Gene Expression Database Research Articles

#1437 Renal expression pattern of the relaxin receptor, RXFP1, and effects of the RXFP1 agonist, AZD5462, on renin in non-human primates and humans

Abstract Background and Aims RXFP1 is a G protein-coupled receptor (GPCR) for the pregnancy hormone, relaxin. While preclinical studies, performed primarily in rodent, describe beneficial effects of this pleiotropic peptide across several organ systems, there has been a disappointing lack of success in translating these observations into clinical benefit. To provide a potential pharmacological explanation accounting for this translational gap, the aim of this study was thus to thoroughly evaluate RXFP1 expression across species and tissues as well as to evaluate the renal-intrinsic effects of the RXFP1 agonist, AZD5462. Method Unbiased bioinformatic analysis of several gene expression databases was used as a first approach to compare RXFP1 tissue-level expression between rodent and human. Experimental validation was subsequently performed using scRNAseq, RNAscope and immunohistochemistry on mouse, rat, non-human primate (NHP) and human kidney. The putative renal target engagement effects of RXFP1 agonism were assessed by determining the acute and chronic effects of the RXFP1-selective small molecule agonist, AZD5462, on plasma renin concentrations in both NHPs and in a Phase 1 randomized, single-blind, placebo-controlled study in healthy humans. Results RXFP1 was identified as one of the most highly expressed GPCRs in human and NHP kidney glomeruli. Specifically, by multiple assays, we identified glomerular endothelial cells as the principal cell type expressing RXFP1. This observation is in stark contrast to mouse and rat kidney, where RXFP1 was not readily detected. AZD5462 administered orally to NHPs and healthy human participants elicited an early and sustained dose-dependent increase in plasma renin concentration, and in humans an additional decline in serum creatinine. Conclusion Human RXFP1 kidney glomerular expression is conserved with NHPs but not rodent, thus highlighting the translational and pharmacological challenges in studying RXFP1/relaxin biology across species. The concordant ability of AZD5462 to induce elevations in renin and reduction in serum creatinine, together with relaxin's reported renal-hemodynamic activity in humans, may underlie a previously unappreciated renal-intrinsic RXFP1 target engagement mechanism driving its hemodynamic and renal effects. The potential therapeutic benefits of RXFP1 agonism are the subject of on-going clinical trials in heart failure patients.

Sex-specific developmental gene expression atlas unveils dimorphic gene networks in C. elegans

Sex-specific traits and behaviors emerge during development by the acquisition of unique properties in the nervous system of each sex. However, the genetic events responsible for introducing these sex-specific features remain poorly understood. In this study, we create a comprehensive gene expression atlas of pure populations of hermaphrodites and males of the nematode Caenorhabditis elegans across development. We discover numerous differentially expressed genes, including neuronal gene families like transcription factors, neuropeptides, and G protein-coupled receptors. We identify INS-39, an insulin-like peptide, as a prominent male-biased gene expressed specifically in ciliated sensory neurons. We show that INS-39 serves as an early-stage male marker, facilitating the effective isolation of males in high-throughput experiments. Through complex and sex-specific regulation, ins-39 plays pleiotropic sexually dimorphic roles in various behaviors, while also playing a shared, dimorphic role in early life stress. This study offers a comparative sexual and developmental gene expression database for C. elegans. Furthermore, it highlights conserved genes that may underlie the sexually dimorphic manifestation of different human diseases.

Integrative analyses identified gap junction beta-2 as a prognostic biomarker and therapeutic target for breast cancer.

Increasing evidence has shown that connexins are involved in the regulation of tumor development, immune escape, and drug resistance. This study investigated the gene expression patterns, prognostic values, and potential mechanisms of connexins in breast cancer. We conducted a comprehensive analysis of connexins using public gene and protein expression databases and clinical samples from our institution. Connexin mRNA expressions in breast cancer and matched normal tissues were compared, and multiomics studies were performed. Gap junction beta-2 mRNA was overexpressed in breast cancers of different pathological types and molecular subtypes, and its high expression was associated with poor prognosis. The tumor membrane of the gap junction beta-2 mutated group was positive, and the corresponding protein was expressed. Somatic mutation and copy number variation of gap junction beta-2 are rare in breast cancer. The gap junction beta-2 transcription level in the p110α subunit of the phosphoinositide 3-kinase mutant subgroup was higher than that in the wild-type subgroup. Gap junction beta-2 was associated with the phosphoinositide 3-kinase-Akt signaling pathway, extracellular matrix-receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, gap junction beta-2 overexpression may be associated with phosphoinositide 3-kinase and histone deacetylase inhibitor resistance, and its expression level correlated with infiltrating CD8+ T cells, macrophages, neutrophils, and dendritic cells. Gap junction beta-2 may be a promising therapeutic target for targeted therapy and immunotherapy and may be used to predict breast cancer prognosis.

A Comprehensive Analysis of HOXB13 Expression in Hepatocellular Carcinoma.

Background and objectives: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and is caused by multiple factors. To explore novel targets for HCC treatment, we comprehensively analyzed the expression of HomeoboxB13 (HOXB13) and its role in HCC. Materials and Methods: The clinical significance of HCC was investigated using open gene expression databases, such as TIMER, UALCAN, KM, OSlihc, and LinkedOmics, and immunohistochemistry analysis. We also analyzed cell invasion and migration in HCC cell lines transfected with HOXB13-siRNA and their association with MMP9, E2F1, and MEIS1. Results: HOXB13 expression was higher in fibrolamellar carcinoma than in other histological subtypes. Its expression was associated with lymph node metastasis, histological stage, and tumor grade. It was positively correlated with immune cell infiltration of B cells (R = 0.246), macrophages (R = 0.182), myeloid dendritic cells (R = 0.247), neutrophils (R = 0.117), and CD4+ T cells (R = 0.258) and negatively correlated with immune cell infiltration of CD8+ T cells (R = -0.107). A positive correlation was observed between HOXB13, MMP9 (R = 0.176), E2F1 (R = 0.241), and MEIS1 (R = 0.189) expression (p < 0.001). The expression level of HOXB13 was significantly downregulated in both HepG2 and PLC/PFR/5 cell lines transfected with HOXB13-siRNA compared to that in cells transfected with NC siRNA (p < 0.05). Additionally, HOXB13 significantly affected cell viability and wound healing. Conclusions: HOXB13 overexpression may lead to poor prognosis in patients with HCC. Additional in vivo studies are required to improve our understanding of the biological role and the exact mechanism of action of HOXB13 in HCC.

DNA Damage-Induced Apoptosis Suppressor Triggers Progression and Stemness of Glioma by Enhancing Lymphoid Enhancer-Binding Factor 1 Expression.

DNA damage-induced apoptosis suppressor (DDIAS) has recently been discovered to induce cancer progression, but its functions and mechanisms in glioma have not been well studied. DDIAS expression in glioma tissues was analyzed by the Gene Expression Profiling Interactive Analysis server (GEPIA) and the Gene Expression database of Normal and Tumor tissue 2 (GENT2) databases. The role of DDIAS in glioma progression was studied by short hairpin RNA (shRNA) targeting DDIAS. The effects of DDIAS on glioma cell viability, cell proliferation, invasion, migration, and tumor sphere formation were determined by cell counting kit-8 (CCK-8), EdU, Transwell, tumor spheroid formation, extreme limiting dilution analysis assays in vitro and xenograft model construction in vivo. In addition, RNA sequencing and further functional experiments were used to analyze the DDIAS regulatory mechanism in glioma. We found that DDIAS was highly expressed in glioma and that upregulated DDIAS indicated poor prognosis. Functionally, DDIAS knockdown inhibited glioma cell viability, cell proliferation, invasion and migration in vitro and tumor growth in vivo. In addition, lymphoid enhancer-binding factor 1 (LEF1) was identified as the downstream effector of DDIAS by RNA sequencing. DDIAS downregulation inhibited LEF1 mRNA and protein expression. The expression of DDIAS and LEF1 was positively correlated, and LEF1 overexpression rescued the inhibitory phenotype induced by DDIAS downregulation. We further showed that DDIAS downregulation inhibited cyclin A1, vimentin and the stemness-related factor CD133 and decreased the sphere formation capability, but these features were rescued by upregulation of LEF1. Taken together, these findings suggest that DDIAS promotes glioma progression and stemness by inducing LEF1 expression, proving that DDIAS may be a potential target for the treatment of glioma.

Mouse Genome Informatics: an integrated knowledgebase system for the laboratory mouse.

Mouse Genome Informatics (MGI) is a federation of expertly curated information resources designed to support experimental and computational investigations into genetic and genomic aspects of human biology and disease using the laboratory mouse as a model system. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are core MGI databases that share data and system architecture. MGI serves as the central community resource of integrated information about mouse genome features, variation, expression, gene function, phenotype, and human disease models acquired from peer-reviewed publications, author submissions, and major bioinformatics resources. To facilitate integration and standardization of data, biocuration scientists annotate using terms from controlled metadata vocabularies and biological ontologies (e.g. Mammalian Phenotype Ontology, Mouse Developmental Anatomy, Disease Ontology, Gene Ontology, etc.), and by applying international community standards for gene, allele, and mouse strain nomenclature. MGI serves basic scientists, translational researchers, and data scientists by providing access to FAIR-compliant data in both human-readable and compute-ready formats. The MGI resource is accessible at https://informatics.jax.org. Here, we present an overview of the core data types represented in MGI and highlight recent enhancements to the resource with a focus on new data and functionality for MGD and GXD.

CCL20 and CD8A as potential diagnostic biomarkers for HBV-induced liver fibrosis in chronic hepatitis B

BackgroundThe main cause of the liver fibrosis (LF) remains hepatitis B virus (HBV) infection, especially in China. Histologically, liver fibrosis still occurs progressively in chronic hepatitis B (CHB) patients, even if HBV-DNA is negative or undetectable. The diagnosis of LF is beneficial to control the development of it, also it may promote the reversal of LF. Although liver biopsy is the gold standard of diagnosis in LF at present, it isa traumatic diagnosis. There are no diagnostic biomarkers as yet for the condition. It is badly in need of biomarkers clinically, which is simple to test, minimally invasive, highly specific, and sensitive. Early detection of HBV-LF development is crucial in the prevention, treatment, and prognosis prediction of HBV-LF. Cytokines are closely associated with both immune regulation and inflammation in the progression of hepatitis B virus associated-liver fibrosis (HBV-LF). In this bioinformatic study, we not only analyzed the relationship between HBV-LF and immune infiltration, but also identified key genes to uncover new therapeutic targets. ObjectivesTo find potential biomarkers for liver fibrosis in the development of chronic hepatic B patients. Materials and methodsWe obtained two sets of data including CHB/healthy control and CHB/HBV-LF from the Integrated Gene Expression (GEO) database to select for differential expression analysis. Protein-protein interaction (PPI) network was also generated, while key genes and important gene modules involved in the occurrence and development of HBV-LF were identified. These key genes were analyzed by functional enrichment analysis, module analysis, and survival analysis. Furthermore, the relationship between these two diseases and immune infiltration was explored. ResultsAmong the identified genes, 150 were individually associated with CHB and healthy control in the differential gene expression (DGE) analysis. While 14 with CHB and HBV-LF. It was also analyzed in the Robust rank aggregation (RRA) analysis, 34 differential genes were further identified by Cytohubba. Among 34 differential genes, two core genes were determined: CCL20 and CD8A. CCL20 was able to predict CHB positivity (area under the receiver operating characteristic curve [AUC-ROC] = 0.883, 95% confidence interval [CI] 0.786–0.963), while HBV-LF positivity ([AUC-ROC] = 0.687, 95% confidence interval [CI] 0.592–0.779). And CD8A was able to predict CHB positivity ([AUC-ROC] = 0.960, 95% confidence interval [CI] 0.915–0.992), while HBV-LF positivity ([AUC-ROC] = 0.773, 95% confidence interval [CI] 0.680–0.856). Relationship between CCL20 gene expression and LF grades was P < 0.05, as well as CD8A. ConclusionCCL20 and CD8A were found to be potential biomarkers and therapeutic targets for HBV-LF. It is instructive for research on the progression of LF in HBV patients, suppression of chronic inflammation, and development of molecularly targeted-therapy for HBV-LF.

HIHISIV: a database of gene expression in HIV and SIV host immune response

In the battle of the host against lentiviral pathogenesis, the immune response is crucial. However, several questions remain unanswered about the interaction with different viruses and their influence on disease progression. The simian immunodeficiency virus (SIV) infecting nonhuman primates (NHP) is widely used as a model for the study of the human immunodeficiency virus (HIV) both because they are evolutionarily linked and because they share physiological and anatomical similarities that are largely explored to understand the disease progression. The HIHISIV database was developed to support researchers to integrate and evaluate the large number of transcriptional data associated with the presence/absence of the pathogen (SIV or HIV) and the host response (NHP and human). The datasets are composed of microarray and RNA-Seq gene expression data that were selected, curated, analyzed, enriched, and stored in a relational database. Six query templates comprise the main data analysis functions and the resulting information can be downloaded. The HIHISIV database, available at https://hihisiv.github.io, provides accurate resources for browsing and visualizing results and for more robust analyses of pre-existing data in transcriptome repositories.

Abstract 6150: MMP14 and MKLN1 as colorectal cancer susceptibility genes and a drug repurposing candidate from genome-wide association study in South Korea

Abstract Background: One of the major topics about colorectal cancer (CRC) is to find susceptible genes. Furthermore, functional interpretation of post-GWAS analysis gains attention and various approaches to find drug-repurposing candidates are used in cancer research. Our study aims to identify susceptible genes for CRC and provide drug-repurposing candidates. Methods: CRC patients in Seoul National University Hospital with prospective follow-up were recruited. From blood-derived DNA, genome-wide SNPs were genotyped using the Korea Biobank Array and 409,063 SNPs were extracted. SNP-based logistic regression model was fit for the event of CRC estimating beta values. Furthermore, post-GWAS analysis was conducted using regulatory function, multiple annotation and gene expression database. Drug-repurposing candidate was identified through the pre-trained deep neural network with susceptible genes. Results: We used 500 participants of CRC cases and 1,500 participants of healthy controls. For GWAS, statistically significant associations were mapped to MKLN1, MMP14, PTPN14 and MKL2 genes. For post-GWAS analysis, strong associations were found for MKLN1 (rs75170436, 7q32.3, Beta=-0.90, P-value=5.90×10-13) and MMP14 (rs3751489, 14q11.2, Beta=-1.91, P-value=2.31×10-12). From the drug-repurposing analysis, PPARδ/β agonist (GW0742; Binding score=3.79(MKLN1), 12.06(MMP14)) was identified for both genes with the highest score. Conclusions: We revealed MKLN1 and MMP14 genes as susceptible genes associated with CRC development. Additionally, we identified PPARδ/β agonist (GW0742) as a drug-repurposing candidate for the treatment of CRC. These findings can promote the understanding of CRC development and provide a novel therapeutic candidate for CRC patients in the future. Citation Format: Dabin Yun, Jung-Ho Yang, Sun-Seong Kweon, Jin-ah Sim, Minjung Kim, Ji Won Park, Seung Yong Jeong, Aesun Shin, Nan Song. MMP14 and MKLN1 as colorectal cancer susceptibility genes and a drug repurposing candidate from genome-wide association study in South Korea [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 6150.

Comprehensive pan-cancer analysis of 33 human cancers reveals immunotherapeutic value of focal adhesion tyrosine kinase.

The immune environment in tumors is the key factor affecting the survival and immunotherapeutic response of patients. This research aimed to explore the underlying association between focal adhesion tyrosine kinase (FAK/PTK2) and cancer immunotherapy in 33 human cancers. Gene expression data and clinical features of 33 cancers were retrieved from the Cancer Genome Atlas Database. The immunotherapy cohorts included GSE67501, GSE78220, and IMVIGOR210, which were derived from the comprehensive gene expression database or from previous studies. Clinical parameters including patient age, gender, survival rate, and tumor stage were analyzed to evaluate the prognostic value of FAK/PTK2. FAK/PTK2 activity was detected by single-sample gene set enrichment analysis and used to compare the difference between FAK/PTK2 transcriptome and protein expression levels. To better understand the role of FAK/PTK2 in cancer immunotherapy, we analyzed its correlations with tumor microenvironment and with immune processes/elements (e.g., immune cell infiltration, immunosuppressants, and stimulants) and major histocompatible complexes. Potential pathways associated with FAK/PTK2 signaling in cancers were also explored. Correlations between FAK/PTK2 and 2 immunotherapeutic biomarkers (tumor mutation load and microsatellite instability) were studied. Finally, the 3 independent immunotherapy cohorts were used to study the relationship between FAK/PTK2 and immunotherapeutic response. Although FAK/PTK2 is not closely associated with age (13/33), gender (5/33), or tumor stage (5/33) in any of the studied human cancers, it has potential prognostic value for predicting patient survival. Consistency between FAK/PTK2 activity and expression exists in some cancers (3/33). Generally, FAK/PTK2 is robustly correlated with immune cell infiltration, immune modulators, and immunotherapeutic markers. Moreover, high FAK/PTK2 expression is significantly related to immune-relevant pathways. However, FAK/PTK2 is not significantly correlated with the immunotherapeutic response. Research on the immunotherapeutic value of FAK/PTK2 in 33 human cancers provides evidence regarding the function of FAK/PTK2 and its role in clinical treatment. However, given the use of a bioinformatics approach, our results are preliminary and require further validation.

PvGeneExpDB: An integrative gene expression database for in-depth understanding on the Pacific white shrimp (Litopenaeus vannamei)

The Pacific white shrimp (Litopenaeus vannamei) is a high-valued economic farming species. With the development of high-throughput sequencing technology, cumulative large-scale transcriptomic studies have been revealing molecular landscape of various biological conditions including genetic selection, breeding, evolution, disease landscape, etc. However, no single experiment or databases allow thorough investigations of transcriptomic dynamics for these progressions. Meanwhile, the available datasets are often scattered and lack management. Here, we have established PvGeneExpDB, the first gene expression database for L. vannamei (www.bio-marine-scau.com/pv_ex/), which encompasses gene expression profiles, differential expression, and co-expression analyses under various biological conditions. Based on the analyses of 7 datasets, which include 53 samples with accurate and detailed records, PvGeneExpDB identifies 20,599 novel transcripts, shows expression profiles of a total of 20,817 genes, and implements Gene Ontology (GO) reconstruction of 76.7 % of these genes. Besides, 26 co-expressed groups were first identified by large-scale, cross-sample Weighted Gene Co-expression Network Analysis (WGCNA). By integrating the gene expression data in the database, our goal is to deepen the biological understanding of L. vannamei.

Integrated transcriptome and proteome analysis reveals the unique molecular features and nutritional components on the muscles in Chinese Taihe black-bone silky fowl chicken.

The Taihe Black-Bone silky fowl chicken (BB-sfc) is a renowned dietary and medicinal chicken globally recognized for its high nutritional and medicinal value. Compared to the local Black-Bone black-feathered chicken (BB-bfc), the Taihe silky fowl chicken has higher levels of amino acids, trace elements, and unsaturated fatty acids in their muscles, which offer anti-aging, anti-cancer, and immune enhancing benefits. Despite this, the unique nutritional components, genes, and proteins in Taihe silky fowl chicken muscles are largely unknown. Therefore, we performed a comprehensive transcriptome and proteome analysis of muscle development between BB-sfc and BB-bfc chickens using RNA-Seq and TMT-based quantitative proteomics methods. RNA-Seq analysis identified 286 up-regulated genes and 190 down-regulated genes in BB-sfc chickens, with oxidoreductase activity and electron transfer activity enriched in up-regulated genes, and phospholipid homeostasis and cholesterol transporter activity enriched in down-regulated genes. Proteome analysis revealed 186 significantly increased and 287 significantly decreased proteins in Taihe BB-sfc chicken muscles, primarily affecting mitochondrial function and oxidative phosphorylation, crucial for enhancing muscle antioxidant capacity. Integrated transcriptome and proteome analysis identified 6 overlapped up-regulated genes and 8 overlapped down-regulated genes in Taihe silky fowl chicken, related to improved muscle antioxidant status. Taken together, this research provides a comprehensive database of gene expression and protein information in Taihe Black-Bone silky fowl chicken muscles, aiding in fully exploring their unique economic value in the future.

Inhibition of O6‐methylguanine‐DNA‐methyltransferase (MGMT) by lomeguatrib reduces multiple myeloma cell viability and impairs DNA repair in MGMT‐proficient cells

AbstractThe function of direct DNA damage repair protein, namely MGMT in MM, and the impact of MGMT on melphalan treatment remains unclear. We showed a significantly higher MGMT mRNA expression in CD138+ myeloma cells than in matched CD138‐nontumorigenic cells derived from newly diagnosed and relapsed/refractory MM patients using qPCR. However, using gene expression databases, a similar expression of MGMT was observed during disease progression. MGMT depletion by its specific inhibitor lomeguatrib reduced myeloma cell viability, impaired S phase entry and DNA repair, and increased DNA damage and apoptosis. Apoptosis and DNA damage were further elevated by combined treatment with lomeguatrib and melphalan in RPMI 8226 cells. This is the first study demonstrating MGMT inhibition enhances DNA damage‐induced apoptosis and melphalan cytotoxicity in MGMT‐proficient MM cells and suggesting using lomeguatrib might have clinical importance in treating MM and overcoming melphalan resistance in MGMT‐proficient patients.

Exploring the comorbidity mechanisms between psoriasis and obesity based on bioinformatics.

Psoriasis is a chronic, recurrent, immune-mediated inflammatory skin disease characterized by erythematous scaly lesions. Obesity is currently a major global health concern, increasing the risk of diseases such as cardiovascular diseases and diabetes. Since the correlation between psoriasis and obesity, as well as hypertension, diabetes, and cardiovascular diseases, has been clinically evidenced, it is of certain clinical significance to explore the mechanisms underlying the comorbidity of psoriasis with these conditions. Gene targets for both diseases were obtained from the Gene Expression Omnibus (GEO) comprehensive gene expression database. Differential gene analysis, intersection gene analysis, construction and visualization of protein-protein interaction networks (PPI) using R software, Cytoscape 3.8.2 software, online tools such as String, and enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed, with relevant graphics generated. Analysis identified 29 intersecting genes between the two diseases, with 10 key targets such as S100A7 and SERPINB4. Enrichment analysis indicated their involvement in regulating biological processes such as leukocyte chemotaxis, migration, and chronic inflammatory responses through cellular structures such as intracellular vesicles and extracellular matrix. Molecular functions, including RAGE receptor binding, Toll-like receptor binding, and fatty acid binding, were found to simultaneously regulate psoriasis and obesity. Psoriasis and obesity may mutually influence each other through multiple targets and pathways, emphasizing the importance of considering comorbidity treatment and daily care in clinical practice.

Evaluation of ABT-751, a novel anti-mitotic agent able to overcome multi-drug resistance, in melanoma cells

PurposeDrug efflux transporter associated multi-drug resistance (MDR) is a potential limitation in the use of taxane chemotherapies for the treatment of metastatic melanoma. ABT-751 is an orally bioavailable microtubule-binding agent capable of overcoming MDR and proposed as an alternative to taxane-based therapies.MethodsThis study compares ABT-751 to taxanes in vitro, utilizing seven melanoma cell line models, publicly available gene expression and drug sensitivity databases, a lung cancer cell line model of MDR drug efflux transporter overexpression (DLKP-A), and drug efflux transporter ATPase assays.ResultsMelanoma cell lines exhibit a low but variable protein and RNA expression of drug efflux transporters P-gp, BCRP, and MDR3. Expression of P-gp and MDR3 correlates with sensitivity to taxanes, but not to ABT-751. The anti-proliferative IC50 profile of ABT-751 was higher than the taxanes docetaxel and paclitaxel in the melanoma cell line panel, but fell within clinically achievable parameters. ABT-751 IC50 was not impacted by P-gp-overexpression in DKLP-A cells, which display strong resistance to the P-gp substrate taxanes compared to DLKP parental controls. The addition of ABT-751 to paclitaxel treatment significantly decreased cell proliferation, suggesting some reversal of MDR. ATPase activity assays suggest that ABT-751 is a potential BCRP substrate, with the ability to inhibit P-gp ATPase activity.ConclusionOur study confirms that ABT-751 is active against melanoma cell lines and models of MDR at physiologically relevant concentrations, it inhibits P-gp ATPase activity, and it may be a BCRP and/or MDR3 substrate. ABT-751 warrants further investigation alone or in tandem with other drug efflux transporter inhibitors for hard-to-treat MDR melanoma.

Predicting Survival in Glioblastoma Using Gene Expression Databases: A Neural Network Analysis.

Glioblastoma (GBM) is the most aggressive and lethal brain tumor. Artificial neural networks (ANNs) have the potential to make accurate predictions and improve decision making. The aim of this study was to create an ANN model to predict 15-month survival in GBM patients according to gene expression databases. Genomic data of GBM were downloaded from the CGGA, TCGA, MYO, and CPTAC. Logistic regression (LR) and ANN model were used. Age, gender, IDH wild-type/mutant and the 31 most important genes from our previous study, were determined as input factors for the established ANN model. 15-month survival time was used to evaluate the results. The normalized importance scores of each covariate were calculated using the selected ANN model. The area under a receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow (H-L) statistic and accuracy of prediction were measured to evaluate the two models. SPSS 26 was utilized. A total of 551 patients (61% male, mean age 55.5 ± 13.3 years) patients were divided into training, testing, and validation datasets of 441, 55 and 55 patients, respectively. The main candidate genes found were: FN1, ICAM1, MYD88, IL10, and CCL2 with the ANN model; and MMP9, MYD88, and CDK4 with LR model. The AUCs were 0.71 for the LR and 0.81 for the ANN analysis. Compared to the LR model, the ANN model showed better results: Accuracy rate, 83.3 %; H-L statistic, 6.5 %; and AUC, 0.81 % of patients. The findings show that ANNs can accurately predict the 15-month survival in GBM patients and contribute to precise medical treatment.

HIF-1A as a prognostic biomarker related to invasion, migration and immunosuppression of cervical cancer

BackgroundThe incidence of cervical cancer ranks second among malignant tumors in women, exerting a significant impact on their quality of life and overall well-being. The hypoxic microenvironment plays a pivotal role in the initiation and progression of tumorigenesis. The present study aims to investigate the fundamental genes and pathways associated with the hypoxia-inducible factor (HIF-1A) in cervical cancer, aiming to identify potential downstream targets for diagnostic and therapeutic purposes. MethodsWe obtained dataset GSE63514 from the Comprehensive Gene Expression Database (GEO). The dataset comprised of 24 patients in the normal group and 28 patients in the tumor group. Gene set difference analysis (GSVA) and gene set enrichment analysis (GSEA) were used to identify the genes related to HIF-1A expression and the specific signaling pathways involved.The association between HIF-1A and tumor immune infiltration was examined in the TCGA dataset. The WGCAN network was constructed to identify key genes within the blue module, and subsequent gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to determine the pathways and functional annotations associated with HIF-1A. The protein interaction network of the HIF-1A gene was obtained from the STRING database and visualized using Cytoscape in the meantime.The function of HIF-1A and its related gene expression were verified in vivo. ResultsHIF-1A was a risk factor in both univariate and multivariate Cox regression analysis of cervical cancer patients. A total of 344 genes significantly correlated with the expression of HIF-1A were identified through correlation analysis, and the genes exhibiting the strongest correlation were obtained. The major signaling pathways involved in HIF-1A encompass TNF-α/NF-κB, PI3K/AKT/MTOR, TGF-β, JAK-STAT, and various other signaling cascades. Reinforced by qRT-PCR, we identified Integrin beta-1 (ITGB1), C–C motif chemokine ligand 2 (CCL2), striatin 3 (STRN3), and endothelin-1 (EDN1) as pivotal downstream genes influenced by HIF-1A. HIF-1A is associated with immune infiltration of natural killer (NK) cells, mast cells, CD4+T cells, M0 macrophages, neutrophils, follicular helper T cells, CD8+T cells, and regulatory T cells (Treg). HIF-1A is associated with sensitivity to chemotherapy drugs. The identification of the HIF-1A pathway and its function primarily focuses on cytoplasmic translation, aerobic respiration, cellular respiration, oxidative phosphorylation, thermogenesis, among others. The results of in vivo experiments have confirmed that HIF-1A plays a crucial role in promoting the migration and invasion of cervical cancer cells. Moreover, the overexpression of HIF-1A led to an upregulation in the expressions of ITGB1, CCL2, STRN3, and EDN1. ConclusionsThe role of HIF-1A in cervical cancer was determined through a combination of bioinformatics analysis and experimental validation. The genes potentially implicated in the tumorigenesis mechanism of HIF-1A were identified. These findings has the potential to enhance our comprehension of the progression of cervical cancer and offer promising therapeutic targets for its clinical management.

Identification and verification of feature biomarkers associated with immune cells in recurrent pregnancy loss.

The aim of this study was to investigate the causes, diagnostic markers, and treatment methods for recurrent pregnancy loss (RPL) using bioinformatics approaches. Bioinformatics methods were utilized to analyze gene expression databases to identify key genes and modules associated with RPL. Weighted gene co-expression network analysis (WGCNA) was employed to identify gene sets related to maternal-fetal immunity. Gene set variation analysis (GSVA) and protein-protein interaction networks were used to explore signaling pathways and molecular interactions in RPL. Immune cell infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA). Thirteen genes were identified as potential diagnostic markers, some of which were involved in placental amino acid transport, glucose absorption, and reactive oxygen species production. Several gene sets related to protein transport, steroid synthesis, and glycosaminoglycan degradation were found to be associated with RPL. Immune cell infiltration analysis found that CD56bright NK cells and monocytes showed significantly increased infiltration in RPL and were associated with key hub genes. The validation of hub genes, including PCSK5, CCND2, SLC5A3, RASAL1, MYZAP, MFAP4, and P2RY14, as potential diagnostic markers, showed promising value. This study contributes to a better understanding of the etiology of RPL and potential diagnostic markers. The identified immune-related gene sets, signaling pathways, and immune cell infiltrations provide valuable insights for future research and therapeutic advancements in RPL.

In-depth analysis of prognostic markers associated with the tumor immune microenvironment and genetic mutations in breast cancer based on an NK cell-related risk model

The natural killer (NK) cell population is unique because it consists of innate lymphocytes capable of detecting and eliminating tumors and virus-infected cells. This research aims to identify a new prognostic signal in breast cancer (BRCA) based on NK-cell-related genes (NKRGs). A variety of sequencing and gene mutation data, along with clinical information, were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Database (GEO). COX regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were conducted to identify prognostic genes. In addition, the immune-related analysis was performed to evaluate the association between the immune microenvironment and clusters and risk model. The Edu assay, colony assay, wound healing assay, and transwell assay were performed to evaluate the cell proliferative and invasive abilities. A 4-NKRG-based prognostic model was constructed. Patients in high-risk groups were associated with poorer OS in TCGA and GSE42568. Further, a nomogram was constructed for better prediction of the prognosis of patients with BRCA. Finally, it was discovered that the over-expression of IFNE could suppress the proliferative and invasive abilities of BRCA cells, which might be a promising biomarker for patients with BRCA. As a result, we developed a novel 4-NKRG signal and nomogram capable of predicting the prognosis of patients with BRCA. Additionally, this model was closely associated with the immune microenvironment, which opened new therapeutic avenues for the treatment of cancer in the future.

Comprehensive Analysis of N6-Methyladenosine RNA Methylation Regulators in the Diagnosis and Subtype Classification of Rheumatoid Arthritis.

m6A modification is the most abundant mRNA modifications and plays an integral role in various biological processes in eukaryotes. However, the role of m6A regulators in rheumatoid arthritis remains unknown. To determine the expression of m6A RNA methylation regulators in rheumatoid arthritis and their possible functional and prognostic value. In this study, we performed differential analysis in the comprehensive gene expression database GSE93272 dataset between non-rheumatoid arthritis patients and rheumatoid arthritis patients to obtain 15 important m6A regulators. A random forest model and lasso regression were used to screen the five most important m6A regulators to predict the risk of developing rheumatoid arthritis. After further validation using in vitro qPCR experiments, a nomogram model was developed based on the four most important m6A regulators (ELAVL1, WTAP, YTHDF1, and ALKBH5). Immuno-infiltration analysis and consensus clustering analysis were then performed. An analysis of the decision curve showed that the nomogram model could be beneficial to patients. According to selected important m6A regulators, patients with rheumatoid arthritis were classified into two m6A models (ClusterA and ClusterB) via consensus approach. Activated B cells, CD56dim natural killer cells, immature B cells, monocytes, natural killer T cells, and T lymphocytes were associated with ClusterA in immune infiltration analysis. Importantly, immune infiltration in patients with high ELAVL1 expression was strikingly similar to ClusterA. m6A regulators play a non-negligible role in the development of rheumatoid arthritis. A study of m6A patterns may provide future therapeutic options for rheumatoid arthritis.