MetaTiME integrates single-cell gene expression to characterize the meta-components of the tumor immune microenvironment

Integration and comparison of multiple single cell sequencing datasets can be used to compare different studies. Here the authors propose MetaTiME which compares the gene expression of single cells from the tumour microenvironment across different tumours and uses transportable labels and metacomponents to annotate cell types and states. Recent advances in single-cell RNA sequencing have shown heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can indicate common cell types and states in the tumor microenvironment (TME). We develop a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

Automated summary

MetaTiME is a method that compares gene expression of single cells in the tumor microenvironment across different tumors and annotates cell types and states using transportable labels and metacomponents. It integrates multiple single-cell sequencing datasets to reveal common cell types and states in the tumor microenvironment. MetaTiME learns meta-components that encode independent components of gene expression and provides a tool to annotate cell states and gene regulators for tumor immunity and cancer immunotherapy.