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Basic and Translational Science Projects
Circulating Tumor DNA As an Early Marker of Radiation Response in an Animal Model of Spine Metastases
Principal Investigators: Daniel Sciubba, M.D., and Chetan Bettegowda, M.D., Ph.D.
Not all tumors are radiation sensitive and, unfortunately, a patient may have completed the regimen by the time that is learned. A potential new technology to determine if radiation treatment is effective involves measurement of circulating tumor DNA (ctDNA), which is found in many kinds of cancer. In our model, we will implant human tumors into the spines of rats and then treat them with focused radiation. Levels of ctDNA will be measured before and after radiation to see if they correspond to cancer cell death. If shown to be good markers, changes in ctDNA levels could be used by care providers to: 1) learn if radiation is effectively treating the cancer and 2) change or discontinue the radiation treatment plan.
Chemotherapeutic and Radiographic Interventions in the Treatment of Primary and Recurrent Chordoma
Currently, the gold standard for chordoma care is complete resection, combined with radiation administered either before or after surgery. However, radiation can often prevent proper fusion of the spinal hardware. Additionally, no good chemotherapeutic drugs have been identified for treatment of chordoma. As a result, we seek to identify both chemotherapeutic regimens and optimal radiation timing in an animal model of chordoma, with the hope that such work can lead to clinical trials and improvements in the treatment of spinal and sacral chordoma.
Our previous work to this end has included creating an animal model of chordoma that replicates the disease’s radiographic, behavioral and neurological features (source). We are now hoping to begin the next phase of the project, which uses this model to address the previously mentioned endpoints.
Cysteamine As Inhibitor of Breast Cancer Spinal Metastasis in Mice
One of the most common sites of breast cancer metastases is the axial skeleton, leading to significant pain and a decrease in quality of life. Triple-negative breast cancer carries a particularly poor prognosis, with a median survival time of 6.7 months compared to 22.4 months for patients with receptor-positive tumors. Unlike hormone-responsive tumors, triple-negative disease has few good options for systemic therapy and often leads to rapid metastatic spread.
Given the difficulties of gaining Food and Drug Administration (FDA) approval for new medications, we also seek to identify agents with demonstrated safety and prior governmental approval.
Cysteamine is FDA approved for treatment of nephropathic cystinosis, and has shown a great safety profile in humans as young as 2 years-old. Preliminary in vitro data has also suggested that cysteamine can block the metastatic spread of triple-negative breast cancer. If successful, the evidence provided by this investigation could be used to support early phase clinical trials.
Clinical Research Projects
Predicting Survival for Metastatic Spine Disease — Comparison of Scoring Systems
One of the outstanding questions regarding treatment of spinal metastases is about patient survival. Though surgery can be a good option for many patients, not everyone will benefit. Specifically, patients with advanced disease may be too moribund to recover. We seek to apply existing scoring systems to patients who have been treated at The Johns Hopkins Hospital to determine which systems are the best predictors of survival.
Predicting Survival for Metastatic Spine Disease — Cachexia and Spine Metastases
Tumor type has historically been considered the best determinant of survival following surgery for spinal metastases. However, recent evidence suggests that surgeons must consider the entire clinical picture, including overall health and nutrition. One risk factor for poor outcomes is cachexia: fat and muscle loss seen in patients with significant disease burden. We hope to look at our clinical series of patients with spinal metastases to see if nutritional status/cachexia are predictive of survival.