BMC Medical Genomics最新文献

Background: Glioma, the most common aggressive tumor found in the central nervous system, is linked to a poor prognosis. Anoikis is a form of cell death that arises from the detachment of cells. Disruption of the anoikis pathway can facilitate the survival and dispersal of cancer cells from the primary tumor site, thus playing a critical role in the spread and advancement of cancer. The process of Epithelial-to-mesenchymal transition (EMT) is crucial in the progression and spread of cancer, where epithelial cells undergo a loss of polarity and adhesion, transitioning into mesenchymal cells with heightened capability for invasion and metastasis. However, there is a dearth of research examining the mechanism of anoikis and its correlation with the EMT process in glioma.

Methods: In our study, data was extracted from 1317 samples of glioma for comparative examination. Through the utilization of 28 genes associated with resistance to cell detachment, we aimed to distinguish various categories of glioma patients by evaluating the immune environment and pathways of enrichment within the two subgroups. By implementing diverse statistical methodologies such as COX regression analysis and the least absolute shrinkage and selection operator regression, we developed a risk scoring system to categorize glioma patients into cohorts of high and low risk. The clinical features, infiltration of immune cells, and responsiveness to drugs were thoroughly investigated for both categories, highlighting distinctions across various domains. Moreover, our investigation encompassed in vitro trials to assess the function and expression of the pivotal gene, PLAU.

Results: The differences in prognoses, immune status, and drug sensitivities between high-risk and low-risk groups highlight the need for personalized treatment approaches in glioma patients. By integrating risk scores with clinicopathological characteristics, a nomogram was created to better predict patient outcomes and guide treatment decisions. The nomogram demonstrated its usefulness through decision curve analysis, showing potential benefits for enhancing clinical strategies in glioma management. In cell experiments, targeting Plasminogen activator urokinase (PLAU)led to a notable decrease in the growth, spread, and movement abilities of T98G and U251 cell lines, as well as blocking the epithelial-mesenchymal transition process.

Conclusion: The study we conducted establishes the groundwork for comprehending the function of anoikis genes in glioma, and recognizes PLAU as a potential biomarker for glioma.

Multiple sclerosis is a neurological autoimmune disease with sex-imbalanced incidence; in the USA, the disease is more likely to affect females at a ratio of 3:1. In addition, males are more likely to have a more severe disease course at time of diagnosis. Questions about both causes and downstream effects of this disparity remain. We aim to investigate gene expression differences at a cellular level while considering sex to discover fine-scale sex disparities. These investigations could provide new avenues for treatment targeting, or treatment planning based on sex.Public single-nuclei RNA-sequencing data from three publications of progressive MS including control brains were analysed using the Seurat R package. Differential gene and pathway expression was looked at both within a specific data set which has sub-lesion level sample dissection and across all studies to provide a broader lens. This allowed for the consideration of cell types and spatial positioning in relation to the interrogated lesion in some of the calculations.Our analysis showed expression changes in the female MS oligodendrocytes and oligodendrocyte progenitor cells compared to healthy controls, which were not observed in the corresponding male affected cells. Differentially up-regulated genes in females include increased HLA-A in the oligodendrocytes, and increased clusterin in the oligodendrocyte progenitor cells. There are also several mitochondrial genes in both the oligodendrocytes and oligodendrocyte progenitors which are up-regulated in females, including several directly involved in electron transport and which have previously been associated with neurodegenerative diseases.These results point to altered states in oligodendrocyte progenitors and oligodendrocytes that in combination with known physiological dissimilarities between sexes may denote different programming in males and females in response to the onset of demyelinating lesions. The potential for increased debris clearance mediated by clusterin and availability of oligodendrocyte progenitors in females may indicate an environment more primed for repair, potentially including remyelination. This could contribute to the disparity in etiology in females versus males.

Background: Breast cancer (BC) is the most common malignancy diagnosed among women worldwide. The Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway plays a critical role in regulating cellular differentiation, maturation, proliferation, and apoptosis across various cell types involved in cancer initiation and progression. The suppressor of cytokine signaling 3 (SOCS3) acts as a key negative regulator of the JAK/STAT pathway. Therefore, investigating the role of single nucleotide polymorphisms (SNPs) in the SOCS3 gene is essential to better understand their contribution to the pathogenesis of breast cancer.

Methods: This case-control study included 300 female patients with breast cancer and 300 healthy female volunteers as controls. Ethical approval was obtained from the Institutional Ethics Committee prior to the commencement of study and was in compliance with the Helsinki Declaration. Written informed consent was obtained from all participants. Three SOCS3 SNPs-rs4969169 (C > T), rs12953258 (C > A), and rs1061489 (G > A)-were genotyped using Polymerase chain reaction-Restriction fragment length Polymorphism and Amplification refractory mutation system-PCR methods. Genotypic distributions, allele frequencies, and haplotype associations were analyzed, with statistical significance set at p < 0.05.

Results: The TT genotype and T allele of rs4969169 (C > T) conferred 4.29-fold and 2.16-fold increased risk, respectively, for breast cancer. Similarly, the CA genotype and A allele of rs12953258 (C > A) were associated with 1.95-fold and 2.02-fold increased risk, while the GA genotype and A allele of rs1061489 (G > A) conferred 4.58-fold and 3.87-fold increased risk, respectively. Haplotype analysis revealed significant associations with advanced disease stage, lymph node involvement, lobular carcinoma, and negative receptor status for ER, PR, and HER2/neu. The T-C-G, C-A-G, C-C-A, and T-C-A haplotypes conferred 2.18-, 2.64-, 3.65-, and 13.66-fold increased risk, respectively, for breast cancer development.

Conclusion: Therefore, our study results suggest the significance of genotypic and haplotype analysis of SOCS3 gene polymorphisms and its impact on progression and risk prediction of breast cancer.

Background: Transcriptomic analysis is common in large cohort studies but is generally restricted to cells in blood, which limits inferences about organs of interest, and direct organ sampling is mostly infeasible in large cohorts. New techniques for RNA-seq from noninvasive biosamples may provide the opportunity to profile transcriptomes of additional tissues for more organ-relevant insights at scale. We investigated the feasibility and utility of hair follicle gene expression profiling in a multi-center study of chronic obstructive pulmonary disease (COPD).

Methods: Bulk RNA-seq was performed on hair follicles collected in the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS), a multi-center longitudinal study of COPD (n = 97). The resulting hair follicle gene expression data were characterized and compared both to gene expression in whole blood and bronchial epithelium previously measured in SPIROMICS and to Genotype-Tissue Expression (GTEx) project tissue gene expression by principal component analysis and single-sample gene enrichment analysis, used to estimate hair follicle cell type proportions, and tested for association with disease-relevant lung phenotypes. eQTL discovery was also performed and colocalization with a genome-wide association study for lung function was tested.

Results: Hair follicles reliably produced transcriptomic data of sufficient quality and number for cell type composition, which revealed mostly epithelial and fibroblast cells. Comparison to other tissues previously profiled in SPIROMICS and GTEx project demonstrated transcriptomes from hair follicles were much more similar to those from lung parenchyma than blood. Combining these data with rich clinical, imaging, and genomic profiling in SPIROMICS, we found that they provided an attractive approach for discovery of associations with complex lung phenotypes, particularly of the airways. Finally, we investigated hair follicle genetic architecture through expression quantitative trait locus (eQTL) discovery and demonstrated better colocalization with lung-related genetic associations than blood.

Conclusion: Here, we demonstrated that RNA-seq applied to hair follicle transcriptomic profiling can be scaled up successfully in a multi-center study to yield inferences not available from blood transcriptomics.

Susceptibility genes, including single-nucleotide polymorphisms (SNPs) in the DNA sequences, genetically predispose certain individuals to developing adverse events (AEs) following vaccination. Such AEs are often undetected in initial clinical safety trials during vaccine licensing evaluations. Therefore, a comprehensive understanding of susceptibility genes is crucial for vaccine development, safety monitoring, and precision immunization. VaegenDB is a web-based centralized database and analysis system designed for managing, storing, and analyzing susceptibility genes associated with vaccine AEs. Basic information on these genes and supporting evidence are curated from peer-reviewed literature, while more detailed gene, AE, and vaccine data are automatically extracted from existing databases such as RefSeq and VIOLIN using in-house scripts. Currently, VaegenDB contains information on 160 susceptibility genes linked to 151 AEs and 86 vaccines. The system offers a user-friendly web interface that enables interactive querying and visualization of susceptibility genes. Bioinformatics analyses using VaegenDB reveal that a single susceptibility gene may harbor multiple genetic variations, one vaccine can be associated with several AEs, and a single AE may be influenced by multiple genes or SNPs. In addition, KEGG and GO enrichment analyses were employed to identify gene signatures-including functional annotations, mutation types, and expression patterns-associated with adverse reactions. The construction of this database and subsequent bioinformatics analyses help clarify enriched gene profiles and underlying mechanisms of vaccine-related AEs, thereby supporting rational vaccine design and advances in precision medicine.