The 3D organization of the genome is a regulator of gene expression. However, in different types of cancer, including multiple myeloma (MM) and chronic myelogenous leukemia (CML), the folding of chromosomes is altered, which impairs the proper regulation of transcriptional activity. In addition, genes located in such misfolded chromosomal loci are often involved in cancerous mechanisms. Despite the connection between genome organization and tumorigenesis, robust models of healthy and cancerous cells that rely on genome organization are lacking. This absence makes predicting which cells are likely to become cancerous due to impaired genomic organization impossible.

One reason for the inaccura...

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The 3D organization of the genome is a regulator of gene expression. However, in different types of cancer, including multiple myeloma (MM) and chronic myelogenous leukemia (CML), the folding of chromosomes is altered, which impairs the proper regulation of transcriptional activity. In addition, genes located in such misfolded chromosomal loci are often involved in cancerous mechanisms. Despite the connection between genome organization and tumorigenesis, robust models of healthy and cancerous cells that rely on genome organization are lacking. This absence makes predicting which cells are likely to become cancerous due to impaired genomic organization impossible.

One reason for the inaccuracy of existing models stems from the observation that genome organization is subject to high variability at the single-cell level, which influences the cell-to-cell variability of transcriptional activity. The majority of existing data relies on population-level genome organization and gene expression studies that are produced from different samples. To overcome these limitations, I propose to employ recent state-of-the-art imaging technologies, which I developed for studying genome organization at the single-cell level. I will integrate these technologies with RNA imaging of the same cells in order to directly relate a given chromosomal structure with its transcriptional response.

I will focus on CML and MM, where genome organization has been well-characterized in the population-level, but not the single-cell level. Specifically, I will determine whether the 3D structure of the Philadelphia chromosome supports the expression of an oncogenic protein and whether I can determine the risk factor(s) of developing cancer according to the position of proto-oncogenes and tumor suppressors with respect to chromatin interfaces.

As a result of these studies, we will have a deeper understanding of the relationship between genome structure and gene regulation during cellular transformation.

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