Transcriptomic, genomic and phenotypic characterization of an immunocompetent putative leiomyosarcoma mouse model

Background Soft tissue sarcomas (STS) are rare but very genetically diverse mesenchymal malignancies with limited therapeutic options, especially for metastatic disease. Leiomyosarcoma (LMS) is one of the most common human STSs, characterized by high proliferation indices, complex karyotype, and low sensitivity to established therapies, including immunotherapy. LMS therapeutic progress is hampered by the absence of models that could adequately reflect the biology of the tumor in an immunocompetent context. Methods This PhD work developed a preclinical platform for the study of LMS using human LMS cell lines, patient-derived xenografts, and a novel immunocompetent murine model in which Usp18, a deubiquitinase, is lost. Murine tumors as well as syngeneic grafts were characterized according to histopathological analysis, IHC, transcriptomic, and whole-exome sequencing. RNA sequencing data from murine and human LMS were compared with public datasets, including TCGA, and the immune landscape of the syngeneic murine model was investigated by multiple deconvolution tools. Results Usp18-/- mice developed spontaneous LMS with severe genomic instability, whose transcriptomic profiles were highly similar to those of human LMS. Comparative transcriptomic studies clearly established the high conservation of gene expression signatures for LMS between human samples and the syngeneic mouse model, besides identifying differences between uterine and extra-uterine LMS. Genomic studies showed that Usp18-/- mice developed leiomyosarcomas with defects in homologous recombination repair pathways. Conclusions This research establishes a robust immunocompetent preclinical model that accurately recapitulates the phenotypic and histopathologic, genomic, and transcriptomic profiles of human LMS, establishing a translational platform for the study of combination therapies to ultimately expand the treatment armamentarium of human LMS