Chromosomal instability (CIN) is a main cause of tumor heterogeneity, tumor evolution and therapy resistance of cancers. Chromosomally instable gastric cancer (CIN-gastric cancer) accounts for 50-70% of gastric tumors and is the poorest prognosis tumor subtype with the most suppressed tumor immune microenvironment. However, it is not understood how CIN contributes to poor prognosis and edits the tumor immune response of CIN-gastric cancer, due to a lack of assays investigating native CIN-driving mechanisms at the single cell level. I invented a pioneering, microscopy-based functional single cell sequencing method, which enables selective profiling of rare subpopulations of cells displaying dynamic phenotypes of interest. In this proposal, I will use my expertise to develop novel advanced single cell and multiplexed sequencing methods and create a new research line with the aim of dissecting the driving mechanisms of CIN in CIN-gastric cancer, investigating the impact of CIN on tumor microenvironment, and elucidating the molecular pathways leading to the poor prognosis of CIN-gastric cancer. To fulfill this aim, I defined three research objectives: In Objective I, I will develop a deep learning-based functional single cell sequencing (deepFUNseq) method to identify and profile rare, naturally occurring CIN-mother and -daughter cells derived from CIN-gastric cancer patients. In Objective II, I will develop a multiplexed functional & spatial single cell sequencing method(multi-FUNseq) to transcriptomically profile (non-)CIN gastric cancer cells and their interacting immune cells. In Objective III, I will investigate CIN-driving mechanisms and CIN-associated consequences in CIN-gastric cancer, including the role of CIN in immunoediting. The technologies developed in this proposal will result in a leap in our understanding of CIN in the context of cancer, and will lead to advances in fields where profiling cell-cell interactions is important, like tumor immunology.