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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.

Waddington's epigenetic landscape is an abstract metaphor frequently used to explain cell fate decisions. Recent advances in single-cell genomics are altering our understanding of the Waddington landscape. Yet, the molecular regulations behind remain poorly understood. We construct a dynamic cell landscape of mouse lineage differentiation at the single-cell level and thereby reveal both lineage-common and lineage-specific regulatory programs during cell type maturation. We verify lineage-common regulatory programs that are universal during the development of invertebrates and vertebrates. In particular, we identify Xbp1 as an evolutionarily conserved regulator of cell fate determinations across different species. We demonstrate that Xbp1 transcriptional regulation is important for the stabilization of the genetic network for a wide range of cell types. Our results offer genetic and molecular insights into the gene regulatory programs systematically and provide resources to advance the understanding of the cell fate decisions.

The tumor microenvironment heterogeneity of papillary thyroid cancer (PTC) is poorly characterized. The relationship between PTC and Hashimoto thyroiditis (HT) is also in doubt. Here, we used single-cell RNA sequencing to map the transcriptome landscape of PTC from eight PTC patients, of which three were concurrent with HT. Predicted copy number variation in epithelial cells and mesenchymal cells revealed the distinct molecular signatures of carcinoma cells. Carcinoma cells demonstrated intertumoral heterogeneity based on BRAF V600E mutation or lymph node metastasis, and some altered genes were identified to be correlated with disease-free survival in The Cancer Genome Atlas datasets. In addition, transcription factor regulons of follicular epithelial cells unveil the different transcription activation state in PTC patients with or without concurrent HT. The immune cells in tumors exhibited distinct transcriptional states, and the presence of tumor-infiltrating B lymphocytes was predominantly linked to concurrent HT origin. Trajectory analysis of B cells and plasma cells suggested their migration potential from HT adjacent tissues to tumor tissues. Furthermore, we revealed diverse ligand–receptor pairs between non-immune cells, infiltrating myeloid cells, and lymphocytes. Our results provided a single-cell landscape of human PTC. These data would deepen the understanding of PTC, as well as the immunological link between PTC and HT.

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Background. Drug-induced acute kidney injury (D-AKI) is increasingly common and can extend the hospital length of stay and increase mortality. This study is aimed at analyzing the clinical characteristics of hospitalized patients with D-AKI and the associated risk factors in a multidrug environment. Methods. A retrospective study among hospitalized patients was conducted in July 2019 based on the Adverse Drug Events Active Surveillance and Assessment System-2 developed by the authors. Four controls were matched with each case according to the matching criteria. The risk factors for D-AKI were identified by binary multivariate logistic regression. Results. A total of 23,073 patients were hospitalized in July 2019, 21,131 of whom satisfied the inclusion criteria. The independent risk factors for D-AKI consisted of alcohol abuse (odds ratio (OR), 2.05; 95% confidence interval (CI), 1.04-4.07), nonsteroidal anti-inflammatory drug (NSAID) use (OR, 2.39; 95% CI, 1.25-4.58), diuretic use (OR, 2.64; 95% CI, 1.42-4.92), prior anemia (OR, 4.10; 95% CI, 1.94-8.67), and prior chronic kidney disease (OR, 2.33; 95% CI, 1.07-5.08). Conclusions. The occurrence of D-AKI in hospitalized patients had significant associations with alcohol abuse, combination therapy with NSAIDs or diuretics, and prior anemia or chronic kidney disease. Clinicians should meticulously follow patients with the above characteristics.