Pharmaco-proteogenomics for synovial sarcoma towards novel therapy

Background

Sarcomas originate in various mesenchymal tissues, consisting of more than 100 subtypes with different histological, biological, and clinical characteristics. Given that these tumors generally lack targetable mutations, genomic technology has obvious limitations in sarcoma research. With this in mind, we conduct pharmaco-proteogenomics to develop novel treatments for sarcomas. Synovial sarcoma (SS) is defined by the SS18-SSX fusion gene, with no effective anti-cancer drug available for patients with advanced SS. The genomic aberrations useful for treatments have not been reported in SS, probably because the SS18-SSX fusion drives oncogenesis dominantly. Therefore, phenomic and proteomic approaches are worth attempting to develop novel therapy in SS.

Objective

This pharmaco-proteogenomic study aims to discover innovative seeds for novel therapy in SS.

Methods

Patient-derived cancer models, such as cell lines, organoids, and xenografts were established from fresh surgical specimens. Drug sensitivity tests were conducted using a drug library consisting of 214 anti-cancer drugs. DIA mass spectrometry, RNA-seq, and target sequencing were performed for proteomics, transcriptomics, and genomics, respectively.

Results

In vitro models (cell lines and organoids) and in vivo models (xenografts) were established from six and three patients, respectively. We found that five anti-cancer drugs suppressed the proliferation of all cell lines examined at extremely low concentrations. Although the five drugs included a tyrosine kinase inhibitor approved for the treatment of a particular type of lung cancer with unique mutations, there were no corresponding mutations in the SS cells. Proteomic and transcriptomic backgrounds were collectively investigated to reveal the molecular signatures preserved in the models.

Discussion

We need to consider the utility of omics techniques other than genomics, as genome medicine is limited in malignancies with no targetable mutations. The combination of drug sensitivity screening and the proteogenomic approach is powerful, because we can simultaneously obtain phenotype, proteotype, and genotype data. In such studies, the adequate and appropriate use of patient-derived cancer models is critical, and we successfully established such models. Our approach has three limitations. Firstly, we need to clarify how precisely our models recapitulate their original tumors. Secondly, the results of drug screening should be validated in animal models, and the link among different models should be optimized. Thirdly, we need to study multiple aspects of the proteome, such as expression, activity, and protein interactions. By addressing these challenges, our pharmaco-proteogenomics strategy will have versatile utility and can be applied to various types of malignancies.