Developing Novel Genomic Risk Stratification Models in Soft Tissue and Uterine Leiomyosarcoma.

PURPOSE: Leiomyosarcomas (LMS) are clinically and molecularly heterogeneous tumors. Despite genomic studies, current LMS risk stratification is not informed by molecular alterations. We propose a clinically applicable genomic risk stratification model.

EXPERIMENTAL DESIGN: We performed comprehensive genomic profiling in a cohort of 195 soft tissue LMS (STLMS), 151 primary at presentation, and a control group of 238 uterine LMS (ULMS), 177 primary at presentation, with at least one-year follow up.

RESULTS: In STLMS, FNCLCC grade but not tumor size predicted progression-free survival (PFS) or disease-specific survival (DSS). In contrast, in ULMS, tumor size, mitotic rate and necrosis were associated with inferior PFS and DSS. In STLMS, a 3-tier genomic risk stratification performed well for DSS: high risk - co-occurrence of RB1 mutation and chr12q deletion (del12q)/ATRX mutation; intermediate risk - presence of RB1 mutation, ATRX mutation or del12q; low risk - lack of any of these three alterations. The ability of RB1 and ATRX alterations to stratify STLMS was validated in an external AACR GENIE cohort. In ULMS, a 3-tier genomic risk stratification was significant for both PFS and DSS: high risk - concurrent TP53 mutation and chr20q amplification/ATRX mutations; intermediate risk - presence of TP53 mutation, ATRX mutation or amp20q; low risk - lack of any of these three alterations. Longitudinal sequencing showed that most molecular alterations were early clonal events that persisted during disease progression.

CONCLUSIONS: Compared to traditional clinicopathologic models, genomic risk stratification demonstrates superior prediction of clinical outcome in STLMS and is comparable in ULMS.