNA CGP by the Guardant (G360) 73 gene panel were included. In addition, G360 74 gene panel was used to identify CDK12 mutation (not detected in 73 gene panel) in an independent cohort of aPC pts. Barnard’s test was used to evaluate the association between genetic mutation and gene. Genomic landscape was also compared by a Bayesian Network (BN) machine learning approach. Results: A total of 552 pts (125 AA, 427 CA) tested by G360 73 gene panel were included. Multiple genomic aberrations were enriched in AA patients (Table). In the independent cohort of 261 aPC patients (AA=106 pts, CA=155 pts) tested by G360 74 gene panel, CDK12 mutation was significant enriched in AA pts. (9.4% vs. 1.9%, p=0.006). Machine learning analysis supported these results, and will be presented at the meeting. Conclusions: These hypothesis generating data suggest significant differences in the tumor genomic profile between AA and CA pts with aPC. Identification of molecular drivers of tumor progression enriched in AA pts may allow development of tailored systemic therapy for these men, and decrease disparities in disease related outcomes. Data need external validation. PB,RR,MAB contributed equally to this work.[Table: see text]
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