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PP2Ac Deficiency Enhances Tumor Immunogenicity by Activating STING-Type I Interferon Signaling in Glioblastoma.
UNLABELLED: Glioblastoma (GBM) is an immunologically "cold" tumor that does not respond to current immunotherapy. Here, we demonstrate a fundamental role for the α-isoform of the catalytic subunit of protein phosphatase-2A (PP2Ac) in regulating glioma immunogenicity. Genetic ablation of PP2Ac in glioma cells enhanced double-stranded DNA (dsDNA) production and cGAS-type I IFN signaling, MHC-I expression, and tumor mutational burden. In coculture experiments, PP2Ac deficiency in glioma cells promoted dendritic cell (DC) cross-presentation and clonal expansion of CD8+ T cells. In vivo, PP2Ac depletion sensitized tumors to immune-checkpoint blockade and radiotherapy treatment. Single-cell analysis demonstrated that PP2Ac deficiency increased CD8+ T-cell, natural killer cell, and DC accumulation and reduced immunosuppressive tumor-associated macrophages. Furthermore, loss of PP2Ac increased IFN signaling in myeloid and tumor cells and reduced expression of a tumor gene signature associated with worse patient survival in The Cancer Genome Atlas. Collectively, this study establishes a novel role for PP2Ac in inhibiting dsDNA-cGAS-STING signaling to suppress antitumor immunity in glioma. SIGNIFICANCE: PP2Ac deficiency promotes cGAS-STING signaling in glioma to induce a tumor-suppressive immune microenvironment, highlighting PP2Ac as a potential therapeutic target to enhance tumor immunogenicity and improve response to immunotherapy.
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miR-9-5p/HMMR regulates the tumorigenesis and progression of clear cell renal cell carcinoma through EMT and JAK1/STAT1 signaling pathway.
BACKGROUND: The most common malignant type of kidney cancer is clear cell renal cell carcinoma (ccRCC). The expression levels of hyaluronan-mediated motility receptor (HMMR) in many tumor types are significantly elevated. HMMR is closely associated with tumor-related progression, treatment resistance, and poor prognosis, and has yet to be fully investigated in terms of its expression patterns and molecular mechanisms of action in ccRCC. Further research is imperative to elucidate these aspects. METHODS: We used The Cancer Genome Atlas (TCGA) database to preliminarily investigate HMMR expression and function in ccRCC and the data for 19 samples from the NCBI GEO database (GSE207493) for single-cell analysis. We assessed the differential expression level of HMMR between ccRCC cancerous tissues and their matched non-tumor tissues. Subsequently, a series of in vivo and in vitro experiments were designed to elucidate the biological function of HMMR in ccRCC, including Transwell assays, CCK-8 assays, clone formation assays and subcutaneous xenograft experiments in nude mice. Through bioinformatics analysis, we identified potential microRNAs (miRNAs) that may regulate HMMR, as well as the possible signaling pathways involved. Finally, we conducted a series of cellular functional experiments to validate our hypotheses regarding the HMMR axis. RESULTS: HMMR expression was significantly up-regulated in tumor tissues of ccRCC patients, and elevated HMMR expression level showed a strong correlation with ccRCC progression and adverse prognoses of patients. Knocking down HMMR inhibited the proliferative and migratory abilities of ccRCC cells, while its overexpression amplified these oncogenic properties. In nude mice model, reduced HMMR expression inhibited ccRCC tumor proliferation in vivo. Furthermore, overexpression of an upstream transcriptional regulator, miR-9-5p, effectively downregulated HMMR expression and thus impeded ccRCC cells proliferation and migration. HMMR might influence ccRCC growth via the Epithelial-Mesenchymal Transition (EMT) pathway and the Janus Kinase 1/Signal Transducer and Activator of Transcription 1 (JAK1/STAT1) pathway. CONCLUSIONS: HMMR is overexpressed in ccRCC, and there is a significant link between high HMMR expression and tumor progression, as well as poor patient prognosis. Specifically, HMMR could be targeted and inhibited by miR-9-5p and might modulate the tumorigenesis and progression of ccRCC through both EMT and JAK1/STAT1 signaling pathway.
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The human secretome.
The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immunoassays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.
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High TRAF3IP3 Level Predicts Poor Prognosis of Patients with Gliomas.
BACKGROUND: Tumor necrosis factor receptor-related factor 3 (TRAF3) interacting protein 3 (TRAF3IP3) is involved in the development of immune tissues and the immune response of the body. Downregulated expression of TRAF3IP3 in malignant melanoma can inhibit tumor growth. The role of TRAF3IP3 in glioma is unknown. METHODS: We used the Wilcoxon rank sum test to compare the expression of TRAF3IP3 in glioma and normal tissues based on The Cancer Genome Atlas and Genotype Tissue Expression. Logistics regression was used to evaluate the relationship between TRAF3IP3 and clinicopathologic characters. Gene set enrichment analysis and single-sample gene set enrichment analysis were conducted to annotate biological function of TRAF3IP3. We used Kaplan-Meier and Cox regression to evaluate the prognostic value of TRAF3IP3. RESULTS: We downloaded RNA-seq data of 670 gliomas and 1157 normal tissues. TRAF3IP3 was highly expressed in gliomas (P < 0.001). High expression of TRAF3IP3 and higher World Health Organization grade (odds ratio [OR], 3.57 [2.42-5.34 CI]; P < 0.001), wild-type isocitrate dehydrogenase status (OR, 4.79 [3.40-6.83 CI]; P < 0.001), 1p/19q non-codeletion (OR, 15.32 [9.23-27.01 CI]; P < 0.001), mutant epidermal growth factor receptor status (OR, 2.77 [1.65-4.81 CI]; P < 0.001), worse histologic type (OR, 3.64 [2.48-5.43 CI]; P < 0.001) and worse primary therapy outcome (OR, 2.29 [1.47-3.61 CI]; P < 0.001) were significantly correlated. Six signaling pathways were significantly enriched in the TRAF3IP3 high-expression phenotype group, including JAK-STAT, interferon-γ, apoptosis, P53, programmed cell death protein 1, and CTLA-4 (cytotoxic T-lymphocyte-associated protein 4). High expression of TRAF3IP3 was associated with worse progression-free survival (hazard ratio [HR], 2.39 (1.39-3.01); P < 0.001), disease-free survival (HR, 3.02 (2.27-4.01); P < 0.001) and overall survival (HR, 2.87 (2.20-3.75); P < 0.001). CONCLUSIONS: TRAF3IP3 play an important role in the occurrence and development of glioma and may be a potential biomarker for the prognosis of glioma.
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Integrated plasma and exosome long noncoding RNA profiling is promising for diagnosing non-small cell lung cancer.
OBJECTIVES: Non-small cell lung cancer (NSCLC) accounts for more than 80 % of all lung cancers, and its 5-year survival rate can be greatly improved by early diagnosis. However, early diagnosis remains elusive because of the lack of effective biomarkers. In this study, we aimed to develop an effective diagnostic model for NSCLC based on a combination of circulating biomarkers. METHODS: Tissue-deregulated long noncoding RNAs (lncRNAs) in NSCLC were identified in datasets retrieved from the Gene Expression Omnibus (GEO, n=727) and The Cancer Genome Atlas (TCGA, n=1,135) databases, and their differential expression was verified in paired local plasma and exosome samples from NSCLC patients. Subsequently, LASSO regression was used to screen for biomarkers in a large clinical population, and a logistic regression model was used to establish a multi-marker diagnostic model. The area under the receiver operating characteristic (ROC) curve (AUC), calibration plots, decision curve analysis (DCA), clinical impact curves, and integrated discrimination improvement (IDI) were used to evaluate the efficiency of the diagnostic model. RESULTS: Three lncRNAs-PGM5-AS1, SFTA1P, and CTA-384D8.35 were consistently expressed in online tissue datasets, plasma, and exosomes from local patients. LASSO regression identified nine variables (Plasma CTA-384D8.35, Plasma PGM5-AS1, Exosome CTA-384D8.35, Exosome PGM5-AS1, Exosome SFTA1P, Log10CEA, Log10CA125, SCC, and NSE) in clinical samples that were eventually included in the multi-marker diagnostic model. Logistic regression analysis revealed that Plasma CTA-384D8.35, exosome SFTA1P, Log10CEA, Exosome CTA-384D8.35, SCC, and NSE were independent risk factors for NSCLC (p<0.01), and their results were visualized using a nomogram to obtain personalized prediction outcomes. The constructed diagnostic model demonstrated good NSCLC prediction ability in both the training and validation sets (AUC=0.97). CONCLUSIONS: In summary, the constructed circulating lncRNA-based diagnostic model has good NSCLC prediction ability in clinical samples and provides a potential diagnostic tool for NSCLC.
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Elucidation of Novel Therapeutic Targets for Acute Myeloid Leukemias with RUNX1-RUNX1T1 Fusion.
The RUNX1-RUNX1T1 fusion is a frequent chromosomal alteration in acute myeloid leukemias (AMLs). Although RUNX1-RUNX1T1 fusion protein has pivotal roles in the development of AMLs with the fusion, RUNX1-RUNX1T1, fusion protein is difficult to target, as it lacks kinase activities. Here, we used bioinformatic tools to elucidate targetable signaling pathways in AMLs with RUNX1-RUNX1T1 fusion. After analysis of 93 AML cases from The Cancer Genome Atlas (TCGA) database, we found expression of 293 genes that correlated to the expression of the RUNX1-RUNX1T1 fusion gene. Based on these 293 genes, the cyclooxygenase (COX), vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), and fibroblast growth factor receptor (FGFR) pathways were predicted to be specifically activated in AMLs with RUNX1-RUNX1T1 fusion. Moreover, the in vitro proliferation of AML cells with RUNX1-RUNX1T1 fusion decreased significantly more than that of AML cells without the fusion, when the pathways were inhibited pharmacologically. The results indicate that novel targetable signaling pathways could be identified by the analysis of the gene expression features of AMLs with non-targetable genetic alterations. The elucidation of specific molecular targets for AMLs that have a specific genetic alteration would promote personalized treatment of AMLs and improve clinical outcomes.
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Transcriptional Profiles of Somatostatin and Parvalbumin Interneuron Subtypes in the Human Dorsolateral Prefrontal Cortex: Implications for Schizophrenia.
OBJECTIVE: Alterations in the somatostatin (SST) and parvalbumin (PVALB) classes of inhibitory GABAergic interneurons in the dorsolateral prefrontal cortex (DLPFC) are thought to contribute to the core cognitive impairments of schizophrenia. Both classes of interneurons are composed of multiple subtypes, but the distinguishing features and relative proportions of these subtypes have not been determined in the DLPFC. The aim of this study is to provide a comprehensive analysis of these subtypes from young and middle-age adults with no known psychiatric disorders. METHODS: The authors used single-nucleus RNA sequencing to determine the transcriptional profiles of interneuron subtypes in DLPFC tissue samples from discovery and validation cohorts; fluorescent in situ hybridization to validate selected findings; and comparisons of transcriptome and electrophysiology data from the Allen Brain Atlas to infer functional properties of selected subtypes. RESULTS: The relative proportions of five major interneuron classes and of 37 interneuron subtypes were highly consistent across 19 individuals. Eleven SST subtypes were identified, including two rare subtypes that likely produce dopamine or regulate blood flow, and a subtype derived from the caudal ganglionic eminence. Among the nine PVALB subtypes identified, chandelier cells were transcriptionally distinct from PVALB basket cells (PVBCs) and PVBC subtypes. Moreover, subsets of PVBCs were distinguished by high versus low PVALB expression and had distinctive molecular features consistent with differences in anatomical (i.e., perineuronal nets) and electrophysiological (i.e., firing properties) characteristics. CONCLUSIONS: The robust identification of discrete subtypes of SST and PVALB interneurons in the DLPFC from young and middle-age adults with no known psychiatric disorders provides the means to determine which specific subtypes could be altered in proportional representation and/or gene expression in schizophrenia.
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Cancer-associated fibroblast-derived fibulin-5 promotes epithelial-mesenchymal transition in diffuse-type gastric cancer via cAMP response element-binding protein pathway, showing poor prognosis.
Diffuse-type gastric cancer (DGC), characterized by poorly cohesive cells within fibrotic stroma, is associated with advanced disease and poor prognosis. Here, to identify distinct biomarkers for DGC compared with intestinal-type gastric cancer, we constructed a comprehensive large-scale signaling network using RNA-sequencing data from three genomic databases (The Cancer Genome Atlas, GSE62254 and GSE26253), developed a mathematical model and conducted simulation analyses. For validation, we used tissue microarray blocks of gastric cancers with immunohistochemical staining, single-cell RNA sequencing, primary cultures of cancer-associated fibroblasts (CAFs) and organoids, and a co-culture system involving CAFs and cancer cells. Signaling network analysis identified six differentially activated signaling components across the database, including BIRC5, TTK, NEK2, FHL1, NR2F1 and FBLN5. Among the differentially activated signaling components, high tumoral expression of fibulin-5 protein encoded by FBLN5 correlated with poor overall and disease-specific survival rates in patients with DGC, even after adjusting for the tumor, node, metastases (TNM) stage. Fibulin-5, derived from CAFs within DGC stroma, promoted organoid growth and epithelial-mesenchymal transition (EMT) in DGC cell lines via the cAMP response element-binding protein (CREB) pathway in a CAF co-culture system. FBLN5 knockdown in CAFs reduced the aggressive phenotype of co-cultured DGC cells, while CREB inhibitors reversed EMT. Furthermore, levels of secreted FBLN5 in patient blood samples correlated with its expression in primary tumors. In summary, fibulin-5 secreted by CAFs and interacted with DGC cells promotes EMT and is clinically associated with poor patient outcomes. These findings suggest fibulin-5 as a potential prognostic marker and therapeutic target in patients with DGC.
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Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype.
BACKGROUND AND OBJECTIVES: Transcriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. For example, Aggressive Variant Prostate Cancer (AVPC) presents low PSA per tumor burden, and characterized by de novo resistance to androgen receptor signaling inhibitors (ARIs). Understanding PCa transcriptomic complexity can provide biological insight and therapeutic guidance. However, unsupervised clustering analysis is hindered by potential confounding factors such as stromal contamination and stress-related material degradation. MATERIALS AND METHODS: To focus on prostate epithelial cell-relevant heterogeneity, we defined 1,629 genes expressed by prostate epithelial cells by analyzing publicly available bulk and single- cell RNA sequencing data. Consensus clustering and CIBERSORT deconvolution were used for class discovery and proportion estimate analysis. The Cancer Genome Atlas Prostate Adenocarcinoma dataset served as a training set. The resulting clusters were analyzed in association with clinical, pathologic, and genomic characteristics and impact on survival. Serum markers PSA and PAP was analyzed to predict response to docetaxel chemotherapy in metastatic setting. RESULTS: We identified two luminal subtypes and two aggressive variant subtypes of PCa: luminal A (Adipogenic/AR-active/PSA-high) (30.0%); luminal S (Secretory/PAP-high) (26.0%); AVPC-I (Immune-infiltrative) (14.7%), AVPC-M (Myc-active) (4.2%), and mixed (25.0%). AVPC-I and AVPC-M subtypes predicted to be resistant to ARI and have low PSA per tumor burden. Luminal A and AVPC-M predicted to be resistant to docetaxel and have high PSA/PAP Ratio. Metastatic PCa patients with high PSA/PAP ratio (>20) had significantly shorter progression-free survival than those with low ratio (≤20) following docetaxel chemotherapy. CONCLUSION: We propose four prostate adenocarcinoma subtypes with distinct transcriptomic, genomic, and pathologic characteristics. PSA/PAP ratio in advanced cancer may aid in determining which patients would benefit from maximized androgen receptor inhibition or early use of antimicrotubule agents.
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Supervised Learning and Multi-Omics Integration Reveals Clinical Significance of Inner Membrane Mitochondrial Protein (IMMT) in Prognostic Prediction, Tumor Immune Microenvironment and Precision Medicine for Kidney Renal Clear Cell Carcinoma.
Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman's correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies.