Single-cell integrative analysis reveals consensus cancer cell states and clinical relevance in breast cancer.

High heterogeneity and complex interactions of malignant cells in breast cancer has been recognized as a driver of cancer progression and therapeutic failure. However, complete understanding of common cancer cell states and their underlying driver factors remain scarce and challenging. Here, we revealed seven consensus cancer cell states recurring cross patients by integrative analysis of single-cell RNA sequencing data of breast cancer. The distinct biological functions, the subtype-specific distribution, the potential cells of origin and the interrelation of consensus cancer cell states were systematically elucidated and validated in multiple independent datasets. We further uncovered the internal regulons and external cell components in tumor microenvironments, which contribute to the consensus cancer cell states. Using the state-specific signature, we also inferred the abundance of cells with each consensus cancer cell state by deconvolution of large breast cancer RNA-seq cohorts, revealing the association of immune-related state with better survival. Our study provides new insights for the cancer cell state composition and potential therapeutic strategies of breast cancer.

The Heterogeneous Cellular States of Glioblastoma Stem Cells Revealed by Single Cell Analysis.

Glioblastoma stem cells (GSCs) contributed to the progression, treatment resistance, and relapse of glioblastoma (GBM). However, current researches on GSCs were performed usually outside the human tumor microenvironment, ignoring the importance of the cellular states of primary GSCs. In this study, we leveraged single-cell transcriptome sequencing data of 6 independent GBM cohorts from public databases, and combined lineage and stemness features to identify primary GSCs. We dissected the cell states of GSCs and correlated them with the clinical outcomes of patients. As a result, we constructed a cellular hierarchy where GSCs resided at the center. In addition, we identified and characterized 2 different and recurrent GSCs subpopulations: proliferative GSCs (pGSCs) and quiescent GSCs (qGSCs). The pGSCs showed high cell cycle activity, indicating rapid cell division, while qGSCs showed a quiescent state. Then we traced the processes of tumor development by pseudo-time analysis and tumor phylogeny, and found that GSCs accumulated throughout the whole tumor development period. During the process, pGSCs mainly contributed to the early stage and qGSCs were enriched in the later stage. Finally, we constructed an 8-gene prognostic signature reflecting pGSCs activity and found that patients whose tumors were enriched for the pGSC signature had poor clinical outcomes. Our study highlights the primary GSCs heterogeneity and its correlation to tumor development and clinical outcomes, providing the potential targets for GBM treatment.