Single-cell omics technologies have revolutionized the study of long non-coding RNAs (lncRNAs), offering unprecedented resolution in elucidating their expression dynamics, cell-type specificity, and associated gene regulatory networks (GRNs). Concurrently, the integration of artificial intelligence (AI) methodologies has significantly advanced our understanding of lncRNA functions and its implications in disease pathogenesis. This chapter discusses the progress in single-cell omics data analysis, emphasizing its pivotal role in unraveling the molecular mechanisms underlying cellular heterogeneity and the associated regulatory networks involving lncRNAs. Additionally, we provide a summary of single-cell omics resources and AI models for constructing single-cell gene regulatory networks (scGRNs). Finally, we explore the challenges and prospects of exploring scGRNs in the context of lncRNA biology.
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http://dx.doi.org/10.1007/978-1-0716-4290-0_11 | DOI Listing |
Discov Oncol
January 2025
Second Department of Oncology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China.
Introduction: We conducted a panoramic analysis of GBN5 expression and prognosis in 33 cancers, aiming to deepen the systematic understanding of GBN5 in cancer.
Materials And Methods: We employed a multi-omics approach, including transcriptomic, genomic, proteomic, single-cell cytomic, spatial transcriptomic, and genomic data, to explore the prognostic value and potential oncogenic mechanisms of GBN5 across pan-cancers from multiple perspectives.
Results: We found that GBN5 was differentially expressed in multiple tumors and showed early diagnostic value.
Pharmaceuticals (Basel)
January 2025
Department of Biomedicine, Texas A&M University, College Station, TX 77843, USA.
Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of the tumor microenvironment (TME), leading to important advancements toward a much deeper understanding of how tumor microenvironment heterogeneity contributes to cancer progression and therapeutic resistance. These technologies are able to integrate data from molecular genomic, transcriptomic, proteomics, and metabolomics studies of cells at a single-cell resolution scale that give rise to the full cellular and molecular complexity in the TME. Understanding the complex and sometimes reciprocal relationships among cancer cells, CAFs, immune cells, and ECs has led to novel insights into their immense heterogeneity in functions, which can have important consequences on tumor behavior.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Clinical Division of General Anaesthesia and Intensive Care Medicine, Department of Anesthesia, Genera Intensive Care and Pain Therapy, Medical University Vienna, 1090 Vienna, Austria.
Drug development for human disease relies on preclinical model systems such as human cell cultures and animal experiments before therapeutic treatments can ultimately be tested on humans in clinical studies. We here describe the generation of a novel human cell line (HLMVEC/SVTERT289) that we generated by transfection of microvascular endothelial cells from healthy donor lung tissue with the catalytic domain of telomerase and the SV40 large T/small t-antigen. These cells exhibited satisfactory growth characteristics and largely maintained their native characteristics, including morphology, cell surface marker expression, angiogenic potential and the protein composition of secreted extracellular vesicles.
View Article and Find Full Text PDFGenes (Basel)
December 2024
Institute for Complex Systems and Mathematical Biology, King's College, University of Aberdeen, Old Aberdeen AB24 3UE, UK.
Background/objectives: A prominent endophenotype in Autism Spectrum Disorder (ASD) is the synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigate the postsynaptic signal transduction network in glutamatergic neurons and integrate single-cell nucleus transcriptomics data from the Prefrontal Cortex (PFC) to unveil the malfunction of translation control.
Methods: We devise an innovative and highly dependable pipeline to transform our acquired signal transduction network into an mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level.
Cancers (Basel)
January 2025
SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Research Institute (PACRI), University of Pretoria, Hartfield, Pretoria 0028, South Africa.
Endometrial cancer (EC), a prevalent gynecological malignancy, presents significant challenges due to its genetic complexity and heterogeneity. The genomic landscape of EC is underpinned by genetic alterations, such as mutations in PTEN, PIK3CA, and ARID1A, and chromosomal abnormalities. The identification of molecular subtypes-POLE ultramutated, microsatellite instability (MSI), copy number low, and copy number high-illustrates the diverse genetic profiles within EC and underscores the need for subtype-specific therapeutic strategies.
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