Multiplexed Nanoflares for Predicting Chemotherapy Responses of Metastatic Melanomas

With personalized medicine a reality in the near future, targeting specific malignancies based on genetic changes will become commonplace. One current example of strategic targeting of malignancy is the recent availability of BRAF inhibitors for metastatic melanoma based on the high percentage of cells expressing a specific BRAF point mutation (BRAFV600E) that activates BRAF signaling. Nevertheless, the melanomas treated with these inhibitors rapidly become resistant to therapy. We hypothesize that the genetic changes which confer BRAF inhibitor resistance in metastatic melanoma arise from the selective advantage during therapy of cells with a resistant phenotype (e.g. upregulating PDGFR-beta or N-RAS), present at the initiation of treatment; these melanoma cells become the predominant tumor mass as sensitive cells are selectively suppressed with therapy. To test this hypothesis, we will use a novel multiplexed nanoflare platform that will allow us to quantify relative gene expression distributions within a population of tumor cells. Gene expression distributions will be quantified at regular time intervals in a population of BRAF V600E-positive melanoma cells cultured in vitro with chronic exposure to vemurafenib. In addition, we will prepare single-cell suspensions of human metastatic tumor samples on which we will perform a nanoflare analysis to characterize human metastatic melanoma tumor heterogeneity. Data on patients’ clinical courses will be collected and used to detect trends in tumor heterogeneity of gene expression versus chemotherapeutic responses.