Developing novel genomic risk stratification models in soft tissue and uterine leiomyosarcoma Journal Article
| Authors: | Dermawan, J. K.; Chiang, S.; Singer, S.; Jadeja, B.; Hensley, M. L.; Tap, W. D.; Movva, S.; Maki, R. G.; Antonescu, C. R. |
| Article Title: | Developing novel genomic risk stratification models in soft tissue and uterine leiomyosarcoma |
| Abstract: | Purpose: 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. 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 1-year follow-up. Results: 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. Conclusions: Compared with traditional clinicopathologic models, genomic risk stratification demonstrates superior prediction of clinical outcome in STLMS and is comparable in ULMS. © 2024 American Association for Cancer Research. |
| Keywords: | immunohistochemistry; adult; controlled study; human tissue; aged; aged, 80 and over; middle aged; gene mutation; major clinical study; overall survival; genetics; mutation; mortality; follow up; genetic analysis; biological marker; phenotype; progression free survival; cytogenetics; pathology; necrosis; protein p53; tumor marker; dna methylation; risk assessment; mismatch repair; soft tissue sarcoma; genomics; genome; mitosis rate; leiomyosarcoma; uterine neoplasms; b raf kinase; disease specific survival; disease exacerbation; soft tissue neoplasms; soft tissue tumor; uterus tumor; copy number variation; germline mutation; procedures; machine learning; high throughput sequencing; very elderly; humans; prognosis; human; male; female; article; whole exome sequencing; biomarkers, tumor; transcriptional regulator atrx |
| Journal Title: | Clinical Cancer Research |
| Volume: | 30 |
| Issue: | 10 |
| ISSN: | 1078-0432 |
| Publisher: | American Association for Cancer Research |
| Date Published: | 2024-05-15 |
| Start Page: | 2260 |
| End Page: | 2271 |
| Language: | English |
| DOI: | 10.1158/1078-0432.Ccr-24-0148 |
| PUBMED: | 38488807 |
| PROVIDER: | scopus |
| PMCID: | PMC11096044 |
| DOI/URL: | |
| Notes: | Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PubMed and PDF -- MSK corresponding author is Christina Antonescu -- Source: Scopus |
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