Transcriptome Microarray Research Articles

Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus

BackgroundOsteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.MethodWe analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.ResultAfter quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.ConclusionThis research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

Screening of differentially expressed RNAs and identifying a ceRNA axis during cadmium-induced oxidative damage in pancreatic β cells

Cadmium, a common metal pollutant, has been demonstrated to induce type 2 diabetes by disrupting pancreatic β cells function. In this study, transcriptome microarray was utilized to identify differential gene expression in oxidative damage to pancreatic β cells following cadmium exposure. The results indicated that a series of mRNAs, LncRNAs, and miRNAs were altered. Of the differentially expressed miRNAs, miR-29a-3p exhibited the most pronounced alteration, with an 11.62-fold increase relative to the control group. Following this, the target gene of miR-29a-3p was identified as Col3a1 through three databases (miRDB, miRTarbase and Tarbase), which demonstrated a decrease across the transcriptome microarray. The upstream target gene of miR-29a-3p was identified as NONMMUT036805, with decreased expression observed in the microarray. Finally, the expression trend of NONMMUT036805/miR-29a-3p/Col3a1 was reversed following NAC pretreatment. This was accompanied by a reduction in oxidative damage indicators, MDA/ROS/GSH-Px appeared to be negatively affected to varying degrees. In conclusion, this study has demonstrated that multiple RNAs are altered during cadmium exposure-induced oxidative damage in pancreatic β cells. The NONMMUT036805/miR-29a-3p/Col3a1 axis has been shown to be involved in this process, which provides a foundation for the identification of potential targets for cadmium toxicity intervention.

Ferroptosis-Associated Extracellular Matrix Remodeling in Radiation-Induced Lung Fibrosis Progression.

Background: Radiation-induced lung fibrosis (RILF) is a life-threatening complication of thoracic radiotherapy. Ferroptosis, a recently discovered type of cell death, is believed to contribute to RILF, though the associated mechanisms are unknown. This study aimed to investigate the potential mechanism of ferroptosis in RILF and examine the contribution of different cell types to ferroptosis during RILF progression. Methods: Histopathological changes in RILF lung tissue were assessed through H&E and Masson staining. IHC staining investigated ferroptosis markers (GPX4, ACSL4, NCOA4). Ferroptosis-related genes (FRG) and pathway scores were derived from RILF transcriptome microarray data. The sc-RNAseq analysis detected FRG score dynamics across cell types, validated by IF staining for PDGFR-α and ACSL4. Results: ACSL4 and NCOA4 protein levels were significantly higher and GPX4 lower in IR than control. FRG scores were positively correlated with fibrosis-related pathway scores in the RILF transcriptome data. FRG and ECM scores were concurrently upregulated in myofibroblasts. Enhanced co-staining of PDGFR-α and ACSL4 were observed in the fibrotic areas of RILF lungs. Conclusions: Our research indicated that in RILF, fibroblasts undergoing ferroptosis may release increased levels of ECM, potentially accelerating the progression of lung fibrosis. This finding presents ferroptosis as a potential therapeutic target in RILF.

Endotypes of severe neutrophilic and eosinophilic asthma from multi-omics integration of U-BIOPRED sputum samples.

Clustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development. To determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma. We analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics. Five stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy. Multi-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes. Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22.

Alteration of N6-methyladenosine modification profiles in the neutrophilic RNAs following ischemic stroke

BackgroundN6-methyladenosine (m6A) is one of the most extensive RNA methylation modifications in eukaryotes and participates in the pathogenesis of numerous diseases including ischemic stroke. Peripheral blood neutrophils are forerunners after ischemic brain injury and exert crucial functions. This study aims to explore the transcriptional profiles of m6A modification in neutrophils of patients with ischemic stroke. ResultsWe found that the expression levels of m6A regulators FTO and YTHDC1 were notably decreased in the neutrophils following ischemic stroke, and FTO expression was negatively correlated with neutrophil counts and neutrophil-to-lymphocyte ratio (NLR). The m6A mRNA&lncRNA epigenetic transcriptome microarray identified 416 significantly upregulated and 500 significantly downregulated mRNA peaks in neutrophils of ischemic stroke patients. Moreover, 48 mRNAs and 18 lncRNAs were hypermethylated, and 115 mRNAs and 29 lncRNAs were hypomethylated after cerebral ischemia. Gene ontology (GO) analysis identified that these m6A-modified mRNAs were primarily enriched in calcium ion transport, long-term synaptic potentiation, and base-excision repair. The signaling pathways involved were EGFR tyrosine kinase inhibitor resistance, ErbB, and base excision repair signaling pathway. MeRIP-qPCR validation results showed that NRG1 and GDPD1 were significantly hypermethylated, and LIG1, CHRND, lncRNA RP11-442J17.2, and lncRNA RP11-600P1.2 were significantly hypomethylated after cerebral ischemia. Moreover, the expression levels of major m6A regulators Mettl3, Fto, Ythdf1, and Ythdf3 were obviously declined in the brain and leukocytes of post-stroke mouse models. ConclusionThis study explored the RNA m6A methylation pattern in the neutrophils of ischemic stroke patients, indicating that it is an intervention target of epigenetic regulation in ischemic stroke.

M6A modification of lncRNA in middle ear cholesteatoma.

Middle ear cholesteatoma is a non-tumorous condition that typically leads to hearing loss, bone destruction, and other severe complications. Despite surgery being the primary treatment, the recurrence rate remains high. Therefore, exploring the molecular mechanisms underlying cholesteatoma is crucial for discovering new therapeutic approaches. This study aims to explore the involvement of N6-methyladenosine (m6A) methylation in long non-coding RNAs (lncRNAs) in the biological functions and related pathways of middle ear cholesteatoma. The m6A modification patterns of lncRNA in middle ear cholesteatoma tissues (n=5) and normal post-auricular skin tissues (n=5) were analyzed using an lncRNA m6A transcriptome microarray. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to identify potential biological functions and signaling pathways involved in the pathogenesis of middle ear cholesteatoma. Methylated RNA immunoprecipitation (MeRIP)-PCR was used to validate the m6A modifications in cholesteatoma and normal skin tissues. Compared with normal skin tissues, 1 525 lncRNAs were differentially methylated in middle ear cholesteatoma tissues, with 1 048 showing hypermethylation and 477 showing hypomethylation [fold change (FC)≥3 or <1/3, P<0.05]. GO enrichment analysis indicated that hypermethylated lncRNAs were involved in protein phosphatase inhibitor activity, neuron-neuron synapse, and regulation of α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor activity. Hypomethylated lncRNAs were associated with mRNA methyltransferase activity, secretory granule membrane, and mRNA methylation. KEGG analysis revealed that hypermethylated lncRNAs were mainly associated with 5 pathways: the Hedgehog signaling pathway, viral protein interaction with cytokines and cytokine receptors, mitogen-activated protein kinase (MAPK) signaling pathway, cytokine-cytokine receptor interaction, and adrenergic signaling in cardiomyocytes. Hypomethylated lncRNAs were mainly involved in 4 pathways: Renal cell carcinoma, tumor necrosis factor signaling pathway, transcriptional misregulation in cancer, and cytokine-cytokine receptor interaction. Additionally, MeRIP-PCR confirmed the changes in m6A methylation levels in NR_033339, NR_122111, NR_130744, and NR_026800, consistent with microarray analysis. Real-time PCR also confirmed the significant upregulation of MAPK1 and NF-κB, key genes in the MAPK signaling pathway. This study reveals the m6A modification patterns of lncRNAs in middle ear cholesteatoma, suggests a direction for further research into the role of lncRNA m6A modification in the etiology of cholesteatoma. The findings provide potential therapeutic targets for the treatment of middle ear cholesteatoma.

TNF-α can promote membrane invasion by activating the MAPK/MMP9 signaling pathway through autocrine in bone-invasive pituitary adenoma.

A bone-invasive pituitary adenoma exhibits aggressive behavior, leading to a worse prognosis. We have found that TNF-α promotes bone invasion by facilitating the differentiation of osteoclasts, however, before bone-invasive pituitary adenoma invades bone tissue, it needs to penetrate the dura mater, and this mechanism is not yet clear. We performed transcriptome microarrays on specimens of bone-invasive pituitary adenomas (BIPAs) and noninvasive pituitary adenomas (NIPAs) and conducted differential expressed gene analysis and enrichment analysis. We altered the expression of TNF-α through plasmids, then validated the effects of TNF-α on GH3 cells and verified the efficacy of the TNF-α inhibitor SPD304. Finally, the effects of TNF-α were validated in invivo experiments. Pathway act work showed that the MAPK pathway was significantly implicated in the pathway network. The expression of TNF-α, MMP9, and p-p38 is higher in BIPAs than in NIPAs. Overexpression of TNF-α elevated the expression of MAPK pathway proteins and MMP9 in GH3 cells, as well as promoted proliferation, migration, and invasion of GH3 cells. Flow cytometry indicated that TNF-α overexpression increased the G2 phase ratio in GH3 cells and inhibited apoptosis. The expression of MMP9 was reduced after blocking the P38 MAPK pathway; overexpression of MMP9 promoted invasion of GH3 cells. Invivo experiments confirm that the TNF-α overexpression group has larger tumor volumes. SPD304 was able to suppress the effects caused by TNF-α overexpression. Bone-invasive pituitary adenoma secretes higher levels of TNF-α, which then acts on itself in an autocrine manner, activating the MAPK pathway and promoting the expression of MMP9, thereby accelerating the membrane invasion process. SPD304 significantly inhibits the effect of TNF-α and may be applied in the clinical treatment of bone-invasive pituitary adenoma.

CD302 predicts achievement of deep molecular response in patients with chronic myeloid leukemia treated with imatinib

AbstractAchieving a deep molecular response (DMR) is a prerequisite for treatment-free remission in chronic myeloid leukemia (CML) and a key milestone for patients with CML. This study identified patients unlikely to achieve a 5-year DMR through differential expression of cluster of differentiation (CD) genes, and clinical variables at diagnosis. Peripheral blood samples (n = 131) from patients treated with imatinib or nilotinib underwent transcriptomic microarray profiling. The decision-tree analysis delineated 2 distinct poor-risk (PR) cohorts, distinguished by high 3-month BCR::ABL1% (PR-1), or high CD302 expression (PR-2). The 5-years DMR achievement rate was significantly lower in both PR groups than in the good-risk (GR) group in patients treated frontline with imatinib (0% vs 27% vs 83%; P < .0001) or nilotinib (PR-2 vs GR, 17% vs 83%; P = .02). Gene-set enrichment analysis revealed reduced expression of cell cycle–related genes in PR-2, as well as increased metabolism and STAT3 pathway genes, which has previously been linked to leukemic cell persistence and resistance to tyrosine kinase inhibitors. Moreover, PR-2 had a higher frequency of CD34+CD302+ and CD14+CD302+ cells than GR samples. Strategies aimed at targeting STAT3 and/or metabolic pathways associated with high CD302 may provide novel therapeutic approaches that could help improve treatment outcomes and eradicate residual disease.

ATPR induces acute promyelocytic leukemia cells differentiation and cycle arrest via the lncRNA CONCR/DDX11/PML-RARα signaling axis

Acute promyelocytic leukemia (APL) is a type of acute myeloid leukemia (AML) with a high mortality rate, and the production of PML-RARα fusion protein is the cause of its pathogenesis. Our group has synthesized a novel compound, 4-amino-2-trifluoromethyl-phenyl retinate (ATPR), by structural modification of All-trans retinoic acid (ATRA), which has strong cell differentiation-inducing effects and inhibits the expression of PML-RARα. In this study, acute promyelocytic leukemia NB4 cells before and after ATPR induction were analyzed by whole transcriptome microarray, and the expression of lncRNA CONCR was found to be significantly downregulated. The role of CONCR in ATPR-induced cell differentiation and cycle arrest was explored through overexpression and silencing of CONCR. And then the database was used to predict that CONCR may bind to DEAD/H-Box Helicase 11 (DDX11) protein to further explore the role of CONCR binding to DDX11. The results showed that ATPR could reduce the expression of CONCR, and overexpression of CONCR could reverse the ATPR-induced cell differentiation and cycle blocking effect, and conversely silencing of CONCR could promote this effect. RNA immunoprecipitation (RIP) experiments showed that CONCR could bind to DDX11, the protein expression levels of DDX11 and PML-RARα were elevated after overexpression of CONCR. These results suggest that ATPR can regulate the expression of DDX11 through CONCR to affect the expression of PML-RARα fusion protein, which in turn induces the differentiation and maturation of APL cells.

Abstract 575: Identification of SORL1 as a key regulator of chemoresistance in ovarian cancer

Abstract This study aimed to understand the molecular mechanism of platinum chemoresistance in recurrent ovarian tumors with a focus on the SORL1-regulated pathways. SORL1 is an intracellular sorting receptor that binds to HER2 in breast cancer; this promotes HER2 recycling to the cell surface, which ultimately impacts the progression and treatment of breast cancer. The role of SORL1 in ovarian cancer has not been extensively studied. Method: RNA was extracted from 15 pairs of matched primary and recurrent high grade serous ovarian tumors collected from patients. Human transcriptomic microarray was used to identify the differentially expressed genes. The identified genes were validated by RT-QPCR and western blot in five ovarian cancer cell lines that were treated or untreated with carboplatin. To study the effects of identified target gene SORL1, overexpression and knockdown in ovarian cancer cell lines were established using SORL1 plasmid and shRNA. Proliferation and response to carboplatin were analyzed using celltiter Glo and caspase-3/7 activity assays respectively. EGFR and FGFR4 were identified as the interacting proteins of SORL1 in ovarian cancer cells through FGF1 and EGF1 treatment and co-immunoprecipitation. A proximity ligation assay was performed to validate their interactions. Finally, a xenograft mouse model was used to compare the tumor forming abilities and the response to carboplatin of SORL1-knockdown ovarian cancer cells and the control cancer cells in vivo. Protein expression of SORL1, EGFR, and FGFR4 in the collected tumors was determined via western blot. Result: Transcriptomic analysis of matched human primary and recurrent ovarian tumors identified SORL1 as an upregulated gene in recurrent tumors compared to primary samples. SORL1 expression was also upregulated in ovarian cancer cells surviving carboplatin treatment. Proliferation assays demonstrated that SORL1-overexpressing and knockdown cell lines had increased and inhibited proliferative capabilities respectively. Caspase-3 activity assays showed that SORL1-overexpressing and knockdown cell lines had reduced and increased sensitivity to carboplatin treatment respectively. SORL1 was found to bind to and promote the expression of EGFR and FGFR4. When injected subcutaneously into nude mice, SORL1-knockdown cells had reduced tumor forming capabilities and increased sensitivity to carboplatin. SORL1-knockdown caused the tumors to express lower levels of SORL1, EGFR, and FGFR4 proteins in comparison with the control tumors. Conclusion: This study demonstrates that SORL1 regulates the EGFR and FGF4 pathways to promote the growth and carboplatin resistance of ovarian cancer cells. Targeting this pathway has potential to aid in the treatment of platinum-resistant ovarian cancer. Citation Format: Miranda Mansolf, Ziyan Jian, Fangfang Bi, Tobias M. Hartwich, Yang Yang-Hartwich. Identification of SORL1 as a key regulator of chemoresistance in ovarian cancer [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 575.

Abstract 5651: Personalized transcriptomic profiling for advanced prostate cancer: Guiding second-generation hormonal drug selection

Abstract Introduction: Second-generation hormonal drugs have demonstrated significant efficacy in extending the survival of patients with advanced prostate cancer. These drugs operate through two distinct molecular mechanisms: inhibition of androgen biosynthesis and blockade of the androgen receptor. However, due to concerns of side effects, concurrent usage of multiple drugs is not recommended. A notable challenge is the eventual development of drug resistance, rendering all second-generation hormonal therapies ineffective. Currently, there is a lack of guidelines for helping patients choose the most suitable drug. In the context of pharmacogenomics, genetic differences can influence drug susceptibility and efficacy, with variations in genomic sequences and regulatory mechanisms impacting drug response at the transcriptional and translational levels. Considered the rapid processing capabilities of Affymetrix transcriptomic microarrays, we hypothesized that distinct gene signatures in patients who respond well or poorly to second-generation hormonal drugs could be identified and could act as a companion diagnostic tool. Methods: We enrolled 180 advanced prostate cancer patients, who fulfilled Taiwan national health insurance criteria of using second-generation hormonal drugs, from seven medical centers or regional hospitals in Taiwan at 3 time points: prior to drug administration, 3 months after treatment started and drug resistance developed. The RNA expression data and clinical parameters were analyzed, and classification models were built using IPA and R. Good or poor responders were defined by 3-month prostate-specific antigen (PSA) lowered by 90 percent. Results:: Differential expression and enrichment analyses post-treatment highlighted the activation of NF-kappa B signaling and various immune cell pathways. Notably, pathways related to primary immunodeficiency and IL-17 became prominent following the development of drug resistance. At the initial stages, distinct alterations in cell cycle pathways, particularly G1/S and G2/M, were observed between good and poor responders. This was elucidated through principal component analysis and subsequent dbscan clustering. To further distinguish between these responder groups, we utilized an integrative approach for feature selection, combining support vector machine, random forest classifier, and lasso regression. Despite the innovative approach, the model's error rate stood at approximately 15%, attributed mainly to the limited number of cases. Conclusion: Our study highlights the potential of using transcriptomic analysis to predict responses to second-generation hormonal drugs in advanced prostate cancer, paving the way for personalized treatment strategies. However, the need for larger cohort studies is evident to refine these predictive models and enhance their accuracy. Citation Format: Li-Hsin Chang, Hao-Han Chang, Xin-Yi Lin, Shu-Chi Wang, Chih-Pin Chuu, Deng-Neng Chen, Shu-Pin Huang, Chia-Yang Li. Personalized transcriptomic profiling for advanced prostate cancer: Guiding second-generation hormonal drug selection [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 5651.

Prevention of Metastasis by Suppression of Stemness Genes Using a Combination of microRNAs.

We propose an original strategy for metastasis prevention using a combination of three microRNAs that blocks the dedifferentiation of cancer cells in a metastatic niche owing to the downregulation of stemness genes. Transcriptome microarray analysis was applied to identify the effects of a mixture of microRNAs on the pattern of differentially expressed genes in human breast cancer cell lines. Treatment of differentiated CD44- cancer cells with the microRNA mixture inhibited their ability to form mammospheres in vitro. The combination of these three microRNAs encapsulated into lipid nanoparticles prevented lung metastasis in a mouse model of spontaneous metastasis. The mixture of three microRNAs (miR-195-5p/miR-520a/miR-630) holds promise for the development of an antimetastatic therapeutic that blocks tumor cell dedifferentiation, which occurs at secondary tumor sites and determines the transition of micrometastases to macrometastases.

Identification of novel molecules and pathways associated with fascin actin‑bundling protein 1 in laryngeal squamous cell carcinoma through comprehensive transcriptome analysis.

Laryngeal squamous cell carcinoma (LSCC) is a common malignant tumor with a poor prognosis. Fascin actin‑bundling protein 1 (FSCN1) has been reported to play a crucial role in the development and progression of LSCC; however, the underlying molecular mechanisms remain unknown. Herein, a whole transcriptome microarray analysis was performed to screen for differentially expressed genes (DEGs) in cells in which FSCN1 was knocked down. Atotal of 462 up and 601 downregulated mRNA transcripts were identified. Functional annotation analysis revealed that these DEGs were involved in multiple biological functions, such as transcriptional regulation, response to radiation, focal adhesion, extracellular matrix‑receptor interaction, steroid biosynthesis and others. Through co‑expression and protein‑protein interaction analysis, FSCN1 was linked to novel functions, including defense response to virus and steroid biosynthesis. Furthermore, crosstalk analysis with FSCN1‑interacting proteins revealed seven DEGs, identified as FSCN1‑interacting partners, in LSCC cells, three of which were selected for further validation. Co‑immunoprecipitation validation confirmed that FSCN1 interacted with prostaglandin reductase 1 and 24‑dehydrocholesterol reductase (DHCR24). Of note, DHCR24 is a key enzyme involved in cholesterol biosynthesis, and its overexpression promotes the proliferation and migration of LSCC cells. These findings suggest that DHCR24 is a novel molecule associated with FSCN1 in LSCC, and that the FSCN1‑DHCR24 interaction may promote LSCC progression by regulating cholesterol metabolism‑related signaling pathways.

Network Analysis Performed on Transcriptomes of Parkinson's Disease Patients Reveals Dysfunction in Protein Translation.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra region of the brain. The hallmark pathological feature of PD is the accumulation of misfolded proteins, leading to the formation of intracellular aggregates known as Lewy bodies. Recent data evidenced how disruptions in protein synthesis, folding, and degradation are events commonly observed in PD and may provide information on the molecular background behind its etiopathogenesis. In the present study, we used a publicly available transcriptomic microarray dataset of peripheral blood of PD patients and healthy controls (GSE6613) to investigate the potential dysregulation of elements involved in proteostasis-related processes at the transcriptomic level. Our bioinformatics analysis revealed 375 differentially expressed genes (DEGs), of which 281 were down-regulated and 94 were up-regulated. Network analysis performed on the observed DEGs highlighted a cluster of 36 elements mainly involved in the protein synthesis processes. Different enriched ontologies were related to translation initiation and regulation, ribosome structure, and ribosome components nuclear export. Overall, this data consistently points to a generalized impairment of the translational machinery and proteostasis. Dysregulation of these mechanics has been associated with PD pathogenesis. Understanding the precise regulation of such processes may shed light on the molecular mechanisms of PD and provide potential data for early diagnosis.

HOCl sensitivity associates with a reduced p53 transcriptional network and calreticulin expression in 25 human cancer cell lines

Reactive oxygen species (ROS) play roles in physiological processes and pathological conditions. Higher ROS levels induce oxidative distress and cytotoxic responses, such as chronic inflammatory conditions and cancer. While the cellular responses of various cell types to cytotoxic pro-oxidative conditions have been well studied in the past decades, much less is known about the cellular gene and expression profiles that are a priori associated with subsequent cellular demise to oxidative stress. To this end, we used 25 human cancer cell lines of different origins and established the inhibitory concentration (IC25) of hypochlorous acid (HOCl), an oxidant readily produced by neutrophils frequently present in many inflamed tissues, including cancer. The HOCl sensitivity varied throughout the 25 cell lines investigated, showing a more than 5-fold difference between the most sensitive and resistant types. In parallel, we investigated untreated cells and their basal gene expression using transcriptomic microarray and performed correlation analyses to HOCl IC25 values of all cell lines. Transcriptomic analyses and functional classification of significant correlating genes revealed reduced expression of tumor protein p53 signaling network members, including BAX, CDKN1A (p21), and BTG2, as well as the p53 gene (TP53) itself to associate with cell line sensitivity to HOCl toxicity. Further, baseline surface membrane expression analysis of 33 inflammation- and redox-related molecules identified nitric oxide (NO) synthase 2 and the ER-stress-associated chaperone calreticulin to correlate significantly with HOCl resistance. We identified targets associated with HOCl sensitivity. Nevertheless, further studies are needed to map gene and protein expression patterns associated with oxidative stress-induced cytotoxicity.

Bioinformatics Analysis Reveals a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma.

Background: Esophageal squamous cell carcinoma (ESCC), a gastrointestinal cancer, is associated with poor prognosis. Prognostic models predict the likelihood of disease progression and are important for the management of patients with ESCC. The objective of this study was to develop a prognostic model for ESCC using bioinformatics analysis. Methods: Two transcriptome microarray Gene Expression Omnibus ESCC datasets (GSE53624 and GSE53622) were analyzed using bioinformatics methods. Differentially expressed genes (DEGs) were identified using the R package limma, and genes associated with survival outcomes in both datasets were identified by Kaplan-Meier analysis. Genes with diagnostic or prognostic value were selected for further analysis, and hazard ratios and their relationship with pathological TNM (pTNM) staging were investigated using univariate and multivariate Cox analysis. After selecting the independent factors from pTNM staging, Cox analysis and nomogram plotting were performed. The ability of the model to stratify risk and predict survival was evaluated and compared with the pTNM staging system to determine its potential clinical value. Key genes were analyzed by immunohistochemistry and RT-PCR. Results: Four candidate genes (B3GNT3, MACC1, NELL2, and USH1G) with prognostic value were identified from the two transcriptome microarray datasets. Age, pTNM stage, and B3GNT3, MACC1, and NELL2 were identified as independent factors associated with survival in the multivariate Cox analysis and used to establish a prognostic model. The model demonstrated significantly higher accuracy in predicting 3-year survival than the pTNM staging system and was useful for further risk stratification in patients with ESCC. B3GNT3 was significantly downregulated in ESCC tumor tissues and negatively associated with lymph node metastasis. Bioinformatics analysis indicated that B3GNT3 may play a role in immune regulation by regulating M2 macrophages. Conclusion: This study developed a new prognostic model for ESCC and identified B3GNT3 as a potential biomarker negatively associated with lymph node metastasis, which warrants further validation.

METTL16 participates in haemoglobin H disease through m6A modification.

Haemoglobin H (HbH) disease is caused by a disorder of α-globin synthesis, and it results in a wide range of clinical symptoms. M6A methylation modification may be one of the mechanisms of heterogeneity. Therefore, this article explored the role of methyltransferase like 16 (METTL16) in HbH disease. The results of epigenetic transcriptome microarray were analysed and verified through bioinformatic methods and qRT-PCR, respectively. The overexpression or knock down of METTL16 in K562 cells was examined to determine its role in reactive oxygen species (ROS), cell cycle processes or iron overload. YTH domain family protein 3 (YTHDF3) was knocked down in K562 cells and K562 cells overexpressing METTL16 via siRNA to investigate its function. In addition, haemoglobin expression was detected through benzidine staining. qRT-PCR, WB, methylated RNA Immunoprecipitation (MeRIP) and (RNA Immunoprecipitation) RIP experiments were conducted to explore the mechanism of intermolecular interaction. METTL16, YTHDF3 and solute carrier family 5 member 3 (SLC5A3) mRNA and the methylation level of SLC5A3 mRNA were downregulated in HbH patients. Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) mRNA expression was negatively correlated with HGB content among patients with HbH-CS disease. Overexpression of METTL16 increased ROS and intracellular iron contents in K562 cells, changed the K562 cell cycle, reduced hemin-induced haemoglobin synthesis, increased the expressions of SLC5A3 and HBG and increased SLC5A3 mRNA methylation levels. Knockdown of METTL16 reduced ROS and intracellular iron contents in K562 cells. Hemin treatment of K562 cells for more than 14 days reduced the protein expressions of METTL16 and SLC5A3 and SLC5A3 mRNA methylation levels. Knockdown of YTHDF3 rescued the intracellular iron content changes induced by the overexpression of METTL16. The RIP experiment revealed that SLC5A3 mRNA can be enriched by METTL16 antibody. METTL16 may affect the expression of SLC5A3 by changing its m6A modification level and regulating ROS synthesis, intracellular iron and cycle of red blood cells. Moreover, METTL16 possibly affects the expression of haemoglobin through IGF2BP3, which regulates the clinical phenotype of HbH disease.

A circular network of adenosine-mediated mitochondrial dysfunction as coregulators of acute myocardial infarction.

This study aims to explore the molecular mechanisms and associated pathways of myocardial infarction (MI). We employed a variety of analytical methods, including Mendelian Randomization (MR) analysis, transcriptome microarray data analysis, gene function and pathway enrichment analysis, untargeted metabolomic mass spectrometry analysis, and gene-metabolite interaction network analysis. The MR analysis results revealed a significant impact of mitochondrial DNA copy number on MI and coronary artery bypass grafting. Transcriptome analysis unveiled numerous differentially expressed genes associated with myocardial ischemia, with enrichment observed in cardiac function and energy metabolism pathways. Metabolomic analysis indicated a significant downregulation of mitochondrial regulation pathways in ischemic myocardium. T500 metabolite quantification analysis identified 90 differential metabolites between MI and Sham groups, emphasizing changes in metabolites associated with energy metabolism. Gene-metabolite interaction network analysis revealed the significant roles of key regulatory molecules such as HIF1A, adenosine, TBK1, ATP, NRAS, and EIF2AK3, in the pathogenesis of myocardial ischemia. In summary, this study provides important insights into the molecular mechanisms of MI and highlights interactions at multiple molecular levels, contributing to the establishment of new theoretical foundations for the diagnosis and treatment of MI.

Exosomal LncRNA TM7SF3-AU1 Aggravates White Matter Injury via MiR-702-3p/SARM1 Signaling After Subarachnoid Hemorrhage in Rats.

Subarachnoid hemorrhage (SAH) is a devastating disease associated with a high mortality and morbidity. Exosomes have been considered as a potential therapeutic target for SAH. However, the effect of exosomes in SAH remains to be elucidated. In this study, we focused on investigating the effect of plasma exosomal lncRNA TM7SF3-AU1 in white matter injury after SAH. The SAH model was established by means of endovascular perforation. Exosomes were extracted from rat plasma samples. The expression of RNAs in the exosomes was detected by the transcriptomic microarray. Differentially expressed circRNA, lncRNA, and mRNA were obtained. The ceRNA network showed that the lncRNA TM7SF3-AU1 and miR-702-3p were closely associated with SARM1. Knocking down TM7SF3-AU1 promoted the expression of miR-702-3p and suppressed the expression of SARM1, and knocking down TM7SF3-AU1 alsoattenuated white matter injury after SAH. In addition, knocking down TM7SF3-AU1 improved the neurological deficits in locomotion, anxiety, learning, memory, and electrophysiological activity after SAH. Mechanistically, TM7SF3-AU1 was able to absorb miR-702-3p, which directly bind the SARM1 mRNA. Furthermore, the white matter injury attenuated by knockdown of TM7SF3-AU1 was partially reversed by the miR-702-3p antagomir in SAH rats. Taken together, this study showed that TM7SF3-AU1 acts as a sponge for miR-702-3p, reducing the inhibitory effect of miR-702-3p on SARM1, resulting in increased SARM1 expression and thus leading to white matter injury after SAH. Our study provides new insights into exosome-associated white matter injury. It also highlights TM7SF3-AU1 as a potential therapeutic target for white matter injury after SAH.

Identification of hub genes based on integrated analysis of single-cell and microarray transcriptome in patients with pulmonary arterial hypertension

BackgroundPulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution.MethodsSingle-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database (GSE210248) was included and analyzed comprehensively. Additionally, microarray transcriptome data including 15 lung tissue from PAH patients and 11 normal samples (GSE113439) was also obtained. Seurat R package was applied to process scRNA-seq data. Uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification, and the SingleR package was performed for cell annotation. FindAllMarkers analysis and ClusterProfiler package were applied to identify differentially expressed genes (DEGs) for each cluster in GSE210248 and GSE113439, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) were used for functional enrichment analysis of DEGs. Microenvironment Cell Populations counter (MCP counter) was applied to evaluate the immune cell infiltration. STRING was used to construct a protein-protein interaction (PPI) network of DEGs, followed by hub genes selection through Cytoscape software and Veen Diagram.ResultsNineteen thousand five hundred seventy-six cells from 3 donors and 21,896 cells from 3 PAH patients remained for subsequent analysis after filtration. A total of 42 cell clusters were identified through UMAP and annotated by the SingleR package. 10 cell clusters with the top 10 cell amounts were selected for consequent analysis. Compared with the control group, the proportion of adipocytes and fibroblasts was significantly reduced, while CD8+ T cells and macrophages were notably increased in the PAH group. MCP counter revealed decreased distribution of CD8+ T cells, cytotoxic lymphocytes, and NK cells, as well as increased infiltration of monocytic lineage in PAH lung samples. Among 997 DEGs in GSE113439, module 1 with 68 critical genes was screened out through the MCODE plug-in in Cytoscape software. The top 20 DEGs in each cluster of GSE210248 were filtered out by the Cytohubba plug-in using the MCC method. Eventually, WDR43 and GNL2 were found significantly increased in PAH and identified as the hub genes after overlapping these DEGs from GSE210248 and GSE113439.ConclusionWDR43 and GNL2 might provide novel insight into revealing the new molecular mechanisms and potential therapeutic targets for PAH.