Graduate Student, Cancer Biology
Dr. Jonathan Irish (Thesis)
Dr. Mark Kelley (Clinical)
Melanoma is a heterogeneous tumor derived from neuroectodermal origin that is curable with early detection and surgical resection; unfortunately melanoma has a preference for early metastasis with a median survival below nine months. In particular, patients often acquire activating mutations in NRAS, BRAF, or KIT to drive inappropriate signaling events that mediate transcription of genes to maintain a malignant phenotype. Therapy for melanoma has advanced greatly due to targeting signaling network nodes activated by oncogenes, however these therapies often fail in advanced stage melanomas suggesting therapy resistant subsets emerge to drive relapse. While it is clear that changes to signaling occur in therapy resistant melanoma cells, it is not known which of the many signaling changes drive therapy resistance and what biomarkers could be used to track disease progression. Furthermore, most approaches to tracking resistance work at the “sample level’ and cannot detect single cell evolution of resistance.
To improve our understanding of resistance in melanoma, the Irish lab uses systems biology techniques to measure signaling networks at the single cell level. This ability to measure many features simultaneously on every melanoma cell is made possible using innovative mass cytometry technology (CyTOF) at Vanderbilt. In this project I enjoy the interaction from my clinical mentor Dr. Mark Kelley, chief of the Division of Surgical Oncology and Endocrine Surgery. Working with Dr. Kelley I have the opportunity to work on an innovative clinical trial that targets oncogenic BRAF and MEK kinase signaling in patients before, during, and after therapy. Using this translational research approach, we will track therapy resistant cells in melanoma tumors taken over time during the clinical trial and identify biomarkers of therapy resistant cells. Overall we anticipate these studies will enable us to (I) identify and target therapy resistant melanoma subsets using high –dimensional mass cytometry of signaling before and after targeted therapy, (II) determine the driving mechanism of resistance in melanoma cell subsets and (III) identify the influence of melanoma subsets on the tumor microenvironment before and after targeted therapy.
With this research we aim to develop single cell signaling profiles of patient’s cancer cells as a diagnostic tool to suggest therapeutic strategies to kill all cancer cells.