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A CFH- and SPINT2-based prognostic signature for cholangiocarcinoma.
BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant tumor with a poor prognosis, and reliable biomarkers for postoperative risk stratification remain limited. This study aimed to develop and validate a CFH- and SPINT2-based prognostic signature to support postoperative risk stratification and inform adjuvant therapy selection in CCA through integrative machine learning and single-cell transcriptomics. METHODS: Differentially expressed genes were screened from GSE26566. Integrative machine learning (least absolute shrinkage and selection operator-Cox, random forest, and univariate Cox regression) was performed in the training cohort (GSE89749; n=115) to construct a risk model, which was externally validated in two independent cohorts: cohort 1 (E-MTAB-6389; n=75) and cohort 2 [The Cancer Genome Atlas Cholangiocarcinoma (TCGA-CHOL) data set; n=36]. Systematic analysis was conducted and included examinations of immune infiltration [via single-sample gene set enrichment analysis (ssGSEA)], pathway enrichment (via hallmark GSEA), cellular localization (via single-cell RNA sequencing), and drug sensitivity (via the Genomics of Drug Sensitivity in Cancer 2 database). RESULTS: Two genes, CFH and SPINT2, were identified and incorporated into a prognostic risk score. High-risk patients in the training cohort had a significantly worse overall survival (log-rank P=0.02). External validation was performed in two independent cohorts. In validation cohort 1, the risk group was an independent prognostic factor [hazard ratio =2.27, 95% confidence interval (CI): 1.18-4.37; P=0.01]. In validation cohort 2, the model demonstrated acceptable discriminative ability (concordance index =0.721; 3-year area under the curve =0.692). The high-risk group exhibited an immunosuppressive microenvironment characterized by increased infiltration of macrophages and myeloid-derived suppressor cells, along with the activation of epithelial-mesenchymal transition, inflammatory response, and NF-κB signaling pathways. Single-cell analysis revealed a cell-type-specific expression pattern: CFH was predominantly expressed in fibroblasts, while SPINT2 was mainly expressed in malignant cells. Drug sensitivity analysis demonstrated that the high-risk group was more sensitive to gemcitabine, cisplatin, poly(ADP-ribose) polymerase (PARP) inhibitors, and mammalian target of rapamycin (mTOR) inhibitors, whereas the low-risk group was more sensitive to lapatinib. CONCLUSIONS: The CFH- and SPINT2-based prognostic signature may serve as an independent biomarker for postoperative risk stratification in CCA. High-risk patients, characterized by fibroblast-derived CFH enrichment and malignant-cell SPINT2 loss, exhibit an immunosuppressive microenvironment and may be more suitable for gemcitabine-based chemotherapy or PARP/mTOR inhibitors, whereas low-risk patients may benefit from less intensive adjuvant strategies or HER2/EGFR-targeted lapatinib. Prospective validation is warranted before clinical implementation.
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Stalled developmental programs at the root of pediatric brain tumors.
Childhood brain tumors have suspected prenatal origins. To identify vulnerable developmental states, we generated a single-cell transcriptome atlas of >65,000 cells from embryonal pons and forebrain, two major tumor locations. We derived signatures for 191 distinct cell populations and defined the regional cellular diversity and differentiation dynamics. Projection of bulk tumor transcriptomes onto this dataset shows that WNT medulloblastomas match the rhombic lip-derived mossy fiber neuronal lineage and embryonal tumors with multilayered rosettes fully recapitulate a neuronal lineage, while group 2a/b atypical teratoid/rhabdoid tumors may originate outside the neuroectoderm. Importantly, single-cell tumor profiles reveal highly defined cell hierarchies that mirror transcriptional programs of the corresponding normal lineages. Our findings identify impaired differentiation of specific neural progenitors as a common mechanism underlying these pediatric cancers and provide a rational framework for future modeling and therapeutic interventions.
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EGFL6 predicts unfavorable prognosis and serves as a potential indicator in esophageal carcinoma.
BACKGROUND: The EGF-like domain multiple 6 (EGFL6) has been documented as an oncogene across diverse cancer types. Despite its known importance in tumorigenesis, EGFL6's involvement in esophageal carcinoma (ESCA) remains largely unexplored. Herein, we integrated multi-source omics data to characterize EGFL6's expression landscape, biological functions, and immunological implications in ESCA-with a focus on its prognostic value. METHODS: To identify dysregulated basement membrane-related genes (BMRGs) in ESCA, we performed Venn overlap analysis on RNA-seq data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and a curated BMRG reference list. Weighted gene co-expression analysis (WGCNA) was used to identify EGFL6-related modules and functional enrichment of differentially expressed genes (DEGs) were identified via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). EGFL6-specific epigenetic (DNA methylation) and genetic alterations were validated using Methsurv and cBioPortal. Single-sample GSEA (ssGSEA) was applied to explore immune infiltration and its correlation with EGFL6. Prognostic significance of EGFL6 was examined via Kaplan-Meier and receiver operating characteristic (ROC) analyses. RESULTS: Venn overlap analysis indicated EGFL6 as a significantly overexpressed gene in ESCA that closely correlated with multiple clinical and pathological features. WGCNA and subsequent functional enrichment analysis revealed that EGFL6-related DEGs participate in critical biological processes. Kaplan-Meier analysis demonstrated that increased EGFL6 contributed to reduced disease-specific survival (DSS) and progression-free interval (PFI) in patients with ESCA. In vitro experiments confirmed that EGFL6 promotes ESCA by enhancing cell proliferation, invasion and regulating cell-cycle progression. CONCLUSION: EGFL6 is significantly upregulated in ESCA and is related to various clinical factors, immune modulation and reduced prognosis. EGFL6 could be identified as a novel prognostic biomarker and a viable therapeutic target for the development of personalized treatment approaches in ESCA.
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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.