3'RNA Sequencing Accurately Classifies Formalin-Fixed Paraffin-Embedded Uterine Leiomyomas.

Simple Summary Uterine leiomyomas are benign smooth muscle tumors affecting millions of women globally. On a molecular level, leiomyomas can be classified into three main subtypes, each characterized by mutations affecting either MED12, HMGA2, or FH. Leiomyomas are still widely regarded as a single entity, although early observations suggest that different subtypes behave differently, in terms of both clinical outcomes and therapeutic requirements. The majority of classification studies on leiomyomas have been performed using fresh frozen tissue. Archival formalin-fixed paraffin-embedded (FFPE) tissue represents an invaluable source of biological material that can be studied retrospectively. Methods capable of generating high-quality data from FFPE material are in high demand. Here, we show that 3 ' RNA sequencing can accurately classify leiomyomas that have been stored as FFPE tissue in hospital archives for years. A targeted 3 ' RNA sequencing panel could provide researchers and clinicians with a cost-effective and scalable diagnostic tool for classifying smooth muscle tumors. Uterine leiomyomas are benign smooth muscle tumors occurring in 70% of women of reproductive age. The majority of leiomyomas harbor one of three well-established genetic changes: a hotspot mutation in MED12, overexpression of HMGA2, or biallelic loss of FH. The majority of studies have classified leiomyomas by complex and costly methods, such as whole-genome sequencing, or by combining multiple traditional methods, such as immunohistochemistry and Sanger sequencing. The type of specimens and the amount of resources available often determine the choice. A more universal, cost-effective, and scalable method for classifying leiomyomas is needed. The aim of this study was to evaluate whether RNA sequencing can accurately classify formalin-fixed paraffin-embedded (FFPE) leiomyomas. We performed 3 ' RNA sequencing with 44 leiomyoma and 5 myometrium FFPE samples, revealing that the samples clustered according to the mutation status of MED12, HMGA2, and FH. Furthermore, we confirmed each subtype in a publicly available fresh frozen dataset. These results indicate that a targeted 3 ' RNA sequencing panel could serve as a cost-effective and robust tool for stratifying both fresh frozen and FFPE leiomyomas. This study also highlights 3 ' RNA sequencing as a promising method for studying the abundance of unexploited tissue material that is routinely stored in hospital archives.