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PubMed2025

Single-cell glycome and transcriptome profiling enabled by a library of anti-glycan antibodies.

Glycans play critical roles in cellular processes and clinical applications, but they remain difficult to study due to a shortage of well-characterized anti-glycan reagents and high-throughput technologies for glycome profiling, especially ones capable of single-cell resolution. To meet these needs, we generated a database of 650 anti-glycan antibody sequences, recombinantly expressed a library of 154 antibodies, and extensively characterized their binding properties using glycan microarrays. In addition to providing valuable information and resources for the field, the sequence database and microarray data also enabled development of "Glycomic-seq" (Glycome profiling via multiplexed immunoglobulins combined with sequencing), a DNA-barcoded anti-glycan antibody platform that enables high-throughput, single-cell profiling of both RNA and cell-surface glycan expression. Using Glycomic-seq, we profiled two isogenic colorectal cancer cell lines. The results revealed various glycans associated with cancer stem cells and metastasis, demonstrating the power of integrating glycomic information with multi-omic efforts to discover biomarkers and therapeutic targets.

Polysaccharides↗

PubMed2024

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma.

BACKGROUND: Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood. METHODS: The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan-Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray. RESULT: ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma. CONCLUSION: ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Humans↗

PubMed2024

Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis.

BACKGROUND: Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. METHODS: The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. RESULTS: In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. CONCLUSIONS: Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.

Bipolar Disorder↗

PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗

PubMed2025

Biomarker-Based Nomogram to Predict Neoadjuvant Chemotherapy Response in Muscle-Invasive Bladder Cancer.

Background/Objectives: The aim of this study was to identify response prediction and prognostic biomarkers in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC). Methods: A retrospective multicentre study including 191 patients with MIBC who received NAC previous to radical cystectomy (RC) between 1996 and 2013. Gene expression patterns were analysed in 34 samples from transurethral resection of the bladder (TURB) using Illumina microarrays. The expression levels of 45 selected differentially expressed genes between responders and non-responders to NAC were validated by quantitative PCR in an independent cohort of 157 patients. Regression analysis was used to identify predictors of downstaging and relapse. A nomogram for predicting downstaging and relapse-including clinicopathological and gene expression variables-was developed. Results: The expression levels of 1352 transcripts differed between responders and non-responders to NAC. A nomogram based on the most predictive clinical variables (age, Tis (in situ), gender, history of NMIBC, and lymphadenopathy) and genes selected following the Akaike information criterion (AIC) (CBTB16, CHMP6, DDX54, CASP8, LOR, and PLEC) was then created. In addition, a three-gene expression prognostic model to predict tumour relapse was generated. This model was able to discriminate between two groups of patients with a significantly different probability of tumour relapse (HR: 2.11; CI: 1.16-3.83, p = 0.01). Conclusions: Our nomogram based on gene expression and clinical data is a useful tool to predict downstaging and tumour relapse after NAC in MIBC patients. Further validation is warranted.

bladder cancer↗

PubMed2026

Development and Validation of a Prognostic Signature Based on Transcription Factors Associated with Endoplasmic Reticulum Stress in Pancreatic Adenocarcinoma.

BACKGROUND: Endoplasmic reticulum stress (ER stress) plays a crucial role in influencing the malignant behaviors of various tumors. Targeting the expression or degradation of transcription factors (TFs) offers a promising avenue for cancer treatment. However, a detailed understanding of how ER stress affects TF function and their interactions remains limited. This study aims to develop a prognostic model and identify TFs associated with ER stress in pancreatic ductal adenocarcinoma (PDAC). METHODS: We obtained gene expression profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA). To develop a prognostic signature, we performed several analyses, including unsupervised clustering, enrichment analysis, immune infiltration assessment, as well as univariate, LASSO, and multivariate Cox regression analyses. Four transcription factors-STAT1, IRF6, NRF1, and RXRA-were incorporated into a risk model, which was subsequently validated using the GSE dataset. Additionally, we examined IRF6 through quantitative PCR, western blotting, flow cytometry, and immunohistochemistry in vitro using pancreatic cancer cell lines and a tissue microarray. RESULTS: The high-risk group identified by the model exhibited significant associations with immune cell infiltration and poorer survival outcomes, though there was no significant correlation with tumor purity (p = 0.19). Furthermore, IRF6 downregulation in vitro was found to inhibit pancreatic cancer cell proliferation and promote apoptosis. IRF6 depletion also increased the expression of key molecules involved in ER stress at both the transcriptional and translational levels. Immunohistochemical analysis revealed marked differences in IRF6 expression between tumor and adjacent non-tumor tissues (59.29±29.88 vs. 95.22±40.80, p<0.001). CONCLUSION: This study provides evidence that the constructed risk model can effectively predict prognosis in PDAC patients. Transcription factors related to ER stress, such as IRF6, show promise as both prognostic biomarkers and potential therapeutic targets for PDAC.

Humans↗

PubMed2024

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN. METHODS: We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes. RESULTS: Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN. CONCLUSION: This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Diabetic Nephropathies↗

PubMed2024

Genomic insights from a deeply phenotyped highly consanguineous neurodevelopmental disorders cohort.

PURPOSE: The genetic underpinning of neurodevelopmental disorders (NDDs) in diverse ethnic populations, especially those with high rates of consanguinity, remains largely unexplored. Here, we aim to elucidate genomic insight from 576 well-phenotyped and highly consanguineous (16%) NDD cohort. METHODS: We used chromosomal microarray (CMA; N:247), exome sequencing (ES; N:127), combined CMA and ES (N:202), and long-read genome sequencing to identify genetic etiology. Deep clinical multivariate data were coupled with genomic variants for stratification analysis. RESULTS: Genetic diagnosis rates were 17% with CMA, 29.92% with ES, and 37.13% with combined CMA and ES. Notably, children of consanguineous parents showed a significantly higher diagnostic yield (P < .01) compared to those from nonconsanguineous parents. Among the ES-identified pathogenic variants, 36.19% (38/105) were novel, implicating 35 unique genes. Long-read sequencing of seizure participants unresolved by combined test identified expanded FMR1 trinucleotide repeats. Additionally, we identified 2 recurrent X-linked variants in the G6PD in 3.65% (12/329) of NDD participants. These variants were absent in large-population control cohorts and cohort comprising neurodevelopmental and neuropsychiatric populations of European descendants, indicating a possible associated risk factor potentially resulting from ancient genetic drift. CONCLUSION: This study unveils unique clinical and genomic insights from a consanguinity rich Bangladeshi NDD cohort.

Humans↗

PubMed2026

ceRNA network of lncRNAs and mRNAs in OSF-to-OSCC progression: Diagnostic biomarkers and functional pathways.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic potentially malignant disorder that can progress to oral squamous cell carcinoma (OSCC). Although dysregulated non-coding RNAs have been implicated in oral carcinogenesis, the competing endogenous RNA (ceRNA)-mediated regulatory mechanisms underlying OSF-to-OSCC progression remain poorly understood. This study aimed to identify candidate regulatory molecules and construct a putative lncRNA-miRNA-mRNA network associated with malignant transformation. METHODS: Publicly available microarray datasets (GSE117973 and GSE125866) were analyzed to identify differentially expressed genes between OSF and OSCC. Differentially expressed transcripts were classified into mRNAs and lncRNAs based on public transcript annotations. Highly correlated lncRNA-mRNA pairs were identified using Pearson correlation analysis and integrated with multiMiR-supported miRNA-mRNA interactions obtained from public databases to construct a putative ceRNA regulatory network. Functional characterization focused on apoptosis, epithelial-mesenchymal transition (EMT), and immune checkpoint-related pathways. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic performance, and selected biomarkers were externally validated using The Cancer Genome Atlas (TCGA) OSCC cohort. RESULTS: Integrated transcriptomic analysis identified several dysregulated mRNAs and lncRNAs associated with OSF-to-OSCC progression. Network analysis highlighted TBC1D3B, RREB1, TEAD3, SREBF1, TMEM41B, FOXK2, and KIAA1958 as prominent hub genes within the putative regulatory network. Functional analyses demonstrated significant associations with apoptosis-, EMT-, and immune checkpoint-related genes, suggesting potential involvement in multiple biological processes contributing to malignant transformation. Several hub genes exhibited strong diagnostic performance, with ROC analysis yielding AUC values ranging from 0.891 to 1.000, indicating excellent discrimination between OSF and OSCC samples. External validation using TCGA further supported the relevance of the identified biomarkers in OSCC. CONCLUSIONS: This study provides a comprehensive transcriptomic framework describing putative lncRNA-miRNA-mRNA regulatory interactions associated with OSF progression to OSCC. The identified hub genes and regulatory networks represent candidate biomarkers for early detection and provide a foundation for future mechanistic and experimental validation. As the proposed ceRNA interactions are computationally inferred, further biological validation is required before clinical application.

RNA, Long Noncoding↗

PubMed2025

NME2 modulates HCC progression through 4EBP1 phosphorylation and autophagy regulation independent of mTOR.

BACKGROUND: To investigate the role of nucleoside diphosphate kinase 2 (NME2) in HCC progression, assessing its therapeutic potential. METHODS: Utilizing transcriptome sequencing data from The Cancer Genome Atlas (TCGA) and immunohistochemical staining of tissue microarrays, we analyzed NME2 expression in HCC tumor tissues. The effects of NME2 on HCC cell proliferation and autophagy flux were assessed through knockdown and overexpression experiments. Additionally, the relationship between NME2 and 4EBP1 phosphorylation was explored through specific site mutation analysis. RESULTS: NME2 overexpression in HCC correlated with poor prognosis. NME2 knockdown significantly hindered HCC cell proliferation and induced autophagy flux. Notably, NME2 modulates 4EBP1 phosphorylation (Thr37/46) independently of mTOR, unveiling a novel axis in HCC pathogenesis. Additionally, NME2 modulates eukaryotic translation initiation factor 4F (eIF4F) complex formation and autophagy flux. CONCLUSIONS: NME2 plays a crucial role in HCC development by modulating 4EBP1 phosphorylation and autophagy through an mTOR-independent pathway. Our research underscores NME2's significance as a potential therapeutic target in HCC, meriting further exploration of its underlying mechanisms and clinical applicability.

Humans↗

PubMed2025

Tonic signaling of the B-cell antigen-specific receptor is a common functional hallmark in chronic lymphocytic leukemia cell phosphoproteomes at early disease stages.

B-cell chronic lymphocytic leukemia (B-CLL) is characterized by highly heterogeneous genomic alterations and altered signaling pathways, with limited studies on its proteome. Our study presents a comprehensive analysis of the proteome and phosphoproteome in B-CLL and CLL-like monoclonal B-cell lymphocytosis (MBL) primary cells. Using high-resolution mass spectrometry, we identified 2970 proteins and 316 phosphoproteins across five tumor samples, including 55 newly identified phosphopeptides (ProteomeXchange-PXD005997). Our multifaceted approach also integrated protein microarrays and western blotting for further data validation in a new patient cohort of 14 patients. Despite sharing 73% of their proteomes, the phosphoproteomes varied significantly among samples, independent of cytogenetic alterations and immunoglobulin heavy variable cluster (IGHV) mutational status. We identified common functional hallmarks in B-CLL and MBL phosphoproteomes, notably tonic signaling (low-level, constitutive signaling) of the B-cell antigen-specific receptor (BCR) and nuclear factor NF-kappa-B (NF-kβ)/signal transducer and activator of transcription 3 (STAT3) pathways. Nine phosphoproteins involved in BCR signaling were further validated, showing a high correlation with early disease stages. Our study advances the field by providing a detailed perspective on the proteome and phosphoproteome of B-CLL cells, revealing signaling pathways crucial for disease development and progression. Integrating diverse proteomics techniques and identifying novel phosphopeptides offers new insights into CLL biology, potentially informing future therapeutic strategies and biomarker development for early diagnosis and personalized treatment.

Humans↗

PubMed2025

Bioinformatic analyses and validated experiments reveal an aging hallmark gene set and protective miR of coronary artery disease.

To investigate how aging hallmarks exert roles in the age-related disease of coronary artery disease (CAD). R software and the GEO2R online tool identified differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMis) in CAD microarray datasets from the Gene Expression Omnibus. Genes common to target genes of DEMis, DEGs, and an aging gene list from Human Aging Genomic Resources were then identified and analyzed for protein-protein interactions and functional and pathway enrichment. An miR-mRNA network was constructed using Cytoscape. Receiver operating characteristic curve analysis assessed the diagnostic utility of DEMis in CAD. The expression of two DEMis from a CAD cohort was employed to validate the findings. An aging hallmark gene set, comprising 18 genes, was delineated, with the hub gene TP53 established through protein-protein interaction and microRNA-mRNA networks. Within the microRNA-mRNA network, two DEMis (hsa-miR-423-5p and hsa-miR-564) potentially regulated TP53, rendering them potential CAD biomarkers, as indicated by their area under the curves (AUC) surpassing 0.6. Validation experiments corroborated an AUC of 0.7002 for hsa-miR-423-5p and 0.7261 for hsa-miR-564, highlighting its protective association with CAD. Combining hsa-miR-423-5p, hsa-miR-564, total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), white blood cells (WBC) achieved an area under the receiver operating characteristics curve of 0.783. A CAD-associated gene set was identified, with TP53 as the central hub. Hsa-miR-564 emerged as a potential protective factor against CAD.

Humans↗

PubMed2006

Pooled DNA genotyping on Affymetrix SNP genotyping arrays.

BACKGROUND: Genotyping technology has advanced such that genome-wide association studies of complex diseases based upon dense marker maps are now technically feasible. However, the cost of such projects remains high. Pooled DNA genotyping offers the possibility of applying the same technologies at a fraction of the cost, and there is some evidence that certain ultra-high throughput platforms also perform with an acceptable accuracy. However, thus far, this conclusion is based upon published data concerning only a small number of SNPs. RESULTS: In the current study we prepared DNA pools from the parents and from the offspring of 30 parent-child trios that have been extensively genotyped by the HapMap project. We analysed the two pools with Affymetrix 10 K Xba 142 2.0 Arrays. The availability of the HapMap data allowed us to validate the performance of 6843 SNPs for which we had both complete individual and pooled genotyping data. Pooled analyses averaged over 5-6 microarrays resulted in highly reproducible results. Moreover, the accuracy of estimating differences in allele frequency between pools using this ultra-high throughput system was comparable with previous reports of pooling based upon lower throughput platforms, with an average error for the predicted allelic frequencies differences between the two pools of 1.37% and with 95% of SNPs showing an error of < 3.2%. CONCLUSION: Genotyping thousands of SNPs with DNA pooling using Affymetrix microarrays produces highly accurate results and can be used for genome-wide association studies.

Alleles↗

PubMed2026

MAdLandExpression: integrating sexual reproduction into the Physcomitrium patens expression atlas.

Physcomitrium patens is a bryophyte model system particularly valuable for evolutionary developmental and comparative genomics studies. Sexual reproduction in bryophytes offers unique insights into the evolution of land plant reproduction. Unlike seed plants, bryophytes have a dominant gametophyte phase and provide significant advantages for studying sexual reproduction, such as the possibility to maintain embryo-lethal mutants through vegetative propagation or the presence of motile male gametes. More than 25 years after the first publications of transcriptomic data for P. patens, expression data of most developmental stages of P. patens as well as its responses to various biotic and abiotic perturbations have been represented by microarrays or RNA-seq datasets. To facilitate the use of such data, we introduce the MAdLandExpression atlas as a successor of PEATmoss (Physcomitrium Expression Atlas Tool), integrating its 109 P. patens expression experiments and expanding it with 20 recently published RNA-seq samples of sexual reproduction stages, thus completing the coverage of the P. patens life cycle. The MAdLandExpression atlas also introduces new features for data visualization and analysis, such as the comparison of samples from multiple datasets and gene set normalization. Using this tool, the sexual reproduction dataset was analyzed, identifying genes potentially important for egg and sperm cell development, and confirming the behavior of known key genes in sexual development observed in previous studies.

Bryopsida↗

PubMed2025

Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles.

In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.

Journal Article↗

PubMed2026

Multi-omics and experimental validation identify RAPGEF2 as a protective prognostic biomarker in clear cell renal cell carcinoma.

Kidney Renal Clear Cell Carcinoma (KIRC) is characterized by marked molecular heterogeneity and metabolic reprogramming, underscoring the need for reliable biomarkers for prognostic assessment and individualized treatment. RAPGEF2, a guanine nucleotide exchange factor has been implicated in cell adhesion and differentiation, but its role in KIRC remains unclear. In this study, we systematically evaluated the expression pattern, prognostic significance, genomic associations, biological function, and therapeutic relevance of RAPGEF2 in KIRC through integrated multi-omics analyses and experimental validation. Pan-cancer single-cell and Spatial transcriptomic analysis revealed heterogeneous RAPGEF2 expression across tumor types, with a relatively prominent signal in KIRC, where RAPGEF2 was mainly enriched in endothelial cells. Survival analyses in the TCGA-KIRC showed that high RAPGEF2 expression was significantly associated with favorable overall survival, disease-specific survival, and progression-free interval, and these findings were validated in independent ICGC_RECA-EU and E-MTAB-1980 cohorts. Multivariate Cox regression further confirmed RAPGEF2 as an independent protective prognostic factor. Immunohistochemistry in a tissue microarray cohort demonstrated that higher RAPGEF2 protein expression was associated with improved overall survival. Genomic analyses showed that low RAPGEF2 expression was related to higher mutational burden. Functional assays demonstrated that RAPGEF2 knockdown promoted KIRC progression. Enrichment analyses indicated that RAPGEF2 may be associated with metabolic pathway remodeling, while immunotherapy cohort analyses suggested its potential association with therapeutic benefit. Collectively, RAPGEF2 is identified as a protective prognostic biomarker and potential functional regulator in KIRC.

Biomarker↗

PubMed2026

Development of a universal primer set for the identification of enterovirus serotypes using next-generation sequencing.

Enteroviruses have been recognized as major etiological agents of viral myocarditis, a significant contributor to sudden cardiac death. However, the causative virus genomes are rarely identified in forensic autopsy specimens, because extensive nucleic acid degradation compromises analysis. The aim of this study was to develop a next-generation sequencing (NGS)-based method for detecting and identifying the serotype of enteroviruses, which are one of the primary viral causes of myocarditis. We developed a primer set using sequences from 21 representative enterovirus serotypes. The sensitivity of the method was assessed using 13 artificial enteroviral DNA constructs. To confirm the clinical performance of our proposed method, a subset of nasal specimens was analyzed independently by a commercial laboratory using the BioFire Respiratory Panel 2.1 microarray-based viral screening assay, and the results were compared with those obtained using our method. Our method was able to detect as few as 10 copies of artificial DNA and successfully identified all 13 evaluated serotypes, even within a mixture sample. Compared with the BioFire Respiratory Panel 2.1 microarray-based assay, our NGS-based method demonstrated concordant results in 12 out of 14 evaluated cases, showing comparable detection sensitivity. In a trial application of the method, we were also able to detect and serotype enteroviruses in frozen myocardial samples from three forensic myocarditis cases. Overall, the findings of this study suggest that the NGS-based method developed here is a promising diagnostic approach for identifying the causative pathogens of viral myocarditis in forensic autopsy cases.

Autopsy myocardial sample↗

PubMed2005

AnoEST: toward A. gambiae functional genomics.

Here, we present an analysis of 215,634 EST and cDNA sequences of a major vector of human malaria Anopheles gambiae structured into the AnoEST database. The expressed sequences are grouped into clusters using genomic sequence as template and associated with inferred functional annotation, including the following: corresponding Ensembl gene prediction, putative orthologous genes in other species, homology to known proteins, protein domains, associated Gene Ontology terms, and corresponding classification into broad GO-slim functional groups. AnoEST is a vital resource for interpretation of expression profiles derived using recently developed A. gambiae cDNA microarrays. Using these cDNA microarrays, we have experimentally confirmed the expression of 7961 clusters during mosquito development. Of these, 3100 are not associated with currently predicted genes. Moreover, we found that clusters with confirmed expression are nonbiased with respect to the current gene annotation or homology to known proteins. Consequently, we expect that many as yet unconfirmed clusters are likely to be actual A. gambiae genes. [AnoEST is publicly available at http://komar.embl.de, and is also accessible as a Distributed Annotation Service (DAS).].

Animals↗