Integrated Bioinformatics Analysis Research Articles

Identification and Validation of SLC9A2 as A Potential Tumor Suppressor in Colorectal Cancer: Integrating Bioinformatics Analysis with Experimental Confirmation.

To uncover the mechanisms underlying the development of colorectal cancer (CRC), we applied bioinformatic analyses to identify key genes and experimentally validated their possible roles in CRC onset and progression. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis on differentially expressed genes (DEGs), constructed a protein-protein interaction (PPI) network to find the top 10 hub genes, and analyzed their expression in colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ). We also studied the correlation between these genes and immune cell infiltration and prognosis and validated the expression of SLC9A2 in CRC tissues and cell lines using qRT-PCR and Western blotting. Functional experiments were conducted in vitro to investigate the effects of SLC9A2 on tumor growth and metastasis. We found 130 DEGs, with 45 up-regulated and 85 down-regulated in CRC. GO analysis indicated that these DEGs were primarily enriched in functions related to the regulation of cellular pH, zymogen granules, and transmembrane transporter activity. KEGG pathway analysis revealed that the DEGs played pivotal roles in pancreatic secretion, rheumatoid arthritis, and the IL-17 signaling pathway. We identified 10 hub genes: CXCL1, SLC26A3, CXCL2, MMP7, MMP1, SLC9A2, SLC4A4, CLCA1, CLCA4, and ZG16. GO enrichment analysis showed that these hub genes were predominantly involved in the positive regulation of transcription. Gene expression analysis revealed that CXCL1, CXCL2, MMP1, and MMP7 were highly expressed in CRC, whereas CLCA1, CLCA4, SLC4A4, SLC9A2, SLC26A3, and ZG16 were expressed at lower levels. Survival analysis revealed that 5 key genes were significantly associated with the prognosis of CRC. Both mRNA and protein expression levels of SLC9A2 were markedly reduced in CRC tissues and cell lines. Importantly, SLC9A2 overexpression in SW480 cells led to a notable inhibition of cell proliferation, migration, and invasion. Western blotting analysis revealed that the expression levels of phosphorylated ERK (p-ERK) and phosphorylated JNK (p-JNK) proteins were significantly increased, whereas there were no significant changes in the expression levels of ERK and JNK following SLC9A2 overexpression. Correlation analysis indicated a potential link between SLC9A2 expression and the MAPK signaling pathway. Our study suggests that SLC9A2 acts as a tumor suppressor through the MAPK pathway and could be a potential target for CRC diagnosis and therapy.

Integrative Bioinformatics Approaches to Uncover Hub Genes and Pathways Involved in Cardiovascular Diseases.

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.

Exploring shared molecular signatures and regulatory mechanisms in nonalcoholic steatohepatitis and inflammatory bowel disease using integrative bioinformatics analysis.

The co-existence of inflammatory bowel disease (IBD) and non-alcoholic steatohepatitis (NASH) has raised interest in identifying shared molecular mechanisms and potential therapeutic targets. However, the relationship between these two diseases remains unclear and effective medical treatments are still lacking. Through the bioinformatics analysis in this study, 116 shared differentially expressed genes (SDEGs) were identified between IBD and NASH datasets. GO and KEGG pathway analyses revealed significant involvement of SDEGs in apoptotic processes, cell death, defense response, cytokine and chemokine activity, and signaling pathways. Furthermore, weighted gene co-expression network analysis (WGCNA) identified five shared signature genes associated specifically with IBD and NASH, they were CXCL9, GIMAP2, ADAMTS5, GRAP, and PRF1. These five genes represented potential diagnostic biomarkers for distinguishing patients with diseases from healthy individuals by using two classifier algorithms and were positively related to autophagy, ferroptosis, angiogenesis, and immune checkpoint factors in the two diseases. Additionally, single-cell analysis of IBD and NASH samples highlighted the expression of regulatory genes in various immune cell subtypes, emphasizing their significance in disease pathogenesis. Our work elucidated the shared signature genes and regulatory mechanisms of IBD and NASH, which could provide new potential therapies for patients with IBD and NASH.

GCNT3 Promotes Hepatocellular Carcinoma Progression and EMT by Activating the PI3K/AKT Pathway.

Primary liver cancer, specifically hepatocellular carcinoma (HCC), is a major global health concern. GCNT3 has been identified as an oncogene in various human malignancies. This investigation aimed to discover the GCNT3 function in HCC. The present study employed integrated bioinformatics analyses to assess the expression pattern, prognostic implications, and putative function of GCNT3 in HCC. Transwell flow cytometry, CCK-8, and wound healing assays were performed to examine HCC cell growth, cell cycle, apoptosis, invasion, and migration. In addition, the epithelial-mesenchymal transition (EMT) markers and PI3K/AKT mechanism markers were examined via western blot analysis to elucidate the underlying mechanisms. In HCC, GCNT3 was significantly overexpressed, which was connected with enhanced tumor aggressiveness and an unfavorable prognosis of individuals. In vitro experiments demonstrated that elevated levels of GCNT3 promoted cell growth, migration, cell cycle development, and invasion, in addition to EMT, while suppressing apoptosis. Conversely, knockdown of GCNT3 exerted the opposite effects. GCNT3 overexpression increased PI3K/AKT phosphorylation in HCC cells, and LY294002 counteracted the impacts of upregulated GCNT3 on cell cycle, migration, invasion, proliferation, and EMT in HCC. The investigation showed that GCNT3 may enhance HCC progression and EMT by stimulating PI3K/AKT mechanism.

P4HA2 contributes to head and neck squamous cell carcinoma progression and EMT through PI3K/AKT signaling pathway

Head and neck squamous cell carcinoma (HNSCC) can be defined as a deadly illness with a dismal prognosis in advanced stages. Therefore, we seek to examine P4HA2 expression and effect in HNSCC, along with the underlying mechanisms. This study utilized integrated bioinformatics analyses to evaluate the P4HA2 expression pattern, prognostic implication, and probable function in HNSCC. The study conducted various in vitro experiments, including colony formation, CCK-8, flow cytometry, wound healing, and transwell assays, on the human HNSCC cell line CAL-27 to examine the involvement of P4HA2 in HNSCC progression. Moreover, western blotting was used to investigate epithelial-mesenchymal transition (EMT) markers and PI3K/AKT pathway markers to elucidate the underlying mechanisms. P4HA2 expression was significantly enhanced in HNSCC, and its overexpression was correlated to tumor aggressiveness and a poor prognosis in patients. Based on in vitro experiments, the overexpressed P4HA2 enhanced cell proliferation, migration, invasion, as well as EMT while reducing apoptosis, whereas P4HA2 silencing exhibited the reverse effect. P4HA2 overexpression enhanced PI3K/AKT phosphorylation in HNSCC cells. Moreover, LY294002 was observed to counteract the effects of upregulated P4HA2 on proliferation, migration, invasion, and EMT in HNSCC. Collectively, we indicated that P4HA2 promoted HNSCC progression and EMT via PI3K/AKT signaling pathway.

Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson’s disease progression

BackgroundParkinson’s disease (PD) is a progressive neurodegenerative disease with increasing prevalence. Effective diagnostic markers and therapeutic methods are still lacking. Exploring key molecular markers and mechanisms for PD can help with early diagnosis and treatment improvement.MethodsThree datasets GSE174052, GSE77668, and GSE168496 were obtained from the GEO database to search differentially expressed circRNA (DECs), miRNAs (DEMis), and mRNAs (DEMs). GO and KEGG enrichment analyses, and protein–protein interaction (PPI) network construction were implemented to explore possible actions of DEMs. Hub genes were selected to establish circRNA-related competing endogenous RNA (ceRNA) networks.ResultsThere were 1005 downregulated DECs, 21 upregulated and 21 downregulated DEMis, and 266 upregulated and 234 downregulated DEMs identified. The DEMs were significantly enriched in various PD-associated functions and pathways such as extracellular matrix organization, dopamine synthesis, PI3K-Akt, and calcium signaling pathways. Twenty-one hub genes were screened out, and a PD-related ceRNA regulatory network was constructed containing 31 circRNAs, one miRNA (miR-371a-3p), and one hub gene (KCNJ6).ConclusionWe identified PD-related molecular markers and ceRNA regulatory networks, providing new directions for PD diagnosis and treatment.

Investigation of the Shared Biomarkers in Heterotopic Ossification Between Ossification of the Ligamentum Flavum and Ankylosing Spondylitis.

Bioinformatics analysis of Gene Expression Omnibus (GEO). Ossification of the ligamentum flavum (OLF) and ankylosing spondylitis (AS) represent intricate conditions marked by the gradual progression of endochondral ossification. This investigation endeavors to unveil common biomarkers associated with heterotopic ossification and explore the potential molecular regulatory mechanisms. Microarray and RNA-sequencing datasets retrieved from the Gene Expression Omnibus (GEO) repository were harnessed to discern differentially expressed genes (DEGs) within the OLF and AS datasets. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) was implemented to pinpoint co-expression modules linked to OLF and AS. Common genes were further subjected to an examination of functional pathway enrichment. Moreover, hub intersection genes were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) regression, followed by an evaluation of diagnostic performance in external OLF and AS cohorts. Lastly, an analysis of immune cell infiltration was conducted to scrutinize the correlation of immune cell presence with shared biomarkers in OLF and AS. A total of 1353 and 91 Differentially Expressed Genes (DEGs) were identified in OLF and AS, respectively. Using the Weighted Gene Co-expression Network Analysis (WGCNA), 2 modules were found to be notably significant for OLF and AS. The integrative bioinformatic analysis revealed 3 hub genes (MAB21L2, MEGF10, ISLR) as shared risk biomarkers, with MAB21L2 being the central focus. Receiver Operating Characteristic (ROC) analysis exhibited a strong diagnostic potential for these hub genes. Gene Ontology (GO) analysis indicated their involvement in the positive regulation of myoblast proliferation. Notably, MAB21L2 was singled out as the optimal common biomarker for OLF and AS. Furthermore, an analysis of immune infiltration demonstrated a correlation between MAB21L2 expression and changes in immune cells. Activated CD8 T cells were identified as shared differential immune infiltrating cells significantly linked to MAB21L2 in both OLF and AS. This study represents the first instance of identifying MAB21L2 as a prospective diagnostic marker for patients contending with OLF associated with AS. The research results indicate that the ECM-receptor interaction and the cell-cell adhesion may play a role in both disease processes. This newfound knowledge not only enhances our understanding of the pathogenesis behind spinal ligament ossification but also uncovers potential targets for therapeutic interventions.

Integrated Bioinformatics Analysis Reveals ceRNA Triplet Related to Apoptosis in Gastric Cancer

Apoptosis is a form of programmed cell death and evading the apoptosis is a milestone in gastric cancer (GC) tumorigenesis. Various RNAs such as miRNA (microRNA), mRNA (messenger RNA), lncRNA (long non-coding RNA), circRNA (circular RNA), play crucial roles in the apoptosis mechanism. In this present study, we aimed to understand the role played by these RNAs in apoptosis in GC. We constructed a ceRNA (competitive endogenous RNA) network using the expression profiles obtained from SRA (Sequence Read Archive) and GEO (Gene Expression Omnibus) datasets. After network construction, the differentially expressed mRNAs were used for gene prioritization. The prioritized genes and the RNAs interacting with them were analyzed to study their role in GC apoptosis. Then, we performed functional and pathway analysis to understand the role played by these genes in gastric cancer. This resulted in 37 miRNA-mRNA interactions, one miRNA-lncRNA interaction, and 17 miRNA-circRNA interactions. The binding site analysis resulted in 10 miRNAs that share common MRE (miRNA Response Elements) among mRNA, lncRNAs, circRNA. Besides, we found 33 miRNA-mRNA-circRNA and two miRNA-mRNA-lncRNA valid interactions. Integration of multiple omics datasets revealed dysregulated genes, including IGF1, MME, CCND2, CDH2, and COL1A1, implicated in GC apoptosis. Functional enrichment analysis highlighted pathways related to apoptosis, with CCND2 emerging as a key player. The integrative methodology has revealed a new potential diagnostic biomarker for the regulation of gastric cancer (GC) apoptosis: the CCND2-miR-141-3p-hsa_circ_0008035 ceRNA triplet. This discovery offers fresh perspectives into the intricate regulatory pathways governing gene expression in GC, promising significant insights into its pathology.

Identification of circRNA–miRNA–mRNA regulatory network associated to the autism spectrum disorder in children through integrated bioinformatics analysis

BackgroundAutism spectrum disorder (ASD) is a complex neurological disability with multifactorial etiology. ASD is described by behavior, speech, language, and communication defects. CircRNA is a type of ceRNA that plays an important role in modulating microRNAs (miRNA) in several disorders. However, the potential role of the circRNA/miRNA/mRNA regulatory network in the pathogenesis of ASD is not fully understood. Therefore, this study aimed to create a circRNA/miRNA/mRNA network associated with ASD to cast light on the pathogenesis of ASD.MethodsCircRNA expression profile data were recruited from Gene Expression Omnibus datasets, and the differentially expressed circRNAs (DEcircRNAs) were identified. Then, miRNAs modulated by these circRNAs were predicted and overlapped with differentially expressed miRNAs. Next, the potentially involved genes were identified by overlapping predicted targets, and differentially expressed genes. The enrichment analysis was performed, and a PPI network was projected. Subsequently, ten key genes were selected from the network. Furthermore, a circRNA/miRNA/mRNA regulatory network was constructed, and probable molecules and drugs with potential anti-ASD effects were predicted.Results11 DEcircRNAs and 8 miRNAs regulated by 4 circRNAs were identified as being significantly involved. Subsequently, gene enrichment analysis of 71 overlapped mRNA regulated by these miRNAs showed that they are mostly associated with hippocampal synaptogenesis, neurogenesis, and axon guidance. Additionally, two high-score compounds, GSK3β inhibitor (SB216763) and dexamethasone, and three drugs (haloperidol, nystatin, paroxetine) were confirmed as potential therapeutic options for ASD.ConclusionThe results of this study may help gain deeper insight into the pathogenesis of the circRNA/miRNA/mRNA regulatory network in ASD, providing potential therapeutic management options.

Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal disease of unknown etiology with a poor prognosis, characterized by a lack of effective diagnostic and therapeutic interventions. The role of immunity in the pathogenesis of IPF is significant, yet remains inadequately understood. This study aimed to identify potential key genes in IPF and their relationship with immune cells by integrated bioinformatics analysis and verify by in vivo and in vitro experiments. Gene microarray data were obtained from the Gene Expression Omnibus (GEO) for differential expression analysis. The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. Then their diagnostic significance and potential co-regulators were elucidated. We further analyzed the correlation between key genes and immune infiltrating cells via single-sample gene set enrichment analysis (ssGSEA). Subsequently, a single-cell RNA sequencing data (scRNA-seq) was used to explore which cell types expressed key genes in IPF samples. Finally, a series of in vivo and in vitro experiments were conducted to validate the expression of candidate genes by western blot (WB), quantitative real-time PCR (qRT-PCR), and immunohistochemistry (IHC) analysis. A total of 647 DEGs of IPF were identified based on two datasets, including 225 downregulated genes and 422 upregulated genes. They are closely related to biological functions such as cell migration, structural organization, immune cell chemotaxis, and extracellular matrix. CFH and FHL2 were identified as key genes with diagnostic accuracy for IPF by three machine learning algorithms. Analysis using ssGSEA revealed a significant association of both CFH and FHL2 with diverse immune cells, such as B cells and NK cells. Further scRNA-seq analysis indicated CFH and FHL2 were specifically upregulated in human IPF tissues, which was confirmed by in vitro and in vivo experiments. In this study, CFH and FHL2 have been identified as novel potential biomarkers for IPF, with potential diagnostic utility in future clinical applications. Subsequent investigations into the functions of these genes in IPF and their interactions with immune cells may enhance comprehension of the disease's pathogenesis and facilitate the identification of therapeutic targets.

Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer

To investigate the expression of mRNA in esophageal cancer (ESCA) tissues and its potential and diagnostic and prognostic value by high-throughput sequencing data. Using the Cancer Genome Atlas Program (TCGA) database in USA by integrative bioinformatics analysis methods, the gene expression profiles and clinical data of 173 patients with ECSA were collected. The mRNA expression levels in ESCA tissue and para-cancerous tissue samples were analyzed using DESeq2, edgeR and limma to screen the differentially expressed genes (DEGs). DEGs-related protein network diagrams were drawn. GO and KEGG function enrichment analysis were performed and the hub genes were screened and the survival analysis of hub genes was analyzed. Genes related to the prognosis of ESCA were selected and their prognostic value in ESCA was analyzed. Finally, the receiver operating characteristic curve was drawn to evaluate its diagnostic value. The results showed that using TCGA cancer data, a total of 620 up-regulated DEGs and 668 down-regulated DEGs with significant differential expression between ESCA and para-cancerous tissues were screened. DEGs were mainly involved in receptor complexes, ubiquitin ligase complexes, etc., playing GTPase activity, phospholipid binding, and other molecular functions, and participating in the regulation of intracellular substance transport, small molecule metabolism, and other biological processes. Protein functional enrichment analysis showed that these proteins were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, Epstein-Barr virus infection, neutrophil extracellular trap formation, and other pathways involved in the formation and development process of ESCA. Survival analysis showed that the overall survival rate of ESCA patients with high expression of KIF4A, RAD51AP1, and CDKN3 was significantly shortened, and the difference was statistically significant (P<0.05). Furthermore, the areas under the curve (AUC) of KIF4A, RAD51AP1, and CDKN3 for diagnosing esophageal cancer were 0.956, 0.951 and 0.979, respectively, with sensitivities and specificities both exceeding 80%. Additionally, ROC results of the combined diagnostic model of these three genes showed an AUC of 0.979, with sensitivities and specificities of 0.914 and 1, respectively. This indicates that KIF4A, RAD51AP1 and CDKN3 have individual or combined auxiliary diagnostic value for ESCA. In conclusion, KIF4A, RAD51AP1 and CDKN3 have high diagnostic efficiency for ESCA, and their increased expression is closely related to the prognosis, suggesting that these three genes could be used as auxiliary diagnostic and prognostic factors for ESCA.

Identification of biomarkers for abdominal aortic aneurysm in Behçet's disease via mendelian randomization and integrated bioinformatics analyses.

Behçet's disease (BD) is a complex autoimmune disorder impacting several organ systems. Although the involvement of abdominal aortic aneurysm (AAA) in BD is rare, it can be associated with severe consequences. In the present study, we identified diagnostic biomarkers in patients with BD having AAA. Mendelian randomization (MR) analysis was initially used to explore the potential causal association between BD and AAA. The Limma package, WGCNA, PPI and machine learning algorithms were employed to identify potential diagnostic genes. A receiver operating characteristic curve (ROC) for the nomogram was constructed to ascertain the diagnostic value of AAA in patients with BD. Finally, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were conducted. The MR analysis indicated a suggestive association between BD and the risk of AAA (odds ratio [OR]: 1.0384, 95% confidence interval [CI]: 1.0081-1.0696, p = 0.0126). Three hub genes (CD247, CD2 and CCR7) were identified using the integrated bioinformatics analyses, which were subsequently utilised to construct a nomogram (area under the curve [AUC]: 0.982, 95% CI: 0.944-1.000). Finally, the immune cell infiltration assay revealed that dysregulation immune cells were positively correlated with the three hub genes. Our MR analyses revealed a higher susceptibility of patients with BD to AAA. We used a systematic approach to identify three potential hub genes (CD247, CD2 and CCR7) and developed a nomogram to assist in the diagnosis of AAA among patients with BD. In addition, immune cell infiltration analysis indicated the dysregulation in immune cell proportions.

Identification of potential tissue-specific biomarkers involved in pig fat deposition through integrated bioinformatics analysis and machine learning

Backfat thickness (BT) and intramuscular fat (IMF) content are closely appertained to meat production and quality in pig production. Deposition in subcutaneous adipose (SA) and IMF concerns different genes and regulatory mechanisms. And larger studies with rigorous design should be carried to explore the molecular regulation of fat deposition in different tissues. The purpose of this study is to gain a better understanding of the molecular mechanisms underlying differences in fat deposition among different tissues and identify tissue-specific genes involved in regulating fat deposition. The SA-associated datasets (GSE122349 and GSE145956) and IMF-associated datasets (GSE165613 and GSE207279) were downloaded from the Gene Expression Omnibus (GEO) as the BT and IMF group, respectively. Subsequently, the Robust Rank Aggregation (RRA) algorithm identified 27 down- and 29 up-regulated differentially expressed genes (DEGs) in the BT group. Based on bioinformatics and three machine learning algorithms, four SA deposition-related potential biomarkers, namely ACLY, FASN, ME1, and ARVCF were selected. FASN was evaluated as the most valuable biomarker for the SA mechanism. The 18 down- and 34 up-regulated DEGs in the IMF group were identified, and ACTA2 and HMGCL were screened as the IMF deposition-related candidate core genes, especially the ACTA2 may play the critical role in IMF deposition regulation. Moreover, based on the constructed ceRNA network, we postulated that the role of predicted ceRNA interaction network of XIST, NEAT1/miR-15a-5p, miR-16-5p, miR-424-5p, miR-497-5p/FASN were vital in the SA metabolism, XIST, NEAT1/miR-27a/b-3p, 181a/c-5p/ACTA2 might contribute to the regulation to IMF metabolism, which all gave suggestions in molecular mechanism for regulation of fat deposition. These findings may facilitate advancements in porcine quality at the genetic and molecular levels and assist with human obesity-associated diseases.

Integrated Bioinformatics Analysis for Revealing CBL is a Potential Diagnosing Biomarker and Related Immune Infiltration in Parkinson’s Disease

Integrated Bioinformatics Analysis for Revealing CBL is a Potential Diagnosing Biomarker and Related Immune Infiltration in Parkinson’s Disease

LOXL1-AS1 contributes to metastasis in sonic-hedgehog medulloblastoma by promoting cancer stem-like phenotypes

BackgroundMedulloblastomas (MBs) are one of the most common malignant brain tumor types in children. MB prognosis, despite improvement in recent years, still depends on clinical and biological risk factors. Metastasis is the leading cause of MB-related deaths, which highlights an unmet need for risk stratification and targeted therapy to improve clinical outcomes. Among the four molecular subgroups, sonic-hedgehog (SHH)-MB harbors clinical and genetic heterogeneity with a subset of high-risk cases. Recently, long non-coding (lnc)RNAs were implied to contribute to cancer malignant progression, but their role in MB remains unclear. This study aimed to identify pro-malignant lncRNAs that have prognostic and therapeutic significance in SHH-MB.MethodsThe Daoy SHH-MB cell line was engineered for ectopic expression of MYCN, a genetic signature of SHH-MB. MYCN-associated lncRNA genes were identified using RNA-sequencing data and were validated in SHH-MB cell lines, MB tissue samples, and patient cohort datasets. SHH-MB cells with genetic manipulation of the candidate lncRNA were evaluated for metastatic phenotypes in vitro, including cell migration, invasion, sphere formation, and expressions of stemness markers. An orthotopic xenograft mouse model was used to evaluate metastasis occurrence and survival. Finally, bioinformatic screening and in vitro assays were performed to explore downstream mechanisms.ResultsElevated lncRNA LOXL1-AS1 expression was identified in MYCN-expressing Daoy cells and MYCN-amplified SHH-MB tumors, and was significantly associated with lower survival in SHH-MB patients. Functionally, LOXL1-AS1 promoted SHH-MB cell migration and cancer stemness in vitro. In mice, MYCN-expressing Daoy cells exhibited a high metastatic rate and adverse effects on survival, both of which were suppressed under LOLX1-AS1 perturbation. Integrative bioinformatic analyses revealed associations of LOXL1-AS1 with processes of cancer stemness, cell differentiation, and the epithelial-mesenchymal transition. LOXL1-AS1 positively regulated the expression of transforming growth factor (TGF)-β2. Knockdown of TGF-β2 in SHH-MB cells significantly abrogated their LOXL1-AS1-mediated prometastatic functions.ConclusionsThis study proved the functional significance of LOXL1-AS1 in SHH-MB metastasis by its promotion of TGF-β2-mediated cancer stem-like phenotypes, providing both prognostic and therapeutic potentials for targeting SHH-MB metastasis.

Identification of PANoptosis-related biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma

PANoptosis plays a crucial role in cancer initiation and progression. However, the roles of PANoptosis-related genes (PARGs) in the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC) remain unclear. Integrated bioinformatics analyses based on the data of HNSCC patients in the TCGA database were conducted. We extracted 48 PARGs expression profile and then conducted differentially expressed analysis, following building a Cox model to predict the survival of HNSCC patients. Subsequently, the relationships between the risk score, immune landscape, chemo-, and immune-therapy responses were analyzed, respectively. Moreover, we investigated the prognostic value, and further predicted the pathways influenced by PARGs. Finally, we identified the biological function of crucial PARGs. A total of 18 differentially expressed PARGs were identified in HNSCC, and a Cox model including CASP8, FADD, NLRP1, TNF, and ZBP1 was constructed, which showed that the risk score was associated with the prognosis as well as immune infiltration of HNSCC patients, and the risk score could be regarded as an independent biomarker. Additionally, patients with high-risk score might be an indicator of lymph node metastasis and advanced clinical stage. High-risk scores also contributed to the chemotherapy resistance and immune escape of HNSCC patients. In addition, FADD and ZBP1 played a crucial role in various cancer-related pathways, such as the MAPK, WNT, and MTOR signaling pathways. On the other hand, we suggested that FADD facilitated the progression and 5-fluorouracil (5-FU) resistance of HNSCC cells. A signature based on PANoptosis showed great predictive power for lymph node metastasis and advanced stage, suggesting that the risk score might be an independent prognostic biomarker for HNSCC. Meanwhile, FADD, identified as a prognostic biomarker, may represent an effective therapeutic target for HNSCC.

Deciphering the latent biomarkers in HBV and HDV- associated HepatoCellular carcinoma – An integrated bioinformatics analysis

Abundant studies convey chronic viral hepatitis (HBV and HDV) infection to be associated with development and promotion of HepatoCellular Carcinoma (HCC), making HBV and HDV contamination as one of the foremost source of HCC development worldwide. In the present study we intended to identify potential therapeutic biomarkers for HBV and HDV induced HCC development and progression. Hereby, we executed meta-analysis of micro-array datasets: GSE121248 comprising 107 viral infected samples categorized as 37 normal adjacent samples and 70 tumor samples along with GSE107170 containing 307 virus-positive tissue samples of which 155 samples were considered for further analysis encompassing 105 normal tissues and 50 HCC tumor samples. Eventually by analyzing an aggregate of 262 samples through GeneSpring Software, 486 Differentially Expressed Genes (DEGs) were identified among HBV and HDV infected samples leading to HCC including 152 up-regulated and 334 down-regulated genes. Subsequently resulted DEGs were processed for functional annotation by using OmicsBox, Pathway enrichment and disease association analysis by using EnrichR webserver. Additionally, Protein-Protein Interaction Network was constructed to identify top 10 most significant hub nodes by using Cytoscape tool and cytohubba plugin. Furthermore the identified top 10 noteworthy hub nodes were analyzed for overall survival, disease free survival and expression validation in HCC samples by employing GEPIA2 and HPA databases. Consequently hub genes were assessed for diagnostic efficacy by Receiver Operating Characteristic curves (ROC) which demonstrates promising performance of all the hub genes. Conclusively, our findings postulate TOP2A, PBK, NUF2, CCNB1, CDC20, BUB1B, NDC80, MAD2L1, DLGAP5 and KIF4A as the plausible biomarkers occupied in oncogenic pathways having a probable function in progression of HBV and HDV contaminated cells to HCC, proliferation of HCC and tumorogenesis. The present study also aids for elevated understanding of virus-associated HCC progression.

MicroRNA-322-5p targeting Smurf2 regulates the TGF-β/Smad pathway to protect cardiac function and inhibit myocardial infarction.

Acute coronary artery blockage leads to acute myocardial infarction (AMI). Cardiomyocytes are terminally differentiated cells that rarely divide. Treatments preventing cardiomyocyte loss during AMI have a high therapeutic benefit. Accumulating evidence shows that microRNAs (miRNAs) may play an essential role in cardiovascular diseases. This study aims to explore the biological function and underlying regulatory molecular mechanism of miR-322-5p on myocardial infarction (MI). This study's miR-322-5p is downregulated in MI-injured hearts according to integrative bioinformatics and experimental analyses. In the MI rat model, miR-322-5p overexpression partially eliminated MI-induced changes in myocardial enzymesand oxidative stress markers, improved MI-caused impairment on cardiac functions, inhibited myocardial apoptosis, attenuated MI-caused alterations in TGF-β, p-Smad2, p-Smad4, and Smad7 protein levels. In oxygen-glucose deprivation (OGD)-injured H9c2 cells, miR-322-5p overexpression partially rescued OGD-inhibited cell viability and attenuated OGD-caused alterations in the TGF-β/Smad signaling. miR-322-5p directly targeted Smurf2 and inhibited Smurf2 expression. In OGD-injured H9c2 cells, Smurf2 knockdown exerted similar effects to miR-322-5p overexpression upon cell viability and TGF-β/Smad signaling; moreover, Smurf2 knockdown partially attenuated miR-322-5p inhibition effects on OGD-injured H9c2 cells. In conclusion, miR-322-5p is downregulated in MI rat heart and OGD-stimulated rat cardiomyocytes; the miR-322-5p/Smurf2 axis improves OGD-inhibited cardiomyocyte cell viability and MI-induced cardiac injuries and dysfunction through the TGF-β/Smad signaling.

Identification of potential hub genes and biological mechanism in rheumatoid arthritis and non-small cell lung cancer via integrated bioinformatics analysis

BackgroundAlthough there is evidence of the association between RA and NSCLC, little is known about their interaction mechanisms. The aim of this study is to identify potential hub genes and biological mechanism in RA and NSCLC via integrated bioinformatics analysis. MethodsThe gene expression datasets of RA and NSCLC were downloaded to discover and validate hub genes. After identifying DEGs, we performed enrichment analysis, PPI network construction and module analysis, selection and validation of hub genes. Moreover, we selected the hub gene PTPRC for expression and prognosis analysis, immune analysis, mutation and methylation analysis in NSCLC. Finally, we performed real-time PCR, colony formation assay, wound healing assay, transwell invasion assay, sphere formation assay and western blotting to validate the role of PTPRC in A549 cells. ResultsWe obtained 320 DEGs for subsequent analysis. Enrichment results showed that the DEGs were mainly involved in Th1, Th2 and Th17 cell differentiation. In addition, four hub genes, BIRC5, PTPRC, PLEK, and FYN, were identified after selection and validation. These hub genes were subsequently shown to be closely associated with immune cells and related pathways. In NSCLC, PTPRC was downregulated, positively correlated with immune infiltration and immune cells. Experiments showed that PTPRC could promote the proliferation, migration and invasion, and the ability to form spheroids of A549 cells. In addition, PTPRC could regulate the increased expression of CD45, β-catenin, c-Myc and LEF1 proteins. ConclusionsThis study explored the hub genes and related mechanisms of RA and NSCLC, demonstrated the central role of the inflammatory response and the adaptive immune system, and identified PTPRC as an immune-related biomarker and potential therapeutic target for RA and NSCLC patients. In addition, PTPRC can significantly promote the proliferation, migration and invasion of A549 cells, and its mechanism may be to promote the EMT process by regulating the Wnt signaling pathway and promote cell stemness, which in turn has a promoting effect on A549 cells.

Identification of key mitochondria-related genes and their relevance to the immune system linking Parkinson's disease and primary Sjögren's syndrome through integrated bioinformatics analyses

BackgroundMitochondria are the metabolic hubs of cells, regulating energy production and antigen presentation, which are essential for activation, proliferation, and function of immune cells. Recent evidence indicates that mitochondrial antigen presentation may have an impact on diseases such as Parkinson's disease (PD) and autoimmune diseases. However, there is limited knowledge about the mechanisms that regulate the presentation of mitochondrial antigens in these diseases. MethodsIn the current study, RNA sequencing was performed on labial minor salivary gland (LSG) from 25 patients with primary Sjögren's syndrome (pSS) and 14 non-pSS aged controls. Additionally, we obtained gene expression omnibus datasets associated with PD patients from NCBI Gene Expression Omnibus (GEO) databases. Single-sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE and Spearman correlations were conducted to explore the association between mitochondrial related genes and the immune system. Furthermore, we applied weighted Gene Co-expression Network Analysis (WGCNA) to identify hub mitochondria-related genes and investigate the correlated networks in both diseases. Single cell transcriptome analysis, immunohistochemical (IHC) staining and quantitative real-time PCR (qRT–PCR) were used to verify the activation of the hub mitochondria-related pathway. Pearson correlations and the CIBERSORT algorithms were employed to further reveal the correlation between hub mitochondria-related pathways and immune infiltration. ResultsThe transcriptome analysis revealed the presence of overlapping mitochondria-related genes and mitochondrial DNA damage in patients with pSS and PD. Reactive oxygen species (ROS), the senescence marker p53, and the inflammatory markers CD45 and Bcl-2 were found to be regionally distributed in LSGs of pSS patients. WGCNA analysis identified the STING pathway as the central mitochondria-related pathway closely associated with the immune system. Single cell analysis, IHC staining, and qRT-PCR confirmed the activation of the STING pathway. Subsequent, bioinformatic analysis revealed the proportion of infiltrating immune cells in the STING-high and STING-low groups of pSS and PD. Furthermore, the study demonstrated the association of the STING pathway with innate and adaptive immune cells, as well as functional cells, in the immune microenvironment of PD and pSS. ConclusionOur study uncovered a central pathway that connects mitochondrial dysfunction and the immune microenvironment in PD and pSS, potentially offering valuable insights into therapeutic targets for these conditions.