Co-expression Analysis Research Articles

Transcriptional and metabolic analyses of leaf responses to low phosphorus levels in quinoa heading stage

Quinoa, a globally significant crop, is highly susceptible to low phosphorus stress, which can significantly impair its production and quality. Therefore, it is necessary to study the molecular mechanisms of quinoa's response to low phosphorus stress must be investigated. In this study, we identified a total of 14,824 genes and 1788 metabolites using transcriptomic and metabolomic techniques. Compared to the control group, 1378 and 8548 differentially expressed genes (DEGs), as well as 210 and 362 differentially accumulated metabolites (DAMs), were identified in the low phosphorus-treated groups, respectively. Bioinformatics analysis showed that these DEGs and DAMs are associated with various biological processes,for instance glycolysis, starch and sugar metabolism, pyruvate metabolism, glycerophospholipid metabolism, photosynthetic biosequestration, galactose metabolism, and citric acid cycle. Moreover, the results of the co-expression analysis highlighted interactions among DEGs and DAMs, particularly in the associated path to starch and sugar metabolism, glycerophospholipid metabolism, photosynthetic biosequestration, and glycolytic metabolic pathways. These results suggest that quinoa responds to low-phosphorus stress through these metabolic pathways. Overall, this study enhances our understanding of quinoa's mechanism in response to phosphorus deficiency and provides a reference for molecular design breeding of quinoa adapted to phosphorus deficiency.

Gradient Boosting Prediction of Overlapping Genes From Weighted Co-expression and Differential Gene Expression Analysis of Wnt Pathway: An Artificial Intelligence-Based Bioinformatics Study.

Introduction The Wnt (wingless-related integration site) signalling pathway is crucial for bone formation and remodelling, regulating the commitment of mesenchymal stem cells (MSCs) to the osteoblastic lineage. It triggers the transcriptional activation of Wnt target genes and promotes osteoblast proliferation and survival. Weighted co-expression network analysis (WGCNA) and differential gene expression analysis help researchers understand gene roles. Gradient boosting, a machine learning technique, enhances understanding of genetic and molecular mechanisms contributing to overlap genes, improving gene regulation and functional genomics. The aim is to predict overlapping genes in the Wnt signalling pathway. Methods Differential gene expression analysis was performed using the National Center for Biotechnology Information (NCBI) geo dataset-GSE251951, focusing on the effect of Wnt signaling on treatment. The WGCNA module was analyzed using the iDEP tool to identify interconnected gene clusters. Hub genes were identified by calculating module eigengenes, correlated with external traits, and ranked based on module membership values. The study utilized gradient boosting, an ensemble learning method, to predict models, evaluate their performance using metrics like accuracy, precision, recall, and F1 score, and adjust predictions based on gradient and learning rate. Results The dendrogram uses the "Dynamic TreeCut" algorithm to analyze gene clusters, aiding researchers in understanding gene modules and biological processes, identifying co-expressed genes, and discovering new pathways. The confusion matrix displays 88 actual and predicted cases. The gradient boosting model achieves 78.9% accuracy in predicting Wnt pathway overlapping genes, with a respectable area under the curve (AUC) and classification accuracy values. It accurately predicts 73.9% of samples, with a high precision ratio and low recall. Conclusion Future research should enhance differential expression analysis and WGCNA to identify key Wnt pathway genes, improve sensitivity, specificity, hyperparameter tuning, and validation experiments, and use larger datasets.

System analysis based on weighted gene co-expression analysis identifies SOX7 as a novel regulator of hepatic stellate cell activation and liver fibrosis.

Hepatic stellate cell (HSC) activation is the essential pathological process of liver fibrosis (LF). The molecular mechanisms regulating HSC activation and LF are incompletely understood. Here, we explored the effect of transcription factor SRY-related high mobility group box7 (SOX7) on HSC activation and LF, and the underlying molecular mechanism. We found the expression levels of SOX7 were decreased in human and mouse fibrotic livers, particularly at the fibrotic foci. SOX7 was also downregulated in primary activated HSCs and TGF-β1 stimulated LX-2 cells. SOX7 knockdown promoted activation and proliferation of LX-2 cells while inhibiting their apoptosis. On the other hand, overexpression of SOX7 suppressed the activation and proliferation of HSCs. Mechanistically, SOX7 attenuates HSC activation and LF by decreasing the expression of β-catenin and phosphorylation of Smad2 and Smad3 induced by TGF-β1. Furthermore, overexpression of SOX7 using AAV8-SOX7 mouse models ameliorated the extent of LF in response to CCl4 treatment invivo. Collectively, SOX7 suppressed HSC activation and LF. Targeting SOX7, therefore, could be a potential novel strategy to protect against LF.

CSF Proteomics in Patients With Progressive Supranuclear Palsy.

Identification of fluid biomarkers for progressive supranuclear palsy (PSP) is critical to enhance therapeutic development. We implemented unbiased DNA aptamer (SOMAmer) proteomics to identify novel CSF PSP biomarkers. This is a cross-sectional study in original (18 clinically diagnosed PSP-Richardson syndrome [PSP-RS], 28 cognitively healthy controls]), validation (23 PSP-RS, 26 healthy controls), and neuropathology-confirmed (21 PSP, 52 non-PSP frontotemporal lobar degeneration) cohorts. Participants were recruited through the University of California, San Francisco, and the 4-Repeat Neuroimaging Initiative. The original and neuropathology cohorts were analyzed with the SomaScan platform version 3.0 (5026-plex) and the validation cohort with version 4.1 (7595-plex). Clinical severity was measured with the PSP Rating Scale (PSPRS). CSF proteomic data were analyzed to identify differentially expressed targets, implicated biological pathways using enrichment and weighted consensus gene coexpression analyses, diagnostic value of top targets with receiver-operating characteristic curves, and associations with disease severity with linear regressions. A total of 136 participants were included (median age 70.6 ± 8 years, 68 [50%] women). One hundred fifty-five of 5,026 (3.1%), 959 of 7,595 (12.6%), and 321 of 5,026 (6.3%) SOMAmers were differentially expressed in PSP compared with controls in original, validation, and neuropathology-confirmed cohorts, with most of the SOMAmers showing reduced signal (83.1%, 95.1%, and 73.2%, respectively). Three coexpression modules were associated with PSP across cohorts: (1) synaptic function/JAK-STAT (β = -0.044, corrected p = 0.002), (2) vesicle cytoskeletal trafficking (β = 0.039, p = 0.007), and (3) cytokine-cytokine receptor interaction (β = -0.032, p = 0.035) pathways. Axon guidance was the top dysregulated pathway in PSP in original (strength = 1.71, p < 0.001), validation (strength = 0.84, p < 0.001), and neuropathology-confirmed (strength = 0.78, p < 0.001) cohorts. A panel of axon guidance pathway proteins discriminated between PSP and controls in original (area under the curve [AUC] = 0.924), validation (AUC = 0.815), and neuropathology-confirmed (AUC = 0.932) cohorts. Two inflammatory proteins, galectin-10 and cytotoxic T lymphocyte-associated protein-4, correlated with PSPRS scores across cohorts. Axon guidance pathway proteins and several other molecular pathways are downregulated in PSP, compared with controls. Proteins in these pathways may be useful targets for biomarker or therapeutic development.

Single-cell RNA sequencing facilitates the elucidation of the complete biosynthesis of the antidepressant hyperforin in St. John’s wort

Hyperforin is the compound responsible for the effectiveness of St. John’s wort (Hypericum perforatum) as an antidepressant, but its complete biosynthetic pathway remains unknown. Gene discovery based on co-expression analysis of bulk RNA-sequencing data or genome mining failed to discover the missing steps in hyperforin biosynthesis. In this study, we sequenced the 1.54-Gb tetraploid H. perforatum genome assembled into 32 chromosomes with the scaffold N50 value of 42.44 Mb. By single-cell RNA sequencing, we identified a type of cell, “Hyper cells”, wherein hyperforin biosynthesis de novo takes place in both the leaves and flowers. Through pathway reconstitution in yeast and tobacco, we identified and characterized four transmembrane prenyltransferases (HpPT1–4) that are localized at the plastid envelope and complete the hyperforin biosynthetic pathway. The hyperforin polycyclic scaffold is created by a reaction cascade involving an irregular isoprenoid coupling and a tandem cyclization. Our findings reveal how and where hyperforin is biosynthesized, enabling synthetic-biology reconstitution of the complete pathway. Thus, this study not only deepens our comprehension of specialized metabolism at the cellular level but also provides strategic guidance for elucidation of the biosynthetic pathways of other specializied metabolites in plants.

Unraveling the molecular mechanisms of Ace2-mediated post-COVID-19 cognitive dysfunction through systems genetics approach

The dysregulation of Angiotensin-converting enzyme 2 (ACE2) in central nervous system is believed associates with COVID-19 induced cognitive dysfunction. However, the detailed mechanism remains largely unknown. In this study, we performed a comprehensive system genetics analysis on hippocampal ACE2 based on BXD mice panel. Expression quantitative trait loci (eQTLs) mapping showed that Ace2 was strongly trans-regulated, and the elevation of Ace2 expression level was significantly correlated with impaired cognitive functions. Further Gene co-expression analysis showed that Ace2 may be correlated with the membrane proteins in Calcium signaling pathway. Further, qRT-PCR confirmed that SARS-CoV-2 spike S1 protein upregulated ACE2 expression together with eight membrane proteins in Calcium Signaling pathway. Moreover, such elevation can be attenuated by recombinant ACE2. Collectively, our findings revealed a potential mechanism of Ace2 in cognitive dysfunction, which could be beneficial for COVID–19–induced cognitive dysfunction prevention and potential treatment.

An integration of neuroimaging and serum proteomics analysis suggests immune and inflammation are associated with white matter microstructure changes in cerebral small vessel disease with depressive symptoms

IntroductionDepressive symptoms are a common concomitant of cerebral small vessel disease (CSVD), of which pathogenesis requires more study. White matter microstructural abnormalities and proteomic alternation have been widely reported regarding depression in the elderly with CSVD. Exploring the relationship between cerebral white matter microstructural alterations and serum proteins may complete the explanation of molecular mechanisms for the findings from neuroimaging research of CSVD combined with depressive symptoms. MethodsAn untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques. ResultsDTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group. ConclusionThe results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms

LncRNA-mRNA co-expression analysis reveals aquaporin-9-promoted neutrophil extracellular trap formation and inflammatory activation in sepsis

Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection. However, the precise regulatory mechanism of sepsis remains unclear. Using a strand-specific RNA-sequencing, we identified 115 hub differentially expressed long noncoding RNAs (lncRNAs) and 443 mRNAs in septic patients, primarily participated in crucial pathways including neutrophil extracellular trap (NET) formation and toll-like receptor signaling. Notably, NETs related gene aquaporin-9 (AQP9) and its associated lncRNAs exhibited significant upregulation in septic neutrophils. Functional experiments revealed AQP9 interacts with its lncRNAs to augment the formation of neutrophil NETs. In murine sepsis models, AQP9 inhibition with phloretin reduced proinflammatory cytokine production and lung damage. These findings provide crucial insights into the regulatory role of AQP9 in sepsis, unraveling its interaction with associated lncRNAs in transmitting downstream signals, holding promise in informing the development of novel therapeutic strategies aimed at ameliorating the debilitating effects of sepsis.

Identification of key genes and long non‑coding RNA expression profiles in osteoporosis with rheumatoid arthritis based on bioinformatics analysis

BackgroundAlthough rheumatoid arthritis (RA) is a chronic systemic tissue disease often accompanied by osteoporosis (OP), the molecular mechanisms underlying this association remain unclear. This study aimed to elucidate the pathogenesis of RA and OP by identifying differentially expressed mRNAs (DEmRNAs) and long non-coding RNAs (lncRNAs) using a bioinformatics approach.MethodsExpression profiles of individuals diagnosed with OP and RA were retrieved from the Gene Expression Omnibus database. Differential expression analysis was conducted. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway enrichment analyses were performed to gain insights into the functional categories and molecular/biochemical pathways associated with DEmRNAs. We identified the intersection of common DEmRNAs and lncRNAs and constructed a protein-protein interaction (PPI) network. Correlation analysis between the common DEmRNAs and lncRNAs facilitated the construction of a coding-non-coding network. Lastly, serum peripheral blood mononuclear cells (PBMCs) from patients with RA and OP, as well as healthy controls, were obtained for TRAP staining and qRT-PCR to validate the findings obtained from the online dataset assessments.ResultsA total of 28 DEmRNAs and 2 DElncRNAs were identified in individuals with both RA and OP. Chromosomal distribution analysis of the consensus DEmRNAs revealed that chromosome 1 had the highest number of differential expression genes. GO and KEGG analyses indicated that these DEmRNAs were primarily associated with " platelets (PLTs) degranulation”, “platelet alpha granules”, “platelet activation”, “tight junctions” and “leukocyte transendothelial migration”, with many genes functionally related to PLTs. In the PPI network, MT-ATP6 and PTGS1 emerged as potential hub genes, with MT-ATP6 originating from mitochondrial DNA. Co-expression analysis identified two key lncRNA-mRNA pairs: RP11 − 815J21.2 with MT − ATP6 and RP11 − 815J21.2 with PTGS1. Experimental validation confirmed significant differential expression of RP11-815J21.2, MT-ATP6 and PTGS1 between the healthy controls and the RA + OP groups. Notably, knockdown of RP11-815J21.2 attenuated TNF + IL-6-induced osteoclastogenesis.ConclusionsThis study successfully identified shared dysregulated genes and potential therapeutic targets in individuals with RA and OP, highlighting their molecular similarities. These findings provide new insights into the pathogenesis of RA and OP and suggest potential avenues for further research and targeted therapies.

Characterizing seed dormancy in Epimedium brevicornu Maxim.: Development of novel chill models and determination of dormancy release mechanisms by transcriptomics

PurposeEpimedium brevicornu Maxim. is a perennial persistent C3 plant of the genus Epimedium Linn. in the family Berberaceae that exhibits severe physiological and morphological seed dormancy.We placed mature E. brevicornu seeds under nine stratification treatment conditions and explored the mechanisms of influence by combining seed embryo growth status assessment with related metabolic pathways and gene co-expression analysis.ResultsWe identified 3.9 °C as the optimum cold-stratification temperature of E. brevicornu seeds via a chilling unit (CU) model. The best treatment was variable-temperature stratification (10/20 °C, 12/12 h) for 4 months followed by low-temperature stratification (4 °C) for 3 months (4-3). A total of 63801 differentially expressed genes were annotated to 2587 transcription factors (TFs) in 17 clusters in nine treatments (0-0, 0-3, 1-3, 2-3, 3-3, 4-3, 4-2, 4-1, 4-0). Genes specifically highly expressed in the dormancy release treatment group were significantly enriched in embryo development ending in seed dormancy and fatty acid degradation, indicating the importance of these two processes. Coexpression analysis implied that the TF GRF had the most reciprocal relationships with genes, and multiple interactions centred on zf-HD and YABBY as well as on MYB, GRF, and TCP were observed.ConclusionIn this study, analyses of plant hormone signal pathways and fatty acid degradation pathways revealed changes in key genes during the dormancy release of E. brevicornu seeds, providing evidence for the filtering of E. brevicornu seed dormancy-related genes.

Joint GWAS and WGCNA Identify Genes Regulating the Isoflavone Content in Soybean Seeds.

Isoflavone is a secondary metabolite of the soybean phenylpropyl biosynthesis pathway with physiological activity and is beneficial to human health. In this study, the isoflavone content of 205 soybean germplasm resources from 3 locations in 2020 showed wide phenotypic variation. A joint genome-wide association study (GWAS) and weighted gene coexpression network analysis (WGCNA) identified 33 single-nucleotide polymorphisms and 11 key genes associated with soybean isoflavone content. Gene ontology enrichment analysis, gene coexpression, and haplotype analysis revealed natural variations in the Glyma.12G109800 (GmOMT7) gene and promoter region, with Hap1 being the elite haplotype. Transient overexpression and knockout of GmOMT7 increased and decreased the isoflavone content, respectively, in hairy roots. The combination of GWAS and WGCNA effectively revealed the genetic basis of soybean isoflavone and identified potential genes affecting isoflavone synthesis and accumulation in soybean, providing a valuable basis for the functional study of soybean isoflavone.

Mutual exclusivity and co-occurrence patterns of immune checkpoints indicate NKG2A relates to anti-PD-1 resistance in gastric cancer

BackgroundAn increasing number of clinical studies have begun to explore combination strategies with immune checkpoint inhibitors, aiming to present new opportunities for overcoming anti-PD-1 treatment resistance in gastric cancer. Unfortunately, the exploration of certain immune checkpoint inhibitor combination strategies has yielded suboptimal results. Therefore, it is necessary to comprehensively analyze the expression patterns of immune checkpoints and identify optimal combination regimens of anti-PD-1 inhibitors with other immune checkpoint inhibitors.MethodsLeveraging single-cell RNA sequencing (scRNA-seq) and multivariate linear regression interaction models, we dissected the immune checkpoint expression characteristics of CD8+ T cells in gastric cancer and the immune checkpoint expression pattern (ICEP) mediating anti-PD-1 treatment resistance. Furthermore, we employed transcription factor analysis and CellOracle to explore the transcriptional regulatory mechanisms governing CD8+ T cell differentiation fates. Finally, we utilized Nichenet and spatial transcriptomic analysis to investigate the spatial expression patterns of immune checkpoints.ResultsInteraction analysis indicated that, among the known immune checkpoints, co-expression of NKG2A and PD-1 might exert a more profound inhibitory effect on the proliferative capacity of CD8+ T cells. The co-expression analysis revealed differential co-expression pattern of PD-1 and NKG2A, defined as ICEP1 (CD8+ T cells co-expressing PD-1, CTLA-4, TIGIT, LAG-3 or CD38) and ICEP2 (CD8+ T cells solely expressing NKG2A or co-expressing with other immune checkpoints), reflecting the co-occurrence pattern of PD-1 and the mutual exclusivity of NKG2A. Further, these two ICEP CD8+ T cell subsets represented distinct CD8+ T cell differentiation fates governed by MSC and RUNX3. Notably, ICEP2 CD8+ T cells were associated with anti-PD-1 therapy resistance in gastric cancer. This phenomenon may be attributed to the recruitment of LGMN+ macrophages mediated by the CXCL16-CXCR6 signaling pathway.ConclusionThis study unveiled two distinct ICEPs and the mutually exclusivity and co-occurrence characteristics of CD8+ T cells in gastric cancer. The ICEP2 CD8+ T cell subset, highly expressed in gastric cancer patients resistant to anti-PD-1 therapy, may be recruited by LGMN+ macrophages through CXCL16-CXCR6 axis. These findings provide evidence for NKG2A as a novel immunotherapeutic target in gastric cancer and offer new insights into combination strategies for immune checkpoint inhibitors in gastric cancer.Graphical

Analysis of different expression RNA binding protein genes in mouse microglia cell from the brains of mice 72 h after subarachnoid hemorrhage or sham operation

BackgroundThe prognosis of brain injury caused by subarachnoid hemorrhage (SAH) is poor. Previous studies showed that abnormal function of RBPs might be involved in brain injury, neuroinflammation and further affect microglia homeostasis. However, no studies have systematically analyzed the genome-wide abnormal expression of RBPs genes in microglia during SAH.MethodsRNA-seq data of microglia from the SAH mouse group (SAH) and control sham-operated mouse group (sham) were downloaded from the GEO database in GSE167957, including four samples from the sham group and four samples from the SAH group for subsequent analysis.Utilizing GO and KEGG functional enrichment analyses, we conducted a comprehensive study of differentially expressed genes (DEGs), alternative splicing patterns, and co-expression networks to gain deeper insights into the differential expression of RNA-binding proteins (RBPs) and differential alternative splicing events (ASEs) between the SAH (subarachnoid hemorrhage) and sham groups. This analysis aimed to elucidate the potential mechanisms underlying the aberrant expression of RBPs in microglia during brain injury caused by SAH.ResultsASEs and co-expression analyses of differentially expressed RBPs and differential ASEs were carried out in microglia in terms of gene expression. GO and KEGG functional enrichment analysis showed that aberrantly expressed RBPs such as Mcm7, Mtdh, SRSF3, and Hnrnpa2b1 may affect and regulate downstream Csnk1d, Uckl1 and other protein phosphorylation-related genes by alterative splicing.ConclusionRBPs were aberrantly expressed in microglia during the development of brain injury secondary to SAH, regulating alterative splicing of downstream genes and influencing the progression of SAH brain injury in this study. This implies that RBPs are important for the identification of new therapeutic targets for brain injury after SAH.

PDCL3 as a prognostic factor and associated with the VEGF signaling pathway in glioma.

New targeted drugs about angiogenesis could develop the treatment of glioma. We aimed to explore the role of phosducin like 3 (PDCL3) in angiogenesis of glioma. RNA sequencing data and matched clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To screen for the reliable genes with the filtering analyses, survival, multivariate Cox, receiver operating characteristic (ROC) curve filtration, and clinical correlation analyses were performed. The PDCL3 gene was validated by immunohistochemistry as a reliable gene for further analysis. Then we used the combined data of TCGA and Genotype-Tissue Expression from UCSC to detect the differential gene expression of PDCL3. Related signal pathways in glioma were explored by the gene set enrichment analysis and co-expression analysis. Lastly, we performed in vitro experiments to verify the gene functions and related mechanisms. The three filtering analyses and immunostaining indicated that the expression of PDCL3 in glioma tissues was higher than the normal tissues. Gene function analysis showed that PDCL3 activated the vascular endothelial growth factor (VEGF) signal pathway, and its mechanism was related to pathways in cancer, like NOD like receptor signaling pathway, the RIG-I like receptor signaling pathway and the P53 signaling pathway by MAPK/AKT in gliomas. This suggested that the proliferation, migration and invasion of glioma cells might be inhibited by the downregulation of PDCL3 in vitro, which may be related to the activation of VEGF signaling pathway. We demonstrated that PDCL3 could function as an independent adverse prognostic marker in glioma. Its pro-oncogenic mechanism may be related to the VEGF signaling pathway.

Construction of lncRNA prognostic model related to disulfidptosis in lung adenocarcinoma

BackgroundLung cancer is one of the malignant tumors with the highest rates of morbidity and mortality worldwide. One of the most common histological types of lung cancer is lung adenocarcinoma (LUAD). Despite the fact that development in medicine has significantly improved some patients’ prognoses, the overall survival (OS) rate is still very low. In glucose-deficient SLC7A11-overexpressed cancer cells, the accumulation of disulfide molecules leads to abnormal disulfide bonding between actin cytoskeletal proteins, interferes with their tissues, and eventually leads to actin network collapse and cell death. This mode of cell death is called disulfidptosis. Studies have shown that disulfidptosis may be a new target for cancer treatment. However, the role of disulfidptosis in LUAD is still unknown. MethodsLUAD transcriptome and clinical information from The Cancer Genome Atlas (TCGA) was downloaded. The co-expression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Cox regression analysis was performed to screen the disulfidptosis-related lncRNAs (DRLs) and build the prognostic model. Kaplan-Meier curve, Cox regression analysis, and receiver operating characteristic (ROC) curve was used to validate the model. Then a nomogram is made to predict the prognosis of LUAD patients. Finally, fresh-collected clinical samples were used to verify the expression of DRLs in LUAD. ResultsThe prognostic model with six DRLs was developed to predict the prognosis of LUAD, with superior prognosis value compared to other clinical variables. The Cox regression analysis revealed that T stage, N stage and the risk score were identified as independent variables that affected LUAD prognosis. ROC curve revealed that the model has a moderate diagnostic value, with an AUC of 1-year 0.684, 3-year 0.664, and 5-year 0.588. Moreover, nine medications connected to LUAD treatment were acquired through drug sensitivity analysis. LUAD tissue validation showed that AC012073.1, AC012615.1, EMSLR, and SNHG12 were highly expressed, while AL606834.1 and AL365181.2 with low expression. ConclusionSix DRLs were screened and verified to construct the prognostic model, which can accurately predict the LUAD prognosis. It establishes a basis for further exploration into the molecular mechanisms underlying LUAD and identification of potential biomarkers for diagnosis, prognosis, and therapeutic targets.

Identification of candidate genes and molecular mechanisms related to asthma progression using bioinformatics

BackgroundAsthma is a heterogeneous disorder. This study aimed to identify changes in gene expression and molecular mechanisms associated with moderate to severe asthma.MethodsDifferentially expressed genes (DEGs) were analyzed in GSE69683 dataset among moderate asthma and its controls as well as between severe asthma and moderate asthma. Key module genes were identified via co-expression analysis, and the molecular mechanism of the module genes was explored through enrichment analysis and gene set enrichment analysis (GSEA). GSE89809 was used to verify the characteristic genes related to moderate and severe asthma.ResultsAccordingly, 2540 DEGs were present between moderate asthma and the control group, while 6781 DEGs existed between severe asthma and moderate asthma. These genes were identified into 14 co-expression modules. Module 7 had the highest positive correlation with severe asthma and was recognized to be a key module by STEM. Enrichment analysis demonstrated that the module genes were mainly involved in oxidative stress-related signaling pathways. The expression of HSPA1A, PIK3CG and PIK3R6 was associated with moderate asthma, while MAPK13 and MMP9 were associated with severe asthma. The AUC values were verified by GSE89809. Additionally, 322 drugs were predicted to target five genes.ConclusionThese results identified characteristic genes related to moderate and severe asthma and their corresponding molecular mechanisms, providing a basis for future research.

LINC01370 suppresses hepatocellular carcinoma proliferation and metastasis by regulating the PI3K/AKT pathway

BackgroundHepatocellular carcinoma (HCC) poses a serious threat to human health worldwide. lncRNA dysregulation is frequently observed in various cancers, including HCC. However, the function of LINC01370 in HCC progression and its underlying mechanisms remain unclear.MethodsLINC01370 expression in HCC tissues with cells was analyzed by applying the GEO and GEPIA databases and qRT-PCR. CCK-8 and Transwell assays were used to assess HCC cell proliferation, migration, and invasion. The PI3K, AKT, with p-AKT protein expression were analyzed by western blotting.ResultsGene Expression Omnibus (GEO) and Gene Expression Profiling Interactive Analysis (GEPIA) showed that LINC01370 expression was significantly lower in HCC tissues than in normal tissues. LINC01370 overexpression markedly repressed HepG2 SMMC-7721 cells proliferation, migration, and invasion. To understand the downstream mechanism of LINC01370 regulation, we further analyzed the genes co-expressed with LINC01370 in GSE136247 and GSE132037 and then performed KEGG analysis. The PA pathway was found to be a downstream pathway regulated by LINC01370 in GSE136247 and GSE132037 via gene co-expression and KEGG analysis. Furthermore, PI3K and p-AKT protein levels decreased after LINC01370 overexpression. Importantly, rescue experiments showed that activation of the PI3K/AKT pathway disrupted the repressive effect of LINC01370 overexpression on the proliferation, migration, and invasion of HepG2 of SMMC-7721 cells.ConclusionsThis study verified that LINC01370 suppresses HCC proliferation with metastasis by regulating the PI3K/AKT pathway.

Development of a disulfidptosis-related lncRNA prognostic signature for enhanced prognostic assessment and therapeutic strategies in lung squamous cell carcinoma

Limited treatment options and poor prognosis present significant challenges in the treatment of lung squamous cell carcinoma (LUSC). Disulfidptosis impacts cancer progression and prognosis. We developed a prognostic signature using disulfidptosis-related long non-coding RNAs (lncRNAs) to predict the prognosis of LUSC patients. Gene expression matrices and clinical information for LUSC were downloaded from the TCGA database. Co-expression analysis identified 209 disulfidptosis-related lncRNAs. LASSO-Cox regression analysis identified nine key lncRNAs, forming the basis for establishing a prognostic model. The model’s validity was confirmed by Kaplan–Meier and ROC curves. Cox regression analysis identified the risk score (RS) as an independent prognostic factor inversely correlated with overall survival. A nomogram based on the RS demonstrated good predictive performance for LUSC patient prognosis. The relationship between RS and immune function was explored using ESTIMATE, CIBERSORT, and ssGSEA algorithms. According to the TIDE database, a negative correlation was found between RS and immune therapy responsiveness. The GDSC database revealed that 49 drugs were beneficial for the low-risk group and 25 drugs for the high-risk group. Silencing C10orf55 expression in SW900 cells reduced invasiveness and migration potential. In summary, this lncRNA model based on TCGA-LUSC data effectively predicts prognosis and assists clinical decision-making.

FASTKD1 as a diagnostic and prognostic biomarker for STAD: Insights into m6A modification and immune infiltration.

Fas-activated serine/threonine kinase domain 1 (FASTKD1), a known modulator of mitochondrial-mediated cell death and survival processes, has garnered attention for its potential role in various biological contexts. However, its involvement in gastric cancer remains unclear. Thus, the present study aimed to investigate the relationship between FASTKD1 expression and key factors, including clinicopathological characteristics, immune infiltration and m6A modification in stomach adenocarcinoma (STAD). The expression of FASTKD1 was analyzed in STAD and normal adjacent tissues to assess its association with clinicopathological characteristics and survival prognosis. Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used in this study. Additionally, the findings were validated through immunohistochemical staining. Co-expression analysis of FASTKD1 was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and LinkedOmics database analysis. An in-depth analysis was conducted using databases, such as Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GEO and TCGA to explore the potential correlation between FASTKD1 expression and immune infiltration and m6A modification in STAD. The results revealed that FASTKD1 was significantly upregulated across different tumor types, including STAD. Notably, FASTKD1 was able to distinguish between tumor and normal tissue samples with accuracy. Furthermore, the expression levels of FASTKD1 were significantly associated with clinical stage and survival. Through GO/KEGG enrichment analysis and GSEA, it was revealed that the genes co-expressed with FASTKD1 were active in a variety of biological processes. Within the TIMER, GEPIA and TCGA databases, a notable inverse correlation was observed between FASTKD1 expression and the abundance of immune cell subsets. Notably, significant correlations were established between FASTKD1 and m6A modification genes, YTHDF1 and LRPPRC, in both TCGA and GEO datasets. In conclusion, FASTKD1 may serve a significant role in m6A modification and immune infiltration processes, making it a potentially valuable diagnostic and prognostic biomarker in STAD.

A comprehensive characterization and expression profiling of defensin family peptides in Arabidopsis thaliana with a focus on their abiotic stress-specific transcriptional modulation

In addition to defensins, plants possess an array of defensin-like peptides that share many of their characteristics, as well as a role in plant’s innate immunity. Their involvement in the response to pathogens is well-known but the contribution in the plant response to abiotic stimuli is not fully understood. We have undertaken an in silico analysis to characterize all defensin family genes hitherto found in Arabidopsis, including genes encoding for defensin-like peptides, by detecting several peptides as candidates for further studies aiming to decipher specific responses to biotic and abiotic stresses, as well as to their crosstalk. We performed several analyses, including co-expression and cis-regulatory elements analyses, using transcriptomic data obtained from the ARS database, which integrates more than 20,000 Arabidopsis RNA-seq libraries.In silico analysis showed that jasmonates and ABA, together with transcription factors belonging to WRKY and AP2/EREBP families, modulate defensin and defensin-like gene expression. Indeed, the analysis performed in this study allowed to extract and organize omics data, which finally supported the inducible nature of defensins under both abiotic and biotic stresses. Moreover, in vivo expression analyses confirmed the heat and drought responsiveness of PDF1.4, ATTI1, PDF1.1, DEFL 206, defensin family genes selected for being upregulated by several abiotic conditions, at transcriptional level. Finally, the co-expression analysis provided information on other biological processes that may be correlated to the defensin induction, such as maintaining ROS homeostasis. Combining the comprehensive analysis of different transcriptional datasets with the integration of in vivo analyses emerged as a robust methodological approach to assess the proposed multi-stress responsive nature of defensin family genes.