The long-term goal of this research program is to develop therapeutic strategies that improve the outcome of patients with disseminated melanoma. Melanoma is a highly metastatic tumor, with a propensity to disseminate to the skin, lungs and brain. In ~5% of cases, patients also develop leptomeningeal melanoma metastases (LMM: e.g. melanoma cell infiltration into the pia mater, the arachnoid membranes and cerebrospinal fluid) which have an even worse prognosis and a median survival of 8-10 weeks. It is likely that the leptomeninges represent ?sanctuary sites? for melanoma cells that evade both targeted and immune therapies. At this time, no therapeutic strategies have been identified that are effective against LMM. Melanomas are genetically heterogeneous, suggesting that distinct genetic clones/patterns of mutation determine which cells home to the brain and leptomeninges. Progress in this area has been limited due to the technical difficulties of obtaining specimens from the leptomeninges, cerebrospinal fluid (CSF) and sub-arachnoid space. Recently our group has begun the routine collection of CSF from patients with LMM, which we have shown to contain circulating melanoma cells (circulating tumor cells: CTCs). We have also established protocols to obtain serial CSF samples from patients undergoing off-label treatment BRAF-MEK inhibitor treatment for LMM. Methods for the isolation and amplification of RNA and DNA from single cells have become available and are ideally suited for analyzing rare populations of cells, such as those found in the CSF. The overarching goal of this R21 is to define the genetic and transcriptional profiles of the CTCs from patients with LMM and to identify novel therapeutic targets for these tumors. We will use the Fluidigm C1 platform to perform sophisticated single cell RNA and DNA analysis to define the clonal relationship between LMM CTCs and matched melanoma specimens from other sites. We will then collect serial CSF specimens from LMM patients undergoing treatment with targeted therapy and will determine how treatment drives clonal selection. Validation experiments will be performed in which BRAF-mutant LMM cells are orthotopically implanted into the leptomeninges of mice and treated with personalized drug combinations based upon dabrafenib-trametinib and drugs targeted against the actionable mutations/pathways that we identify. These studies are expected to provide critical new insights into the biology of brain and leptomeningeal melanoma metastases and form the groundwork for the development of clinically relevant drug combinations.

Public Health Relevance

Patients with Leptomeningeal melanoma metastases (LMM: e.g. melanoma cell infiltration into the pia mater, the arachnoid membranes and cerebrospinal fluid) have a bleak prognosis and a median survival of 8-10 weeks. Incidence of LMM is increasing and emerging data suggests that both the brain and the leptomeninges represent ?sanctuary sites? for melanoma cells that evade both targeted and immune therapies. The aim of this proposal is to use single cell RNA and DNA analysis to model the clonal diversity of BRAF-mutant LMM and to determine how BRAF-MEK inhibitor therapy alters this. We will then use the single cell level mutation/expression data and orthotopic xenograft models to develop combination therapy strategies that target and eliminate LMM.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21CA216756-02
Application #
9452934
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Arya, Suresh
Project Start
2017-03-13
Project End
2019-02-28
Budget Start
2018-03-01
Budget End
2019-02-28
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
Abate-Daga, Daniel; Ramello, Maria C; Smalley, Inna et al. (2018) The biology and therapeutic management of melanoma brain metastases. Biochem Pharmacol 153:35-45
Li, Jiannong; Smalley, Inna; Schell, Michael J et al. (2017) SinCHet: a MATLAB toolbox for single cell heterogeneity analysis in cancer. Bioinformatics 33:2951-2953