My research interest is the correlation between tumor heterogeneity and ecDNA, especially related to immune regulation.
Honors & Awards
Outstanding Graduate of Peking University, Peking University (2020)
Howard Chang, Postdoctoral Faculty Sponsor
Single-cell transcriptomic profiling reveals the tumor heterogeneity of small-cell lung cancer.
Signal transduction and targeted therapy
2022; 7 (1): 346
Small-cell lung cancer (SCLC) is the most aggressive and lethal subtype of lung cancer, for which, better understandings of its biology are urgently needed. Single-cell sequencing technologies provide an opportunity to profile individual cells within the tumor microenvironment (TME) and investigate their roles in tumorigenic processes. Here, we performed high-precision single-cell transcriptomic analysis of ~5000 individual cells from primary tumors (PTs) and matched normal adjacent tissues (NATs) from 11 SCLC patients, including one patient with both PT and relapsed tumor (RT). The comparison revealed an immunosuppressive landscape of human SCLC. Malignant cells in SCLC tumors exhibited diverse states mainly related to the cell cycle, immune, and hypoxic properties. Our data also revealed the intratumor heterogeneity (ITH) of key transcription factors (TFs) in SCLC and related gene expression patterns and functions. The non-neuroendocrine (non-NE) tumors were correlated with increased inflammatory gene signatures and immune cell infiltrates in SCLC, which contributed to better responses to immune checkpoint inhibitors. These findings indicate a significant heterogeneity of human SCLC, and intensive crosstalk between cancer cells and the TME at single-cell resolution, and thus, set the stage for a better understanding of the biology of SCLC as well as for developing new therapeutics for SCLC.
View details for DOI 10.1038/s41392-022-01150-4
View details for PubMedID 36195615
Single-cell transcriptome and genome analyses of pituitary neuroendocrine tumors
2021; 23 (11): 1859-1871
Pituitary neuroendocrine tumors (PitNETs) are the second most common intracranial tumor. We lacked a comprehensive understanding of the pathogenesis and heterogeneity of these tumors.We performed high-precision single-cell RNA sequencing for 2679 individual cells obtained from 23 surgically resected samples of the major subtypes of PitNETs from 21 patients. We also performed single-cell multi-omics sequencing for 238 cells from 5 patients.Unsupervised clustering analysis distinguished all tumor subtypes, which was in accordance with the classification based on immunohistochemistry and provided additional information. We identified 3 normal endocrine cell types: somatotrophs, lactotrophs, and gonadotrophs. Comparisons of tumor and matched normal cells showed that differentially expressed genes of gonadotroph tumors were predominantly downregulated, while those of somatotroph and lactotroph tumors were mainly upregulated. We identified novel tumor-related genes, such as AMIGO2, ZFP36, BTG1, and DLG5. Tumors expressing multiple hormone genes showed little transcriptomic heterogeneity. Furthermore, single-cell multi-omics analysis demonstrated that the tumor had a relatively uniform pattern of genome with slight heterogeneity in copy number variations.Our single-cell transcriptome and single-cell multi-omics analyses provide novel insights into the characteristics and heterogeneity of these complex neoplasms for the identification of biomarkers and therapeutic targets.
View details for DOI 10.1093/neuonc/noab102
View details for Web of Science ID 000718357900012
View details for PubMedID 33908609
View details for PubMedCentralID PMC8563320
Single-cell transcriptomics identifies divergent developmental lineage trajectories during human pituitary development
2020; 11 (1): 5275
The anterior pituitary gland plays a central role in regulating various physiological processes, including body growth, reproduction, metabolism and stress response. Here, we perform single-cell RNA-sequencing (scRNA-seq) of 4113 individual cells from human fetal pituitaries. We characterize divergent developmental trajectories with distinct transitional intermediate states in five hormone-producing cell lineages. Corticotropes exhibit an early intermediate state prior to full differentiation. Three cell types of the PIT-1 lineage (somatotropes, lactotropes and thyrotropes) segregate from a common progenitor coexpressing lineage-specific transcription factors of different sublineages. Gonadotropes experience two multistep developmental trajectories. Furthermore, we identify a fetal gonadotrope cell subtype expressing the primate-specific hormone chorionic gonadotropin. We also characterize the cellular heterogeneity of pituitary stem cells and identify a hybrid epithelial/mesenchymal state and an early-to-late state transition. Here, our results provide insights into the transcriptional landscape of human pituitary development, defining distinct cell substates and subtypes and illustrating transcription factor dynamics during cell fate commitment.
View details for DOI 10.1038/s41467-020-19012-4
View details for Web of Science ID 000585918500010
View details for PubMedID 33077725
View details for PubMedCentralID PMC7572359
A single-cell transcriptomic landscape of primate arterial aging
2020; 11 (1): 2202
Our understanding of how aging affects the cellular and molecular components of the vasculature and contributes to cardiovascular diseases is still limited. Here we report a single-cell transcriptomic survey of aortas and coronary arteries in young and old cynomolgus monkeys. Our data define the molecular signatures of specialized arteries and identify eight markers discriminating aortic and coronary vasculatures. Gene network analyses characterize transcriptional landmarks that regulate vascular senility and position FOXO3A, a longevity-associated transcription factor, as a master regulator gene that is downregulated in six subtypes of monkey vascular cells during aging. Targeted inactivation of FOXO3A in human vascular endothelial cells recapitulates the major phenotypic defects observed in aged monkey arteries, verifying FOXO3A loss as a key driver for arterial endothelial aging. Our study provides a critical resource for understanding the principles underlying primate arterial aging and contributes important clues to future treatment of age-associated vascular disorders.
View details for DOI 10.1038/s41467-020-15997-0
View details for Web of Science ID 000532362000001
View details for PubMedID 32371953
View details for PubMedCentralID PMC7200799
Decoding the development of the human hippocampus
2020; 577 (7791): 531-+
The hippocampus is an important part of the limbic system in the human brain that has essential roles in spatial navigation and the consolidation of information from short-term memory to long-term memory1,2. Here we use single-cell RNA sequencing and assay for transposase-accessible chromatin using sequencing (ATAC-seq) analysis to illustrate the cell types, cell linage, molecular features and transcriptional regulation of the developing human hippocampus. Using the transcriptomes of 30,416 cells from the human hippocampus at gestational weeks 16-27, we identify 47 cell subtypes and their developmental trajectories. We also identify the migrating paths and cell lineages of PAX6+ and HOPX+ hippocampal progenitors, and regional markers of CA1, CA3 and dentate gyrus neurons. Multiomic data have uncovered transcriptional regulatory networks of the dentate gyrus marker PROX1. We also illustrate spatially specific gene expression in the developing human prefrontal cortex and hippocampus. The molecular features of the human hippocampus at gestational weeks 16-20 are similar to those of the mouse at postnatal days 0-5 and reveal gene expression differences between the two species. Transient expression of the primate-specific gene NBPF1 leads to a marked increase in PROX1+ cells in the mouse hippocampus. These data provides a blueprint for understanding human hippocampal development and a tool for investigating related diseases.
View details for DOI 10.1038/s41586-019-1917-5
View details for Web of Science ID 000509200100018
View details for PubMedID 31942070
A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex
2018; 555 (7697): 524-+
The mammalian prefrontal cortex comprises a set of highly specialized brain areas containing billions of cells and serves as the centre of the highest-order cognitive functions, such as memory, cognitive ability, decision-making and social behaviour. Although neural circuits are formed in the late stages of human embryonic development and even after birth, diverse classes of functional cells are generated and migrate to the appropriate locations earlier in development. Dysfunction of the prefrontal cortex contributes to cognitive deficits and the majority of neurodevelopmental disorders; there is therefore a need for detailed knowledge of the development of the prefrontal cortex. However, it is still difficult to identify cell types in the developing human prefrontal cortex and to distinguish their developmental features. Here we analyse more than 2,300 single cells in the developing human prefrontal cortex from gestational weeks 8 to 26 using RNA sequencing. We identify 35 subtypes of cells in six main classes and trace the developmental trajectories of these cells. Detailed analysis of neural progenitor cells highlights new marker genes and unique developmental features of intermediate progenitor cells. We also map the timeline of neurogenesis of excitatory neurons in the prefrontal cortex and detect the presence of interneuron progenitors in early developing prefrontal cortex. Moreover, we reveal the intrinsic development-dependent signals that regulate neuron generation and circuit formation using single-cell transcriptomic data analysis. Our screening and characterization approach provides a blueprint for understanding the development of the human prefrontal cortex in the early and mid-gestational stages in order to systematically dissect the cellular basis and molecular regulation of prefrontal cortex function in humans.
View details for DOI 10.1038/nature25980
View details for Web of Science ID 000427937900054
View details for PubMedID 29539641