Weighted Gene Correlation Network Analysis Research Articles

Gene Expression Profile of Benign, Intermediate, and Malignant Spitz and Spitzoid Melanocytic Lesions

Spitz and Spitzoid lesions represent one of the most challenging melanocytic neoplasms in dermatopathology. Nosologic classification has been more recently improved by the discovery of novel molecular drivers, particularly translocations. In the current study, we aimed to use an unbiased approach to explore the gene expression profile of a group of melanocytic Spitz and Spitzoid melanocytic lesions ranging from benign lesions to melanoma, including intermediate lesions such as SPARK nevi and atypical Spitz tumors/melanocytomas. Using unsupervised analysis of gene expression data, we found some distinct hierarchical clusters of lesions, including groups characterized by ALK and NTRK translocations. Few non-ALK translocated tumors demonstrated increased ALK expression, confirmed by immunohistochemistry. Spitz tumors with overlapping features of dysplastic nevi, so-called SPARK nevi, appear to have a common gene expression profile by hierarchical clustering. Finally, weighted gene correlation network analysis identified gene modules variably regulated in subtypes of these cases. Thus, gene expression profiling of Spitz and Spitzoid lesions represents a viable instrument for the characterization of these lesions.

Neutrophil and macrophage crosstalk might be a potential target for liver regeneration.

The regenerative capability of the liver is remarkable, but further research is required to understand the role that neutrophils play in this process. In the present study, we reanalyzed single-cell RNA sequencing data from a mouse partial hepatectomy (PH) model to track the transcriptional changes in hepatocytes and non-parenchymal cells. Notably, we unraveled the regenerative capacity of hepatocytes at diverse temporal points after PH, unveiling the contributions of three distinct zones in the liver regeneration process. In addition, we observed that the depletion of neutrophils reduced the survival and liver volume after PH, confirming the important role of neutrophils in liver regeneration. CellChat analysis revealed an intricate crosstalk between neutrophils and macrophages promoting liver regeneration and, using weighted gene correlation network analysis, we identified the most significant genetic module associated with liver regeneration. Our study found that hepatocytes in the periportal zone of the liver are more active than in other zones, suggesting that the crosstalk between neutrophils and macrophages might be a potential target for liver regeneration treatment.

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma

BackgroundKidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP.MethodsRNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors.ResultsIn total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP.ConclusionsWe suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

Biomarkers associated with pulmonary exacerbations in a randomized trial of nintedanib for radiation pneumonitis

Background and purposeRadiation pneumonitis (RP) is a common side effect of thoracic radiotherapy and often has a long course characterized by acute exacerbations and progression to permanent lung fibrosis. There are no validated biomarkers of prognosis in patients diagnosed with RP. Materials and methodsWe analyzed a time course of serum chemokines, cytokines, and other proteins from patients with grade 2+ RP in a randomized clinical trial of a steroid taper plus nintedanib, a multiple tyrosine kinase inhibitor, versus placebo plus a steroid taper for the treatment of RP. Weighted gene correlation network analysis (WGCNA) and univariable zero inflated Poisson models were used to identify groups of correlated analytes and their associations with clinical outcomes. ResultsThirty enrolled patients had biomarker data available, and 17 patients had enough analytes tested for network analysis. WGNCA identified ten analytes, including transforming growth factor beta-1 (TGF-β1), monocyte chemoattractant protein-1 (MCP-1), and platelet-derived growth factor (PDGF), that in aggregate were correlated with the occurrence of pulmonary exacerbations (p = 0.008), the total number of acute pulmonary exacerbations (p = 0.002), and treatment arm (p = 0.036). By univariable analysis, an increase in rate of change of two components of the RP module were associated with an increased incidence rate of pulmonary exacerbations: interleukin 5 (IL-5, incidence rate ratio (IRR) 1.02, 95% CI 1.01–1.04, p = 0.002), and tumor necrosis factor superfamily 12 (TNFSF12, IRR 1.06, CI 1–1.11, p = 0.036). An increased slope of epidermal growth factor (EGF) was associated with a decreased incidence rate of exacerbations (IRR 0.94, CI 0.89–1, p = 0.036). ConclusionWe identified a panel of serum biomarkers that showed association with nintedanib treatment and acute pulmonary exacerbations in patients with RP. A confirmatory study will be needed to validate this panel for use as a prognostic tool in patients with RP.

LncRNA GAS6-AS1 contributes to 5-fluorouracil resistance in colorectal cancer by facilitating the binding of PCBP1 with MCM3

5-Fluorouracil (5-FU) resistance has always been a formidable obstacle in the adjuvant treatment of advanced colorectal cancer (CRC). In recent years, long non-coding RNAs have emerged as key regulators in various pathophysiological processes including 5-FU resistance. TRG is a postoperative pathological score of the chemotherapy effectiveness for CRC, of which TRG 0–1 is classified as chemotherapy sensitivity and TRG 3 as chemotherapy resistance. Here, RNA-seq combined with weighted gene correlation network analysis confirmed the close association of GAS6-AS1 with TRG. GAS6-AS1 expression was positively correlated with advanced clinicopathological features and poor prognosis in CRC. GAS6-AS1 increased the 50% inhibiting concentration of 5-FU, enhanced cell proliferation and accelerated G1/S transition, both with and without 5-FU, both in vitro and in vivo. Mechanistically, GAS6-AS1 enhanced the stability of MCM3 mRNA by recruiting PCBP1, consequently increasing MCM3 expression. Furthermore, PCBP1 and MCM3 counteracted the effects of GAS6-AS1 on 5-FU resistance. Notably, the PDX model indicated that combining chemotherapeutic drugs with GAS6-AS1 knockdown yielded superior outcomes in vivo. Together, our findings elucidate that GAS6-AS1 directly binds to PCBP1, enhancing MCM3 expression and thereby promoting 5-FU resistance. GAS6-AS1 may serve as a robust biomarker and potential therapeutic target for combination therapy in CRC.

Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis.

Accumulating evidences indicate that abnormalities in tubular lipid metabolism play a crucial role in the development of diabetic kidney disease (DKD). We aim to identify novel lipid metabolism-related genes associated with tubular injury in DKD by utilizing bioinformatics approaches. Differentially expressed genes (DEGs) between control and DKD tubular tissue samples were screened from the Gene Expression Omnibus (GEO) database, and then were intersected with lipid metabolism-related genes. Hub genes were further determined by combined weighted gene correlation network analysis (WGCNA) and protein-protein interaction (PPI) network. We performed enrichment analysis, immune analysis, clustering analysis, and constructed networks between hub genes and miRNAs, transcription factors and small molecule drugs. Receiver operating characteristic (ROC) curves were employed to evaluate the diagnostic efficacy of hub genes. We validated the relationships between hub genes and DKD with external datasets and our own clinical samples. There were 5 of 37 lipid metabolism-related DEGs identified as hub genes. Enrichment analysis demonstrated that lipid metabolism-related DEGs were enriched in pathways such as peroxisome proliferator-activated receptors (PPAR) signaling and pyruvate metabolism. Hub genes had potential regulatory relationships with a variety of miRNAs, transcription factors and small molecule drugs, and had high diagnostic efficacy. Immune infiltration analysis revealed that 13 immune cells were altered in DKD, and hub genes exhibited significant correlations with a variety of immune cells. Through clustering analysis, DKD patients could be classified into 3 immune subtypes and 2 lipid metabolism subtypes, respectively. The tubular expression of hub genes in DKD was further verified by other external datasets, and immunohistochemistry (IHC) staining showed that except ACACB, the other 4 hub genes (LPL, AHR, ME1 and ALOX5) exhibited the same results as the bioinformatics analysis. Our study identified several key lipid metabolism-related genes (LPL, AHR, ME1 and ALOX5) that might be involved in tubular injury in DKD, which provide new insights and perspectives for exploring the pathogenesis and potential therapeutic targets of DKD.

Identification of potential biomarkers of gout through weighted gene correlation network analysis.

Although hyperuricemia is not always associated with acute gouty arthritis, uric acid is a significant risk factor for gout. Therefore, we investigated the specific mechanism of uric acid activity. Using the gout-associated transcriptome dataset GSE160170, we conducted differential expression analysis to identify differentially expressed genes (DEGs). Moreover, we discovered highly linked gene modules using weighted gene coexpression network analysis (WGCNA) and evaluated their intersection. Subsequently, we screened for relevant biomarkers using the cytoHubba and Mcode algorithms in the STRING database, investigated their connection to immune cells and constructed a competitive endogenous RNA (ceRNA) network to identify upstream miRNAs and lncRNAs. We also collected PBMCs from acute gouty arthritis patients and healthy individuals and constructed a THP-1 cell gout inflammatory model, RT-qPCR and western blotting (WB) were used to detect the expression of C-X-C motif ligand 8 (CXCL8), C-X-C motif ligand 2 (CXCL2), and C-X-C motif ligand 1 (CXCL1). Finally, we predicted relevant drug targets through hub genes, hoping to find better treatments. According to differential expression analysis, there were 76 upregulated and 28 downregulated mRNAs in GSE160170. Additionally, WGCNA showed that the turquoise module was most strongly correlated with primary gout; 86 hub genes were eventually obtained upon intersection. IL1β, IL6, CXCL8, CXCL1, and CXCL2 are the principal hub genes of the protein-protein interaction (PPI) network. Using RT-qPCR and WB, we found that there were significant differences in the expression levels of CXCL8, CXCL1, and CXCL2 between the gouty group and the healthy group, and we also predicted 10 chemicals related to these proteins. In this study, we screened and validated essential genes using a variety of bioinformatics tools to generate novel ideas for the diagnosis and treatment of gout.

Integrated Full-Length Transcriptomics and Metabolomics Reveal Glycosyltransferase Involved in the Biosynthesis of Flavonol Glycosides in Laportea bulbifera.

Many species of the Urticaceae family are important cultivated fiber plants that are known for their economic and industrial values. However, their secondary metabolite profiles and associated biosynthetic mechanisms have not been well-studied. Using Laportea bulbifera as a model, we conducted widely targeted metabolomics, which revealed 523 secondary metabolites, including a unique accumulation of flavonol glycosides in bulblet. Through full-length transcriptomic and RNA-seq analyses, the related genes in the flavonoid biosynthesis pathway were identified. Finally, weighted gene correlation network analysis and functional characterization revealed four LbUGTs, including LbUGT78AE1, LbUGT72CT1, LbUGT71BX1, and LbUGT71BX2, can catalyze the glycosylation of flavonol aglycones (kaempferol, myricetin, gossypetin, and quercetagetin) using UDP-Gal and UDP-Glu as the sugar donors. LbUGT78AE1 and LbUGT72CT1 showed substrate promiscuity, whereas LbUGT71BX1 and LbUGT71BX2 exhibited different substrate and sugar donor selectivity. These results provide a genetic resource for studying Laportea in the Urticaceae family, as well as key enzymes responsible for the metabolism of valuable flavonoid glycosides.

Novel insights into the pathogenesis of thyroid eye disease through ferroptosis-related gene signature and immune infiltration analysis.

Thyroid eye disease (TED) has brought great physical and mental trauma to patients worldwide. Although a few potential signaling pathways have been reported, knowledge of TED remains limited. Our objective is to explore the fundamental mechanism of TED and identify potential therapeutic targets using diverse approaches. To perform a range of bioinformatic analyses, such as identifying differentially expressed genes (DEGs), conducting enrichment analysis, establishing nomograms, analyzing weighted gene correlation network analysis (WGCNA), and studying immune infiltration, the datasets GSE58331, GSE105149, and GSE9340 were integrated. Further validation was conducted using qPCR, western blot, and immunohistochemistry techniques. Eleven ferroptosis-related DEGs derived from the lacrimal gland were originally screened. Their high diagnostic value was proven, and diagnostic prediction nomogram models with high accuracy and robustness were established by using machine learning. A total of 15 hub gene-related DEGs were identified by WGCNA. Through CIBERSORTx, we uncovered five immune cells highly correlated with TED and found several special associations between these immune cells and the above DEGs. Furthermore, EGR2 from the thyroid sample was revealed to be closely negatively correlated with most DEGs from the lacrimal gland. High expression of APOD, COPB2, MYH11, and MYCN, as well as CD4/CD8 T cells and B cells, was verified in the periorbital adipose tissues of TED patients. To summarize, we discovered a new gene signature associated with ferroptosis that has a critical impact on the development of TED and provides valuable insights into immune infiltration. These findings might highlight the new direction and therapeutic strategies of TED.

Abstract 7347: A transcriptome correlation network analysis of the high grade serous ovarian tumor immune microenvironment

Abstract High Grade Serous Ovarian Cancer (HGSOC) affects many women and is the most common and lethal histopathological type of ovarian cancer. The molecular subtypes delineated by TCGA–mesenchymal, proliferative, immunoreactive, and differentiated subtypes, offer a sophisticated and innovative framework for HGSOC classification. These subtypes not only provide a detailed molecular characterization but also contribute to understanding the HGSOC Tumor Immune Microenvironment (TIME), comprised of both immune and tumor cells. The interplay within the TIME significantly influences pro- or anti-tumor responses, creating an important link between molecular landscape and dynamic immune-tumor interactions. Currently, there is a lack of understanding for the key drivers of clinical outcomes, molecular phenotypes, and diagnostic biomarkers for HGSOC. Here, we answer the question, does immune cell type, and proportion, drive clinical and molecular subtyping of primary HGSOC? Primary ovarian tumor samples from The Cancer Genome Atlas, TCGA (n=358) samples were collected and RNA-sequenced. FPKM values were used to construct the Weighted Gene Correlation Network Analysis (WGCNA), Gene Ontology (GO) and Proportion Estimations of Immune and Cancer cells (EPIC). Enrichment of HGSOC network module overlaps using a Fischer Exact Test were used to identify novel components of HGSOC progression that were significantly associated with clusters of highly correlated gene expression profiles, HGSOC stage, grade, and molecular phenotypes. We show genes associated with T cell proliferation (CD84) and B cell regulation (CD37), epithelial to mesenchymal transition (DOCK2), adaptor proteins present in T cells and myeloid cells (LCP2), inflammatory and metabolic signaling modulators (AIF1,CD53, SASH3), immunosuppressors of T lymphocytes and dendritic cells (FGL2), cell proliferation (PI3K) and relevant tertiary lymphoid structure gene (TNFAIP8L2) significantly correlated with HGSOC progression in both estimated tumor and proportions of immune cells. Future studies aim to confirm phosphorylation cascades associated with the aggressive molecular phenotypes of HGSOC and immune cell pathobiology. Citation Format: Kaylin M. Carey, Eric B. Dammer, Corey Young, Rajesh Singh, Ti'ara Griffen, James W. Lillard. A transcriptome correlation network analysis of the high grade serous ovarian tumor immune microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7347.

Diagnostic Value of GDF10 for the Tumorigenesis and Immune Infiltration in Lung Squamous Cell Carcinoma.

Lung squamous cell carcinoma (LUSC) is associated with a low survival rate. Evidence suggests that bone morphogenetic proteins (BMPs) and their receptors (BMPRs) play crucial roles in tumorigenesis and progression. However, a comprehensive analysis of their role in LUSC is lacking. Our study aimed to explore the relationship between BMPs/BMPRs expression levels and the tumorigenesis and prognosis of LUSC. The "R/Limma" package was utilized to analyze the differential expression characteristics of BMPs/BMPRs in LUSC, using data from TCGA, GTEx, and GEO databases. Concurrently, the "survminer" packages were employed to investigate their prognostic value and correlation with clinical features in LUSC. The core gene associated with LUSC progression was further explored through weighted gene correlation network analysis (WGCNA). LASSO analysis was conducted to construct a prognostic risk model for LUSC. Clinical specimens were examined by immunohistochemical analysis to confirm the diagnostic value in LUSC. Furthermore, based on the tumor immune estimation resource database and tumor-immune system interaction database, the role of the core gene in the tumor microenvironment of LUSC was explored. GDF10 had a significant correlation only with the pathological T stage of LUSC, and the protein expression level of GDF10 decreased with the tumorigenesis of LUSC. A prognostic risk model was constructed with GDF10 as the core gene and 5 hub genes (HRASLS, HIST1H2BH, FLRT3, CHEK2, and ALPL) for LUSC. GDF10 showed a significant positive correlation with immune cell infiltration and immune checkpoint expression. GDF10 might serve as a diagnostic biomarker reflecting the tumorigenesis of LUSC and regulating the tumor immune microenvironment to guide more effective treatment for LUSC.

Alpha 2-adrenoceptor participates in anti-hyperalgesia by regulating metabolic demand.

The α2-adrenoceptor agonist dexmedetomidine is a commonly used drug for sedatives in clinics and has analgesic effects; however, its mechanism of analgesia in the spine remains unclear. In this study, we systematically used behavioural and transcriptomic sequencing, pharmacological intervention, electrophysiological recording and ultrasound imaging to explore the analgesic effects of the α2-adrenoceptor and its molecular mechanism. Firstly, we found that spinal nerve injury changed the spinal transcriptome expression, and the differential genes were mainly related to calcium signalling and tissue metabolic pathways. In addition, α2-adrenoceptor mRNA expression was significantly upregulated, and α2-adrenoceptor was significantly colocalised with markers, particularly neuronal markers. Intrathecal dexmedetomidine suppressed neuropathic pain and acute inflammatory pain in a dose-dependent manner. The transcriptome results demonstrated that the analgesic effect of dexmedetomidine may be related to the modulation of neuronal metabolism. Weighted gene correlation network analysis indicated that turquoise, brown, yellow and grey modules were the most correlated with dexmedetomidine-induced analgesic effects. Bioinformatics also annotated the involvement of metabolic processes and neural plasticity. A cardiovascular-mitochondrial interaction was found, and ultrasound imaging revealed that injection of dexmedetomidine significantly enhanced spinal cord perfusion in rats with neuropathic pain, which might be regulated by pyruvate dehydrogenase kinase 4 (pdk4), cholesterol 25-hydroxylase (ch25h) and GTP cyclohydrolase 1 (gch1). Increasing the perfusion doses of dexmedetomidine significantly suppressed the frequency and amplitude of spinal nerve ligation-induced miniature excitatory postsynaptic currents. Overall, dexmedetomidine exerts analgesic effects by restoring neuronal metabolic processes through agonism of the α2-adrenoceptor and subsequently inhibiting changes in synaptic plasticity.

Roles of pyroptosis and immune infiltration in aortic dissection.

Introduction: Aortic dissection (AD) is often fatal, and its pathogenesis involves immune infiltration and pyroptosis, though the molecular pathways connecting these processes remain unclear. This study aimed to investigate the role of immune infiltration and pyroptosis in AD pathogenesis using bioinformatics analysis. Methods: Two Gene Expression Omnibus datasets and a Gene Cards dataset of pyroptosis-related genes (PRGs) were utilized. Immunological infiltration was assessed using CIBERSORT, and AD diagnostic markers were identified through univariate logistic regression and least absolute shrinkage and selection operator regression. Interaction networks were constructed using STRING, and weighted gene correlation network analysis (WGCNA) was employed to identify important modules and essential genes. Single-sample gene set enrichment analysis determined immune infiltration, and Pearson correlation analysis assessed the association of key genes with infiltrating immune cells. Results: Thirty-one PRGs associated with inflammatory response, vascular epidermal growth factor receptor, and Rap1 signaling pathways were identified. WGCNA revealed seven important genes within a critical module. CIBERSORT detected immune cell infiltration, indicating significant changes in immune cell infiltration and pyroptosis genes in AD and their connections. Discussion: Our findings suggest that key PRGs may serve as indicators for AD or high-risk individuals. Understanding the role of pyroptosis and immune cell infiltration in AD pathogenesis may lead to the development of novel molecular-targeted therapies for AD. Conclusion: This study provides insights into the molecular mechanisms underlying AD pathogenesis, highlighting the importance of immune infiltration and pyroptosis. Identification of diagnostic markers and potential therapeutic targets may improve the management of AD and reduce associated morbidity and mortality.

Drilling into the physiology, transcriptomics, and metabolomics to enhance insight on Vallisneria denseserrulata responses to nanoplastics and metalloid co-stress

Co-contamination of nanoplastics (NPs) and arsenic (As) in aquatic environments poses a serious threat to the growth of aquatic plants, but the molecular toxicity mechanism leading to this joint effect on submerged macrophytes is still unclear. Here, we investigated the physiological, transcriptomic, metabolomic responses, and organelle changes in submerged macrophyte, Vallisneria denseserrulata (V. denseserrulata), to single/combined exposure to NPs and As. Our results showed that co-exposure alters physiological traits in V. denseserrulata including chlorophyll, sugars, proteins, malondialdehyde, and antioxidant enzymes. The presence of NPs exacerbated As distribution 36.2–47.2% higher than the control in plant tissues, thus enhancing combined pollution to plants. Integration of physiological traits and differentially expressed genes via weighted correlation network analysis implicated stress-responsive candidate modules related to key enzymes, such as ribulose-bisphosphate carboxylase, alanine transaminase, aspartate aminotransferase, phosphofructokinase-1, and phenylalanine ammonia-lyase. Metabolomics profiling identified carbohydrates, amino acids, organic acids, and fatty acids. Conjoint transcriptome and metabolome analysis revealed that photosynthetic systems, energy conversion, and oxidative and antioxidant regulation are the key defensive response mechanisms for V. denseserrulata under NPs-As co-exposure. Taken together, our multi-omics study provided new molecular insights into submerged macrophytes tolerance mechanisms against combined NPs and As toxicity, highlighting potential targets for stress mitigation and biomonitoring in contaminated aquatic ecosystems.

Identification of marker genes for spinal cord injury.

Spinal cord injury (SCI) is a profoundly disabling and devastating neurological condition, significantly impacting patients' quality of life. It imposes unbearable psychological and economic pressure on both patients and their families, as well as placing a heavy burden on society. In this study, we integrated datasets GSE5296 and GSE47681 as training groups, analyzed gene variances between sham group and SCI group mice, and conducted Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis based on the differentially expressed genes. Subsequently, we performed Weighted Gene Correlation Network Analysis (WGCNA) and Lasso regression analyses. We identified four characteristic disease genes: Icam1, Ch25h, Plaur and Tm4sf1. We examined the relationship between SCI and immune cells, and validated the expression of the identified disease-related genes in SCI rats using PCR and immunohistochemistry experiments. In conclusion, we have identified and verified four genes related to SCI: Icam1, Ch25h, Plaur and Tm4sf1, which could offer insights for SCI treatment.

Integrative ATAC-seq and RNA-seq analysis associated with diabetic nephropathy and identification of novel targets for treatment by dapagliflozin.

Dapagliflozin (DAPA) are clinically effective in improving diabetic nephropathy (DN). However, whether and how chromatin accessibility changed by DN responds to DAPA treatment is unclear. Therefore, we performed ATAC-seq, RNA-seq, and weighted gene correlation network analysis to identify the chromatin accessibility, the messenger RNA (mRNA) expression, and the correlation between clinical phenotypes and mRNA expression using kidney from three mouse groups: db/m mice (Controls), db/db mice (case group), and those treated with DAPA (treatment group). RNA-Seq and ATAC-seq conjoint analysis revealed many overlapping pathways and networks suggesting that the transcriptional changes of DN and DAPA intervention largely occured dependently on chromatin remodeling. Specifically, the results showed that some key signal transduction pathways, such as immune dysfunction, glucolipid metabolism, oxidative stress and xenobiotic and endobiotic metabolism, were repeatedly enriched in the analysis of the RNA-seq data alone, as well as combined analysis with ATAC-seq data. Furthermore, we identified some candidate genes (UDP glucuronosyltransferase 1 family, Dock2, Tbc1d10c, etc.) and transcriptional regulators (KLF6 and GFI1) that might be associated with DN and DAPA restoration. These reversed genes and regulators confirmed that pathways related to immune response and metabolism pathways were critically involved in DN progression.

Cathepsin G promotes arteriovenous fistula maturation by positively regulating the MMP2/MMP9 pathway

Background Arteriovenous fistula (AVF) is currently the preferred vascular access for hemodialysis patients. However, the low maturation rate of AVF severely affects its use in patients. A more comprehensive understanding and study of the mechanisms of AVF maturation is urgently needed. Methods and results In this study, we downloaded the publicly available datasets (GSE119296 and GSE220796) from the Gene Expression Omnibus (GEO) and merged them for subsequent analysis. We screened 84 differentially expressed genes (DEGs) and performed the functional enrichment analysis. Next, we integrated the results obtained from the degree algorithm provided by the Cytohubba plug-in, Molecular complex detection (MCODE) plug-in, weighted gene correlation network analysis (WGCNA), and Least absolute shrinkage and selection operator (LASSO) logistic regression. This integration allowed us to identify CTSG as a hub gene associated with AVF maturation. Through the literature search and Pearson’s correlation analysis, the genes matrix metalloproteinase 2 (MMP2) and MMP9 were identified as potential downstream effectors of CTSG. We then collected three immature clinical AVF vein samples and three mature samples and validated the expression of CTSG using immunohistochemistry (IHC) and double-immunofluorescence staining. The IHC results demonstrated a significant decrease in CTSG expression levels in the immature AVF vein samples compared to the mature samples. The results of double-immunofluorescence staining revealed that CTSG was expressed in both the intima and media of AVF veins. Moreover, the expression of CTSG in vascular smooth muscle cells (VSMCs) was significantly higher in the mature samples compared to the immature samples. The results of Masson’s trichrome and collagen I IHC staining demonstrated a higher extent of collagen deposition in the media of immature AVF veins compared to the mature. By constructing an in vitro CTSG overexpression model in VSMCs, we found that CTSG upregulated the expression of MMP2 and MMP9 while downregulating the expression of collagen I and collagen III. Furthermore, CTSG was found to inhibit VSMC migration. Conclusions CTSG may promote AVF maturation by stimulating the secretion of MMP2 and MMP9 from VSMCs and reducing the extent of medial fibrosis in AVF veins by inhibiting the secretion of collagen I and collagen III.

A novel peptide PDHK1-241aa encoded by circPDHK1 promotes ccRCC progression via interacting with PPP1CA to inhibit AKT dephosphorylation and activate the AKT-mTOR signaling pathway

BackgroundClear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer with high aggressive phenotype and poor prognosis. Accumulating evidence suggests that circRNAs have been identified as pivotal mediators in cancers. However, the role of circRNAs in ccRCC progression remains elusive.MethodsThe differentially expressed circRNAs in 4 paired human ccRCC and adjacent noncancerous tissues ccRCC were screened using circRNA microarrays and the candidate target was selected based on circRNA expression level using weighted gene correlation network analysis (WGCNA) and the gene expression omnibus (GEO) database. CircPDHK1 expression in ccRCC and adjacent noncancerous tissues (n = 148) were evaluated along with clinically relevant information. RT-qPCR, RNase R digestion, and actinomycin D (ActD) stability test were conducted to identify the characteristics of circPDHK1. The subcellular distribution of circPDHK1 was analyzed by subcellular fractionation assay and fluorescence in situ hybridization (FISH). Immunoprecipitation-mass spectrometry (IP-MS) and immunofluorescence (IF) were employed to evaluate the protein-coding ability of circPDHK1. ccRCC cells were transfected with siRNAs, plasmids or lentivirus approach, and cell proliferation, migration and invasion, as well as tumorigenesis and metastasis in nude mice were assessed to clarify the functional roles of circPDHK1 and its encoded peptide PDHK1-241aa. RNA-sequencing, western blot analysis, immunoprecipitation (IP) and chromatin immunoprecipitation (ChIP) assays were further employed to identify the underlying mechanisms regulated by PDHK1-241aa.ResultsCircPDHK1 was upregulated in ccRCC tissues and closely related to WHO/ISUP stage, T stage, distant metastasis, VHL mutation and Ki-67 levels. CircPDHK1 had a functional internal ribosome entry site (IRES) and encoded a novel peptide PDHK1-241aa. Functionally, we confirmed that PDHK1-241aa and not the circPDHK1 promoted the proliferation, migration and invasion of ccRCC. Mechanistically, circPDHK1 was activated by HIF-2A at the transcriptional level. PDHK1-241aa was upregulated and interacted with PPP1CA, causing the relocation of PPP1CA to the nucleus. This thereby inhibited AKT dephosphorylation and activated the AKT-mTOR signaling pathway.ConclusionsOur data indicated that circPDHK1-encoded PDHK1-241aa promotes ccRCC progression by interacting with PPP1CA to inhibit AKT dephosphorylation. This study provides novel insights into the multiplicity of circRNAs and highlights the potential use of circPDHK1 or PDHK1-241aa as a therapeutic target for ccRCC.

Multi-omics analysis of a fatty liver model using human hepatocyte chimeric mice

We developed a fatty liver mouse model using human hepatocyte chimeric mice. As transplanted human hepatocytes do not respond to mouse growth hormone (GH) and tend to accumulate fat, we hypothesized that addition of human GH would alter lipid metabolism and reduce accumulation of fat in the liver even when fed a high-fat diet. Six uPA/SCID chimeric mice were fed a high-fat GAN diet to induce fatty liver while six were fed a normal CRF1 diet, and GH was administered to three mice in each group. The mice were euthanized at 8 weeks, and human hepatocytes were extracted for RNA-Seq, DIA proteomics, and metabolomics analysis. Abdominal echocardiography revealed that the degree of fatty liver increased significantly in mice fed GAN diet (p < 0.001) and decreased significantly in mice treated with GH (p = 0.026). Weighted gene correlation network analysis identified IGF1 and SEMA7A as eigengenes. Administration of GH significantly reduced triglyceride levels and was strongly associated with metabolism of amino acids. MiBiOmics analysis identified perilipin-2 as a co-inertia driver. Results from multi-omics analysis revealed distinct gene expression and protein/metabolite profiles in each treatment group when mice were fed a high-fat or normal diet with or without administration of GH.

Gene coexpression networks reveal a broad role for lncRNAs in inflammatory bowel disease.

The role of long noncoding RNAs (lncRNAs) in disease is incompletely understood, but their regulation of inflammation is increasingly appreciated. We addressed the extent of lncRNA involvement in inflammatory bowel disease (IBD) using biopsy-derived RNA-sequencing data from a large cohort of deeply phenotyped patients with IBD. Weighted gene correlation network analysis revealed gene modules of lncRNAs coexpressed with protein-coding genes enriched for biological pathways, correlated with epithelial and immune cell signatures, or correlated with distal colon expression. Correlation of modules with clinical features uncovered a module correlated with disease severity, with an enriched interferon response signature containing the hub lncRNA IRF1-AS1. Connecting genes to IBD-associated single nucleotide polymorphisms (SNPs) revealed an enrichment of SNP-adjacent lncRNAs in biologically relevant modules. Ulcerative colitis-specific SNPs were enriched in distal colon-related modules, suggesting that disease-specific mechanisms may result from altered lncRNA expression. The function of the IBD-associated SNP-adjacent lncRNA IRF1-AS1 was explored in human myeloid cells, and our results suggested IRF1-AS1 promoted optimal production of TNF-α, IL-6, and IL-23. A CRISPR/Cas9-mediated activation screen in THP-1 cells revealed several lncRNAs that modulated LPS-induced TNF-α responses. Overall, this study uncovered the expression patterns of lncRNAs in IBD that identify functional, disease-relevant lncRNAs.