Inferring gene regulatory networks by hypergraph generative model

Cell Reports Methods, Journal Year: 2025, Volume and Issue: unknown, P. 101026 - 101026

Published: April 1, 2025

We present hypergraph variational autoencoder (HyperG-VAE), a Bayesian deep generative model that leverages representation to single-cell RNA sequencing (scRNA-seq) data. The features cell encoder with structural equation account for cellular heterogeneity and construct gene regulatory networks (GRNs) alongside using self-attention identify modules. synergistic optimization of encoders via decoder improves GRN inference, clustering, data visualization, as validated by benchmarks. HyperG-VAE effectively uncovers regulation patterns demonstrates robustness in downstream analyses, shown B development from bone marrow. Gene set enrichment analysis overlapping genes predicted GRNs confirms the encoder's role refining inference. Offering an efficient solution scRNA-seq construction, also holds potential extending modeling temporal multimodal omics.

Language: Английский

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Inferring gene regulatory networks by hypergraph variational autoencoder

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 2, 2024

Abstract In constructing Gene Regulatory Networks (GRNs), it is crucial to consider cellular heterogeneity and differential gene regulatory modules. However, traditional methods have predominantly focused on heterogeneity, approaching the subject from a relatively narrow scope. We present HyperG-VAE, Bayesian deep generative model that utilizes hypergraph single-cell RNA sequencing (scRNA-seq) data. HyperG-VAE employs cell encoder with Structural Equation Model address build GRNs, alongside using self-attention identify Encoders are synergistically optimized by decoder, enabling excel in GRN inference, clustering, data visualization, evidenced benchmarks. Additionally, effectively reveals regulation patterns shows robustness varied downstream analyses, demonstrated B development bone marrow. The interplay of encoders overlapping genes between predicted GRNs modules further validated set enrichment analysis, underscoring boosts inference. proves efficient scRNA-seq analysis

Language: Английский

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Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(23), P. 16638 - 16638

Published: Nov. 23, 2023

The microbiome has shown a correlation with the diet and lifestyle of each population in health disease, ability to communicate at cellular level host through innate adaptative immune receptors, therefore an important role modulating inflammatory process related establishment progression cancer. oral cavity is one most interaction windows between human body environment, allowing entry number microorganisms their passage across gastrointestinal tract lungs. In this review, contribution network systemic diseases like cancer analyzed synergistic interactions bidirectional crosstalk oral-gut-lung axis as well its communication cells. Moreover, impact characteristic microbiota formation multiomics molecular metafirm also state-of-the-art sequencing techniques, which allow global study processes involved flow environmental signals cancer-related cells relationship transcription factor responsible for control regulatory tumorigenesis.

Language: Английский

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Enhancer mutations modulate the severity of chemotherapy-induced myelosuppression

Life Science Alliance, Journal Year: 2024, Volume and Issue: 7(3), P. e202302244 - e202302244

Published: Jan. 16, 2024

Non-small cell lung cancer is often diagnosed at advanced stages, and many patients are still treated with classical chemotherapy. The unselective nature of chemotherapy results in severe myelosuppression. Previous studies showed that protein-coding mutations could not fully explain the predisposition to Here, we investigate possible role enhancer myelosuppression susceptibility. We produced transcriptome promoter-interaction maps (using HiCap) three blood stem-like lines carboplatin or gemcitabine. Taking advantage publicly available datasets, validated HiCap silico living cells using epigenetic CRISPR technology. also developed a network approach for interactome analysis detection differentially interacting genes. Differential interaction provided additional information on relevant genes pathways compared differential gene expression bulk level. Moreover, enhancers highly enriched variants associated differing levels Altogether, our work represents prominent example integrative regulatory datasets functional annotation noncoding mutations.

Language: Английский

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Global transcriptomic network analysis of the crosstalk between microbiota and cancer-related cells in the oral-gut-lung axis

Frontiers in Cellular and Infection Microbiology, Journal Year: 2024, Volume and Issue: 14

Published: Aug. 20, 2024

The diagnosis and treatment of lung, colon, gastric cancer through the histologic characteristics genomic biomarkers have not had a strong impact on mortality rates top three global causes death by cancer.

Language: Английский

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Crosstalk between SOX Genes and Long Non-Coding RNAs in Glioblastoma

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(7), P. 6392 - 6392

Published: March 28, 2023

Glioblastoma (GBM) continues to be the most devastating primary brain malignancy. Despite significant advancements in understanding basic GBM biology and enormous efforts developing new therapeutic approaches, prognosis for patients remains poor with a median survival time of 15 months. Recently, interplay between SOX (SRY-related HMG-box) genes lncRNAs (long non-coding RNAs) has become focus research. Both classes molecules have an aberrant expression play essential roles tumor initiation, progression, therapy resistance, recurrence. In GBM, crosstalk through numerous functional axes, some which are part complex transcriptional epigenetic regulatory mechanisms. This review provides systematic summary current literature data on represents effort underscore effects SOX/lncRNA malignant properties cells. Furthermore, we highlight significance this searching biomarkers approaches treatment.

Language: Английский

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Transcription factor-target gene regulatory network analysis in human lung adenocarcinoma

Journal of Thoracic Disease, Journal Year: 2023, Volume and Issue: 15(12), P. 6996 - 7012

Published: Dec. 1, 2023

Background: Transcription factors (TFs) play a crucial role in the occurrence and progression of lung adenocarcinoma (LUAD), targeting TFs is an important direction for treating LUAD. However, single TF often fails to achieve satisfactory therapeutic outcomes. Furthermore, regulatory TF-target gene networks involved development LUAD complex not yet fully understood. Methods: In this study, we performed RNA sequencing (RNA-seq) analyze transcriptome profile human tissues matched adjacent nontumor tissues. We selected differentially expressed TFs, enrichment analysis survival curve analysis, predicted top differential with their target genes. Finally, alternative splicing analyses were also performed. Results: found that GRHL3, SIX1, SIX2, SPDEF, ETV4 upregulated, while TAL1, EPAS1, SOX17, NR4A1, EGR3 significantly downregulated compared normal propose potential GRHL3-CDH15-Wnt-β-catenin pro-oncogenic signaling axis TAL1-ADAMTS1-vascular antioncogenic axis. addition, intron retention (IR), approximate IR (XIR), multi-IR (MIR), MIR (XMIR), exon ends (XAE) showed abnormally increased frequencies Conclusions: These findings revealed novel related tumorigenesis provided targets mechanisms

Language: Английский

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Prognostic value and molecular mechanisms of OAS1 in lung adenocarcinoma

BMC Pulmonary Medicine, Journal Year: 2024, Volume and Issue: 24(1)

Published: Sept. 27, 2024

Language: Английский

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Prediction Of Lung Cancer and Analysis of Lung Cancer Related Gene Expressions Through Logistic Regression, PCA Random Forest, And LASSO Regression

Highlights in Science Engineering and Technology, Journal Year: 2024, Volume and Issue: 123, P. 156 - 162

Published: Dec. 24, 2024

Research Background: Lung cancer is frequently associated with the expression levels of certain genes, where both over-expression and under-expression may indicate presence disease. It was hypothesized that specific genes might exhibit a more pronounced correlation lung cancer. To explore this, gene data from patients without were obtained initially screened using volcano plots to identify significant differential expression. Study Contributions: The refined dataset subjected comprehensive analysis five distinct methodologies: principal component (PCA), random forest, logistic regression, least absolute shrinkage selection operator (LASSO), method employing lambda cross-validation for selecting influential genes. Each model’s performance assessed by its area under curve (AUC) value, which then informed weighting system prioritize findings. A weighted table subsequently developed finalize diagnosis synthesis these approaches not only enhanced accuracy diagnostic model, confirmed be precise in at 96 percent cases, but also led identification 75 significantly Among these, CLDN18, GKN2, LYVE-1, GPIHBP1, CLIC5 determined most closely linked

Language: Английский

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Lung Cancer through Transcription Factors

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(11), P. 9461 - 9461

Published: May 30, 2023

The body of knowledge on the molecular mechanisms that drive lung cancer, including non-small cell cancer (NSCLC) and small (SCLC), is continuously growing [...].

Language: Английский

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