RESUMEN
Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.
Asunto(s)
Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patología , Plasticidad de la Célula/genética , Epigénesis Genética , Glioma/genética , Glioma/patología , Patrón de Herencia/genética , Transcripción Genética , Línea Celular Tumoral , Islas de CpG/genética , Variaciones en el Número de Copia de ADN/genética , Metilación de ADN/genética , Humanos , Isocitrato Deshidrogenasa/genética , Filogenia , Complejo Represivo Polycomb 2/metabolismo , Regiones Promotoras Genéticas/genética , Análisis de la Célula Individual , Transcriptoma/genéticaRESUMEN
In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care.
Asunto(s)
Biomarcadores de Tumor/genética , ADN Tumoral Circulante/sangre , ADN de Neoplasias/genética , Neoplasias/sangre , Biomarcadores de Tumor/sangre , Ácidos Nucleicos Libres de Células/sangre , Variaciones en el Número de Copia de ADN/genética , ADN de Neoplasias/sangre , Supervivencia sin Enfermedad , Femenino , Genoma Humano/genética , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Estimación de Kaplan-Meier , Masculino , Mutación/genética , Neoplasias/genética , Neoplasias/patología , Carga Tumoral/genética , Secuenciación Completa del GenomaRESUMEN
Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A) are frequently observed in hematological malignancies1-3 and clonal hematopoiesis4,5. Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A-mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif.