Mining proteomic signature of soft tissue sarcoma by mass-spectrometry to find new candidate drug targets

Background

Soft-tissue sarcoma is an aggressive cancer of the mesenchymal tissue. It is a heterogeneous disease since comprises several histotypes and can arise in different areas of the body. Its aggressiveness is mostly related to its high metastasis rate (40-50%) and the unsatisfactory efficacy of traditional therapies. Given this, it is mandatory to deepen the biological knowledge of this group of malignancies and to find out new therapeutic strategies based on their specific molecular patterns. To this aim, drug repurposing is one of the most powerful tool for therapeutic discovery because it allows the reduction of time and costs. In this research, we used an advanced proteomic and bioinformatic approach on sarcoma and healthy tissue, to identify new potential therapeutic targets.

Methods

We performed proteomic analysis of 26 tumors and healthy samples from the same sarcoma patient, including different soft-tisse sarcoma histotypes. Tissue biopsies were lysed, digested, and analyzed on an Ultimate 3000 RSLC nano coupled to an Orbitrap Exploris 480 with a High-Field Asymmetric Waveform Ion Mobility Spectrometry System. The acquired raw MS data files were processed and analyzed using Proteome Discoverer with CHIMERYS algorithm. Bioinformatic analysis were performed on modulated proteins using DAVID and IPA software. Druggable proteome was also investigated using the Drug Bank database. Potential drug targets were further mapped to UniProt, Therapeutic Target Database (TTD) and Cancer/testis antigens database. In addition, investigation of clinical trials" status on ClinicalTrials.gov was performed.

Results

The proteomic analysis allowed the identification of almost 10000 unique proteins and the quantification of more than 8000 proteins. Sarcoma cancer tissue was characterized by a specific proteomic signature: an enrichment of pathways related to PPAR signaling, carbon metabolism and antigen processing and presentation was identified. Regarding molecular functions, an enrichment of proteins related to RNA binding, chromatin and ribosome was found. The comparison of cancer/healthy proteome allowed the identification of specific over-expressed/under-expressed drug targets for each patient / histotype. Among all the drug targets, 370 were present in at least 88% of the samples, of which 314 were upregulated and 56 were down regulated. A more in-depth analysis allowed the identification of six drugs potentially effective against sarcoma, and that were already employed in the treatment of other diseases.

Conclusion

In the presented work we exploited mass spectrometry to create a proteomic mapping of 26 sarcoma biopsies of different soft tissue sarcomas and we were able to characterize the biological signature of soft tissue sarcoma and to obtain a list of reliable new drug targets to develop new therapeutic options. The in vitro validation of the drugs is ongoing.