No abstract

ObjectiveHepatocellular carcinoma (HCC) is heterogeneous, especially in multifocal tumours, which decreases the efficacy of clinical treatments. Understanding tumour heterogeneity is critical when developing novel treatment strategies. However, a comprehensive investigation of tumour heterogeneity in HCC is lacking, and the available evidence regarding tumour heterogeneity has not led to improvements in clinical practice.DesignWe harvested 42 samples from eight HCC patients and evaluated tumour heterogeneity using whole-exome sequencing, RNA sequencing, mass spectrometry-based proteomics and metabolomics, cytometry by time-of-flight, and single-cell analysis. Immunohistochemistry and quantitative polymerase chain reactions were performed to confirm the expression levels of genes. Three independent cohorts were further used to validate the findings.ResultsTumour heterogeneity is considerable with regard to the genomes, transcriptomes, proteomes, and metabolomes of lesions and tumours. The immune status of the HCC microenvironment was relatively less heterogenous. Targeting local immunity could be a suitable intervention with balanced precision and practicability. By clustering immune cells in the HCC microenvironment, we identified three distinctive HCC subtypes with immunocompetent, immunodeficient, and immunosuppressive features. We further revealed the specific metabolic features and cytokine/chemokine expression levels of the different subtypes. Determining the expression levels of CD45 and Foxp3 using immunohistochemistry facilitated the correct classification of HCC patients and the prediction of their prognosis.ConclusionThere is comprehensive intratumoral and intertumoral heterogeneity in all dimensions of HCC. Based on the results, we propose a novel immunophenotypic classification of HCCs that facilitates prognostic prediction and may support decision making with regard to the choice of therapy.

Background Acute myeloid leukemia (AML) is a fatal hematopoietic malignancy and has a prognosis that varies with its genetic complexity. However, there has been no appropriate integrative analysis on the hierarchy of different AML subtypes. Methods Using Microwell-seq, a high-throughput single-cell mRNA sequencing platform, we analyzed the cellular hierarchy of bone marrow samples from 40 patients and 3 healthy donors. We also used single-cell single-molecule real-time (SMRT) sequencing to investigate the clonal heterogeneity of AML cells. Results From the integrative analysis of 191727 AML cells, we established a single-cell AML landscape and identified an AML progenitor cell cluster with novel AML markers. Patients with ribosomal protein high progenitor cells had a low remission rate. We deduced two types of AML with diverse clinical outcomes. We traced mitochondrial mutations in the AML landscape by combining Microwell-seq with SMRT sequencing. We propose the existence of a phenotypic “cancer attractor” that might help to define a common phenotype for AML progenitor cells. Finally, we explored the potential drug targets by making comparisons between the AML landscape and the Human Cell Landscape. Conclusions We identified a key AML progenitor cell cluster. A high ribosomal protein gene level indicates the poor prognosis. We deduced two types of AML and explored the potential drug targets. Our results suggest the existence of a cancer attractor.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal—Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging.