Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning.

Osteosarcoma has a guarded prognosis. A major hurdle in developing more effective osteosarcoma therapies is the lack of disease-specific biomarkers to predict risk, prognosis, or therapeutic response. Exosomes are secreted extracellular microvesicles emerging as powerful diagnostic tools. However, their clinical application is precluded by challenges in identifying disease-associated cargo from the vastly larger background of normal exosome cargo. We developed a method using canine osteosarcoma in mouse xenografts to distinguish tumor-derived from host-response exosomal messenger RNAs (mRNAs). The model allows for the identification of canine osteosarcoma-specific gene signatures by RNA sequencing and a species-differentiating bioinformatics pipeline. An osteosarcoma-associated signature consisting of five gene transcripts (SKA2, NEU1, PAF1, PSMG2, and NOB1) was validated in dogs with spontaneous osteosarcoma by real-time quantitative reverse transcription PCR (qRT-PCR), while a machine learning model assigned dogs into healthy or disease groups. Serum/plasma exosomes were isolated from 53 dogs in distinct clinical groups ("healthy", "osteosarcoma", "other bone tumor", or "non-neoplastic disease"). Pre-treatment samples from osteosarcoma cases were used as the training set, and a validation set from post-treatment samples was used for testing, classifying as "osteosarcoma detected" or "osteosarcoma-NOT detected". Dogs in a validation set whose post-treatment samples were classified as "osteosarcoma-NOT detected" had longer remissions, up to 15 months after treatment. In conclusion, we identified a gene signature predictive of molecular remissions with potential applications in the early detection and minimal residual disease settings. These results provide proof of concept for our discovery platform and its utilization in future studies to inform cancer risk, diagnosis, prognosis, and therapeutic response.

Correction: Regression of primary cardiac angiosarcoma and metastatic nodules following propranolol as a single agent treatment.

[This corrects the article DOI: 10.18632/oncoscience.472.].

Regression of primary cardiac angiosarcoma and metastatic nodules following propranolol as a single agent treatment.

Angiosarcoma is the most common malignant cardiac tumor. Cardiac angiosarcoma is a highly lethal neoplasm that is largely resistant to conventional anti-cancer therapy. Mean survival of patients with cardiac angiosarcoma is only 4 months, and almost all patients will succumb to the disease within 1 year. The beta blocker propranolol is an emerging therapy against angiosarcoma. When combined with conventional therapies, propranolol increases progression free and overall survival in patients with this tumor type. It is currently unknown if propranolol is capable of showing anti-cancer efficacy as a single agent therapy. We report a case of a 61 year old woman diagnosed with primary cardiac angiosarcoma and liver and lung metastases. This patient chose to decline conventional therapy, and instead was prescribed the beta blocker propranolol as a single agent treatment. After 12 months, the mediastinal mass substantially debulked and decreased in size, and the metastatic nodules stabilized or resolved with no evidence of hyper-metabolic activity on PET-CT. This is the first reported data showing long term efficacy of the beta blocker propranolol as a single agent therapy against angiosarcoma.