Spatial atlas of the mouse central nervous system at molecular resolution.

Spatially charting molecular cell types at single-cell resolution across the 3D volume is critical for illustrating the molecular basis of brain anatomy and functions. Single-cell RNA sequencing has profiled molecular cell types in the mouse brain1,2, but cannot capture their spatial organization. Here we used an in situ sequencing method, STARmap PLUS3,4, to profile 1,022 genes in 3D at a voxel size of 194 × 194 × 345 nm3, mapping 1.09 million high-quality cells across the adult mouse brain and spinal cord. We developed computational pipelines to segment, cluster and annotate 230 molecular cell types by single-cell gene expression and 106 molecular tissue regions by spatial niche gene expression. Joint analysis of molecular cell types and molecular tissue regions enabled a systematic molecular spatial cell-type nomenclature and identification of tissue architectures that were undefined in established brain anatomy. To create a transcriptome-wide spatial atlas, we integrated STARmap PLUS measurements with a published single-cell RNA-sequencing atlas1, imputing single-cell expression profiles of 11,844 genes. Finally, we delineated viral tropisms of a brain-wide transgene delivery tool, AAV-PHP.eB5,6. Together, this annotated dataset provides a single-cell resource that integrates the molecular spatial atlas, brain anatomy and the accessibility to genetic manipulation of the mammalian central nervous system.

GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA.

In 2017, we released GEPIA (Gene Expression Profiling Interactive Analysis) webserver to facilitate the widely used analyses based on the bulk gene expression datasets in the TCGA and the GTEx projects, providing the biologists and clinicians with a handy tool to perform comprehensive and complex data mining tasks. Recently, the deconvolution tools have led to revolutionary trends to resolve bulk RNA datasets at cell type-level resolution, interrogating the characteristics of different cell types in cancer and controlled cohorts became an important strategy to investigate the biological questions. Thus, we present GEPIA2021, a standalone extension of GEPIA, allowing users to perform multiple interactive analysis based on the deconvolution results, including cell type-level proportion comparison, correlation analysis, differential expression, and survival analysis. With GEPIA2021, experimental biologists could easily explore the large TCGA and GTEx datasets and validate their hypotheses in an enhanced resolution. GEPIA2021 is publicly accessible at http://gepia2021.cancer-pku.cn/.

Disease network delineates the disease progression profile of cardiovascular diseases.

OBJECTIVE: As Electronic Health Records (EHR) data accumulated explosively in recent years, the tremendous amount of patient clinical data provided opportunities to discover real world evidence. In this study, a graphical disease network, named progressive cardiovascular disease network (progCDN), was built to delineate the progression profiles of cardiovascular diseases (CVD). MATERIALS AND METHODS: The EHR data of 14.3 million patients with CVD diagnoses were collected for building disease network and further analysis. We applied a new designed method, progression rates (PR), to calculate the progression relationship among different diagnoses. Based on the disease network outcome, 23 disease progression pair were selected to screen for salient features. RESULTS: The network depicted the dominant diseases in CVD development, such as the heart failure and coronary arteriosclerosis. Novel progression relationships were also discovered, such as the progression path from long QT syndrome to major depression. In addition, three age-group progCDNs identified a series of age-associated disease progression paths and important successor diseases with age bias. Furthermore, a list of important features with sufficient abundance and high correlation was extracted for building disease risk models. DISCUSSION: The PR method designed for identifying the progression relationship could be widely applied in any EHR database due to its flexibility and robust functionality. Meanwhile, researchers could use the progCDN network to validate or explore novel disease relationships in real world data. CONCLUSION: The first-time interrogation of such a huge CVD patients cohort enabled us to explore the general and age-specific disease progression patterns in CVD development.

GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis.

Introduced in 2017, the GEPIA (Gene Expression Profiling Interactive Analysis) web server has been a valuable and highly cited resource for gene expression analysis based on tumor and normal samples from the TCGA and the GTEx databases. Here, we present GEPIA2, an updated and enhanced version to provide insights with higher resolution and more functionalities. Featuring 198 619 isoforms and 84 cancer subtypes, GEPIA2 has extended gene expression quantification from the gene level to the transcript level, and supports analysis of a specific cancer subtype, and comparison between subtypes. In addition, GEPIA2 has adopted new analysis techniques of gene signature quantification inspired by single-cell sequencing studies, and provides customized analysis where users can upload their own RNA-seq data and compare them with TCGA and GTEx samples. We also offer an API for batch process and easy retrieval of the analysis results. The updated web server is publicly accessible at http://gepia2.cancer-pku.cn/.

Cholesterol biosynthesis supports the growth of hepatocarcinoma lesions depleted of fatty acid synthase in mice and humans.

OBJECTIVE: Increased de novo fatty acid (FA) synthesis and cholesterol biosynthesis have been independently described in many tumour types, including hepatocellular carcinoma (HCC). DESIGN: We investigated the functional contribution of fatty acid synthase (Fasn)-mediated de novo FA synthesis in a murine HCC model induced by loss of Pten and overexpression of c-Met (sgPten/c-Met) using liver-specific Fasn knockout mice. Expression arrays and lipidomic analysis were performed to characterise the global gene expression and lipid profiles, respectively, of sgPten/c-Met HCC from wild-type and Fasn knockout mice. Human HCC cell lines were used for in vitro studies. RESULTS: Ablation of Fasn significantly delayed sgPten/c-Met-driven hepatocarcinogenesis in mice. However, eventually, HCC emerged in Fasn knockout mice. Comparative genomic and lipidomic analyses revealed the upregulation of genes involved in cholesterol biosynthesis, as well as decreased triglyceride levels and increased cholesterol esters, in HCC from these mice. Mechanistically, loss of Fasn promoted nuclear localisation and activation of sterol regulatory element binding protein 2 (Srebp2), which triggered cholesterogenesis. Blocking cholesterol synthesis via the dominant negative form of Srebp2 (dnSrebp2) completely prevented sgPten/c-Met-driven hepatocarcinogenesis in Fasn knockout mice. Similarly, silencing of FASN resulted in increased SREBP2 activation and hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase (HMGCR) expression in human HCC cell lines. Concomitant inhibition of FASN-mediated FA synthesis and HMGCR-driven cholesterol production was highly detrimental for HCC cell growth in culture. CONCLUSION: Our study uncovers a novel functional crosstalk between aberrant lipogenesis and cholesterol biosynthesis pathways in hepatocarcinogenesis, whose concomitant inhibition might represent a therapeutic option for HCC.

GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.

Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.

GE-mini: a mobile APP for large-scale gene expression visualization.

Summary: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects produced large-scale RNA sequencing data, which provides an opportunity for performing integrated expression analysis for all genes across tens of thousands of tumor and normal tissue specimens. Rapid access to and easy visualization of such valuable data could facilitate research in a wide biological area. Here, we present the GE-mini APP for smart phones, a mobile visualization tool for integrated gene expression data based on both TCGA and GTEx. This gene-centric expression viewer provides a convenient method for displaying expression profiles of all available tumor and tissue types, while allowing drilling down to detailed views for specific tissue types. Availability and Implementation: Both the iOS and Android APPs are freely available to all non-commercial users in App Store and Google Play. The QR codes of App store and Google play are also provided for scanning and download. The GE-mini web server is also available at http://gemini.cancer-pku.cn/ . Contacts: tangzefang@pku.edu.cn or huxueda@pku.edu.cn. Supplementary information: Supplementary data are available at Bioinformatics online.

RNA editing is induced by type I interferon in esophageal squamous cell carcinoma.

In recent years, abnormal RNA editing has been shown to play an important role in the development of esophageal squamous cell carcinoma, as such abnormal editing is catalyzed by ADAR (adenosine deaminases acting on RNA). However, the regulatory mechanism of ADAR1 in esophageal squamous cell carcinomas remains largely unknown. In this study, we investigated ADAR1 expression and its association with RNA editing in esophageal squamous cell carcinomas. RNA sequencing applied to esophageal squamous cell carcinoma clinical samples showed that ADAR1 expression was correlated with the expression of STAT1, STAT2, and IRF9. In vitro experiments showed that the abundance of ADAR1 protein was associated with the induced activation of the JAK/STAT pathway by type I interferon. RNA sequencing results showed that treatment with type I interferon caused an increase in the number and degree of RNA editing in esophageal squamous cell carcinoma cell lines. In conclusion, the activation of the JAK/STAT pathway is a regulatory mechanism of ADAR1 expression and causes abnormal RNA editing profile in esophageal squamous cell carcinoma. This mechanism may serve as a new target for esophageal squamous cell carcinoma therapy.

Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer's disease.

Complex diseases are characterized by spatiotemporal cellular and molecular changes that may be difficult to comprehensively capture. However, understanding the spatiotemporal dynamics underlying pathology can shed light on disease mechanisms and progression. Here we introduce STARmap PLUS, a method that combines high-resolution spatial transcriptomics with protein detection in the same tissue section. As proof of principle, we analyze brain tissues of a mouse model of Alzheimer's disease at 8 and 13 months of age. Our approach provides a comprehensive cellular map of disease progression. It reveals a core-shell structure where disease-associated microglia (DAM) closely contact amyloid-ß plaques, whereas disease-associated astrocyte-like (DAA-like) cells and oligodendrocyte precursor cells (OPCs) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerges mainly in excitatory neurons in the CA1 region and correlates with the local enrichment of oligodendrocyte subtypes. The STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing a tool to pinpoint the molecular and cellular changes underlying pathology.

Spatially resolved single-cell translatomics at molecular resolution.

The precise control of messenger RNA (mRNA) translation is a crucial step in posttranscriptional gene regulation of cellular physiology. However, it remains a challenge to systematically study mRNA translation at the transcriptomic scale with spatial and single-cell resolution. Here, we report the development of ribosome-bound mRNA mapping (RIBOmap), a highly multiplexed three-dimensional in situ profiling method to detect cellular translatome. RIBOmap profiling of 981 genes in HeLa cells revealed cell cycle-dependent translational control and colocalized translation of functional gene modules. We mapped 5413 genes in mouse brain tissues, yielding spatially resolved single-cell translatomic profiles for 119,173 cells and revealing cell type-specific and brain region-specific translational regulation, including translation remodeling during oligodendrocyte maturation. Our method detected widespread patterns of localized translation in neuronal and glial cells in intact brain tissue networks.

Deubiquitinating enzyme OTUB1 promotes cancer cell immunosuppression via preventing ER-associated degradation of immune checkpoint protein PD-L1.

Upregulation of programmed death ligand 1 (PD-L1) helps tumor cells escape from immune surveillance, and therapeutic antibodies targeting PD-1/PD-L1 have shown better patient outcomes only in several types of malignancies. Recent studies suggest that the clinical efficacy of anti-PD-1/PD-L1 treatments is associated with PD-L1 levels; however, the underlying mechanism of high PD-L1 protein levels in cancers is not well defined. Here, we report that the deubiquitinase OTUB1 positively regulates PD-L1 stability and mediates cancer immune responses through the PD-1/PD-L1 axis. Mechanistically, we demonstrate that OTUB1 interacts with and removes K48-linked ubiquitin chains from the PD-L1 intracellular domain in a manner dependent on its deubiquitinase activity to hinder the degradation of PD-L1 through the ERAD pathway. Functionally, depletion of OTUB1 markedly decreases PD-L1 abundance, reduces PD-1 protein binding to the tumor cell surface, and causes increased tumor cell sensitivity to human peripheral blood mononuclear cells (PBMCs)-mediated cytotoxicity. Meanwhile, OTUB1 ablation-induced PD-L1 destabilization facilitates more CD8+ T cells infiltration and increases the level of IFN-γ in serum to enhance antitumor immunity in mice, and the tumor growth suppression by OTUB1 silencing could be reversed by PD-L1 overexpression. Furthermore, we observe a significant correlation between PD-L1 abundance and OTUB1 expression in human breast carcinoma. Our study reveals OTUB1 as a deubiquitinating enzyme that influences cancer immunosuppression via regulation of PD-L1 stability and may be a potential therapeutic target for cancer immunotherapy.

Identification of transcriptional isoforms associated with survival in cancer patient.

The Cancer Genome Atlas (TCGA) project produced RNA-Seq data for tens of thousands of cancer and non-cancer samples with clinical survival information, providing an unprecedented opportunity for analyzing prognostic genes and their isoforms. In this study, we performed the first large-scale identification of transcriptional isoforms that are specifically associated with patient prognosis, even without gene-level association. These specific isoforms are defined as Transcripts Associated with Patient Prognosis (TAPPs). Although a group of TAPPs are the principal isoforms of their genes with intact functional protein domains, another group of TAPPs lack important protein domains found in their canonical gene isoforms. This dichotomy in the distribution of protein domains may indicate different patterns of TAPPs association with cancer. TAPPs in protein-coding genes, especially those with altered protein domains, are rich in known cancer driver genes. We further identified multiple types of cancer recurrent TAPPs, such as DCAF17-201, providing a new approach for the detection of cancer-associated events. In order to make the wide research community to study prognostic isoforms, we developed a portal named GESUR (http://gesur.cancer-pku.cn/), which illustrates the detailed prognostic characteristics of TAPPs and other isoforms. Overall, our integrated analysis of gene expression and clinical parameters provides a new perspective for understanding the applications of different gene isoforms in tumor progression.

hCINAP regulates the DNA-damage response and mediates the resistance of acute myelocytic leukemia cells to therapy.

Acute myeloid leukemia (AML) is a genetically heterogeneous malignant disorder of the hematopoietic system, characterized by the accumulation of DNA-damaged immature myeloid precursors. Here, we find that hCINAP is involved in the repair of double-stranded DNA breaks (DSB) and that its expression correlates with AML prognosis. Following DSB, hCINAP is recruited to damage sites where it promotes SENP3-dependent deSUMOylation of NPM1. This in turn results in the dissociation of RAP80 from the damage site and CTIP-dependent DNA resection and homologous recombination. NPM1 SUMOylation is required for recruitment of DNA repair proteins at the early stage of DNA-damage response (DDR), and SUMOylated NPM1 impacts the assembly of the BRCA1 complex. Knockdown of hCINAP also sensitizes a patient-derived xenograft (PDX) mouse model to chemotherapy. In clinical AML samples, low hCINAP expression is associated with a higher overall survival rate in patients. These results provide mechanistic insight into the function of hCINAP during the DNA-damage response and its role in AML resistance to therapy.

A20/TNFAIP3 Regulates the DNA Damage Response and Mediates Tumor Cell Resistance to DNA-Damaging Therapy.

A competent DNA damage response (DDR) helps prevent cancer, but once cancer has arisen, DDR can blunt the efficacy of chemotherapy and radiotherapy that cause lethal DNA breakage in cancer cells. Thus, blocking DDR may improve the efficacy of these modalities. Here, we report a new DDR mechanism that interfaces with inflammatory signaling and might be blocked to improve anticancer outcomes. Specifically, we report that the ubiquitin-editing enzyme A20/TNFAIP3 binds and inhibits the E3 ubiquitin ligase RNF168, which is responsible for regulating histone H2A turnover critical for proper DNA repair. A20 induced after DNA damage disrupted RNF168-H2A interaction in a manner independent of its enzymatic activity. Furthermore, it inhibited accumulation of RNF168 and downstream repair protein 53BP1 during DNA repair. A20 was also required for disassembly of RNF168 and 53BP1 from damage sites after repair. Conversely, A20 deletion increased the efficiency of error-prone nonhomologous DNA end-joining and decreased error-free DNA homologous recombination, destablizing the genome and increasing sensitivity to DNA damage. In clinical specimens of invasive breast carcinoma, A20 was widely overexpressed, consistent with its candidacy as a therapeutic target. Taken together, our findings suggest that A20 is critical for proper functioning of the DDR in cancer cells and it establishes a new link between this NFκB-regulated ubiquitin-editing enzyme and the DDR pathway.Significance: This study identifies the ubiquitin-editing enzyme A20 as a key factor in mediating cancer cell resistance to DNA-damaging therapy, with implications for blocking its function to leverage the efficacy of chemotherapy and radiotherapy. Cancer Res; 78(4); 1069-82. ©2017 AACR.

Adenylate kinase hCINAP determines self-renewal of colorectal cancer stem cells by facilitating LDHA phosphorylation.

Targeting the specific metabolic phenotypes of colorectal cancer stem cells (CRCSCs) is an innovative therapeutic strategy for colorectal cancer (CRC) patients with poor prognosis and relapse. However, the context-dependent metabolic traits of CRCSCs remain poorly elucidated. Here we report that adenylate kinase hCINAP is overexpressed in CRC tissues. Depletion of hCINAP inhibits invasion, self-renewal, tumorigenesis and chemoresistance of CRCSCs with a loss of mesenchymal signature. Mechanistically, hCINAP binds to the C-terminal domain of LDHA, the key regulator of glycolysis, and depends on its adenylate kinase activity to promote LDHA phosphorylation at tyrosine 10, resulting in the hyperactive Warburg effect and the lower cellular ROS level and conferring metabolic advantage to CRCSC invasion. Moreover, hCINAP expression is positively correlated with the level of Y10-phosphorylated LDHA in CRC patients. This study identifies hCINAP as a potent modulator of metabolic reprogramming in CRCSCs and a promising drug target for CRC invasion and metastasis.

Corrigendum: Adenylate kinase hCINAP determines self-renewal of colorectal cancer stem cells by facilitating LDHA phosphorylation.

This corrects the article DOI: 10.1038/ncomms15308.

Metallothionein prevention of arsenic trioxide-induced cardiac cell death is associated with its inhibition of mitogen-activated protein kinases activation in vitro and in vivo.

Cardiotoxicity induced by arsenic trioxide has become a serious blockade of clinical applications of this effective anticancer agent. The general mechanism responsible for arsenic cardiotoxicity has been attributed to its induction of oxidative stress. Metallothionein (MT) has been extensively proven to be a potent endogenous antioxidant that protects heart against oxidative stress-induced cardiac damage. To investigate whether and how MT protects against arsenic cardiotoxicity, MT-overexpressing H9c2 (MT-H9c2) cardiac cells and transgenic (MT-TG) mice with their corresponding controls were exposed to the clinical relevant dose of arsenic trioxide. Cardiac cell apoptosis was detected by molecular indices, including the cleavage of caspase 3 and caspase 12, Bax/Bcl2 expression ratio, CHOP expression and/or confirmed by a terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling assay. Arsenic trioxide dose- and time-dependently induced cardiac cell death in H9c2 cells with a significant activation of major MAPK subfamily members such as ERK1/2, JNK and p38, but not in MT-H9c2 cells. Importantly, the protective effect of MT on arsenic trioxide-induced apoptotic cell death was completely recaptured in the heart of MT-TG with a significant prevention of MAPKs activation. These results indicate that arsenic trioxide-upregulated MAPKs might play important role in arsenic trioxide-induced apoptotic cell death in cardiac cells both in vivo and in vitro, and MT's suppression of arsenic trioxide apoptotic effect was associated with the inhibition of MAPK activation. Therefore, selective elevation of cardiac MT levels with pharmacological approaches may be a potential strategy for the prevention of arsenic cardiotoxicity.