Analysis of Gene Expression and TCR/B Cell Receptor Profiling of Immune Cells in Primary Sjögren's Syndrome by Single-Cell Sequencing.

Primary Sjögren's syndrome (pSS) is a chronic autoimmune disease that is estimated to affect 35 million people worldwide and is characterized by lymphocytic infiltration, elevated circulating autoantibodies, and proinflammatory cytokines. The key immune cell subset changes and the TCR/BCR repertoire alterations in pSS patients remain unclear. In this study, we sought to comprehensively characterize the transcriptional changes in PBMCs of pSS patients by single-cell RNA sequencing and single-cell V(D)J sequencing. Naive CD8+ T cells and mucosal-associated invariant T cells were markedly decreased but regulatory T cells were increased in pSS patients. There were a large number of differentially expressed genes shared by multiple subpopulations of T cells and B cells. Abnormal signaling pathways, including Ag processing and presentation, the BCR signaling pathway, the TCR signaling pathway, and Epstein-Barr virus infection, were highly enriched in pSS patients. Moreover, there were obvious differences in the CD30, FLT3, IFN-II, IL-1, IL-2, IL-6, IL-10, RESISTIN, TGF-ß, TNF, and VEGF signaling networks between pSS patients and healthy controls. Single-cell TCR and BCR repertoire analysis showed that there was a lower diversity of T cells in pSS patients than in healthy controls; however, there was no significant difference in the degree of clonal expansion, CDR3 length distribution, or degree of sequence sharing. Notably, our results further emphasize the functional importance of αß pairing in determining Ag specificity. In conclusion, our analysis provides a comprehensive single-cell map of gene expression and TCR/BCR profiles in pSS patients for a better understanding of the pathogenesis, diagnosis, and treatment of pSS.

Analysis of proteome and post-translational modifications of 2-hydroxyisobutyrylation reveals the glycolysis pathway in oral adenoid cystic carcinoma.

PURPOSE: Oral adenoid cystic carcinoma (OACC) has high rates of both local-regional recurrence and distant metastasis. The objective of this study is to investigate the impact of Khib on OACC and its potential as a targeted therapeutic intervention. EXPERIMENTAL DESIGN: We investigated the DEPs (differentially expressed proteins) and DHMPs between OACC-T and OACC-N using LC-MS/MS-based quantitative proteomics and using several bioinformatics methods, including GO enrichment analysis, KEGG pathway analysis, subcellular localization prediction, MEA (motif enrichment analysis), and PPI (protein-protein interaction networks) to illustrate how Khib modification interfere with OACC evolution. RESULTS: Compared OACC-tumor samples (OACC-T) with the adjacent normal samples (OACC-N), there were 3243 of the DEPs and 2011 Khib sites were identified on 764 proteins (DHMPs). DEPs and DHMPs were strongly associated to glycolysis pathway. GAPDH of K254, ENO of K228, and PGK1 of K323 were modified by Khib in OACC-T. Khib may increase the catalytic efficiency to promote glycolysis pathway and favor OACC progression. CONCLUSIONS AND CLINICAL RELEVANCE: Khib may play a significant role in the mechanism of OACC progression by influencing the enzyme activity of the glycolysis pathway. These findings may provide new therapeutic options of OACC.

A histone deacetylase inhibitor enhances expression of genes inhibiting Wnt pathway and augments activity of DNA demethylation reagent against nonsmall-cell lung cancer.

Development of new inhibitors targeting histone deacetylases (HDACs) with improved efficacy for solid tumor therapy is urgently needed. Here, we report the development of a novel HDAC inhibitor TMU-35435 and verify it as a single agent and in combination treatment with DNA demethylation reagent 5-aza-2'-deoxycytidine (5-aza-dC) in lung cancer preclinical models. TMU-35435 exerted cancer-specific cytotoxicity via mitochondria-mediated apoptosis. Expression microarrays revealed a unique TMU-35435-induced gene networks enriched in biological processes, including "negative regulation of cell proliferation" and "Wnt receptor signaling pathway" compared to FDA-approved HDAC inhibitor SAHA. TMU-35435 inhibited tumor growth with good pharmacokinetic properties and safety features in lung orthotopic and subcutaneously implanted xenograft models. TMU-35435 and 5-aza-dC showed synergistic antitumor effects through reactivation of tumor suppressor genes and those genes encoding negative regulators of Wnt signaling pathway in vitro and in vivo. Some genes showed additive inhibition of DNA methylation upon TMU-35435 and 5-aza-dC combined treatment. Our findings suggested that TMU-35435 is a potential HDAC inhibitor for lung cancer treatment as a single agent and in combination with 5-aza-dC.

Gallic acid inhibits gastric cancer cells metastasis and invasive growth via increased expression of RhoB, downregulation of AKT/small GTPase signals and inhibition of NF-κB activity.

Our previous study demonstrated the therapeutic potential of gallic acid (GA) for controlling tumor metastasis through its inhibitory effect on the motility of AGS cells. A noteworthy finding in our previous experiment was increased RhoB expression in GA-treated cells. The aim of this study was to evaluate the role of RhoB expression on the inhibitory effects of GA on AGS cells. By applying the transfection of RhoB siRNA into AGS cells and an animal model, we tested the effect of GA on inhibition of tumor growth and RhoB expression. The results confirmed that RhoB-siRNA transfection induced GA to inhibit AGS cells' invasive growth involving blocking the AKT/small GTPase signals pathway and inhibition of NF-κB activity. Finally, we evaluated the effect of GA on AGS cell metastasis by colonization of tumor cells in nude mice. It showed GA inhibited tumor cells growth via the expression of RhoB. These data support the inhibitory effect of GA which was shown to inhibit gastric cancer cell metastasis and invasive growth via increased expression of RhoB, downregulation of AKT/small GTPase signals and inhibition of NF-κB activity. Thus, GA might be a potential agent in treating gastric cancer.

Single-cell profiling of lncRNAs in human germ cells and molecular analysis reveals transcriptional regulation of LNC1845 on LHX8.

Non-coding RNAs exert diverse functions in many cell types. In addition to transcription factors from coding genes, non-coding RNAs may also play essential roles in shaping and directing the fate of germ cells. The presence of many long non-coding RNAs (lncRNAs) which are specifically expressed in the germ cells during human gonadal development were reported and one divergent lncRNA, LNC1845, was functionally characterized. Comprehensive bioinformatic analysis of these lncRNAs indicates that divergent lncRNAs occupied the majority of female and male germ cells. Integrating lncRNA expression into the bioinformatic analysis also enhances the cell-type classification of female germ cells. Functional dissection using in vitro differentiation of human pluripotent stem cells to germ cells revealed the regulatory role of LNC1845 on a transcription factor essential for ovarian follicle development, LHX8, by modulating the levels of histone modifications, H3K4me3 and H3K27Ac. Hence, bioinformatical analysis and experimental verification provide a comprehensive analysis of lncRNAs in developing germ cells and elucidate how an lncRNA function as a cis regulator during human germ cell development.

Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells.

Background: Sjögren's syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis. Methods: We downloaded three datasets of SS patients' and healthy pepole's whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers' diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied. Results: We obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2. Conclusion: In this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

Serum metabolomics analysis reveals metabolite profile and key biomarkers of idiopathic membranous nephropathy.

Background: Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease with multiple and complex pathogenic mechanisms. Currently, renal biopsy is considered the gold standard for diagnosing membranous nephropathy. However, there were limitations to the renal puncture biopsy, such as the relatively high cost, longer time consuming, and the risk of invasive procedures. We investigated the profile of serum metabolites in IMN patients based on the UHPLC-QE-MS metabolomics technique for exploring the potential disease biomarkers and clinical implementation. Methods: In our research, we collected serum samples from healthy control (n = 15) and IMN patients (n = 25) to perform metabolomics analysis based on the UHPLC-QE-MS technique. Result: We identified 215 differentially expressed metabolites (DEMs) between the IMN and healthy control (HC) groups. Furthermore, these DEMs were significantly identified in histidine metabolism, arginine and proline metabolism, pyrimidine metabolism, purine metabolism, and steroid hormone biosynthesis. Several key DEMs were significantly correlated with the level of clinical parameters, such as serum albumin, IgG, UTP, and cholesterol. Among them, dehydroepiandrosterone sulfate (DHEAS) was considered the reliable diagnostic biomarker in the IMN group. There was an increased abundance of actinobacteria, phylum proteobacteria, and class gammaproteobacterial in IMN patients for host-microbiome origin analysis. Conclusion: Our study revealed the profiles of DEMs from the IMN and HC groups. The result demonstrated that there were disorders of amino acids, nucleotides, and steroids hormones metabolism in IMN patients. The down-regulation of DHEAS may be associated with the imbalance of the immune environment in IMN patients. In host-microbiome origin analysis, the gut microbiota and metabolite disturbances were present in IMN patients.

Metabolic profiling reveals altered tryptophan metabolism in patients with kawasaki disease.

Kawasaki disease (KD) is a childhood vasculitis disease that is difficult to diagnose, and there is an urgent need for the identification of accurate and specific biomarkers. Here, we aimed to investigate metabolic alterations in patients with KD to determine novel diagnostic and prognostic biomarkers for KD. To this end, we performed untargeted metabolomics and found that several metabolic pathways were significantly enriched, including amino acid, lipid, and tryptophan metabolism, the latter of which we focused on particularly. Tryptophan-targeted metabolomics was conducted to explore the role of tryptophan metabolism in KD. The results showed that Trp and indole acetic acid (IAA) levels markedly decreased, and that l-kynurenine (Kyn) and kynurenic acid (Kyna) levels were considerably higher in patients with KD than in healthy controls. Changes in Trp, IAA, Kyn, and Kyna levels in a KD coronary arteritis mouse model were consistent with those in patients with KD. We further analyzed public single-cell RNA sequencing data of patients with KD and revealed that their peripheral blood mononuclear cells showed Aryl hydrocarbon receptor expression that was remarkably higher than that of healthy children. These results suggest that the Trp metabolic pathway is significantly altered in KD and that metabolic indicators may serve as novel diagnostic and therapeutic biomarkers for KD.

Proteomics profiling and lysine malonylation analysis in primary Sjogren's syndrome.

Primary Sjogren's Syndrome (pSS) is a chronic autoimmune disease, with unclear pathogenies. Lysine-malonylation (Kmal) as a novel post-translational modification (PTMs) was found associated with metabolic, immune, and inflammatory processes. For purpose of investigating the proteomic profile and functions of kmal in pSS, liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis and bioinformatics analysis are performed based on twenty-eight pSS patients versus twenty-seven healthy controls (HCs). A total of 331 down-regulated proteins and 289 up-regulated proteins are observed in differentially expressed proteins (DEPs) of pSS. We discover the expression of transforming growth factor beta-1 (TGFB1) and CD40 ligand downregulate which enriches in the inflammatory associated pathway. Expression of signal transducer and activator of transcription 1-alpha/beta (STAT1) show upregulation and enrich in type I interferon signaling pathway and IL-27-mediated signaling pathway. In differentially malonylated proteins (DMPs) of pSS, we identify 3 proteins are down-regulated in 7 sites and 18 proteins are up-regulated in 19 sites. Expression of malonylated integrin-linked kinase (ILK) significantly enrich in the focal adhesion pathway. Together, our data provide evidence that downregulation of TGFB1 and CD40LG play a critical role in the inflammatory process of pSS, while upregulation of STAT1 may be associated with IL-27 immunity and pSS immune dysfunction. Moreover, kmal modification at the kinase domain of ILK may destabilize ILK that thus contributing to pSS pathogenies by regulating the focal adhesion pathway. SIGNIFICANCE: Our research offered the first characterization of Kmal, a newly identified form of lysine acylation in pSS, as well as proteomic data on individuals with pSS. In this study, we found that several key DMPs were associated with focal adhesion pathway, which contributes to the development of pSS. The present results provide an informative dataset for the future exploration of Kmal in pSS.

SND1 binds to ERG and promotes tumor growth in genetic mouse models of prostate cancer.

SND1 and MTDH are known to promote cancer and therapy resistance, but their mechanisms and interactions with other oncogenes remain unclear. Here, we show that oncoprotein ERG interacts with SND1/MTDH complex through SND1's Tudor domain. ERG, an ETS-domain transcription factor, is overexpressed in many prostate cancers. Knocking down SND1 in human prostate epithelial cells, especially those overexpressing ERG, negatively impacts cell proliferation. Transcriptional analysis shows substantial overlap in genes regulated by ERG and SND1. Mechanistically, we show that ERG promotes nuclear localization of SND1/MTDH. Forced nuclear localization of SND1 prominently increases its growth promoting function irrespective of ERG expression. In mice, prostate-specific Snd1 deletion reduces cancer growth and tumor burden in a prostate cancer model (PB-Cre/Ptenflox/flox/ERG mice), Moreover, we find a significant overlap between prostate transcriptional signatures of ERG and SND1. These findings highlight SND1's crucial role in prostate tumorigenesis, suggesting SND1 as a potential therapeutic target in prostate cancer.

NAD+ rescues aging-induced blood-brain barrier damage via the CX43-PARP1 axis.

Blood-brain barrier (BBB) function deteriorates during aging, contributing to cognitive impairment and neurodegeneration. It is unclear what drives BBB leakage in aging and how it can be prevented. Using single-nucleus transcriptomics, we identified decreased connexin 43 (CX43) expression in cadherin-5+ (Cdh5+) cerebral vascular cells in naturally aging mice and confirmed it in human brain samples. Global or Cdh5+ cell-specific CX43 deletion in mice exacerbated BBB dysfunction during aging. The CX43-dependent effect was not due to its canonical gap junction function but was associated with reduced NAD+ levels and mitochondrial dysfunction through NAD+-dependent sirtuin 3 (SIRT3). CX43 interacts with and negatively regulates poly(ADP-ribose) polymerase 1 (PARP1). Pharmacologic inhibition of PARP1 by olaparib or nicotinamide mononucleotide (NMN) supplementation rescued NAD+ levels and alleviated aging-associated BBB leakage. These findings establish the endothelial CX43-PARP1-NAD+ pathway's role in vascular aging and identify a potential therapeutic strategy to combat aging-associated BBB leakage with neuroprotective implications.

Screening Biomarkers for Systemic Lupus Erythematosus Based on Machine Learning and Exploring Their Expression Correlations With the Ratios of Various Immune Cells.

Background: Systemic lupus erythematosus (SLE) is an autoimmune illness caused by a malfunctioning immunomodulatory system. China has the second highest prevalence of SLE in the world, from 0.03% to 0.07%. SLE is diagnosed using a combination of immunological markers, clinical symptoms, and even invasive biopsy. As a result, genetic diagnostic biomarkers for SLE diagnosis are desperately needed. Method: From the Gene Expression Omnibus (GEO) database, we downloaded three array data sets of SLE patients' and healthy people's peripheral blood mononuclear cells (PBMC) (GSE65391, GSE121239 and GSE61635) as the discovery metadata (nSLE = 1315, nnormal = 122), and pooled four data sets (GSE4588, GSE50772, GSE99967, and GSE24706) as the validate data set (nSLE = 146, nnormal = 76). We screened the differentially expressed genes (DEGs) between the SLE and control samples, and employed the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine recursive feature elimination (SVM-RFE) analyze to discover possible diagnostic biomarkers. The candidate markers' diagnostic efficacy was assessed using the receiver operating characteristic (ROC) curve. The reverse transcription quantitative polymerase chain reaction (RT-qPCR) was utilized to confirm the expression of the putative biomarkers using our own Chinese cohort (nSLE = 13, nnormal = 10). Finally, the proportion of 22 immune cells in SLE patients was determined using the CIBERSORT algorithm, and the correlations between the biomarkers' expression and immune cell ratios were also investigated. Results: We obtained a total of 284 DEGs and uncovered that they were largely involved in several immune relevant pathways, such as type І interferon signaling pathway, defense response to virus, and inflammatory response. Following that, six candidate diagnostic biomarkers for SLE were selected, namely ABCB1, EIF2AK2, HERC6, ID3, IFI27, and PLSCR1, whose expression levels were validated by the discovery and validation cohort data sets. As a signature, the area under curve (AUC) values of these six genes reached to 0.96 and 0.913, respectively, in the discovery and validation data sets. After that, we checked to see if the expression of ABCB1, IFI27, and PLSCR1 in our own Chinese cohort matched that of the discovery and validation sets. Subsequently, we revealed the potentially disturbed immune cell types in SLE patients using the CIBERSORT analysis, and uncovered the most relevant immune cells with the expression of ABCB1, IFI27, and PLSCR1. Conclusion: Our study identified ABCB1, IFI27, and PLSCR1 as potential diagnostic genes for Chinese SLE patients, and uncovered their most relevant immune cells. The findings in this paper provide possible biomarkers for diagnosing Chinese SLE patients.

Comprehensive bulk and single-cell transcriptome profiling give useful insights into the characteristics of osteoarthritis associated synovial macrophages.

Background: Osteoarthritis (OA) is a common chronic joint disease, but the association between molecular and cellular events and the pathogenic process of OA remains unclear. Objective: The study aimed to identify key molecular and cellular events in the processes of immune infiltration of the synovium in OA and to provide potential diagnostic and therapeutic targets. Methods: To identify the common differential expression genes and function analysis in OA, we compared the expression between normal and OA samples and analyzed the protein-protein interaction (PPI). Additionally, immune infiltration analysis was used to explore the differences in common immune cell types, and Gene Set Variation Analysis (GSVA) analysis was applied to analyze the status of pathways between OA and normal groups. Furthermore, the optimal diagnostic biomarkers for OA were identified by least absolute shrinkage and selection operator (LASSO) models. Finally, the key role of biomarkers in OA synovitis microenvironment was discussed through single cell and Scissor analysis. Results: A total of 172 DEGs (differentially expressed genes) associated with osteoarticular synovitis were identified, and these genes mainly enriched eight functional categories. In addition, immune infiltration analysis found that four immune cell types, including Macrophage, B cell memory, B cell, and Mast cell were significantly correlated with OA, and LASSO analysis showed that Macrophage were the best diagnostic biomarkers of immune infiltration in OA. Furthermore, using scRNA-seq dataset, we also analyzed the cell communication patterns of Macrophage in the OA synovial inflammatory microenvironment and found that CCL, MIF, and TNF signaling pathways were the mainly cellular communication pathways. Finally, Scissor analysis identified a population of M2-like Macrophages with high expression of CD163 and LYVE1, which has strong anti-inflammatory ability and showed that the TNF gene may play an important role in the synovial microenvironment of OA. Conclusion: Overall, Macrophage is the best diagnostic marker of immune infiltration in osteoarticular synovitis, and it can communicate with other cells mainly through CCL, TNF, and MIF signaling pathways in microenvironment. In addition, TNF gene may play an important role in the development of synovitis.

Combined proteomics and single cell RNA-sequencing analysis to identify biomarkers of disease diagnosis and disease exacerbation for systemic lupus erythematosus.

Introduction: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease for which there is no cure. Effective diagnosis and precise assessment of disease exacerbation remains a major challenge. Methods: We performed peripheral blood mononuclear cell (PBMC) proteomics of a discovery cohort, including patients with active SLE and inactive SLE, patients with rheumatoid arthritis (RA), and healthy controls (HC). Then, we performed a machine learning pipeline to identify biomarker combinations. The biomarker combinations were further validated using enzyme-linked immunosorbent assays (ELISAs) in another cohort. Single-cell RNA sequencing (scRNA-seq) data from active SLE, inactive SLE, and HC PBMC samples further elucidated the potential immune cellular sources of each of these PBMC biomarkers. Results: Screening of the PBMC proteome identified 1023, 168, and 124 proteins that were significantly different between SLE vs. HC, SLE vs. RA, and active SLE vs. inactive SLE, respectively. The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. Among them, the six-protein combination (IFIT3, MX1, TOMM40, STAT1, STAT2, and OAS3) exhibited good performance for SLE disease diagnosis, with AUC of 0.723 and 0.815 for distinguishing SLE from HC and RA, respectively. Nine-protein combination (PHACTR2, GOT2, L-selectin, CMC4, MAP2K1, CMPK2, ECPAS, SRA1, and STAT2) showed a robust performance in assessing disease exacerbation (AUC=0.990). Further, the potential immune cellular sources of nine PBMC biomarkers, which had the consistent changes with the proteomics data, were elucidated by PBMC scRNAseq. Discussion: Unbiased proteomic quantification and experimental validation of PBMC samples from two cohorts of patients with SLE were identified as biomarker combinations for diagnosis and activity monitoring. Furthermore, the immune cell subtype origin of the biomarkers in the transcript expression level was determined using PBMC scRNAseq. These findings present valuable PBMC biomarkers associated with SLE and may reveal potential therapeutic targets.

Inhibition of LSD1 with Bomedemstat Sensitizes Small Cell Lung Cancer to Immune Checkpoint Blockade and T-Cell Killing.

PURPOSE: The addition of immune checkpoint blockade (ICB) to platinum/etoposide chemotherapy changed the standard of care for small cell lung cancer (SCLC) treatment. However, ICB addition only modestly improved clinical outcomes, likely reflecting the high prevalence of an immunologically "cold" tumor microenvironment in SCLC, despite high mutational burden. Nevertheless, some patients clearly benefit from ICB and recent reports have associated clinical responses to ICB in SCLC with (i) decreased neuroendocrine characteristics and (ii) activation of NOTCH signaling. We previously showed that inhibition of the lysine-specific demethylase 1a (LSD1) demethylase activates NOTCH and suppresses neuroendocrine features of SCLC, leading us to investigate whether LSD1 inhibition would enhance the response to PD-1 inhibition in SCLC. EXPERIMENTAL DESIGN: We employed a syngeneic immunocompetent model of SCLC, derived from a genetically engineered mouse model harboring Rb1/Trp53 inactivation, to investigate combining the LSD1 inhibitor bomedemstat with anti-PD-1 therapy. In vivo experiments were complemented by cell-based studies in murine and human models. RESULTS: Bomedemstat potentiated responses to PD-1 inhibition in a syngeneic model of SCLC, resulting in increased CD8+ T-cell infiltration and strong tumor growth inhibition. Bomedemstat increased MHC class I expression in mouse SCLC tumor cells in vivo and augmented MHC-I induction by IFNγ and increased killing by tumor-specific T cells in cell culture. CONCLUSIONS: LSD1 inhibition increased MHC-I expression and enhanced responses to PD-1 inhibition in vivo, supporting a new clinical trial to combine bomedemstat with standard-of-care PD-1 axis inhibition in SCLC.

Tumor cells generate astrocyte-like cells that contribute to SHH-driven medulloblastoma relapse.

Astrocytes, a major glial cell type in the brain, play a critical role in supporting the progression of medulloblastoma (MB), the most common malignant pediatric brain tumor. Through lineage tracing analyses and single-cell RNA sequencing, we demonstrate that astrocytes are predominantly derived from the transdifferentiation of tumor cells in relapsed MB (but not in primary MB), although MB cells are generally believed to be neuronal-lineage committed. Such transdifferentiation of MB cells relies on Sox9, a transcription factor critical for gliogenesis. Our studies further reveal that bone morphogenetic proteins (BMPs) stimulate the transdifferentiation of MB cells by inducing the phosphorylation of Sox9. Pharmacological inhibition of BMP signaling represses MB cell transdifferentiation into astrocytes and suppresses tumor relapse. Our studies establish the distinct cellular sources of astrocytes in primary and relapsed MB and provide an avenue to prevent and treat MB relapse by targeting tumor cell transdifferentiation.

Dysregulated Kras/YY1/ZNF322A/Shh transcriptional axis enhances neo-angiogenesis to promote lung cancer progression.

Angiogenesis enhances cancer metastasis and progression, however, the roles of transcription regulation in angiogenesis are not fully defined. ZNF322A is an oncogenic zinc-finger transcription factor. Here, we demonstrate a new mechanism of Kras mutation-driven ZNF322A transcriptional activation and elucidate the interplay between ZNF322A and its upstream transcriptional regulators and downstream transcriptional targets in promoting neo-angiogenesis. Methods: Luciferase activity, RT-qPCR and ChIP-qPCR assays were used to examine transcription regulation in cell models. In vitro and in vivo angiogenesis assays were conducted. Immunohistochemistry, Kaplan-Meier method and multivariate Cox regression assays were performed to examine the clinical correlation in tumor specimens from lung cancer patients. Results: We validated that Yin Yang 1 (YY1) upregulated ZNF322A expression through targeting its promoter in the context of Kras mutation. Reconstitution experiments by knocking down YY1 under KrasG13V activation decreased KrasG13V-promoted cancer cell migration, proliferation and ZNF322A promoter activity. Knockdown of YY1 or ZNF322A attenuated angiogenesis in vitro and in vivo. Notably, we validated that ZNF322A upregulated the expression of sonic hedgehog (Shh) gene which encodes a secreted factor that activates pro-angiogenic responses in endothelial cells. Clinically, ZNF322A protein expression positively correlated with Shh and CD31, an endothelial cell marker, in 133 lung cancer patient samples determined using immunohistochemistry analysis. Notably, patients with concordantly high expression of ZNF322A, Shh and CD31 correlated with poor prognosis. Conclusions: These findings highlight the mechanism by which dysregulation of Kras/YY1/ZNF322/Shh transcriptional axis enhances neo-angiogenesis and cancer progression in lung cancer. Therapeutic strategies that target Kras/YY1/ZNF322A/Shh signaling axis may provide new insight on targeted therapy for lung cancer patients.

Single­cell RNA sequencing of t(8;21) acute myeloid leukemia for risk prediction.

Single­cell RNA sequencing (scRNA­seq) of bone marrow or peripheral blood samples from patients with acute myeloid leukemia (AML) enables the characterization of heterogeneous malignant cells. A total of 87 cells from two patients with t(8;21) AML were analyzed using scRNA­seq. Clustering methods were used to separate leukemia cells into different sub­populations, and the expression patterns of specific marker genes were used to annotate these populations. Among the 31 differentially expressed genes in the cells of a patient who relapsed after hematopoietic stem cell transplantation, 13 genes were identified to be associated with leukemia. Furthermore, three genes, namely AT­rich interaction domain 2, lysine methyltransferase 2A and synaptotagmin binding cytoplasmic RNA interacting protein were validated as possible prognostic biomarkers using two bulk expression datasets. Taking advantage of scRNA­seq, the results of the present study may provide clinicians with several possible biomarkers to predict the prognostic outcomes of t(8;21) AML.

NeuroD1 Dictates Tumor Cell Differentiation in Medulloblastoma.

Tumor cells are characterized by unlimited proliferation and perturbed differentiation. Using single-cell RNA sequencing, we demonstrate that tumor cells in medulloblastoma (MB) retain their capacity to differentiate in a similar way as their normal originating cells, cerebellar granule neuron precursors. Once they differentiate, MB cells permanently lose their proliferative capacity and tumorigenic potential. Differentiated MB cells highly express NeuroD1, a helix-loop-helix transcription factor, and forced expression of NeuroD1 promotes the differentiation of MB cells. The expression of NeuroD1 in bulk MB cells is repressed by trimethylation of histone 3 lysine-27 (H3K27me3). Inhibition of the histone lysine methyltransferase EZH2 prevents H3K27 trimethylation, resulting in increased NeuroD1 expression and enhanced differentiation in MB cells, which consequently reduces tumor growth. These studies reveal the mechanisms underlying MB cell differentiation and provide rationales to treat MB (potentially other malignancies) by stimulating tumor cell differentiation.

AKT-mediated phosphorylation enhances protein stability and transcription activity of ZNF322A to promote lung cancer progression.

ZNF322A is an oncogenic zinc-finger transcription factor. Our published results show that ZNF322A positively regulates transcription of alpha-adducin (ADD1) and cyclin D1 (CCND1) to promote tumorgenicity of lung cancer. However, the upstream regulatory mechanisms of ZNF322A protein function remain elusive. Here, we demonstrate that AKT could phosphorylate ZNF322A by in vitro kinase assay and cell-based mass spectrometry analysis. Overexpression of AKT promoted ZNF322A protein stability and transcriptional activity, whereas these effects were inhibited by knockdown of AKT or treating with AKT inhibitor. We studied AKT-mediated phosphorylation sites, viz. Thr-150, Ser-224, Thr-234, and Thr-262. ZNF322A phosphorylation at Thr-262 by AKT promoted ZNF322A protein stability thus increased ADD1 promoter activity. Interestingly, phosphorylation at Thr-150, Ser-224, and Thr-234 enhanced transcription activity without affecting protein stability of ZNF322A. Chromatin immunoprecipitation and DNA affinity precipitation assays showed that ZNF322A phosphorylation defective mutants Thr-150A, Ser-224A, and Thr-234A attenuated chromatin binding and DNA binding affinity to ADD1 and CCND1 promoters compared with wild-type ZNF322A. Furthermore, AKT-mediated Thr-150, Ser-224, Thr-234, and Thr-262 phosphorylation promoted lung cancer cell growth and metastasis in vitro and in vivo. Clinically, expression of phosphorylated ZNF322A (p-ZNF) correlated with actively phosphorylated AKT (p-AKT) in tumor specimens from 150 lung cancer patients. Multivariate Cox regression analysis indicated that combined p-AKT and p-ZNF expression profile was an independent factor to predict the clinical outcome in lung cancer patients. Our results reveal a new mechanism of AKT signaling in promoting ZNF322A protein stability and transcriptional activity in lung cancer cell, xenograft, and clinical models.