Endometrial stromal tumors include translocation-associated low- and high-grade endometrial stromal sarcomas (ESS) and highly malignant undifferentiated uterine sarcomas (UUS). UUS is considered a poorly defined group of aggressive tumors and is often seen as a diagnosis of exclusion after ESS and leiomyosarcoma (LMS) have been ruled out. We performed a comprehensive analysis of gene expression, copy number variation, point mutations, and immune cell infiltrates in the largest series to date of all major types of uterine sarcomas to shed light on the biology of UUS and to identify potential novel therapeutic targets. We show that UUS tumors have a distinct molecular profile from LMS and ESS. Gene expression and immunohistochemical analyses revealed the presence of high numbers of tumor-associated macrophages (TAMs) in UUS, which makes UUS patients suitable candidates for therapies targeting TAMs. Our results show a high genomic instability of UUS and downregulation of several TP53-mediated tumor suppressor genes, such as NDN, CDH11, and NDRG4. Moreover, we demonstrate that UUS carry somatic mutations in several oncogenes and tumor suppressor genes implicated in RAS/PI3K/AKT/mTOR, ERBB3, and Hedgehog signaling.
Joanna Przybyl, Magdalena Kowalewska, Anna Quattrone, Barbara Dewaele, Vanessa Vanspauwen, Sushama Varma, Sujay Vennam, Aaron M. Newman, Michal Swierniak, Elwira Bakuła-Zalewska, Janusz A. Siedlecki, Mariusz Bidzinski, Jan Cools, Matt van de Rijn, Maria Debiec-Rychter
Usage data is cumulative from August 2021 through August 2022.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.