An extraordinary aspect of complex multicellular organisms, such as mammals, is the diversity of different types of cells that arise from the same genome. Each type of cell, or cell state, differs drastically in morphology, function, and physiology and must be carefully regulated during both the development and the daily life of the organism. This includes both tight control of cell state transitions and the stabilization of cell states against external stimuli and internal disturbances, including genomic mutations. Underlying specific cell states are networks of expressed genes. Although it is now commonplace to measure the expression of every gene within a population of cells with a single experiment, little is known about how the individual genes within a large network function together. This is especially true in complex human diseases, such as cancer, where the population of cells from a single tumor can contain many different cell states. The objective of this project is to both identify and to functionally dissect networks of interacting genes that stabilize melanocytes and early- stage melanomas against transitions into more advanced disease states. The central approach is microRNA- based detection of functional gene networks. MicroRNAs (miRNAs) are transcribed from the genome but do not encode for proteins, rather regulating the translation and stability of mRNA networks. It has recently been shown that miRNAs serve as excellent tools for identifying networks of genes that regulate cell state transitions. These co-regulated networks of genes are enriched for genetic interactions, which can be identified using mapping techniques recently adapted for mammalian cells from their previous extensive use in single cell organisms. In the first aim of this application, these methods will be used to investigate the relationship between different melanoma driver mutations (those changes to the genome that initiate melanoma progression) and the networks of genes that stabilize against further progression, testing the hypothesis that different initiatig events result in distinct multigenic barriers to tumorigenesis. MiRNAs known to advance melanoma will be introduced into a panel of mouse melanocytes with different driver mutations. When progression is induced, the network of genes targeted by the miRNA will be experimentally determined and their individual function and genetic interactions investigated. In the second aim, the miRNA-targeted networks that correlate with human melanoma progression in both expression and function will be tested using primary patient samples and reconstituted skin culture. In the third aim, populations of tumor cells will be analyzed on the single cell leve. Each cell will be assayed for its ability to progress or to transition into a therapy-resistant cel state, and the miRNA profiles associated with each transition will be measured. Collectively, these approaches will improve our knowledge of the networks of genes that work together to prevent melanoma progression, increasing our potential to conduct meaningful personalized therapies for this deadly disease.

Public Health Relevance

The development and progression of cancer, particularly melanoma, involves the failure of stabilizing genetic programs to prevent the transition of a normal cell into a cancerous cell. Each genetic program consists of the simultaneous expression and co-regulation of networks of dozens to hundreds of different genes. The proposed research seeks to advance our fundamental knowledge of cancer biology by identifying the networks of genes that normally prevent melanoma progression, which should lead to both more accurate diagnosis and personalized treatment of tumors that are likely to become lethal.

National Institute of Health (NIH)
Office of The Director, National Institutes of Health (OD)
Early Independence Award (DP5)
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Special Emphasis Panel (ZRG1-RPHB-W (53))
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Basavappa, Ravi
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University of California San Francisco
Schools of Medicine
San Francisco
United States
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Zeng, Hanlin; Jorapur, Aparna; Shain, A Hunter et al. (2018) Bi-allelic Loss of CDKN2A Initiates Melanoma Invasion via BRN2 Activation. Cancer Cell 34:56-68.e9
Hejna, Miroslav; Jorapur, Aparna; Song, Jun S et al. (2017) High accuracy label-free classification of single-cell kinetic states from holographic cytometry of human melanoma cells. Sci Rep 7:11943