mRNA Expression Profiling Data Research Articles

Single-cell sequencing analysis revealed that WDR72 was a novel cancer stem cells related gene in gastric cancer

BackgroundCancer stem cells (CSCs) are pivotal in tumor resistance to chemotherapy and gastric cancer's rapid proliferation and metastasis. We aimed to explore the CSCs-related genes in gastric cancer epithelial cells. MethodsThe mRNA expression profile and single-cell sequencing data of gastric cancer were downloaded from the public database. ResultsWe identified WDR72 as a CSCs-related gene in gastric cancer epithelial cells. WDR72 was highly expressed in gastric cancer tissues, and high expression of WDR72 was associated with inferior prognosis of patients. WDR72 expression had a significant negative correlation with the infiltration of CD8 + T cells and activated memory CD4 + T cells. PD-L1 expression was significantly reduced in gastric cancer patients with high WDR72 expression. WDR72 was correlated with IC50 of multiple small-molecule drugs. ConclusionWe identified a novel CSCs-related gene in gastric cancer epithelial cells, WDR72, which was highly expressed in patients with high stemness scores.

A signature of four ferroptosis-related genes in laryngeal squamous cell carcinoma.

Laryngeal squamous cell carcinoma (LSCC) prognosis has not improved significantly in the past few decades, and more effective treatments are needed to be explored. Ferroptosis is a newly discovered kind of regulated cell death in recent years, which is related to tumor immunity and can used to treat tumors. Therefore, the prognostic value of ferroptosis-related genes in laryngeal cancer needs further clarification. In this study, the mRNA expression profile data of LSCC were downloaded from the public database. After identifying ferroptosis-related differentially expressed genes (FDGs), we explored the role of these genes through functional enrichment analysis. FDGs with prognostic significance were identified by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. By calculating the risk score, we constructed a prognostic model. Kaplan-Meier (K-M) analysis, the receiver operating characteristic (ROC) curves, and the nomogram were utilized to investigate this model. Public databases and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to verify the expression of model genes. The model consisting of four FDGs was acknowledged to be a self-determining predictor of prognosis. The K-M survival curves and the ROC curves confirmed the model's predictive ability. The C index (0.805) indicates that the nomogram has a good predictive ability. In vitro studies have confirmed the differential expression of the four FDGs. We identified a novel ferroptosis-related gene signature for predicting prognosis in LSCC.

Transcriptomics analysis revealed that TAZ regulates the proliferation of KIRC cells through mitophagy.

Transcriptional Co-Activator with PDZ-Binding Motif (TAZ, also known as WWTR1) is a downstream effector of the Hippo pathway, involved in the regulation of organ regeneration and cell differentiation in processes such as development and regeneration. TAZ has been shown to play a tumor-promoting role in various cancers. Currently, many studies focus on the role of TAZ in the process of mitophagy. However, the molecular mechanism and biological function of TAZ in renal clear cell carcinoma (KIRC) are still unclear. Therefore, we systematically analyzed the mRNA expression profile and clinical data of KIRC in The Cancer Genome Atlas (TCGA) dataset. We found that TAZ expression was significantly upregulated in KIRC compared with normal kidney tissue and was closely associated with poor prognosis of patients. Combined with the joint analysis of 36 mitophagy genes, it was found that TAZ was significantly negatively correlated with the positive regulators of mitophagy. Finally, our results confirmed that high expression of TAZ in KIRC inhibits mitophagy and promotes KIRC cell proliferation. In conclusion, our findings reveal the important role of TAZ in KIRC and have the potential to be a new target for KIRC therapy.

Serum IGFBP-1 as a promising diagnostic and prognostic biomarker for colorectal cancer

Our previous study showed that levels of circulating insulin-like growth factor binding protein-1 (IGFBP-1) has potential diagnostic value for early-stage upper gastrointestinal cancers. This study aimed to assess whether serum IGFBP-1 is a potential diagnostic and prognostic biomarker for CRC patients. IGFBP-1 mRNA expression profile data of peripheral blood in colorectal cancer (CRC) patients were downloaded and analyzed from Gene Expression Omnibus database. We detected serum IGFBP-1 in 138 CRC patients and 190 normal controls using enzyme-linked immunosorbent assay. Blood IGFBP-1 mRNA levels were higher in CRC patients than those in normal controls (P = 0.027). In addition, serum IGFBP-1 protein levels in the CRC group were significantly higher than those in normal control group (P < 0.0001). Serum IGFBP-1 demonstrated better diagnostic accuracy for all CRC and early-stage CRC, respectively, when compared with carcinoembryonic antigen (CEA), carbohydrate antigen19-9 (CA 19-9) or the combination of CEA and CA19-9. Furthermore, Cox multivariate analysis revealed that serum IGFBP-1 was an independent prognostic factor for OS (HR = 2.043, P = 0.045). Our study demonstrated that serum IGFBP-1 might be a potential biomarker for the diagnosis and prognosis of CRC. In addition, the nomogram might be helpful to predict the prognosis of CRC.

Crucial role of hsa-mir-503, hsa-mir-1247, and their validation in prostate cancer.

Prostate cancer (PC) is a common urinary system malignancy, and advanced PC patients had a poor prognosis due to recurrence or distant metastasis. Therefore, it's imperative to reveal more details in tumorigenesis and prognosis of PC patients. The miRNA and mRNA expression profile data of 485 PC patients were obtained from The Cancer Genome Atlas database. The univariate Cox regression was applied to screen miRNAs relating to prognosis of PC. Then miRTarBase was used to predict target mRNAs of miRNAs. The hsa-mir-503/hsa-mir-1247 knockdown in 22RV1 cells was established to evaluate the effect of these two miRNAs on tumor cell migration and invasion ability. Flow cytometry was used to detect the effect of hsa-mir-503/hsa-mir-1247 knockdown on 22RV1 apoptosis rate. Univariate Cox regression analysis identified hsa-mir-503 as a poor and hsa-mir-1247 as a favorable prognostic marker. Totally 649 target mRNAs were screened, among which DUSP19, FGF2, and SLC2A5 had a negative correlation with hsa-mir-503, while FGF2 and VSTM4 had a positive correlation with hsa-mir-1247. In 22RV1 cells, hsa-mir-503 was up-regulated, and hsa-mir-1247 was down-regulated. hsa-mir-503 knockdown attenuated the migration and invasion of 22RV1 cells, while hsa-mir-1247 knockdown exhibited the opposite effect. In addition, hsa-mir-503 knockdown promoted 22RV1 cell apoptosis. hsa-mir-1247 overexpression significantly inhibited the tumor growth of PC in vivo. Herein, we demonstrated that hsa-mir-503 and hsa-mir-1247 could serve as new prognostic markers of PC, and hsa-mir-1247 had great potential to inhibit PC progression by suppressing the migration and invasion ability in vitro and in vivo.

MRNA expression profile reveals differentially expressed genes in splenocytes of experimental autoimmune encephalomyelitis model.

Experimental autoimmune encephalomyelitis (EAE) is a mouse model that can be used to investigate aetiology, pathogenesis, and treatment approaches for multiple sclerosis (MS). A novel integrated bioinformatics approach was used to understand the involvement of differentially expressed genes (DEGs) in the spleen of EAE mice through data mining of existing microarray and RNA-seq datasets. We screened differentially expressed mRNAs using mRNA expression profile data of EAE spleens takenfrom Gene Expression Omnibus (GEO). Functional and pathway enrichment analyses of DEGs were performed by Database for Annotation, Visualization, and Integrated Discovery (DAVID). Subsequently, the DEGs-encoded protein-protein interaction (PPI) network was constructed. The 784 DEGs in GSE99300 A.SW PP-EAE mice spleen mRNA profiles, 859 DEGs in GSE151701 EAE mice spleen mRNA profiles, and 646 DEGs in GSE99300 SJL/J PP-EAE mice spleen mRNA profiles were explored. Functional enrichment of 55 common DEGs among 3 sub-datasets revealed several immune-related terms, such as neutrophil extravasation, leucocyte migration, antimicrobial humoral immune response mediated by an antimicrobial peptide, toll-like receptor 4 bindings, IL-17 signalling pathway, and TGF-beta signalling pathway. In the screening of 10 hub genes, including MPO, ELANE, CTSG, LTF, LCN2, SELP, CAMP, S100A9, ITGA2B, and PRTN3, and in choosing and validating the 5 DEGs, including ANK1, MBOAT2, SLC25A21, SLC43A1, and SOX6, the results showed that SLC43A1 and SOX6 were significantly decreased in EAE mice spleen. Thus this study offers a list of genes expressed in the spleen that might play a key role in the pathogenesis of EAE.

Development of lactate-related gene signature and prediction of overall survival and chemosensitivity in patients with colorectal cancer.

Colorectal cancer (CRC) is a malignant tumor of the digestive system that contains high levels of immune cells. Lactic acid, a major metabolite, plays a crucial role in tumor development, maintenance, and therapeutic response. However, the prognostic potential and therapeutic biomarker potential of lactate-related genes (LRGs) in CRC patients remain to be elucidated. We collected the mRNA expression profile and clinical data of CRC patients from the Cancer Genome Atlas (TCGA) database and the GSE59382 cohort. Univariate Cox regression, Lasso regression and multivariate Cox regression analysis were used to construct the prognosis model. Combined with the risk score and important clinicopathological features, the nomogram was established. In addition, the relationship between risk score and immune infiltration, immune checkpoint gene expression, and drug sensitivity was investigated. We constructed lactate-related gene signatures (LRGS) based on four LRGs, which independently predicted the prognosis of CRC. Patients with different risk scores are found to have distinct immune status, tumor mutation load, immune response, and drug sensitivity. In addition, nomogram results determined by risk scores and clinical factors have higher predictive performance. We found that LRGS is a reliable biomarker for predicting clinical outcomes, evaluating immune infiltration and efficacy, and predicting the sensitivity to drugs in patients with CRC.

SOX17: A Highly Sensitive and Specific Immunomarker for Ovarian and Endometrial Carcinomas

PAX8 is the most commonly used immunomarker to link a carcinoma to the gynecologic tract; however, it lacks specificity. Through mining The Cancer Genome Atlas mRNA expression profile data, we identified SOX17 as a potential specific marker at the mRNA level for gynecologic tumors. To evaluate the utility of this marker in the identification of the gynecologic origin of a given carcinoma, we performed immunochemical staining in a large cohort of ovarian and endometrial cancer cases (n = 416), together with a large cohort of solid tumors from other organs (n = 1544) in tissue microarrays. Similar to PAX8, SOX17 was highly expressed in different subtypes of ovarian carcinoma (97.5% for SOX17 vs 97% for PAX8 in serous carcinoma, 90% vs 90% in endometrioid carcinoma, and 100% vs 100% in clear cell carcinoma), except for mucinous carcinoma (0% vs 27%), and was also highly expressed in different subtypes of endometrial carcinoma (88% vs 84% in endometrioid carcinoma, 100% vs 100% in serous and clear cell carcinoma). SOX17 was not expressed in thyroid and renal cell carcinomas, whereas PAX8 expression was high (86% and 85%, respectively). In addition, SOX17 was expressed at low levels in cervical adenocarcinoma (20%) and had no expression in cervical squamous carcinoma, mesothelioma, and carcinomas from the breast, lung, pancreas, colon, stomach, liver, bladder, and salivary gland. Our data indicate that SOX17 is not only a sensitive but also a specific marker for the origin of ovarian and endometrial carcinomas.

Expression of Galectin-9-related immune checkpoint receptors in B-cell acute lymphoblastic leukemia.

Exhausted CD8+ T-cells over-express immune checkpoint receptors (ICRs), which interact with their ligands on malignant cells. However, some ICRs have been reported to be expressed on both T-cells and tumor cells, including V-domain immunoglobulin suppressor of T cell activation (VISTA), Galectin-9, and T-cell immunoglobulin mucin-3 (TIM-3). We aimed to evaluate the mRNA expression of VISTA, Galectin-9, and TIM-3 on CD8+ T-cells and leukemic cells in B-cell acute lymphoblastic leukemia (B-ALL). Samples were obtained from 26 untreated B-ALL patients and 25 control subjects. CD8+ T-cells were isolated using Magnetic Activated Cell Sorting (MACS). Relative gene expression was then evaluated by qRT-PCR with specific primers for VISTA, Galectin-9, and TIM-3. Also, the mRNA expression profile and clinical data of 154 B-ALL patients were obtained from the TARGET. mRNA expression of Galectin-9 on CD8+ T-cells in B-ALL patients was significantly lower than those in the control group (P=0.043), while VISTA expression was not significantly different between the two study groups (P=0.259). Besides, TIM-3 expression was significantly higher in B-ALL patients than in the control group (P<0.001). Also, data obtained from TARGET showed that the relapse incidence was not significantly different between patients with high and low expression of Galectin-9 and TIM-3 in leukemic cells (P=0.360 and P=0.655, respectively). Collectively, gene expression results suggest an important role for TIM-3, but not VISTA and Galectin-9, in B-ALL and it seems that TIM-3 could be a candidate for immune checkpoint therapy.

Elevated Fras1-related extracellular matrix 3 in isocitrate dehydrogenase 1-mutant astrocytoma World Health Organization grade 4 predicts favorable prognosis in glioma: A bioinformatic and experimental analysis

Background and Aim: World Health Organization (WHO) grade 4 glioma is a malignancy of the central nervous system characterized by refractoriness to treatment and a high mortality rate. Isocitrate dehydrogenase (IDH) mutation is a crucial molecular event for the classification of glioma and associated with prognosis and exploring genetic and molecular differences between IDH mutant and wildtype glioma is crucial. The aim of this study was to investigate the prognostic gene between IDH mutant and wildtype WHO grade 4 glioma and its functional significance. Materials and Methods: The mRNA expression profile data of WHO grade 4 glioma were downloaded from the Gene Expression Omnibus and Chinese Glioma Genome Atlas databases. Bioinformatic analysis was performed to identify the differentially expressed genes between IDH1-mutant and wildtype WHO grade 4 glioma. Survival analysis, functional enrichment analysis, immune cell infiltration evaluation, and in vitro experimental validation were conducted to evaluate the prognostic and functional significance of Fras1-related extracellular matrix 3 (FREM3). This study was approved by the Institutional Ethics Committee of Xinqiao Hospital, Third Military Medical University (approval No. 2021-Y068-01). Results: Elevated expression of FREM3 in IDH1-mutant WHO grade 4 astrocytoma predicted favorable prognosis in glioma. FREM3 was negatively associated with epithelial–mesenchymal transition (EMT), angiogenesis, and hypoxia; notably, low expression of FREM3 was associated with a higher degree of immune cell infiltration. In vitro experiments demonstrated that high FREM3 expression might attenuate the process of EMT and cellular proliferation in glioma. Conclusions: The gene FREM3 plays a major role in IDH1-mutant WHO grade 4 glioma and elevated FREM3 predicts a favorable prognosis of glioma. Further investigation on FREM3 is warranted to elucidate the mechanisms underlying the malignant evolution of glioma.

Construction of a prognostic assessment model for colon cancer patients based on immune-related genes and exploration of related immune characteristics.

Objectives: To establish a novel risk score model that could predict the survival and immune response of patients with colon cancer. Methods: We used The Cancer Genome Atlas (TCGA) database to get mRNA expression profile data, corresponding clinical information and somatic mutation data of patients with colon cancer. Limma R software package and univariate Cox regression were performed to screen out immune-related prognostic genes. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used for gene function enrichment analysis. The risk scoring model was established by Lasso regression and multivariate Cox regression. CIBERSORT was conducted to estimate 22 types of tumor-infiltrating immune cells and immune cell functions in tumors. Correlation analysis was used to demonstrate the relationship between the risk score and immune escape potential. Results: 679 immune-related genes were selected from 7846 differentially expressed genes (DEGs). GO and KEGG analysis found that immune-related DEGs were mainly enriched in immune response, complement activation, cytokine-cytokine receptor interaction and so on. Finally, we established a 3 immune-related genes risk scoring model, which was the accurate independent predictor of overall survival (OS) in colon cancer. Correlation analysis indicated that there were significant differences in T cell exclusion potential in low-risk and high-risk groups. Conclusion: The immune-related gene risk scoring model could contribute to predicting the clinical outcome of patients with colon cancer.

541. In Silico Modeling by Causal Inference for Identifying Biomarkers of Sepsis

Abstract Background “Every 3 seconds, someone in the world dies of sepsis” (https://sepsistrust.org/about/). We used causal inference theory as a in silico method to identify biomarkers of sepsis. Causal Inference is a theory in Machine Learning that seeks for the root causes of an event. Methods In the study it was used transcription profile data downloaded from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12624. This dataset has 70 samples, being 34 sepsis and 36 non-sepsis samples. Data set contains 8,519 attributes: 7,672 genes obtained after preprocessing of the mRNA expression profile data. The method applied in the dataset was a modification in the HEISA, a local learner of two stages algorithm (Figure 1). In the first stage HEISA identifies variables that compounds the set of parents, children, parents of parents and children of children of a target. During the second stage is calculated the causal effect using do-calculus method, of the selected variables of the first stage in the target. At end of the second stage, features with causal effect greater than 0.2 is selected. After selecting the features mRNA expression, it was applied two algorithms of classification, Random Forest and K-means, in order to evaluate the ability of the selected variables of identifying the occurrence of sepsis. Figure 1- Causal inference HEISA algorithm. Results As shown in Table I, after applying the algorithm, it was select six mRNA expressions that better explains whether sepsis occurs, or not. Analyzing these genes it was possible to observe that three of them are known biomarkers, they are related to sepsis: NM_017526, NM_004649 and NM_006099. It is important to stress that the second one, Homo sapiens leptin receptor overlapping transcript (LEPROT) transcript variant 1 mRNA, is known to be inversely proportional to sepsis (its causal effect is negative). The other three biomarkers, NM_017526, NM_001274, and NM_001071 also are inversely proportional to sepsis. Their relationship with sepsis is still unknown. Regarding the classification task, using only those six mRNA expressions, the accuracy of the task of classification was 100%. Table I- Sepsis biomarkers candidates. Conclusion In a big set of 7,672 genes, only six were returned as sepsis biomarkers candidates. This is a very promising in silico discovery, made by a novel mathematical method, the Causal Inference theory. Disclosures All Authors: No reported disclosures.

The Identification and Analysis of MicroRNAs Combined Biomarkers for Hepatocellular Carcinoma Diagnosis.

Hepatocellular carcinoma (HCC) is a common malignant tumor with high morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs) are novel biomarkers with higher accuracy. We aimed to identify combinatorial biomarkers of miRNAs to construct a classification model for the diagnosis of HCC. The mature miRNA expression profile data of six cancers (liver, lung, gastric, breast, prostate, and colon) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database with accession number GSE36915, GSE29250, GSE99417, GSE41970, GSE64333 and GSE35982. The messenger RNA (mRNA) expression profile data of these six cancers were obtained from TCGA. Three R software packages, student's t-test, and a normalized foldchange method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs). Using all combinations of obtained HCC-specific DEMs as input features, we constructed a classification model by support vector machine searching for the optimal combination. Furthermore, target genes prediction was conducted on the miRWalk 2.0 website to obtain differentially expressed mRNAs (DEmRNAs), and KEGG pathway enrichment was analyzed on the DAVID website. The optimal combination consisted of four miRNAs (hsa-miR-130a-3p, hsa-miR-450b-5p, hsa-miR-136-5p, and hsa-miR-24-1-5p), of which the last one has not been currently reported to be relevant to HCC. The target genes of hsa-miR-24-1-5p (CDC7, ACACA, CTNNA1, and NF2) were involved in the cell cycle, AMPK signaling pathway, Hippo signaling pathway, and insulin signaling pathway, which affect the proliferation, metastasis, and apoptosis of cancer cells. Moreover, the area under the receiver operating characteristic curves of the four miRNAs were all higher than 0.85. These results suggest that the miRNAs combined biomarkers were reliable for the diagnosis of HCC. Hsa-miR-24-1-5p was a novel biomarker for HCC diagnosis identified in this study.

Upregulation of matrix metalloproteinase 14 (MMP14) is associated with poor prognosis in renal clear cell carcinoma-a bioinformatics analysis.

Matrix metalloproteinase 14 (MMP14) has been reported to be upregulated in some types of cancer and to promote cancer cell invasion and metastasis. However, the expression profile and functional role of MMP14 in kidney renal clear cell carcinoma (KIRC) remains unknown. This study investigated the association between MMP14 expression level and prognosis in KIRC. The messenger RNA (mRNA) expression profile and clinical data (including T stage, N stage, M stage, pathologic stage, gender, race, age, histologic grade, serum calcium, hemoglobin) were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. Protein expression was evaluated by immunohistochemistry in the Human Protein Atlas (HPA) database. Correlation analyses between MMP14 and all mRNAs in KIRC were batch calculated, and gene set enrichment analyses (GSEA) were then conducted of Disease Ontology (DO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using R packages. Multivariate logistic regression analysis was used to explore the prognostic factors of KIRC patients. The gene expression of MMP14 was significantly upregulated in KIRC tissues when compared with the normal tissue (P<0.001). The predictive ability of MMP14 as a variable for predicting tumor and normal outcomes had certain accuracy based on the receiver operating characteristic (ROC) model [area under the curve (AUC) =0.881, confidence interval (CI): 0.844-0.917]. When compared with the normal kidney tissue, the protein expression of MMP14 in KIRC got an increased trend, but due to the limited sample size, the difference is not statistically significant (P>0.05). Survival analysis revealed that MMP14 was significantly associated with overall survival in KIRC (P=0.013). GSEA of DO terms indicated high expression of MMP14 was related to KIRC, and GSEA of KEGG pathways showed that MMP14 and its coexpressed genes were significantly positively correlated with pathways in cancer. Signaling pathway GSEA indicated the upregulation of MMP14 in KIRC may activate cancer pathways. MMP14 may be associated with poor prognosis in KIRC and may be a potential prognostic marker for KIRC.

The Role of Gender-Related Immune Genes in Childhood Acute Myeloid Leukemia.

The study of immune genes and immune cells is highly focused in recent years. To find immunological genes with prognostic value, the current study examines childhood acute myeloid leukemia according to gender. The TARGET database was used to gather the “mRNA expression profile data” and relevant clinical data of children with AML. To normalize processing and find differentially expressed genes (DEG) between male and female subgroups, the limma software package is utilized. We identified prognostic-related genes and built models using LASSO, multivariate Cox, and univariate Cox analysis. The prognostic significance of prognostic genes was then examined through the processing of survival analysis and risk score (RS) calculation. We investigated the connections between immune cells and prognostic genes as well as the connections between prognostic genes and medications. Finally, five immune genes from the TARGET database have been identified. These immune genes are considerably correlated to the prognosis of male patients.

A novel cuproptosis-related subtypes and gene signature associates with immunophenotype and predicts prognosis accurately in neuroblastoma.

BackgroundNeuroblastoma (NB) is the most frequent solid tumor in pediatrics, which accounts for roughly 15% of cancer-related mortality in children. NB exhibited genetic, morphologic, and clinical heterogeneity, which limited the efficacy of available therapeutic approaches. Recently, a new term ‘cuproptosis’ has been used to denote a unique biological process triggered by the action of copper. In this instance, selectively inducing copper death is likely to successfully overcome the limitations of conventional anticancer drugs. However, there is still a gap regarding the role of cuproptosis in cancer, especially in pediatric neuroblastoma.MethodsWe characterized the specific expression of cuproptosis-related genes (CRGs) in NB samples based on publicly available mRNA expression profile data. Consensus clustering and Lasso-Cox regression analysis were applied for CRGs in three independent cohorts. ESTIMATE and Xcell algorithm was utilized to visualize TME score and immune cell subpopulations’ relative abundances. Tumor Immune Dysfunction and Exclusion (TIDE) score was used to predict tumor response to immune checkpoint inhibitors. To decipher the underlying mechanism, GSVA was applied to explore enriched pathways associated with cuproptosis signature and Connectivity map (CMap) analysis for drug exploration. Finally, qPCR verified the expression levels of risk-genes in NB cell lines. In addition, PDHA1 was screened and further validated by immunofluorescence in human clinical samples and loss-of-function assays.ResultsWe initially classified NB patients according to CRGs and identified two cuproptosis-related subtypes that were associated with prognosis and immunophenotype. After this, a cuproptosis-related prognostic model was constructed and validated by LASSO regression in three independent cohorts. This model can accurately predict prognosis, immune infiltration, and immunotherapy responses. These genes also showed differential expression in various characteristic groups of all three datasets and NB cell lines. Loss-of-function experiments indicated that PDHA1 silencing significantly suppressed the proliferation, migration, and invasion, in turn, promoted cell cycle arrest at the S phase and apoptosis of NB cells.ConclusionsTaken together, this study may shed light on new research areas for NB patients from the cuproptosis perspective.

Downregulation of Sepina3n Aggravated Blood–Brain Barrier Disruption after Traumatic Brain Injury by Activating Neutrophil Elastase in Mice

Traumatic brain injury (TBI) is the leading cause of death in young adults and the main cause of mortality and disability across all ages worldwide. We previously analyzed the expression profile data of TBI models obtained from the Gene Expression Omnibus (GEO) database and found that the seripina3n mRNA was markedly upregulated in the acute phase of TBI in four mRNA expression profile data sets, indicating that serpina3n may be involved in the pathophysiological process of TBI. Therefore, we further investigated the biological role and molecular mechanism of serpina3n in traumatic brain injury in this study. As a result, the endogenous level of sepina3n was markedly elevated in the cortex around the contusion sit in mice at day 1 and day 3 after TBI. Inhibiting the expression of serpina3n caused aggravation of neutrophil elastase (NE) expression, BBB disruption, and neurological deficit. With the inactivation of NE, even if serpina3n was silenced, the disruption of the BBB was not further aggravated. In vitro experiments further proved that recombinant serpina3n dose-dependently inhibited the activity of recombinant NE. Based on the above, this study demonstrated that the endogenous level of sepina3n was significantly elevated in the cortex around the contusion sit after TBI in mice, which reduced the secondary blood–brain barrier disruption by inhibiting the activity of neutrophil elastase.

In silico identification and verification of ferroptosis-related genes in type 2 diabetic islets.

Type 2 diabetes (T2D) is a major global public health burden, with β-cell dysfunction a key component in its pathogenesis. However, the exact pathogenesis of β-cell dysfunction in T2D is yet to be fully elucidated. Ferroptosis, a recently discovered regulated form of non-apoptotic cell death, plays a vital role in the development of diabetes and its complications. The current study aimed to identify the key molecules involved in β-cell ferroptosis3 in patients with T2D using the mRNA expression profile data of GSE25724 by bioinformatic approaches. The differentially expressed mRNAs (DE-mRNAs) in human islets of patients with T2D were screened using the islet mRNA expression profiling data from the Gene Expression Omnibus and their intersection with ferroptosis genes was then obtained. Ferroptosis-related DE-mRNA functional and pathway enrichment analysis in T2D islet were performed. Using a protein-protein interaction (PPI) network constructed from the STRING database, Cytoscape software identified ferroptosis-related hub genes in the T2D islet with a Degree algorithm. We constructed a miRNA-hub gene network using the miRWalk database. We generated a rat model of T2D to assess the expression of hub genes. A total of 1,316 DE-mRNAs were identified in the islet of patients between T2D and non-T2D (NT2D), including 221 and 1,095 up- and down-regulated genes. Gene set enrichment analysis revealed that the ferroptosis-related gene set was significantly different in islets between T2D and NT2D at an overall level. A total of 33 ferroptosis-related DE-mRNAs were identified, most of which were significantly enriched in pathways including ferroptosis. The established PPI network with ferroptosis-related DE-mRNAs identified five hub genes (JUN, NFE2L2, ATG5, KRAS, and HSPA5), and the area under the ROC curve of these five hub genes was 0.929 in the Logistic regression model. We constructed a regulatory network of hub genes and miRNAs, and the results showed that suggesting that hsa-miR-6855-5p, hsa-miR-9985, and hsa-miR-584-5p could regulate most hub genes. In rat model of T2D, the protein expression levels of JUN and NFE2L2 in pancreatic tissues were upregulated and downregulated, respectively. These results contribute to further elucidation of ferroptosis-related molecular mechanisms in the pathogenesis of β-cell dysfunction of T2D.

BTC as a Novel Biomarker Contributing to EMT via the PI3K-AKT Pathway in OSCC.

Purpose: Oral squamous cell carcinoma (OSCC) is one of the most common malignant tumors of the head and neck, while metastasis is the main cause of OSCC-related death. There is an urgent need to explore novel prognostic biomarkers and identify biological targets related to metastasis in OSCC treatment. Methods: Analysis of differential expression was performed using datasets in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Immunohistochemistry (IHC) was conducted to assess the expression of betacellulin (BTC) in OSCC. SCC4 and CAL27 cells were used for in vitro experiments, in which CCK-8, transwell assays, and wounding healing assays were performed to verify the biological functions of BTC. The role of BTC in EMT was analyzed by EMT score and Western blot. Results: Through the analysis of the mRNA expression profile data from TCGA database in OSCC, we found that only low expression of BTC was significantly correlated with a poor prognosis in OSCC patients. The results of IHC assays and TCGA databases showed that the expression level of BTC was related to the tumor stage, histological grade, and metastasis status. In vitro analysis showed that overexpression of BTC significantly suppressed the proliferation and migration of OSCC cells. Furthermore, we confirmed that BTC could affect EMT through the PI3K-AKT signaling pathway. Conclusion: The overexpression of BTC suppresses the proliferation, migration, and EMT of OSCC cells via the PI3K-AKT pathways, leading to a better prognosis in OSCC. BTC may be used as a novel molecular marker to assess the prognosis of OSCC patients.

Identification of miRNA-mRNA Pairs in the Alzheimer's Disease Expression Profile and Explore the Effect of miR-26a-5p/PTGS2 on Amyloid-β Induced Neurotoxicity in Alzheimer's Disease Cell Model.

Alzheimer’s disease (AD) is a progressive neurodegenerative disease and the most common type of dementia. MicroRNAs (miRNAs) have been extensively studied in many diseases, including AD. To identify the AD-specific differentially expressed miRNAs and mRNAs, we used bioinformatics analysis to study candidate miRNA–mRNA pairs involved in the pathogenesis of AD. These miRNA–mRNAs may serve as promising biomarkers for early diagnosis or targeted therapy of AD patients. In this study, based on the AD mRNA and miRNA expression profile data in Gene Expression Omnibus (GEO), through differential expression analysis, functional annotation and enrichment analysis, weighted gene co-expression network analysis, miRNA–mRNA regulatory network, protein–protein interaction network, receiver operator characteristic and Least absolute shrinkage and selection operator (LASSO) regression and other analysis, we screened the key miRNA–mRNA in the progress of AD: miR-26a-5p/PTGS2. Dual-luciferase and qPCR experiments confirmed that PTGS2 is a direct target gene of miR-26a-5p. The expression of miR-26a-5p in the peripheral blood of AD patients and AD model cells (SH-SY5Y cells treated with Aβ25–35) was up-regulated, and the expression of PTGS2 was down-regulated. Functional gain -loss experiments confirmed that PTGS2 protects AD model cells from damage by inhibiting proliferation and migration. However, the expression of miR-26a-5p promotes the proliferation of AD model cells. It is further found that PTGS2 is involved in the regulation of miR-26a-5p and can reverse the effect of miR-26a-5p on the proliferation of AD model cells. In addition, through network pharmacology, qPCR and CCK-8, we found that baicalein may affect the progression of AD by regulating the expression of PTGS2. Therefore, PTGS2 can be used as a target for AD research, and miR-26a-5p/PTGS2 can be used as an axis of action to study the pathogenesis of AD.