IMAT-ITCR Collaboration: Artificial intelligence enhanced breast cancer dormancy cell classification-based organelle-morphology and topology

项目总结/文摘

PROJECT SUMMARY/ABSTRACT Background: Metastasis in distant organs years after treatment is the primary cause of cancer death. Late progression occurs through the reactivation of dormant tumor cells that disseminated early in the disease. To date, no therapy has been designed to target those cells and the lack of understanding on their biology prevents the development of selective strategies to kill them. We aim to gain molecular insight into the gene regulatory signature of the cancer dormancy state and use this information to devise a dormant cancer cell biosensor that will allow us to identify, profile, and genetically manipulate them in vivo. Hypothesis: We hypothesize that the application of intersectional genetics tools to define the unique transcriptional profile of dormant cells will reveal vulnerabilities that could be exploited to eliminate those cells. Specific Aims: Aim 1. To obtain and validate the enhancer activity profiles of dormant cancer cells in an in vivo context Aim 2. To develop a dormant cancer cell biosensor and test its in vivo potential to selectively identify dormant cancer cells. Study design/Methods: To increase the specificity of dormant cancer cell identification in vivo, reduce side- effects on non-target normal cells, and allow the systematization of the generation of dormant cell-specific biosensors and its downstream applications, such as targeted cell ablation therapies, we propose to develop a new dormant cell biosensor that bypasses cell-surface marker requirements distinguishing them instead via intracellular properties that can be harnessed to allow the precise and exclusive genetic manipulation of these cells within the body. We will validate our biosensor in vivo by using cellular dormancy models and intravital two- photon microscopy. Relevance: The mechanisms of cancer cell dormancy are poorly understood, hence the options available for their targeted treatment to prevent metastasis are limited. Here, we propose to use state-of-the-art genomic activity profiling technology to gain molecular insight into the genetic program that defines the cancer dormancy state in vivo. We will then couple our unique computational and synthetic biology know-how to define unique signatures of the dormancy program to engineer genetic sensors that can be systemically-delivered into the body to find dormant cancer cells. With this strategy, we hope to develop strategies to eliminate metastatic dormant cells, the source of metastasis.