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scMMAE: masked cross-attention network for single-cell multimodal omics fusion to enhance unimodal omics.
Brief Bioinform
November 2024
Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems, Great Bay University, No. 16 Daxue Rd, Songshanhu District, Dongguan, Guangdong, 523000, China.
Multimodal omics provide deeper insight into the biological processes and cellular functions, especially transcriptomics and proteomics. Computational methods have been proposed for the integration of single-cell multimodal omics of transcriptomics and proteomics. However, existing methods primarily concentrate on the alignment of different omics, overlooking the unique information inherent in each omics type.
View Article and Find Full Text PDFMacrophage heterogeneity and oncogenic mechanisms in lung adenocarcinoma: insights from scRNA-seq analysis and predictive modeling.
Front Immunol
January 2025
Tianjin Chest Hospital, Tianjin University, Tianjin, China.
Background: Macrophages play a dual role in the tumor microenvironment(TME), capable of secreting pro-inflammatory factors to combat tumors while also promoting tumor growth through angiogenesis and immune suppression. This study aims to explore the characteristics of macrophages in lung adenocarcinoma (LUAD) and establish a prognostic model based on macrophage-related genes.
Method: We performed scRNA-seq analysis to investigate macrophage heterogeneity and their potential pseudotime evolutionary processes.
Integrated single-cell and bulk transcriptome analysis of R-loop score-based signature with regard to immune microenvironment, lipid metabolism and prognosis in HCC.
Front Immunol
January 2025
National Key Laboratory of Draggability Evaluation and Systematic Translational Medicine, Tianjin's Clinical Research Center for Cancer, Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Background: Hepatocellular carcinoma (HCC) is one of the most prevalent causes of cancer-related morbidity and mortality worldwide. Late-stage detection and the complex molecular mechanisms driving tumor progression contribute significantly to its poor prognosis. Dysregulated R-loops, three-stranded nucleic acid structures associated with genome instability, play a key role in the malignant characteristics of various tumors.
View Article and Find Full Text PDFCombining single-cell analysis and molecular docking techniques to construct a prognostic model for colon adenocarcinoma and uncovering inhibin subunit βb as a novel therapeutic target.
Front Immunol
January 2025
Department of Preventive Medicine, Shantou University Medical College, Shantou, China.
Background: Colon adenocarcinoma (COAD) is a malignancy with a high mortality rate and complex biological characteristics and heterogeneity, which poses challenges for clinical treatment. Anoikis is a type of programmed cell death that occurs when cells lose their attachment to the extracellular matrix (ECM), and it plays a crucial role in tumor metastasis. However, the specific biological link between anoikis and COAD, as well as its mechanisms in tumor progression, remains unclear, making it a potential new direction for therapeutic strategy research.
View Article and Find Full Text PDFExploring the utility of snRNA-seq in profiling human bladder tissue: A comprehensive comparison with scRNA-seq.
iScience
January 2025
Epigenetics & Molecular Carcinogenesis, M.D. Anderson Cancer Center, Houston, TX 77054, USA.
Single cell sequencing technologies have revolutionized our understanding of biology by mapping cell diversity and gene expression in healthy and diseased tissues. While single-cell RNA sequencing (scRNA-seq) has been widely used, interest in single-nucleus RNA sequencing (snRNA-seq) is growing due to its benefits, including the ability to analyze archival tissues and capture rare cell types that are challenging to dissociate. However, comparative studies across tissues have yielded mixed results, with some reporting enhanced cell type retention using snRNA-seq while others finding cell type identification to be challenging in snRNA-seq data.
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