Memorial Sloan Kettering Cancer Center Archives

2019

Scholar Grant

Filemon Dela Cruz

New York City, NY

Title: Development of a drug screen platform to predict in vivo sensitivity utilizing pediatric patient-derived sarcoma models.

Executive Summary:
Pediatric sarcomas comprise a diverse group of tumors occurring in bone, muscle, cartilage or fat and are treated using a combination of chemotherapy, surgery and radiation. However, pediatric sarcomas that have already spread at diagnosis, or who have their sarcomas recur following 1st line therapy, will die of their disease despite currently available therapies. Increased knowledge of cancer genetics over the past decade has provided clues to tumor vulnerabilities that can be used to target and eradicate even the most aggressive of tumors with existing drugs. However, accurate selection of drugs that effectively treat a child’s cancer remains a significant challenge. Drug screening strategies have been developed to help inform clinicians of specific drugs that may halt growth and kill a patient’s tumor. However, there are no currently effective and validated methods for determining if the drug screen predictions will reliably translate into therapeutic effect in the patient. This proposal will test an approach that uses patient-derived tumor cells to create a prioritized list of drugs predicted to have sensitivity against the tumor cells. We will then test the drug predictions in a mouse model growing the same tumor cells used in the drug screen to evaluate how predictive the drug screen worked to identify drugs that successfully halted tumor growth. The results from this study can be used as a novel way to identify therapeutically effective drugs to treat pediatric sarcoma patients without having to rely on knowledge of the tumor genetics, and when there are no other means to guide and inform the treatment plan for high-risk sarcoma patients. This study will also lay the foundation for the first clinical trial in pediatric cancers that will formally evaluate the predictive power of a matched drug screen-mouse tumor model approach for identifying effective treatments for pediatric sarcomas.

2019

Young Investigator

Michael Kinnaman

New York City, NY

Executive Summary: Our lab focuses on studying how cancer evolves, or changes and adapts over time, to a point where it spreads from the original site of disease to other organs in the body. My research specifically focuses on applying my lab’s expertise to studying different types of pediatric sarcomas. I currently have two active projects studying cancer evolution in both osteosarcoma and rhabdomyosarcoma.

Osteosarcoma is the most common pediatric bone tumor and there have been no significant advances with regards to therapy or overall survival over the last three decades. There are approximately 400 new cases each year that arise in children and adolescents younger than 20 years of age. Unfortunately, only 20% of patients who present with or develop metastases will survive.

To help improve therapy and our understanding of osteosarcoma, my project’s goal is to characterize the tumor cells that are resistant to our current therapy. These cells are the bad actors that we need to characterize in order to cure this disease. To do this we will be doing whole genome sequencing, which allows us to map out the entire genetic code of a cancer cell, on patients’ tumor samples at different time points throughout treatment. We will then compare the genetic makeup of each sample to the samples collected from earlier in a patient’s treatment to see how the tumor has changed. This will allow us to not only identify the resistant tumor cells but also characterize and describe their genetic makeup. We hope this new information will lead to new treatment and treatment strategies that are specifically targeted towards these resistant tumor cells, improving outcomes for our patients with osteosarcoma.

*To help improve therapy and our understanding of osteosarcoma, my project’s goal is to characterize the tumor cells that are resistant to our current therapy.
*We will be doing whole genome sequencing on patients’ tumor samples at different time points throughout treatment allowing us to not only identify the resistant tumor cells but also characterize and describe their genetic makeup.
*This new information will lead to new treatment strategies that are specifically targeted towards these resistant tumor cells, improving outcomes for our patients with osteosarcoma.