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Supplementary Figure S9 from Developing Novel Genomic Risk Stratification Models in Soft Tissue and Uterine Leiomyosarcoma

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posted on 2024-05-15, 07:20 authored by Josephine K. Dermawan, Sarah Chiang, Samuel Singer, Bhumika Jadeja, Martee L. Hensley, William D. Tap, Sujana Movva, Robert G. Maki, Cristina R. Antonescu

Supplementary Figure S9. MSKCC ULMS cohort. Genomic variables (gene level point mutations and copy number changes and chromosomal arm level changes) are input into the OncoCast model using the elastic net (“ENET”) approach, with outcome being overall survival. Variable importance is assigned and visualized in a plot by selection frequency (the event frequency of that feature in the data) and Cox proportional hazard ratios. Dotted lines indicate threshold of 0.50 selection frequency and hazard ratio of 1.

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National Cancer Institute (NCI)

United States Department of Health and Human Services

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Cycle for Survival

Suzie Wolf Coffland Fund

Kristin Ann Carr Foundation

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ARTICLE ABSTRACT

Leiomyosarcomas (LMS) are clinically and molecularly heterogeneous tumors. Despite recent large-scale genomic studies, current LMS risk stratification is not informed by molecular alterations. We propose a clinically applicable genomic risk stratification model. 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 1-year follow-up. In STLMS, French Federation of Cancer Centers (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. Compared with traditional clinicopathologic models, genomic risk stratification demonstrates superior prediction of clinical outcome in STLMS and is comparable in ULMS.

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