The role of vesicular genes in the development of colorectal cancer (CRC) is crucial. Analyzing alterations in these genes at multi-omics can aid in understanding the molecular pathways behind colorectal carcinogenesis and identifying potential treatment targets. However, studies on the overall alteration of vesicular genes in CRC are still lacking. In this study, we aimed to investigate the relationship between vesicle genetic alterations and CRC progression. To achieve this, we analyzed molecular alterations in CRC vesicle genes at eight levels, including mRNA, protein, and epigenetic levels. Additionally, we examined CRC overall survival-related genes that were obtained from a public database. Our analysis of chromatin structural variants, DNA methylation, chromatin accessibility, and proteins (including phosphorylation, ubiquitination, and malonylation), along with RNA-seq data from the TCGA database, revealed multiple levels of alterations in CRC vesicle genes in the collected tissue samples. We progressively examined the alterations of vesicle genes in mRNA and protein levels in CRC and discovered the hub genes. Further investigation identified the probable essential transcription factors. This study contributes to a thorough knowledge of the connection between vesicle gene alterations at multiple levels and the development of CRC and offers a theoretical framework for the identification of novel treatment targets.
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http://dx.doi.org/10.62347/QFKD1805 | DOI Listing |
J Neurosci
January 2025
Nervous System Disorders and Therapy, GIGA Institute, University of Liège, 4000 Liège, Belgium
Synaptic vesicle glycoprotein 2A (SV2A) is a presynaptic protein targeted by the antiseizure drug levetiracetam. One or more of the three SV2 genes is expressed in all neurons and is essential to normal neurotransmission. Loss of SV2A results in a seizure phenotype in mice and mutations in humans are also linked to congential seizures.
View Article and Find Full Text PDFPlacenta
December 2024
Department of Obstetrics & Gynaecology, The University of Auckland, New Zealand. Electronic address:
Introduction: Placental extracellular vesicles (EVs), lipid-enclosed particles released from the placenta, can facilitate intercellular communication and are classified as micro- or nano-EVs depending on size. Placental EVs contain molecules associated with cell proliferation and death. In this study, we investigated whether treating human ovarian tumour explants with placental EVs could induce ovarian tumour cell death.
View Article and Find Full Text PDFBackground: Tauopathies are a group of neurodegenerative disorders which are characterized by the accumulation of abnormal tau protein in the brain. However, the mechanistic understanding of pathogenic tau formation and spread within the brain remains elusive. Astrocytes are major immune reactive cells in the brain and have been implicated in exacerbating tau pathology by releasing extracellular vesicles (AEVs) containing pro-inflammatory cytokines and chemokines upon activation.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Institute for Regenerative Medicine, Department of Cell Biology and Genetics, School of Medicine, Texas A&M University Health Science Center, College Station, Texas, USA., College Station, TX, USA.
Background: Current treatments for Alzheimer's disease (AD) lack disease-modifying interventions. Hence, novel therapies capable of restraining AD progression and maintaining better brain function for extended periods after the initial diagnosis have great significance. Extracellular vesicles (EVs) from human induced pluripotent stem cell (hiPSC)-derived neural stem cells (NSCs) are attractive in this context due to their robust antiinflammatory properties.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
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Background: Polygenic Risk Scores (PRS) are important in predicting disease risk and are usually rely on markers selected by thresholding p-values from genome-wide association studies (GWAS). In traditional approaches, one single model is built to calculate risk scores, employing effect size to determine additive risk. However, this traditional method overlooks potential interactions between genetic loci resulting in reduced prediction power.
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