RESUMO
Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.
Assuntos
Glicoproteínas de Membrana , Células Mieloides , Neoplasias , Receptores Imunológicos , Análise de Célula Única , Microambiente Tumoral , Humanos , Análise de Célula Única/métodos , Microambiente Tumoral/genética , Microambiente Tumoral/imunologia , Células Mieloides/metabolismo , Células Mieloides/patologia , Receptores Imunológicos/metabolismo , Receptores Imunológicos/genética , Glicoproteínas de Membrana/metabolismo , Glicoproteínas de Membrana/genética , Prognóstico , Neoplasias/genética , Neoplasias/patologia , Neoplasias/metabolismo , Feminino , Receptor de Morte Celular Programada 1/metabolismo , Receptor de Morte Celular Programada 1/genética , Biomarcadores Tumorais/metabolismo , Biomarcadores Tumorais/genética , Neoplasias de Mama Triplo Negativas/genética , Neoplasias de Mama Triplo Negativas/patologia , Neoplasias de Mama Triplo Negativas/metabolismo , Neoplasias Ovarianas/patologia , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/metabolismo , Antígeno B7-H1/metabolismo , Antígeno B7-H1/genéticaRESUMO
Intercellular communication orchestrates a multitude of physiologic and pathologic conditions. Algorithms to infer cell-cell communication and predict downstream signalling and regulatory networks are needed to illuminate mechanisms of stem cell differentiation and tissue development. Here, to fill this gap, we developed and applied CellComm to investigate how the aorta-gonad-mesonephros microenvironment dictates haematopoietic stem and progenitor cell emergence. We identified key microenvironmental signals and transcriptional networks that regulate haematopoietic development, including Stat3, Nr0b2, Ybx1 and App, and confirmed their roles using zebrafish, mouse and human models. Notably, CellComm revealed extensive crosstalk among signalling pathways and convergence on common transcriptional regulators, indicating a resilient developmental programme that ensures dynamic adaptation to changes in the embryonic environment. Our work provides an algorithm and data resource for the scientific community.