Браузер не даёт сохранять данные (например, приватный режим): закладки пропадут после закрытия вкладки.
Поиск статей PubMed
Ключевые слова, автор, журнал, годы — результаты из PubMed, аннотации с переводом на русский, закладки в браузере.
Найдено: 4 942
Страница 439 из 495-
Four Decades of Inquiry Into the Genetic Bases of Specific Reading Disability.
PURPOSE: This study investigated the genetic bases of specific reading disability (SRD) by systematically cataloging candidate genes reported as associated with SRD and reading-related processes over the last 4 decades and analyzing their evolutionary conservation, developmental expression patterns, and functional networks to address significant knowledge gaps in understanding the genetic architecture of reading (dis)ability. METHOD: Through a comprehensive literature review, we identified 175 putative SRD (and reading-related processes) candidate genes (hereafter, SRD genes). Using bioinformatic approaches, we analyzed their evolutionary conservation across species, examined their expression patterns in developmental and single-cell transcriptome data sets from the Allen Brain Atlas, and performed functional pathway analyses to identify biological processes associated with these genes. RESULTS: SRD genes showed remarkable evolutionary conservation, with enrichment in ancient taxonomic groups. Developmental transcriptome analysis revealed two distinct gene clusters with expression differentiation around 24 postconception weeks: early genes associated with brain morphology development and later genes involved in synaptic signaling. Single-cell analysis identified cell-type-specific expression patterns and protein-protein interaction networks with hub genes potentially coordinating reading-related neural pathways. CONCLUSIONS: Our findings challenge the notion of the existence of reading-specific genes, suggesting instead that SRD reflects the disruption of ancient evolutionary neural mechanisms operating within human-specific brain architecture. The identification of developmental expression transitions and functional networks provides insight into how genetic variation might impact reading development and offers potential targets for future clinical approaches to the identification and remediation of reading difficulties. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.30290446.
-
Comprehensive Analysis and Experimental Validation of TLL2 as a Potential New Prognostic Biomarker Associated with Immune Infiltration in Lung Adenocarcinoma.
BACKGROUND: The precise function of Tolloid Like 2 (TLL2) remains uncertain within the context of Lung Adenocarcinoma (LUAD). OBJECTIVES: The primary objective of this investigation was to conduct a thorough analysis. METHODS: To assess its diagnostic utility, data from The Cancer Genome Atlas (TCGA) database were used to assess TLL2 expression in pan-cancer and LUAD. The study has also investigated the correlation between TLL2 expression levels and LUAD symptoms and prognosis. Furthermore, the study has explored possible regulatory networks involving TLL2, including its association with immune infiltration, tumor stemness index (mRNAsi), and drug sensitivity in LUAD. We have explored TLL2 expression in single-cell sequencing of LUAD and the genomic variation and clinical significance of TLL2 in LUAD. The expression of TLL2 has been validated in GSE87340 and cell lines by quantitative Real-time PCR (qRT-PCR). RESULTS: An abnormal expression of TLL2 has been found in pan-cancer and LUAD. In LUAD patients, elevated levels of TLL2 were significantly related to the T stage (p = 0.046) and the pathological stage (p = 0.016). The expression of TLL2 in patients with LUAD was significantly associated with poorer Overall Survival (OS) (p < 0.001). The expression of TLL2 was determined to be an independent predictor of poorer OS (p = 0.042). TLL2 was associated with ribosome, neuroactive ligand-receptor interaction, allograft rejection, ECM receptor interaction, asthma, porphyrin and chlorophyll metabolism, focal adhesion, pentose and glucuronate inter-conversions, and ascorbate and aldarate metabolism. The expression of TLL2 in LUAD was correlated with immune infiltration and mRNAsi. The expression of TLL2 was significantly and negatively correlated with TAK-715, XMD13-2, STF-62247, OSI-930, and EHT-1864 in LUAD. The TLL2 gene was up- -regulated in multiple individual LUAD cells. LUAD patients with altered TLL2 had a shorter PFS as opposed to those with unaltered TLL2. The expression of TLL2 was significantly increased in LUAD cells. CONCLUSION: For patients with LUAD, TLL2 may serve as an immunotherapeutic target and a useful prognosis biomarker.
-
Hepatocellular carcinoma hosts cholinergic neural cells and tumoral hepatocytes harboring targetable muscarinic receptors.
BACKGROUND & AIMS: Owing to unexplained interpatient variation and treatment failure in hepatocellular carcinoma (HCC), novel therapeutic approaches remain an urgent clinical need. Hepatic neurons, belonging to the autonomic nervous system (ANS), mediate liver/whole body crosstalk. Pathological innervation of the ANS has been identified in cancer, nurturing tumor stroma and conferring stronger carcinogenic properties. METHODS: We characterized the innervation of liver tumors from the French Liver Biobank, then applied bioinformatics to TCGA (The Cancer Genome Atlas), several other datasets and a European validation cohort, to re-evaluate patient stratification. Cell biology and pharmacology studies were also performed. RESULTS: Densely packed nucleated DCX+, synaptophysin+, NeuN+, VAChT+, TH-, CD31-, CD45- clusters, to date undetected, were identified in human HCCs, and independently confirmed by single-cell RNA sequencing data. Using the new concept of a neuronal score, human and rat HCCs displayed tightly netrin-1-associated neural reconfiguration towards cholinergic polarity, which was associated with chronic liver disease progression, cancer onset and many features of aggressive (proliferative class) HCC, including shortened survival. This score was conditioned by tumoral hepatocytes, and predicted sorafenib efficacy in the STORM HCC phase III trial. Conversely, intratumoral adrenergic lymphocytes were enriched in TEMRA and cytotoxic phenotypes. Amongst all cholinergic transcripts, the medically targeted CHRM3 receptor was enriched and associated with pathogenic traits in HCC, as well as poor prognosis in HCC stages 1-2, while its level dropped upon experimental re-differentiation. Its pharmacological inhibition with low concentrations of anticholinergic drugs, but not cholinomimetics, decreased anchorage-independent growth and anoikis, synergized with sorafenib and lenvatinib in HCC class 1 to 3 lines, yet not in primary human hepatocytes, and preserved mature hepatocyte functions. CONCLUSION: These data identify cholinergic processes as instrumental in liver carcinogenesis and support the use of EMA/FDA-approved cholinergic drugs in HCC research. IMPACT AND IMPLICATIONS: Hepatocellular carcinoma (HCC) care has long been hampered by the enigmatic nature of disease evolution, as well as of response or resistance to treatment. Hepatic neurons are likely the least studied liver cell type and mediate patients singularities from the ANS to the organ in real-time. Cholinergic inputs identified in this study as pathogenic may be targeted with the well charted pharmacopoeia of neurotropic drugs already available, for basic or clinical research purposes, with an expected high level of safety.
-
Development and validation of a novel fibroblast scoring model for lung adenocarcinoma.
The interaction between cancer-associated fibroblasts (CAFs) and the tumor microenvironment (TME) is a key factor for promoting tumor progression. In lung cancer, the crosstalk between CAFs and malignant and immune cells is expected to provide new directions for the development of immunotherapy. In this study, we have systematically analyzed a single-cell dataset and identified interacting genes between CAFs and other cells. Subsequently, a robust fibroblast-related score (FRS) was developed. Kaplan-Meier (KM) and ROC analyses showed its good predictive power for patient prognoses in the training set comprising of specimens from the cancer genome atlas (TCGA) and in three external validation sets from the Gene Expression Omnibus (GEO). Univariate and multivariate Cox regression analyses suggested that FRS was a significant prognostic factor independent of multiple clinical characteristics. Functional enrichment and ssGSEA analyses indicated that patients with a high FRS developed "cold" tumors with active tumor proliferation and immunosuppression capacities. In contrast, those with a low FRS developed "hot" tumors with active immune function and cell killing abilities. Genomic variation analysis showed that the patients with a high FRS possessed a higher somatic mutation burden and copy number alterations and were more sensitive to chemotherapy; patients with a low FRS were more sensitive to immunotherapy, particularly anti-PD1 therapy. Overall, these findings advance the understanding of CAFs in tumor progression and we generated a reliable FRS-based model to assess patient prognoses and guide clinical decision-making.
-
Cervical cancer immune infiltration microenvironment identification, construction of immune scores, assisting patient prognosis and immunotherapy.
BACKGROUND: The immune microenvironment is of great significance in cervical cancer. However, there is still a lack of systematic research on the immune infiltration environment of cervical cancer. METHODS: We obtained cervical cancer transcriptome data and clinical information from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, evaluated the immune microenvironment of cervical cancer, determined immune subsets, constructed an immune cell infiltration scoring system, screened key immune-related genes, and performed single-cell data analysis and cell function analysis of key genes. RESULTS: We combined the TCGA and GEO data sets and obtained three different immune cell populations. We obtained two gene clusters, extracted 119 differential genes, and established an immune cell infiltration (ICI) scoring system. Finally, three key genes, IL1B, CST7, and ITGA5, were identified, and single-cell sequencing data were mined to distribute these key genes in different cell types. By up-regulating CST7 and down-regulating IL1B and ITGA5, cervical cancer cells' proliferation ability and invasion ability were successfully reduced. CONCLUSION: We conducted a comprehensive assessment of the state of the tumor immune microenvironment in cervical cancer, constructed the ICI scoring system, and identified the ICI scoring system as a potential indicator of susceptibility to immunotherapy for cervical cancer, identifying key genes suggesting that IL1B, CST7, and ITGA5 play an essential role in cervical cancer.
-
Construction of immune-related signature and identification of S100A14 determining immune-suppressive microenvironment in pancreatic cancer.
Pancreatic cancer (PC) is a highly lethal and aggressive disease with its incidence and mortality quite discouraging. A robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making. Since the critical role of immune microenvironment in the progression of PC, a prognostic signature based on seven immune-related genes was established, which was validated in The Cancer Genome Atlas (TCGA) training set, TCGA testing set, TCGA entire set and GSE71729 set. Furthermore, S100A14 (S100 Calcium Binding Protein A14) was identified as the gene occupying the most paramount position in risk signature. According to the GSEA, CIBERSORT and ESTIMATE algorithm, S100A14 was mainly associated with lower proportion of CD8 + T cells and higher proportion of M0 macrophages in PC tissue. Meanwhile, analysis of single-cell dataset CRA001160 revealed a significant negative correlation between S100A14 expression in PC cells and CD8 + T cell infiltration, which was further confirmed by tissue microenvironment landscape imaging and machine learning-based analysis in our own PUMCH cohort. Additionally, analysis of a pan-pancreatic cancer cell line illustrated that S100A14 might inhibit CD8 + T cell activation via the upregulation of PD-L1 expression in PC cells, which was also verified by the immunohistochemical results of PUMCH cohort. Finally, tumor mutation burden analysis and immunophenoscore algorithm revealed that patients with high S100A14 expression had a higher probability of responding to immunotherapy. In conclusion, our study established an efficient immune-related prediction model and identified the potential role of S100A14 in regulating the immune microenvironment and serving as a biomarker for immunotherapy efficacy prediction.
-
An integrative analysis reveals the prognostic value and potential functions of PSMD11 in hepatocellular carcinoma.
The global burden of hepatocellular carcinoma (HCC) as a preeminent etiology of cancer-related mortalities sheds light on the imperative necessity for a more profound comprehension of its fundamental biological mechanisms. In this context, the precise function of the 26S proteasome non-ATPase regulatory subunit 11 (PSMD11) in HCC remains equivocal. To address this vital knowledge gap, we interrogated the cancer genome atlas, genotype-tissue expression, International cancer genome consortium, gene expression omnibus, the cancer cell line encyclopedia, and tumor immune single-cell hub databases to evaluate the expression pattern of PSMD11, further confirmed by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) in LO2, MHCC-97H, HepG2, and SMMC7721 cell lines. Additionally, we meticulously assessed the clinical significance and prognostic value of PSMD11, while also exploring its potential molecular mechanisms in HCC. Our findings demonstrated that PSMD11 was highly expressed in HCC tissues, correlating with pathologic stage and histologic grade, thereby conferring a poor prognosis. Mechanistically, PSMD11 appears to exert its tumorigenic effects through the modulation of tumor metabolism-related pathways. Impressively, low PSMD11 expression was associated with increased immune effector cell infiltration, heightened responsiveness to molecular targeted drugs such as dasatinib, erlotinib, gefitinib, and imatinib, as well as reduced somatic mutation rate. Additionally, we demonstrated that PSMD11 might modulate HCC development through intricate interactions with cuproptosis-related genes ATP7A, DLAT, and PDHA1. Our comprehensive analyses collectively suggest that PSMD11 represents a promising therapeutic target in HCC.
-
CSEA-DB: an omnibus for human complex trait and cell type associations.
During the past decade, genome-wide association studies (GWAS) have identified many genetic variants with susceptibility to several thousands of complex diseases or traits. The genetic regulation of gene expression is highly tissue-specific and cell type-specific. Recently, single-cell technology has paved the way to dissect cellular heterogeneity in human tissues. Here, we present a reference database for GWAS trait-associated cell type-specificity, named Cell type-Specific Enrichment Analysis DataBase (CSEA-DB, available at https://bioinfo.uth.edu/CSEADB/). Specifically, we curated total of 5120 GWAS summary statistics data for a wide range of human traits and diseases followed by rigorous quality control. We further collected >900 000 cells from the leading consortia such as Human Cell Landscape, Human Cell Atlas, and extensive literature mining, including 752 tissue cell types from 71 adult and fetal tissues across 11 human organ systems. The tissues and cell types were annotated with Uberon and Cell Ontology. By applying our deTS algorithm, we conducted 10 250 480 times of trait-cell type associations, reporting a total of 598 (11.68%) GWAS traits with at least one significantly associated cell type. In summary, CSEA-DB could serve as a repository of association map for human complex traits and their underlying cell types, manually curated GWAS, and single-cell transcriptome resources.
-
M6A modification-related genes characterize prognostic risk and immune regulation in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD), a molecularly complex and aggressive malignancy, has a dismal 5-year survival rate. N6-methyladenosine (m6A) associated factors regulates cancer progression, but its role in LUAD prognosis and immune regulation remains unclear. METHODS: By integrating LUAD gene expression data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we analyzed the expression differences and genetic variations of m6A regulators. Clustering analysis identified distinct m6A modification patterns, while various regression algorithms were employed to construct a risk model based on m6A-related differentially expressed genes, and assessed its clinical relevance, genetic mutations and sensitivity to immunotherapy. PHLDA2 function was assessed by RT-qPCR, proliferation, migration and invasion assays. Its role in immune regulation was tested via MIF promoter luciferase reporter and MIF neutralization followed by STAT3/PD-L1 analysis. Single-cell RNA sequencing and tools including CellChat and NicheNet were used to map gene expression and cell–cell communication in the tumor microenvironment. RESULTS: Consensus clustering analysis based on 15 differentially expressed m6A regulatory factors identified two m6A clusters. 40 key genes closely associated with m6A modification were identified and a two-gene (PHLDA2 and RGS13) risk model correlated with the prognosis of LUAD patients was constructed. High-risk scores were linked to poor prognosis, advanced TNM(Tumor-Node-Metastasis) stage, and higher mutation frequency. Furthermore, PHLDA2 was found to be highly expressed in LUAD, predominantly localizing in epithelial and T cells, influencing late-stage T cell functions, and regulating LUAD cell proliferation, migration and invasion. Additionally, PHLDA2 was positively correlated with Programmed Death-Ligand 1 (PD-L1) and associated with the initiation or activation of immune cycle processes. Experimental validation shows that PHLDA2 promotes MIF transcription, and that MIF signaling is required for PHLDA2-induced PD-L1 upregulation via STAT3 activation. CONCLUSION: m6A modification patterns and the PHLDA2-RGS13 signature predict LUAD prognosis and immunotherapy response. PHLDA2 contributes to tumor progression and immune evasion through MIF-dependent signaling in mediating PHLDA2-driven PD-L1 expression, highlighting this axis as a potential therapeutic target.
-
ADTnorm: robust integration of single-cell protein measurement across CITE-seq datasets.
Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) enables paired measurement of surface protein and mRNA expression in single cells using antibodies conjugated to oligonucleotide tags. Due to the high copy number of surface protein molecules, sequencing antibody-derived tags (ADTs) allows for robust protein detection, improving cell-type identification. However, variability in antibody staining leads to batch effects in the ADT expression, obscuring biological variation, reducing interpretability, and obstructing cross-study analyses. Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. Benchmarking against 14 existing scaling and normalization methods, we show that ADTnorm accurately aligns populations with negative- and positive-expression of surface protein markers across 13 public datasets, effectively removing technical variation across batches and improving cell-type separation. ADTnorm enables efficient integration of public CITE-seq datasets, each with unique experimental designs, paving the way for atlas-level analyses. Beyond normalization, ADTnorm includes built-in utilities to aid in automated threshold-gating as well as assessment of antibody staining quality for titration optimization and antibody panel selection. Applying ADTnorm to an antibody titration study, a published COVID-19 CITE-seq dataset, and a human hematopoietic progenitors study allowed for identifying previously undetected phenotype-associated markers, illustrating a broad utility in biological applications.