Frontiers in Molecular Biosciences最新文献

Objectives: In this study, we constructed a model based on circadian rhythm associated genes (CRRGs) to predict prognosis and immune infiltration in patients with breast cancer (BC).

Materials and methods: By using TCGA and CGDB databases, we conducted a comprehensive analysis of circadian rhythm gene expression and clinicopathological data. Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. On this basis, a circadian gene prediction model about BC prognosis was constructed and validated. We also evaluated the association of the model's risk score with immune cells and immune checkpoint genes, and analyzed prognostic genes and drug sensitivity in this model.

Results: We screened 62 DEGs, including 30 upregulated genes and 32 downregulated genes, and performed GO and KEGG analysis on them. The above 62 DEGs were included in Cox analysis, LASSO regression, Random Forest and SVMV-RFE, respectively, and then the intersection was used to obtain 5 prognostic related characteristic genes (SUV39H2, OPN4, RORB, FBXL6 and SIAH2). The Risk Score of each sample was calculated according to the expression level and risk coefficient of 5 genes, Risk Score= (SUV39H2 expression level ×0.0436) + (OPN4 expression level ×1.4270) + (RORB expression level ×0.1917) + (FBXL6 expression level ×0.3190) + (SIAH2 expression level × -0.1984).

Conclusion: SUV39H2, OPN4, RORB and FBXL6 were positively correlated with Risk Score, while SIAH2 was negatively correlated with Risk Score. The above five circadian rhythm genes can construct a risk model for predicting the prognosis and immune invasion of BC.

Cerebral vasospasm (CVS), a serious complication following subarachnoid hemorrhage, is associated with high rates of mortality and disability. Emerging evidence suggests that abnormal miRNA and mRNA are involved in the development of CVS. This study aims to identify essential miRNA-mRNA regulatory pairs that contribute to CVS pathogenesis. We compared the differences between spasm and non-spasm groups after cerebral hemorrhage, identifying 183 differentially expressed genes (DEGs) and 19 differentially expressed miRNAs (DEMs) related to cerebral vasospasm from the GEO database. Further functional enrichment and KEGG analysis revealed that these DEGs were enriched in several terms and pathways, including the PI3K/AKT/mTOR signaling pathway, oxidative phosphorylation pathway, RNA degradation, and folate biosynthesis signaling pathway. By employing the degree scores method for each gene, we identified the top 10 genes and developed a protein-protein interaction (PPI) network. Additionally, we discovered 19 DEMs associated with CVS and integrated them with mRNA dataset analysis to construct a miRNA-mRNA network, which comprised 8 functionally differentially expressed DEMs and 6 target mRNAs. Experimental validation confirmed the significant regulatory roles of four miRNAs (Let-7a-5p, miR-24-3p, miR-29-3p, and miR-132-3p) and two mRNAs (CDK6 and SLC2A1) in the pathogenesis of CVS. In conclusion, this comprehensive study identifies pivotal miRNAs and their target mRNAs associated with CVS through an integrated bioinformatics analysis of miRNA-mRNA co-expression networks. This approach elucidates the intricate molecular mechanisms underlying CVS and uncovers potential therapeutic targets, thereby providing a valuable foundation for refining and optimizing future treatment strategies.

HOXC13 antisense RNA (HOXC13-AS, also known as HOXC-AS5) is a long non-coding RNA that is expressed abnormally in various types of tumors and is closely related to clinical staging, clinical pathological features, and patient survival. HOXC13-AS is involved in the occurrence and development of tumors, affecting cell proliferation, migration, invasion, epithelial-mesenchymal transition, and tumor growth. This review summarizes the clinical significance of HOXC13-AS as a biomarker for human tumor diagnosis and prognosis and outlines the function and molecular regulation mechanism of HOXC13-AS in various types of cancer, including nasopharyngeal carcinoma, breast cancer, oral squamous cell carcinoma, glioma, and cervical cancer. Overall, this review emphasizes the potential of HOXC13-AS as a human tumor predictive biomarker and therapeutic target, paving the way for its clinical application.

Intracerebral hemorrhage (ICH) is a non traumatic hemorrhage that occurs in a certain part of the brain. It usually leads to brain cell damage. According to a large number of experimental research, oxidative stress is an important pathophysiological processes of cerebral hemorrhage. In this paper, we aim to determine how changes in oxidative stress biomarkers indicate the damage degree of cerebral hemorrhage, and to explore and summarize potential treatments or interventions. We found that patients with cerebral hemorrhage are characterized by increased levels of oxidative stress markers, such as total malondialdehyde (MDA), F2 isoprostaglandin, hydroxynonenal, myeloperoxidase and protein hydroxyl. Therefore, the changes of oxidative stress caused by ICH on these markers can be used to evaluate and diagnose ICH, predict its prognosis, and guide preventive treatment to turn to antioxidant based treatment as a new treatment alternative.

Glycosylation, a post-translational modification, plays a crucial role in proper localization and function of proteins. It is regulated by multiple glycosyltransferases and can be influenced by various factors. Inherited missense mutations in glycosylated proteins such as NOTCH3, Low-density lipoprotein receptor (LDLR), and Amyloid precursor protein (APP) could affect their glycosylation states, leading to cerebral small vessel disease, hypercholesterolemia, and Alzheimer's disease, respectively. Additionally, physiological states and aging-related conditions can affect the expression levels of glycosyltransferases. However, the interplay between mutations in glycosylated proteins and changes in their glycosylation levels remains poorly understood. This mini-review summarizes the effects of glycosylation on transmembrane proteins with pathogenic mutations, including NOTCH3, LDLR, and APP. We highlight the synergistic contributions of missense amino acids in the mutant proteins and alterations in their glycosylation states to their molecular pathogenesis.

Objective: Endometriosis (EMs) is a chronic inflammatory disease characterized by the presence of endometrial tissue in the non-uterine cavity, resulting in dysmenorrhea, pelvic pain, and infertility. Epidemiologic data have suggested the correlation between EMs and recurrent pregnancy loss (RPL), but the pathological mechanism is unclear. This study aims to investigate the potential biomarkers and immune infiltration in EMs and RPL, providing a basis for early detection and treatment of the two diseases.

Methods: Two RPL and six EMs transcriptomic datasets from the Gene Expression Omnibus (GEO) database were used for differential analysis via limma package, followed by weighted gene co-expression network analysis (WGCNA) for key modules screening. Protein-protein interaction (PPI) network and two machine learning algorithms were applied to identify the common core genes in both diseases. The diagnostic capabilities of the core genes were assessed by receiver operating characteristic (ROC) curves. Moreover, immune cell infiltration was estimated using CIBERSORTx, and the Cancer Genome Atlas (TCGA) database was employed to elucidate the role of key genes in endometrial carcinoma (EC).

Results: 26 common differentially expressed genes (DEGs) were screened in both diseases, three of which were identified as common core genes (MAN2A1, PAPSS1, RIBC2) through the combination of WGCNA, PPI network, and machine learning-based feature selection. The area under the curve (AUC) values generated by the ROC indicates excellent diagnostic powers in both EMs and RPL. The key genes were found to be significantly associated with the infiltration of several immune cells. Interestingly, MAN2A1 and RIBC2 may play a predominant role in the development and prognostic stratification of EC.

Conclusion: We identified three key genes linking EMs and RPL, emphasizing the heterogeneity of immune infiltration in the occurrence of both diseases. These findings may provide new mechanistic insights or therapeutic targets for further research of EMs and RPL.

The dual-target inhibitor strategy is an evolving approach that holds great potential for treating complex diseases by addressing their multifactorial nature. It can enhance therapeutic outcomes, reduce side effects and avoid the emergence of drug resistance, particularly in conditions like cancer, inflammation and neurological disorders, where multiple pathways contribute to disease progression. Identifying suitable targets for a dual inhibitor approach requires a deep understanding of disease biology, knowledge of critical pathways, and selection of complementary or synergistic targets. Human carbonic anhydrases (hCAs) have been recognized as suitable drug targets for this therapeutic approach. These enzymes play a key role in maintaining pH balance, ion transport, and fluid regulation across various tissues and organs and their dysregulation has been associated to a variety of human pathologies. Consequently, the inhibition of hCAs combined to the possibility to modulate the activity of a second molecular target represents a promising way for developing more effective drugs. In this mini-review, we aim to present an overview of the most significant structural results related to the development of novel therapeutics employing hCA inhibitors as dual-targeting compounds for the treatment of complex diseases.

Atherosclerosis, the primary cause of coronary artery disease (CAD), remains a leading global cause of mortality. It is characterized by the accumulation of cholesterol-rich plaques and inflammation, which narrow the coronary arteries and increase the risk of rupture. To elucidate this complex biological process and improve therapeutic strategies, CAD has been extensively explored from an epigenetic perspective over the past two decades. Epigenetics is a field investigating heritable alterations in gene expression without DNA sequence changes, such as DNA methylation, histone modifications, and non-coding RNAs. Increasing evidence has indicated that the development of CAD is significantly influenced by epigenetic changes. Meanwhile, the impact of epigenetics in CAD is now transitioning from pathophysiology to therapeutics. Focusing on the key epigenetic enzymes and their target genes will help to facilitate the diagnosis and treatment of CAD. This review synthesizes novel epigenetic insights into CAD, addressing the pathological processes, key molecular mechanisms, and potential biomarkers. Furthermore, we discuss emerging therapeutic strategies targeting epigenetic pathways. By focusing on pivotal enzymes and their associated genes, this work aims to advance CAD diagnostics and interventions.

Background: The molecular non-genetic changes of resistance to sotorasib are currently uncertain. The aim of this study was to generate a sotorasib-resistant cell line via selective pressure and systematically examine the molecular and phenotypic alterations caused by resistance.

Methods: Mutant NCI-H358 (KRAS^G12C) were exposed to incremental doses (2-512 nM) of sotorasib. Then, resistant clones were separated by single-cell sorting. Proliferation was analyzed in real-time by xCELLigence; protein profiles were quantified by protein arrays; and mRNA expression profile was measured using the PanCancer Pathways panel by NanoString. In silico analyses were conducted from a database comprising patient-derived xenograft (PDX) models and cell lines resistant to sotorasib. AKT and p38. The synergistic effect of combining AKT, p38, and EGFR inhibitors was assessed using the SynergyFinder platform. Additionally, AKT and p38 genes were silenced using esiRNA.

Results: Sotorasib-resistant H358-R cell line displayed markers of the mesenchymal-epithelial transition and loss of cell adhesion. Were identified 30 overexpressed genes in the resistance model, implicating in signaling pathways that leads to AKT activation and heightened protein expression levels of phosphorylated AKT and p38. To identify potential therapeutic strategies for overcoming sotorasib resistance, we investigated the combination of AKT and p38 inhibitors. Notably, combined inhibition of AKT (MK2206) and p38 (adezmapimod) restored sensitivity to sotorasib in resistant cell lines, as did silencing AKT expression.

Conclusion: These findings underscore the importance of adaptive mechanisms in sotorasib resistance in NSCLC cells contributing by EMT activation and demonstrates synergic combination with AKT and p38 inhibitors to restore sotorasib sensitivity in KRAS^G12C cells.