Single-cell integrative analysis reveals consensus cancer cell states and clinical relevance in breast cancer.
Lin PangFengyu XiangHuan YangXinyue ShenMing FangRan LiYongjin LongJiali LiYonghuan YuBo PangPublished in: Scientific data (2024)
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.
Keyphrases
- single cell
- rna seq
- induced apoptosis
- high throughput
- cell cycle arrest
- endoplasmic reticulum stress
- signaling pathway
- squamous cell carcinoma
- end stage renal disease
- oxidative stress
- ejection fraction
- stem cells
- newly diagnosed
- prognostic factors
- electronic health record
- bone marrow
- microbial community
- climate change
- machine learning
- breast cancer risk
- patient reported