Identification of key genes in ruptured atherosclerotic plaques by weighted gene correlation network analysis

Enhancing Cardiovascular Risk Stratification: Radiomics of Coronary Plaque and Perivascular Adipose Tissue - Current Insights and Future Perspectives

Radiomics, the quantitative extraction and mining of features from radiological images, has recently emerged as a promising source of non-invasive image-based cardiovascular biomarkers, potentially revolutionizing diagnostics and risk assessment. This review explores its application within coronary plaques and pericoronary adipose tissue, particularly focusing on plaque characterization and cardiac events prediction. By shedding light on the current state-of-the-art, achievements, and prospective avenues, this review contributes to a deeper understanding of the evolving landscape of radiomics in the context of coronary arteries. Finally, open challenges and existing gaps are emphasized to underscore the need for future efforts aimed at ensuring the robustness and reliability of radiomics studies, facilitating their clinical translation.

A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

Background

Electrocardiogram (ECG) signals are inevitably contaminated with various kinds of noises during acquisition and transmission. The presence of noises may produce the inappropriate information on cardiac health, thereby preventing specialists from making correct analysis.

Methods

In this paper, an efficient strategy is proposed to denoise ECG signals, which employs a time-frequency framework based on S-transform (ST) and combines bi-dimensional empirical mode decomposition (BEMD) and non-local means (NLM). In the method, the ST maps an ECG signal into a subspace in the time frequency domain, then the BEMD decomposes the ST-based time-frequency representation (TFR) into a series of sub-TFRs at different scales, finally the NLM removes noise and restores ECG signal characteristics based on structural self-similarity.

Results

The proposed method is validated using numerous ECG signals from the MIT-BIH arrhythmia database, and several different types of noises with varying signal-to-noise (SNR) are taken into account. The experimental results show that the proposed technique is superior to the existing wavelet based approach and NLM filtering, with the higher SNR and structure similarity index measure (SSIM), the lower root mean squared error (RMSE) and percent root mean square difference (PRD).

Conclusions

The proposed method not only significantly suppresses the noise presented in ECG signals, but also preserves the characteristics of ECG signals better, thus, it is more suitable for ECG signals processing.

Constructing a competitive endogenous RNA network of EndMT-related atherosclerosis through weighted gene co-expression network analysis

Atherosclerosis is a chronic inflammatory disease characterized by endothelial dysfunction and plaque formation. Under pro-inflammatory conditions, endothelial cells can undergo endothelial-to-mesenchymal transition (EndMT), contributing to atherosclerosis development. However, the specific regulatory mechanisms by which EndMT contributes to atherosclerosis remain unclear and require further investigation. Dan-Shen-Yin (DSY), a traditional Chinese herbal formula, is commonly used for cardiovascular diseases, but its molecular mechanisms remain elusive. Emerging evidence indicates that competing endogenous RNA (ceRNA) networks play critical roles in atherosclerosis pathogenesis. In this study, we constructed an EndMT-associated ceRNA network during atherosclerosis progression by integrating gene expression profiles from the Gene Expression Omnibus (GEO) database and weighted gene co-expression network analysis. Functional enrichment analysis revealed this EndMT-related ceRNA network is predominantly involved in inflammatory responses. ROC curve analysis showed the identified hub genes can effectively distinguish between normal vasculature and atherosclerotic lesions. Furthermore, Kaplan-Meier analysis demonstrated that high expression of IL1B significantly predicts ischemic events in atherosclerosis. Molecular docking revealed most DSY bioactive components can bind key EndMT-related lncRNAs, including AC003092.1, MIR181A1HG, MIR155HG, WEE2-AS1, and MIR137HG, suggesting DSY may mitigate EndMT in atherosclerosis by modulating the ceRNA network.

Sodium intake and the risk of various types of cardiovascular diseases: a Mendelian randomization study

Background

The existing literature on the link between sodium intake and cardiovascular disease (CVD) largely consists of observational studies that have yielded inconsistent conclusions. In this study, our objective is to assess the causal relationship between sodium intake and 50 CVDs using two-sample Mendelian randomization (MR) analysis.

Methods

MR analyses were performed to investigate the associations between urinary sodium/creatinine ratio (UNa/UCr), an indicator of sodium intake, and 50 CVDs. The genome-wide association study (GWAS) for UNa/UCr was from the UK Biobank (UKBB), and the GWASs for CVDs were from FinnGen. A false discovery rate (FDR) threshold of 5% was applied for multiple comparison correction.

Results

The inverse-variance weighted method indicated that the genetically predicted UNa/UCr was significantly associated with 7 of 50 CVDs, including "Coronary atherosclerosis" (OR = 2.01; 95% CI: 1.37, 2.95), "Diseases of arteries, arterioles and capillaries" (OR = 1.88; 95% CI: 1.20, 2.94), "Hard cardiovascular diseases" (OR = 1.71; 95% CI: 1.24, 2.35), "Ischemic heart diseases" (OR = 2.06; 95% CI: 1.46, 2.93), "Major coronary heart disease event" (OR = 1.99; 95% CI: 1.36, 2.91), "Myocardial infarction" (OR = 2.03; 95% CI: 1.29, 3.19), and "Peripheral artery disease" (OR = 2.50; 95% CI: 1.35, 4.63). Similar results were obtained with the MR-Egger and weighted median methods. No significant heterogeneity or horizontal pleiotropy was found in this analysis.

Conclusion

Our study has uncovered a significant positive causal relationship between UNa/UCr and various CVDs. These results offer a new theoretical foundation for advocating the restriction of sodium intake as a preventive measure against CVD.

Transcriptome analysis unveils the mechanisms of lipid metabolism response to grayanotoxin I stress in Spodoptera litura

Background

Spodoptera litura (tobacco caterpillar, S. litura) is a pest of great economic importance due to being a polyphagous and world-distributed agricultural pest. However, agricultural practices involving chemical pesticides have caused resistance, resurgence, and residue problems, highlighting the need for new, environmentally friendly methods to control the spread of S. litura.

Aim

This study aimed to investigate the gut poisoning of grayanotoxin I, an active compound found in Pieris japonica, on S. litura, and to explore the underlying mechanisms of these effects.

Methods

S. litura was cultivated in a laboratory setting, and their survival rate, growth and development, and pupation time were recorded after grayanotoxin I treatment. RNA-Seq was utilized to screen for differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to determine the functions of these DEGs. ELISA was employed to analyze the levels of lipase, 3-hydroxyacyl-CoA dehydrogenase (HOAD), and acetyl-CoA carboxylase (ACC). Hematoxylin and Eosin (H & E) staining was used to detect the development of the fat body.

Results

Grayanotoxin I treatment significantly suppressed the survival rate, growth and development, and pupation of S. litura. RNA-Seq analysis revealed 285 DEGs after grayanotoxin I exposure, with over 16 genes related to lipid metabolism. These 285 DEGs were enriched in the categories of cuticle development, larvae longevity, fat digestion and absorption. Grayanotoxin I treatment also inhibited the levels of FFA, lipase, and HOAD in the hemolymph of S. litura.

Conclusion

The results of this study demonstrated that grayanotoxin I inhibited the growth and development of S. litura. The mechanisms might, at least partly, be related to the interference of lipid synthesis, lipolysis, and fat body development. These findings provide valuable insights into a new, environmentally-friendly plant-derived insecticide, grayanotoxin I, to control the spread of S. litura.

Usage of computational method for hemodynamic analysis of intracranial aneurysm rupture risk in different geometrical aspects

The importance of the parent vessel geometrical feature on the risk of cerebral aneurysm rupture is unavoidable. This study presents inclusive details on the hemodynamics of Internal carotid artery (ICA) aneurysms with different parent vessel mean diameters. Different aspects of blood hemodynamics are compared to find a reasonable connection between parent vessel mean diameter and significant hemodynamic factors of wall shear stress (WSS), oscillatory shear index (OSI), and pressure distribution. To access hemodynamic data, computational fluid dynamics is used to model the blood stream inside the cerebral aneurysms. A hemodynamic comparison of the selected cerebral aneurysm shows that the minimum WSS is reduced by about 71% as the parent vessel's mean diameter is increased from 3.18 to 4.48 mm.

RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance

Background

Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD.

Methods

Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA).

Results

The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells.

Conclusions

These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer

Ovarian cancer (OC) is the most lethal gynecological cancer in women. Studies had reported that immune-related lncRNAs signatures were valuable in predicting the survival and prognosis of patients with various cancers. In our study, the prognostic value of immune-related lncRNAs was investigated in OC patients from TCGA-RNA-seq cohort (n=378) and HG-U133_Plus_2 cohort (n=590), respectively. Pearson correlation analysis was implemented to screen the immune-related lncRNA and then univariate Cox regression analysis was performed to explore their prognostic value in OC patients. Five prognostic immune-related lncRNAs were identified as prognostic lncRNAs. Besides, they were inputted into a LASSO Cox regression to establish and validate an immune-related lncRNA prognostic signature in TCGA-RNA-Seq cohort and HG-U133_Plus_2 cohort, respectively. Based on the best cut-off value of risk score, patients were divided into high- and low-risk groups. Survival analysis suggested that patients in the high-risk group had a worse overall survival (OS) than those in the low-risk group in both cohorts. The association between clinicopathological feathers and risk score was then evaluated by using stratification analysis. Moreover, we constructed a nomogram based on risk score, age and stage, which had a strong ability to forecast the OS of the OC patients. The influence of risk score on immune infiltration and immunotherapy response were assessed and the results suggested that patients with high-risk score might recruit multiple immune cells and stromal cells, leading to facilitating immune surveillance evasive. Ultimately, we demonstrated that the risk model was associated with chemotherapy response of multiple antitumor drugs, especially for paclitaxel, metformin and veliparib, which are commonly used in treating OC patients. In conclusion, we constructed a novel immune-related lncRNA signature, which had a potential prognostic value for OC patients and might facilitate personalized counselling for immunotherapy and chemotherapy.

Identification of Monocyte-Associated Genes Related to the Instability of Atherosclerosis Plaque

Background. Atherosclerotic plaque instability is a common cause of stroke and ischemic infarction, and identification of monocyte-associated genes has become a prominent feature in cardiovascular research as a contributing/predictive marker. Methods. Whole genome sequencing data were downloaded from GSE159677, GSE41571, GSE120521, and GSE118481. Single-cell sequencing data analysis was conducted to cluster molecular subtypes of atherosclerotic plaques and identify specific genes. Differentially expressed genes (DEGs) between normal subjects and patients with unstable atheromatous plaques were screened. Weighted gene coexpression network analysis (WGCNA) was performed to find key module genes. In addition, GO and KEGG enrichment analyses explored potential biological signaling pathways to generate protein interaction (PPI) networks. GSEA and GSVA demonstrated activations in plaque instability subtypes. Results. 239 monocyte-associated genes were identified based on bulk and single-cell RNA-sequencing, followed by the recognition of 1221 atherosclerotic plaque-associated DEGs from the pooled matrix. GO and KEGG analyses suggested that DEGs might be related to inflammation response and the PI3K-Akt signaling pathway. Eight no-grey modules were obtained through WGCNA analysis, and the turquoise module has the highest correlation with unstable plaque ( $R^2=0.40$ ), which contained 1323 module genes. After fetching the intersecting genes, CXCL3, FPR1, GK, and LST1 were obtained that were significantly associated with plaque instability, which had an intense specific interaction. Monocyte-associated genes associated with atherosclerotic plaque instability have certain diagnostic significance and are generally overexpressed in this patient population. In addition, 11 overlapping coexpressed genes (CEG) might also activated multiple pathways regulating inflammatory responses, platelet activation, and hypoxia-inducible factors. GSVA showed that the corresponding pathways were significantly activated in high expression samples. Conclusions. Overexpression of CXCL3, GK, FPR1, and LST1 was advanced recognition and intervention factors for unstable plaques, which might become targets for atherosclerosis rupture prevention. We also analyzed the potential mechanisms of CEG from inflammatory and oxidative stress pathways.

Identification of potential key genes for immune infiltration in childhood asthma by data mining and biological validation

Asthma is the most common chronic condition among children; however, the underlying molecular mechanism remains unclear. Dysregulated immune response and different infiltration states of immune cells are critical for asthma pathogenesis. Here, three childhood asthma gene expression datasets were used to detect key genes, immune cells, and pathways involved in childhood asthma. From these datasets, 33 common differentially expressed genes (DEGs) were identified, which showed enrichment in the T helper 1 (Th1) and T helper 2 (Th2) cell differentiation pathway and the T helper 17 (Th17) cell differentiation pathway. Using the weighted gene co-expression network analysis (WGCNA), CD3D and CD3G were identified as key genes closely correlated with childhood asthma. Upregulation of CD3D and CD3G was further validated in bronchoalveolar lavage cells from childhood asthmatics with control individuals by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The immune cell infiltration analysis indicated that CD3D and CD3G were negatively correlated with increased resting mast cells and eosinophils, and highly correlated with several cell markers of Th1, Th2, and Th17 cells. In addition, we found that CD3D and CD3G were closely related to the Th1 and Th2 cell differentiation pathway and the Th17 cell differentiation pathway. Our results reveal the important roles of two key genes and immune infiltration in the pathogenesis of childhood asthma. Thus, this study provides a new perspective for exploring potential molecular targets for childhood asthma treatment.

YY1 affects the levels and function of fibulin‑5 in ox‑LDL‑treated vascular smooth muscle cells

Fibulin-5 is reportedly involved in the pathological process of atherosclerosis (AS) where low expression has been frequently observed in ruptured atherosclerotic plaques. The aim of the present study was to determine the effects of fibulin-5 on the responses of vascular smooth muscle cells (VSMC) to oxidized low-density lipoprotein (ox-LDL). The expression of fibulin-5 was studied in human aortic-VSMCs (HA-VSMCs) treated with ox-LDL. Fibulin-5 was first overexpressed by the transfection of Ov-Fibulin-5 plasmids in HA-VSMCs challenged with ox-LDL to investigate its influence on cell proliferation, migration and invasion using Cell Counting Kit-8, wound healing and Transwell assays. Yin Yang-1 (YY1) was bioinformatically predicted to bind to the promoter sites of fibulin-5, which was subsequently confirmed by dual-luciferase reporter gene assay. Fibulin-5 overexpression was able to suppress cell proliferation, invasion and migration, which was effectively reversed by YY1 silencing by the transfection of siRNA-Fibulin-5 plasmids which could induced fibulin-5 silencing. YY1 binding sites in the promoter region of fibulin-5 were identified and confirmed in vitro by chromatin immunoprecipitation assay and dual-luciferase reporter gene assay. The present results suggested that as a modulator of fibulin-5, YY1 alleviated ox-LDL-induced proliferation, invasion, migration and phenotypic transition from differentiated contractile phenotype to dedifferentiated phenotype in VSMCs. However, the mechanism underlying the YY1-mediated regulation of fibulin-5 expression needs to be confirmed further in vivo. Nevertheless, targeting fibulin-5 and YY1 could be further developed for AS therapy.

Enhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets

BACKGROUND AND AIMS

The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets.

METHODS

Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets.

RESULTS

We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge.

CONCLUSIONS

This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation.

Transcriptomic and Proteomic Profiling of Human Stable and Unstable Carotid Atherosclerotic Plaques

Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis-acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques.

Application of Bioinformatics Methods to Identify Key Genes and Functions in Chronic Pelvic Pain

Neuropathologic pain (NPP) occurs in most patients with chronic pelvic pain (CPP), and the unique physiological characteristics of visceral sensory neurons make the current analgesic effect of CPP patients not optimistic. Therefore, this study explored the possible biological characteristics of key genes in CPP through the bioinformatics method. CPP-related dataset GSE131619 was downloaded from Gene Expression Omnibus to investigate the differentially expressed genes (DEGs) between lumbar dorsal root ganglia (DRG) and sacral DRG, and the functional enrichment analysis was performed. A protein-protein interaction (PPI) network was constructed to search subnet modules of specific biological processes, and then, the genes in the subnet were enriched by single gene set analysis. A CPP mouse model was established, and the expression of key genes were identified by qPCR. The results showed that 127 upregulated DEGs and 103 downregulated DEGs are identified. Functional enrichment analysis showed that most of the genes involved in signal transduction were involved in the pathway of receptor interaction. A subnet module related to neural signal regulation was identified in PPI, including CHRNB4, CHRNA3, and CHRNB2. All three genes were associated with neurological or inflammatory activity and are downregulated in the sacral spinal cord of CPP mice. This study provided three key candidate genes for CPP: CHRNB4, CHRNA3, and CHRNB2, which may be involved in the occurrence and development of CPP, and provided a powerful molecular target for the clinical diagnosis and treatment of CPP.

A Network Pharmacology Approach to Investigate the Mechanism of Erjing Prescription in Type 2 Diabetes

Erjing prescription (EJP) was an ancient formula that was recorded in the General Medical Collection of Royal Benevolence of the Song Dynasty. It has been frequently used to treat type 2 diabetes mellitus (T2DM) in the long history of China. The formula consists of Lycium barbarum L. and Polygonatum sibiricum F. Delaroche with a ratio of 1 : 1. This study aimed to identify the potential effects and mechanisms of EJP treatment T2DM. The target proteins and possible pathways of EJP in T2DM treatment were investigated by the approach of network pharmacology and real-time PCR (RT-PCR). 99 diabetes-related proteins were regulated by 56 bioactive constituents in EJP in 26 signal pathways by Cytoscape determination. According to GO analysis, 606 genes entries have been enriched. The PPI network suggested that AKT1, EGF, EGFR, MAPK1, and GSK3β proteins were core genes. Among the 26 signal pathways, the PI3K-AKT signal pathway was tested by the RT-PCR. The expression level of PI3K p85, AKT1, GSK3β, and Myc mRNA of this pathway was regulated by EJP. The study based on network pharmacology and RT-PCR analysis revealed that the blood sugar level was regulated by EJP via regulating the PI3K-AKT signal pathway. Plenty of new treatment methods for T2DM using EJP were provided by network pharmacology analysis.

Gene Regulation Network of Prognostic Biomarker YAP1 in Human Cancers: An Integrated Bioinformatics Study

Background: Yes-associated protein 1 (YAP1) is the main downstream effector of the Hippo signaling pathway, which is involved in tumorigenesis. This study aimed to comprehensively understand the prognostic performances of YAP1 expression and its potential mechanism in pan-cancers by mining databases.

Methods: The YAP1 expression was evaluated by the Oncomine database and GEPIA tool. The clinical significance of YAP1 expression was analyzed by the UALCAN, GEPIA, and DriverDBv3 database. Then, the co-expressed genes with YAP1 were screened by the LinkedOmics, and annotated by the Metascape and DAVID database. Additionally, by the MitoMiner 4.0 v tool, the YAP1 co-expressed genes were screened to obtain the YAP1-associated mitochondrial genes that were further enriched by DAVID and analyzed by MCODE for the hub genes.

Results: YAP1 was differentially expressed in human cancers. Higher YAP1 expression was significantly associated with poorer overall survival and disease-free survival in adrenocortical carcinoma (ACC), brain Lower Grade Glioma (LGG), and pancreatic adenocarcinoma (PAAD). The LinkedOmics analysis revealed 923 co-expressed genes with YAP1 in adrenocortical carcinoma, LGG and PAAD. The 923 genes mainly participated in mitochondrial functions including mitochondrial gene expression and mitochondrial respiratory chain complex I assembly. Of the 923 genes, 112 mitochondrial genes were identified by MitoMiner 4.0 v and significantly enriched in oxidative phosphorylation. The MCODE analysis identified three hub genes including CHCHD1, IDH3G and NDUFAF5.

Conclusion: Our findings showed that the YAP1 overexpression could be a biomarker for poor prognosis in ACC, LGG and PAAD. Specifically, the YAP1 co-expression genes were mainly involved in the regulation of mitochondrial function especially in oxidative phosphorylation. Thus, our findings provided evidence of the carcinogenesis of YAP1 in human cancers and new insights into the mechanisms underlying the role of YAP1 in mitochondrial dysregulation.

RNA sequencing analysis of FGF2-responsive transcriptome in skin fibroblasts

Background

Fibroblast growth factor 2 (FGF2) is a highly pleiotropic cytokine with antifibrotic activity in wound healing. During the process of wound healing and fibrosis, fibroblasts are the key players. Although accumulating evidence has suggested the antagonistic effects of FGF2 in the activation process of fibroblasts, the mechanisms by which FGF2 hinders the fibroblast activation remains incompletely understood. This study aimed to identify the key genes and their regulatory networks in skin fibroblasts treated with FGF2.

Methods

RNA-seq was performed to identify the differentially expressed mRNA (DEGs) and lncRNA between FGF2-treated fibroblasts and control. DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the networks between mRNAs and lncRNAs were constructed by Pearson correlation analysis and the networkanalyst website. Finally, hub genes were validated by real time-PCR.

Results

Between FGF2-treated fibroblasts and control fibroblasts, a total of 1475 DEGs was obtained. These DEGs were mainly enriched in functions such as the ECM organization, cell adhesion, and cell migration. They were mainly involved in ECM-receptor interaction, PI3K-Akt signaling, and the Hippo pathway. The hub DEGs included COL3A1, COL4A1, LOX, PDGFA, TGFBI, and ITGA10. Subsequent real-time PCR, as well as bioinformatics analysis, consistently demonstrated that the expression of ITGA10 was significantly upregulated while the other five DEGs (COL3A1, COL4A1, LOX, PDGFA, TGFBI) were downregulated in FGF2-treated fibroblasts. Meanwhile, 213 differentially expressed lncRNAs were identified and three key lncRNAs (HOXA-AS2, H19, and SNHG8) were highlighted in FGF2-treated fibroblasts.

Conclusion

The current study comprehensively analyzed the FGF2-responsive transcriptional profile and provided candidate mechanisms that may account for FGF2-mediated wound healing.

Early molecular alterations in anterior cingulate cortex and hippocampus in a rodent model of neuropathic pain

Neuropathic pain is clinically associated with the development of mental disorders. However, the early molecular changes possibly related to the late-set depressive consequence of neuropathic pain were obscure so far. In this genome-wide study, we aimed to characterize the molecular mechanisms at the early and late stages of neuropathic pain. The genetic data from anterior cingulate cortex (ACC) tissues of neuropathic pain mice in Gene Expression Omnibus database were analyzed by weighted gene co-expression network analysis. Modules with clinical significance were respectively distinguished for mice at two and eight weeks after operation. The genes that co-expressed in modules from two postoperative time points were obtained, and annotated by gene ontology and pathway enrichment analyses. Moreover, the hub genes were identified from the protein-protein interaction network, and their expression levels were validated by molecular biology experiments. Overall, two modules were respectively found to be associated with the neuropathic pain mice with and without depressive consequence. A total of 20 genes co-expressed in both modules, and MAPK signaling pathway was the most significant pathway for these genes. Furtherly, Dusp1, c-Fos and Gadd45β were identified as the hub genes. At two weeks after sciatic nerve cuffing, Gadd45β was significantly downregulated at both mRNA and protein levels in ACC and hippocampus, while the significant upregulation was only observed in mRNA and protein levels for c-Fos in ACC. This study firstly compared the gene expression profiles between neuropathic pain animals with and without depressive-like behavior, and we suggested the early changes in the activities of MAPK signaling pathway, c-Fos and Gadd45β might be related to late-onset depressive behavior induced by peripheral nerve injury.

Identification of lncRNA-mRNA Regulatory Module to Explore the Pathogenesis and Prognosis of Melanoma

Skin cutaneous melanoma (SKCM) is an aggressive form of skin cancer that results in high mortality rate worldwide. It is vital to discover effective prognostic biomarkers and therapeutic targets for the treatment of melanoma. Long non-coding RNA (lncRNA) has been verified to play an essential role in the regulation of gene expression in diseases and tumors. Therefore, it is significant to explore the function of lncRNAs in the development and progression of SKCM. In this paper, a set of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were first screened out using 471 cutaneous melanoma samples and 813 normal skin samples. Gene Ontology and KEGG pathway enrichment analysis were performed to obtain the significant function annotations and pathways of DEmRNAs. We also ran survival analysis on both DElncRNAs and DEmRNAs to identify prognostic-related lncRNAs and mRNAs. Next, a set of hub genes derived from protein-protein interaction (PPI) network analysis and lncRNA target genes screened from starbase-ENCORI database were integrated to construct a lncRNA-mRNA regulatory module, which includes 6 lncRNAs 4 target mRNAs. We further checked the capacity of these lncRNA and mRNA in the diagnosis of melanoma, and found that single lncRNA can effectively distinguish tumor and normal tissue. Moreover, we ran CMap analysis to select a list of small molecule drugs for SKCM, such as EGFR inhibitor AG-490, growth factor receptor inhibitor GW-441756 and apoptosis stimulant betulinic-acid, which have shown therapeutic effect in the treatment of melanoma.