Unveiling the Genomic Basis of Chemosensitivity in Sarcomas of the Extremities: An Integrated Approach for an Unmet...

Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) can be considered as a spectrum of the same disease entity, representing one of the most common adult soft tissue sarcoma (STS) of the extremities. While MFS is rarely metastasizing, it shows an extremely high rate of multiple frequent local recurrences (50-60% of cases). On the other hand, UPS is an aggressive sarcoma prone to distant recurrence, which is correlated to a poor prognosis. Differential diagnosis is challenging due to their heterogeneous morphology, with UPS remaining a diagnosis of exclusion for sarcomas with unknown differentiation lineage. Moreover, both lesions suffer from the unavailability of diagnostic and prognostic biomarkers. In this context, a genomic approach combined with pharmacological profiling could allow the identification of new predictive biomarkers that may be exploited for differential diagnosis, prognosis and targeted therapy, with the aim to improve the management of STS patients. RNA-Seq analysis identified the up-regulation of MMP13 and WNT7B in UPS and the up-regulation of AKR1C2, AKR1C3, BMP7, and SGCG in MFS, which were confirmed by in silico analyses. Moreover, we identified the down-regulation of immunoglobulin genes in patient-derived primary cultures that responded to anthracycline treatment compared to non-responder cultures. Globally, the obtained data corroborated the clinical observation of UPS as an histotype refractory to chemotherapy and the key role of the immune system in determining chemosensitivity of these lesions. Moreover, our results confirmed the validity of genomic approaches for the identification of predictive biomarkers in poorly characterized neoplasms as well as the robustness of our patient-derived primary culture models in recapitulating the chemosensitivity features of STS. Taken as a whole, this body of evidence may pave the way toward an improvement of the prognosis of these rare diseases through a treatment modulation driven by a biomarker-based patient stratification.