Determining Doxorubicin Effects on Plasma Extracellular Vesicles Using Proteomics Analysis

Sarcomas are a group of over 100 types of tumors of mesenchymal origin that can be divided into soft tissue sarcomas (STS) and bone sarcomas. The most common agents used to treat all sarcomas are anthracyclines, such as doxorubicin. To date, no real time method of assessing tumor sensitivity and resistance to doxorubicin is available from patient blood samples. If biosignatures of early treatment response or failure can be identified, a future trial that validates the findings will be of great interest to patients.
SARC21 was a trial of Doxorubicin plus Evofosfamide versus doxorubicin alone in locally advanced, unresectable or metastatic soft-tissue sarcoma (TH CR-406/SARC021). This was an international, multicenter, open-label, randomized phase 3 trial that unfortunately was a negative trial. Of interest to this project are samples from the 323 patients that were in the control arm that had doxorubicin. The plasma samples from this trial can be utilized against patient outcomes data to determine the changes that doxorubicin induces to the circulating proteins (the Proteome) in the blood stream.

In this proposal, we aim to solve this problem of developing a blood based assay using extracellular vesicles (EVs) isolated from patient plasma to identify and characterize the tumor response to doxorubicin treament in the SARC21 trial. We hypothesize that: EV proteins will indicate the mechanism of drug resistance and sensitivity and, ultimately, may be able to predict whether a patient is likely to respond prior to chemotherapy.

In our primary aim, we will test the hypothesis that plasma extracellular vesicles are indicators of tumor presence and/or treatment response in sarcoma patients. We will proteomically evaluate sarcoma plasma pre- and post-doxorubicin treatment from the SARC21 clinical trial. We propose to analyze plasma EVs pre- and 6 weeks post-treatment from 25 non-responders and 25 patients that had a progression free survival greater than 9 months. We will perform standard statistical analysis to identify protein candidates of interest and generate signatures. This includes ANOVA filtering, outlier analysis, principal component analysis (PCA), correlation analysis and hierarchical clustering Normal plasma controls will indicate if expression of specific plasma EV proteins indicates presence of sarcoma.

We anticipate finding EV proteins that indicate sensitivity and resistance to doxorubicin. The ability to use a plasma protein biosignature as a surrogate for response or resistance both at early and late time points would yield a tool that sarcoma medical oncologists have been lacking. Through the support of SFA with its pilot we hope to derive the preliminary data needed for obtain the necessary funding to pursue EV proteomics on a larger scale and drive clinical impact of plasma EV analysis in the long term.