Multi-modal transcriptomic analysis reveals metabolic dysregulation and immune responses in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes-EP300, MTOR, NFE2L1, TXN-exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD.

Identification and experimental verification of senescence-related gene signatures and molecular subtypes in idiopathic pulmonary arterial hypertension.

Evidences illustrate that cell senescence contributes to the development of pulmonary arterial hypertension. However, the molecular mechanisms remain unclear. Since there may be different senescence subtypes between PAH patients, consistent senescence-related genes (SRGs) were utilized for consistent clustering by unsupervised clustering methods. Senescence is inextricably linked to the immune system, and the immune cells in each cluster were estimated by ssGSEA. To further screen out more important SRGs, machine learning algorithms were used for identification and their diagnostic value was assessed by ROC curves. The expression of hub genes were verified in vivo and in vitro. Transcriptome analysis was used to assess the effects of silence of hub gene on different pathways. Three senescence molecular subtypes were identified by consensus clustering. Compared with cluster A and B, most immune cells and checkpoint genes were higher in cluster C. Thus, we identified senescence cluster C as the immune subtype. The ROC curves of IGF1, HOXB7, and YWHAZ were remarkable in both datasets. The expression of these genes was increased in vitro. Western blot and immunohistochemical analyses revealed that YWHAZ expression was also increased. Our transcriptome analysis showed autophagy-related genes were significantly elevated after silence of YWHAZ. Our research provided several prospective SRGs and molecular subtypes. Silence of YWHAZ may contribute to the clearance of senescent endothelial cells by activating autophagy.

Integrative analysis of senescence-related genes identifies robust prognostic clusters with distinct features in hepatocellular carcinoma.

INTRODUCTION: Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis. OBJECTIVES: Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC). METHODS: Consensus clustering was used to subtype HCC based on SRGs. Several computational methods, including single sample gene set enrichment analysis (ssGSEA), fuzzy c-means algorithm, were performed. Data of drug sensitivities were utilized to screen potential therapeutic agents for different senescence patients. Additionally, we developed a method called signature-related gene analysis (SRGA) for identification of markers relevant to phenotype of interest. Experimental strategies consisting quantitative real-time PCR (qRT-PCR), ß-galactosidase assay, western blot, and tumor-T cell co-culture system were used to validate the findings in vitro. RESULTS: We identified three robust prognostic clusters of HCC patients with distinct survival outcome, mutational landscape, and immune features. We further extracted signature genes of senescence clusters to construct the senescence scoring system and profile senescence level in HCC at bulk and single-cell resolution. Senescence-induced stemness reprogramming was confirmed both in silico and in vitro. HCC patients with high senescence were immune suppressed and sensitive to Tozasertib and other drugs. We suggested that MAFG, PLIN3, and 4 other genes were pertinent to HCC senescence, and MAFG potentially mediated immune suppression, senescence, and stemness. CONCLUSION: Our findings provide insights into the role of SRGs in patients stratification and precision medicine.

Evaluation of the anti-aging effects of Zinc-α2-glycoprotein peptide in clinical and in vitro study.

BACKGROUND: Skin aging, characterized by the deterioration of skin density and elasticity, is a common concern among individuals seeking to maintain a youthful appearance. Zinc-α2-glycoprotein (ZAG) is secreted by various body fluids, and is associated with lipolysis and identified as an atopic dermatitis biomarker. This study evaluated the potential of ZAG peptides, which exert multiple benefits such as anti-aging. MATERIALS AND METHODS: We conducted a 4-week clinical trial on patients with noticeable periorbital wrinkles (n = 22) using a ZAG peptide-containing product. The effects of the products on skin density, elasticity, and the depth of periorbital wrinkles were evaluated using Cutometer Dual MPA580, Ultrascan, and Antera 3D CS, respectively. The effect of ZAG peptides on UVB-treated keratinocyte cells was evaluated in vitro to understand the mechanisms underlying its effects against impaired skin barrier function, collagen degradation, and senescence. In addition, the effects of ZAG peptides on cell viability and expression of aging and skin barrier-related genes were assessed using cell counting kit assay and quantitative reverse transcription-polymerase chain reaction, respectively. RESULTS: The patients demonstrated improved skin density, elasticity, and reduced periorbital wrinkles. Further, more than 85% patients scored the product as satisfactory regarding anti-aging effects. Furthermore, ZAG peptides reduced SA-ß-gal staining, downregulated the senescence-related genes, and upregulated the skin barrier function-related genes in UVB-irradiated keratinocyte cells. CONCLUSIONS: Our clinical and in vitro findings showed that ZAG peptides exert anti-aging effects and improve skin barrier functions, suggesting their promising potential as therapeutic agents to combat skin aging and improve skin health.

Screening of Biomarkers Associated with Osteoarthritis Aging Genes and Immune Correlation Studies.

Purpose: Osteoarthritis (OA) is a joint disease with a long and slow course, which is one of the major causes of disability in middle and old-aged people. This study was dedicated to excavating the cellular senescence-associated biomarkers of OA. Methods: The Gene Expression Omnibus (GEO) database was searched and five datasets pertaining to OA were obtained. After removing the batch effect, the GSE55235, GSE55457, GSE82107, and GSE12021 datasets were integrated together for screening of the candidate genes by differential analysis and weighted gene co-expression network analysis (WGCNA). Next, those genes were further filtered by machine learning algorithms to obtain cellular senescence-associated biomarkers of OA. Subsequently, enrichment analyses based on those biomarkers were conducted, and we profiled the infiltration levels of 22 types immune cells with the ERSORT algorithm. A lncRNA-miRNA-mRNA regulatory and drug-gene network were constructed. Finally, we validated the senescence-associated biomarkers at both in vivo and in vitro levels. Results: Five genes (BCL6, MCL1, SLC16A7, PIM1, and EPHA3) were authenticated as cellular senescence-associated biomarkers in OA. ROC curves demonstrated the reliable capacity of the five genes as a whole to discriminate OA samples from normal samples. The nomogram diagnostic model based on 5 genes proved to be a reliable predictor of OA. Single-gene GSEA results pointed to the involvement of the five biomarkers in immune-related pathways and oxidative phosphorylation in the development of OA. Immune infiltration analysis manifested that the five genes were significantly correlated with differential immune cells. Subsequently, a lncRNA-miRNA-mRNA network and gene-drug network containing were generated based on five cellular senescence-associated biomarkers in OA. Conclusion: A foundation for understanding the pathophysiology of OA and new insights into OA diagnosis and treatment were provided by the identification of five genes, namely BCL6, MCL1, SLC16A7, PIM1, and EPHA3, as biomarkers associated with cellular senescence in OA.

Revealing the diagnostic value and immune infiltration of senescence-related genes in endometriosis: a combined single-cell and machine learning analysis.

Introduction: Endometriosis is a prevalent and recurrent medical condition associated with symptoms such as pelvic discomfort, dysmenorrhea, and reproductive challenges. Furthermore, it has the potential to progress into a malignant state, significantly impacting the quality of life for affected individuals. Despite its significance, there is currently a lack of precise and non-invasive diagnostic techniques for this condition. Methods: In this study, we leveraged microarray datasets and employed a multifaceted approach. We conducted differential gene analysis, implemented weighted gene co-expression network analysis (WGCNA), and utilized machine learning algorithms, including random forest, support vector machine, and LASSO analysis, to comprehensively explore senescence-related genes (SRGs) associated with endometriosis. Discussion: Our comprehensive analysis, which also encompassed profiling of immune cell infiltration and single-cell analysis, highlights the therapeutic potential of this gene assemblage as promising targets for alleviating endometriosis. Furthermore, the integration of these biomarkers into diagnostic protocols promises to enhance diagnostic precision, offering a more effective diagnostic journey for future endometriosis patients in clinical settings. Results: Our meticulous investigation led to the identification of a cluster of genes, namely BAK1, LMNA, and FLT1, which emerged as potential discerning biomarkers for endometriosis. These biomarkers were subsequently utilized to construct an artificial neural network classifier model and were graphically represented in the form of a Nomogram.

ERBB2-PTGS2 axis promotes intervertebral disc degeneration by regulating senescence of nucleus pulposus cells.

Intervertebral disc degeneration (IDD) is considered one of the main causes of low back pain and lumbar disc herniation. Various studies have shown that disc cell senescence plays a critical role in this process. however, its role in IDD is yet unclear. In this study, we explored the role of senescence-related genes (SR-DEGs) and its underlying mechanism in IDD. A total of 1325 differentially expressed genes (DEGs) were identified using Gene Expression Omnibus (GEO) database GSE41883. 30 SR-DEGs were identified for further functional enrichment and pathway analysis, and two hub SR-DEGs (ERBB2 and PTGS2) were selected to construct transcription factor (TF)-gene interaction and TF-miRNA coregulatory networks, and 10 candidate drugs were screened for the treatment of IDD. Last but not least, in vitro experiments show that ERBB2 expression decreased and PTGS2 expression increased in human nucleus pulposus (NP) cell senescence model treated with TNF-α. After lentivirus-mediated overexpression of ERBB2, the expression of PTGS2 decreased and the senescence level of NP cells decreased. Overexpression of PTGS2 reversed the anti-senescence effects of ERBB2. The findings in this study suggested that ERBB2 overexpression further reduced NP cell senescence by inhibiting PTGS2 levels, which ultimately alleviated IDD. Taken together, our findings provide new insights into the roles of senescence-related genes in IDD and highlight a novel target of ERBB2-PTGS2 axis for therapeutic strategies.

Comprehensive analysis of senescence-related genes and immune infiltration in intervertebral disc degeneration: a meta-data approach utilizing bulk and single-cell RNA sequencing data.

Objectives: This study aims to identify the key senescence genes and potential regulatory mechanisms that contribute to the etiology of intervertebral disc degeneration (IDD). Method: We analyzed GSE34095 and GSE70362 datasets, identifying key senescence-related differentially expressed genes (DEGs) in IDD using lasso regression. Risk scores classified patients into high- and low-risk groups. We compared pathways, functions, and immune infiltration between these groups. Diagnostic ability was assessed using ROC curves and a nomogram predicted IDD incidence. In single-cell dataset GSE165722, we evaluated expression of key senescence-related DEGs. Results: We identified 12 key senescence-related DEGs distinguishing high- and low-risk IDD patients. Enrichment analysis revealed cellular stress response, apoptotic signaling pathway, and protein kinase activation differences. Immune cell analysis showed elevated eosinophils in low-risk group and increased effector memory CD8 T, central memory CD4 T, myeloid-derived suppressor, natural killer, monocyte, Type 1 T helper, plasmacytoid dendritic, and natural killer T cells in high-risk group. A nomogram using AUC >0.75 genes (CXCL8, MAP4K4, MINK1, and TNIK) predicted IDD incidence with good diagnostic power. High senescence scores were observed in neutrophils. Conclusion: Our diagnostic model, based on key senescence-related DEGs and immune cell infiltration, offers new insights into IDD pathogenesis and immunotherapy strategies.

Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction.

Background: Acute myocardial infarction (AMI) is the main clinical cause of death and cardiovascular disease and thus has high rates of morbidity and mortality. The increase in cardiovascular disease with aging is partly the result of vascular endothelial cell senescence and associated vascular dysfunction. This study was performed to identify potential key cellular senescence-related genes (SRGs) as biomarkers for the diagnosis of AMI using bioinformatics. Methods: Using the CellAge database, we identified cellular SRGs. GSE66360 and GSE48060 for AMI patients and healthy controls and GSE19322 for mice were downloaded from the Gene Expression Omnibus (GEO) database. The GSE66360 dataset was divided into a training set and a validation set. The GSE48060 dataset was used as another validation set. The GSE19322 dataset was used to explore the evolution of the screened diagnostic markers in the dynamic process of AMI. Differentially expressed genes (DEGs) of AMI were identified from the GSE66360 training set. Differentially expressed senescence-related genes (DESRGs) selected from SRGs and DEGs were analyzed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed. Results: A total of 520 DEGs were screened from the GSE66360 training set, and 279 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 14 DESRGs, including 4 senescence suppressor genes and 10 senescence inducible genes. The top 10 hub genes, including FOS, MMP9, CEBPB, CDKN1A, CXCL1, ETS2, BCL6, SGK1, ZFP36, and IGFBP3, were screened. Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6. The ROC analysis showed that the respective area under the curves (AUCs) of MMP9, ETS2, and BCL6 were 0.786, 0.848, and 0.852 in the GSE66360 validation set and 0.708, 0.791, and 0.727 in the GSE48060 dataset. In the GSE19322 dataset, MMP9 (AUC, 0.888) and ETS2 (AUC, 0.929) had very high diagnostic values in the early stage of AMI. Finally, based on these three diagnostic genes, we found that drugs such as acetylcysteine and genistein may be targeted for the treatment of age-related AMI. Conclusion: The results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI.

Two Hybrid Histidine Kinases Involved in the Ethylene Regulation of the Mycelial Growth and Postharvest Fruiting Body Maturation and Senescence of Agaricus bisporus.

Ethylene regulates mycelial growth, primordium formation, and postharvest mushroom maturation and senescence in the white button mushroom, Agaricus bisporus. However, it remains unknown how ethylene is detected by the mushroom. In this study, we found that two hybrid histidine kinases in the mushroom, designated AbETR1 and AbETR2, showed domain structures similar to those of plant ethylene receptors. The transmembrane helices of AbETR1 and AbETR2 were expressed in yeast cells and showed ethylene-binding activities. Mushroom strains with downregulated expressions of AbETR1 and AbETR2 showed reduced sensitivity to the ethylene inhibition of mycelial growth, ethylene regulation of their own synthesis, postharvest mushroom maturation, and senescence and expression of maturation- and senescence-related genes. Therefore, AbETR1 and AbETR2 are expected to be biologically functional ethylene receptors and exhibit a different mode of action from that of the receptors of plants. Here, we fill gaps in the knowledge pertaining to higher fungus ethylene receptors, discover a novel mode of action of ethylene receptors, confirm ethylene as a novel fungal hormone, and provide a facilitated approach for preventing the maturation and senescence of postharvest button mushrooms. IMPORTANCE Ethylene regulates diverse physiological activities in bacteria, cyanobacteria, fungi, and plants, but how to perceive ethylene by fungi only remains unknown. In this study, we identify two biologically functional ethylene receptors in the basidiomycete fungus Agaricus bisporus, which fills the gaps of deficient fungal ethylene receptors. Furthermore, we found that decreased expression of the ethylene receptors facilitates preventing the maturation and senescence of postharvest button mushrooms, indicating that the two fungal ethylene receptors positively regulate the ethylene response, in contrast to that in plants.

Clinical significance and immune landscape of KIR2DL4 and the senescence-based signature in cutaneous melanoma.

Senescence is an effective barrier to tumor progression. Mutations that inhibit senescence and promote cell division are mandatory for the development of cancer. Therefore, it is particularly important to explore the differences between cutaneous melanoma (CM) patients with severe and mild degrees of senescence. We clustered all the patients with CM in the Cancer Genome Atlas (TCGA) database based on all the genes of the senescence pathway in the CellAge and MSigDB database. The prognosis, immunotherapy effect, tumor microenvironment score, NRAS mutation rate, expression of CD274, CTLA4, and PDCD1, and abundance of CD8+ T and natural killer (NK) cell infiltration in the younger group of patients (YG) were higher than those in the older group (OG). Compared with the American Joint Committee on Cancer (AJCC) stage, the risk scoring system stratified the risk of CM patients and guided immunotherapy more accurately. The nomogram model, which combined the AJCC stage and risk score, greatly improved the ability and accuracy of prognosis prediction. As KIR2DL4 is the core molecule in the risk scoring system (RSS), knocking down the KIR2DL4 of human NK cells in vitro can inhibit the cytotoxicity of NK cells and can also inhibit the secretion of tumor necrosis factor-α and interferon-γ by NK cells. In contrast, upregulation of KIR2DL4 can activate the MEK/ERK signaling pathway, which is the activation pathway of NK cells. Our RSS and nomogram model can accurately stratify the risk of CM patients and effectively predict the effect of immunotherapy and prognosis in CM patients.

Hydrogen Sulfide: A Gaseous Molecule in Postharvest Freshness.

Hydrogen sulfide (H2S), as a signaling molecule, is involved in the regulation of growth and development in plants. Recent studies have indicated that H2S also plays important roles in regulating postharvest senescence of horticultural products. The focus of this review is to summarize the synthesis of H2S in plants and its potential roles in alleviating the senescence of cut flowers, fruits, and vegetables during postharvest storage. During postharvest of horticultural products, H2S could scavenge reactive oxygen species via promoting the activity of antioxidant enzymes, thereby, sustaining the integrity of the membrane. In fruits, H2S effectively enhanced the tolerance of chilling by increasing the content of proline and polyphenol compounds. During postharvest storage of perishable fruits and vegetables, H2S significantly alleviated decay, which was caused by fungi by inhibiting the growth of fungi spores. Moreover, H2S interacted with other molecules synergistically (NO) or antagonistically (ethylene) to alleviate senescence of horticultural products. At the transcriptional level, H2S regulated the expression of senescence-related genes, which were related to degradation of proteins and chlorophyll, to delay the senescence of horticultural products. Thus, H2S does not only possess positive antioxidant and antifungal properties, but also significantly regulates the senescence-related gene during postharvest of horticultural products. Future studies of H2S in postharvest storage should focus on its molecular mechanism in the posttranslational modifications of proteins as well as its safety attributes in treated fruits and vegetables.