Gene Interaction Network Analysis Research Articles

Gene-gene interaction network analysis indicates CNTN2 is a candidate gene for idiopathic generalized epilepsy.

Twin and family studies have established the genetic contribution to idiopathic generalized epilepsy (IGE). The genetic architecture of IGE is generally complex and heterogeneous, and the majority of the genetic burden in IGE remains unsolved. We hypothesize that gene-gene interactions contribute to the complex inheritance of IGE. CNTN2 (OMIM* 615,400) variants have been identified in cases with familial adult myoclonic epilepsy and other epilepsies. To explore the gene-gene interaction network in IGE, we took the CNTN2 gene as an example and investigated its co-occurrent genetic variants in IGE cases. We performed whole-exome sequencing in 114 unrelated IGE cases and 296 healthy controls. Variants were qualified with sequencing quality, minor allele frequency, in silico prediction, genetic phenotype, and recurrent case numbers. The STRING_TOP25 gene interaction network analysis was introduced with the bait gene CNTN2 (denoted as A). The gene-gene interaction pair mode was presumed to be A + c, A + d, A + e, with a leading gene A, or A + B + f, A + B + g, A + B + h, with a double-gene A + B, or other combinations. We compared the number of gene interaction pairs between the case and control groups. We identified three pairs in the case group, CNTN2 + PTPN18, CNTN2 + CNTN1 + ANK2 + ANK3 + SNTG2, and CNTN2 + PTPRZ1, while we did not discover any pairs in the control group. The number of gene interaction pairs in the case group was much more than in the control group (p = 0.021). Taking together the genetic bioinformatics, reported epilepsy cases, and statistical evidence in the study, we supposed CNTN2 as a candidate pathogenic gene for IGE. The gene interaction network analysis might help screen candidate genes for IGE or other complex genetic disorders.

Recognizing the role of Epstein-Barr virus in gastric cancer: transcriptomic insights into malignancy modulation

BackgroundStudies show that Epstein-Barr virus (EBV) infection can play a role in malignancy and increase the risk of gastric cancer (GC). The objective of this research was to pinpoint genes whose expression may be influenced by EBV and play a role in the development of GC.MethodsCandidate genes potentially susceptible to expression modulation in the presence of EBV were identified through the analysis of GSE185627 and GSE51575 datasets. The association of candidate genes with GC and the survival rate of patients was investigated based on the cancer genome atlas (TCGA) data. Also, pathways related to candidate genes were examined through the MsigDB database. The PPI network was used to identify Hub genes. To corroborate the obtained results, we utilized the RT-qPCR method, employing GC samples from both EBV + and EBV-cases, as well as adjacent normal samples.ResultsOur results showed that genes upregulated by the EBV in the GC cell line, as well as in EBV + samples, are significantly linked to pathways involving the immune response, inflammation, and the P53 pathway. Conversely, genes downregulated by EBV are closely linked to pathways involving cell proliferation and mTORC1. Examining the candidate genes revealed that a considerable portion of genes susceptible to downregulation under the influence of EBV exhibit oncogenic roles based on TCGA data. Moreover, some of these genes are associated with an unfavorable prognosis. Protein-protein interaction network analysis of candidate genes highlighted IFI44L and OAS2 as potential hub genes in the EBV-GC axis. Our RT-qPCR results further validated these findings, demonstrating that the expression levels of IFI44L and OAS2 were higher in EBV + samples compared to both healthy and EBV-samples.ConclusionOur study underscores the capacity of EBV to exert regulatory control over genes associated with GC malignancy. In addition to its inflammatory effects, EBV elicits transcriptomic changes that appear to attenuate the progression of GC.

Construction of a co-expression network affecting intramuscular fat content and meat color redness based on transcriptome analysis.

Introduction: Intramuscular fat content (IFC) and meat color are vital indicators of pork quality. Methods: A significant positive correlation between IFC and redness of meat color (CIE a* value) indicates that these two traits are likely to be regulated by shared molecular pathways.To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and CIE a* value in 147 hybrid pigs, and selected individuls with extreme phenotypes for transcriptome analysis. Results: The results revealed 485 and 394 overlapping differentially expressed genes (DEGs), using the DESeq2, limma, and edgeR packages, affecting the IFC and CIE a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with the IFC and CIE a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting the IFC and CIE a* value, respectively. The protein protein interaction (PPI) network analysis of candidate genes showed that 5 and 13 hub genes affect the IFC and CIE a* value, respectively. These genes mainly participate in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. Discussion and conclusion: After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and the myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of the IFC and CIE a* value, which will provide a theoretical basis for improving pork quality.

Systematic analysis and expression of Gossypium ATG8 family reveals the roles of GhATG8f responding to salt stress in cotton.

Comprehensive analysis of Gossypium ATG8 family indicates that GhATG8f could improve salt tolerance of cotton by increasing SOD, POD and CAT activity and proline accumulation. In plants, autophagy is regulated by several genes that play important roles in initiating and controlling the process. ATG8, functioning as a protein similar to ubiquitin, is involved in crucial tasks throughout the autophagosome formation process. In this research, we conducted an extensive and all-encompassing investigation of 64 ATG8 genes across four varieties of cotton. According to the subcellular localization prediction results, 49 genes were found in the cytoplasm, 6 genes in the chloroplast, 1 gene in the peroxisome, 5 genes in the nucleus, and 3 genes in the extracellular region. Phylogenetic analysis categorized a total of 5 subfamilies containing sixty-four ATG8 genes. The expression of the majority of GhATG8 genes was induced by salt, drought, cold, and heat stresses, as revealed by RNA-seq and real-time PCR. Analysis of cis-elements in the promoters of GhATG8 genes revealed the predominant presence of responsive elements for plant hormones and abiotic stress, suggesting that GhATG8 genes might have significant functions in abiotic stress response. Furthermore, we additionally performed a gene interaction network analysis for the GhATG8 proteins. The salt stress resistance of cotton was reduced due to the downregulation of GhATG8f expression, resulting in decreased activity of CAT, SOD, and POD enzymes, as well as decreased fresh weight and proline accumulation. In summary, our research is the initial exploration of ATG8 gene components in cotton, providing a basis for future investigations into the regulatory mechanisms of ATG8 genes in autophagy and their response to abiotic stress.

[Mutational Signatures Analysis of Micropapillary Components and Exploration of ZNF469 Gene in Early-stage Lung Adenocarcinoma with Ground-glass Opacities].

In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P<0.05). Gene interaction network analysis and GO/KEGG enrichment analysis revealed that COL6A1, COL1A1, COL1A2, TGFB2, MMP2, COL8A2 and C2CD4C interacted with ZNF469 and were mainly involved in encoding collagen proteins and participating in the constitution of extracellular matrix. ZNF469 expression was positively correlated with immune cell infiltration in LUAD (P<0.05). The study has unveiled distinctive mutational signatures in the MPP components of early-stage invasive LUAD in the Asian population. Furthermore, we have identified that the elevated expression of mutated ZNF469 impacts the prognosis and immune infiltration in LUAD, suggesting its potential as a diagnostic and prognostic biomarker in LUAD.

Dermatophagoides farinae microRNAs released to external environments via exosomes regulate inflammation-related gene expression in human bronchial epithelial cells.

Dermatophagoides farinae (DFA) is an important species of house dust mites (HDMs) that causes allergic diseases. Previous studies have focused on allergens with protein components to explain the allergic effect of HDMs; however, there is little knowledge on the role of microRNAs (miRNAs) in the allergic effect of HDMs. This study aimed to unravel the new mechanism of dust mite sensitization from the perspective of cross-species transport of extracellular vesicles-encapsulated miRNAs from HDMs. Small RNA (sRNA) sequencing was performed to detect miRNAs expression profiles from DFA, DFA-derived exosomes and DFA culture supernatants. A quantitative fluorescent real-time PCR (qPCR) assay was used to detect miRNAs expression in dust specimens. BEAS-2B cells endocytosed exosomes were modeled in vitro to detect miRNAs from DFA and the expression of related inflammatory factors. Representative dfa-miR-276-3p and dfa-novel-miR2 were transfected into BEAS-2B cells, and then differentially expressed genes (DEGs) were analyzed by RNA sequencing. Protein-protein interaction (PPI) network analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) terms enrichment analyses were performed on the first 300 nodes of DEGs. sRNA sequencing identified 42 conserved miRNAs and 66 novel miRNAs in DFA, DFA-derived exosomes, and DFA culture supernatants. A homology analysis was performed on the top 18 conserved miRNAs with high expression levels. The presence of dust mites and miRNAs from HDMs in living environment were also validated. Following uptake of DFA-derived exosomes by BEAS-2B cells, exosomes transported miRNAs from DFA to target cells and produced pro-inflammatory effects in corresponding cells. RNA sequencing identified DEGs in dfa-miR-276-3p and dfa-novel-miR2 transfected BEAS-2B cells. GO and KEGG enrichment analyses revealed the role of exosomes with cross-species transporting of DFA miRNAs in inflammatory signaling pathways, such as JAK-STAT signaling pathway, PI3K/AKT signaling pathway and IL-6-mediated signaling pathway. Our findings demonstrate the miRNAs expression profiles in DFA for the first time. The DFA miRNAs are delivered into living environments via exosomes, and engulfed by human bronchial epithelial cells, and cross-species regulation may contribute to inflammation-related processes.

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival.

Identifying Genetic Signatures from Single-Cell RNA Sequencing Data by Matrix Imputation and Reduced Set Gene Clustering

In this current era, the identification of both known and novel cell types, the representation of cells, predicting cell fates, classifying various tumor types, and studying heterogeneity in various cells are the key areas of interest in the analysis of single-cell RNA sequencing (scRNA-seq) data. Due to the nature of the data, cluster identification in single-cell sequencing data with high dimensions presents several difficulties. In this paper, we introduce a new framework that combines various strategies such as imputed matrix, minimum redundancy maximum relevance (MRMR) feature selection, and shrinkage clustering to discover gene signatures from scRNA-seq data. Firstly, we conducted the pre-filtering of the “drop-out” value in the data focusing solely on imputing the identified “drop-out” values. Next, we applied the MRMR feature selection method to the imputed data and obtained the top 100 features based on the MRMR feature selection optimization scores for further downstream analysis. Thereafter, we employed shrinkage clustering on the selected feature matrix to identify the cell clusters using a global optimization approach. Finally, we applied the Limma-Voom R tool employing voom normalization and an empirical Bayes test to detect differentially expressed features with a false discovery rate (FDR) &lt; 0.001. In addition, we performed the KEGG pathway and gene ontology enrichment analysis of the identified biomarkers using David 6.8 software. Furthermore, we conducted miRNA target detection for the top gene markers and performed miRNA target gene interaction network analysis using the Cytoscape online tool. Subsequently, we compared our detected 100 markers with our previously detected top 100 cluster-specified markers ranked by FDR of the latest published article and discovered three common markers; namely, Cyp2b10, Mt1, Alpi, along with 97 novel markers. In addition, the Gene Set Enrichment Analysis (GSEA) of both marker sets also yields similar outcomes. Apart from this, we performed another comparative study with another published method, demonstrating that our model detects more significant markers than that model. To assess the efficiency of our framework, we apply it to another dataset and identify 20 strongly significant up-regulated markers. Additionally, we perform a comparative study of different imputation methods and include an ablation study to prove that every key phase of our framework is essential and strongly recommended. In summary, our proposed integrated framework efficiently discovers differentially expressed stronger gene signatures as well as up-regulated markers in single-cell RNA sequencing data.

Identification of potential biomarkers for nonsurvivor sepsis patients via microarray technology: A study based on GEO datasets

Background: The mechanism of sepsis especially non-survivors has not yet been identified. Objective: To identify the key genes concerned with non-survivor sepsis (NSS) and analyze its molecular mechanism. Methods: The original data were obtained from the GEO database to screen deferentially expressed genes (DEGs). GO and KEGG analysis were performed to analyze the functional annotation of DEGs. The protein-protein interaction (PPI) network and related analysis of hub genes were carried out. Further, hub genes were confirmed in the lipopolysaccharide (LPS)-induced septic mice by western blotting and immunohistochemistry. Results: We obtained 188 DEGs and 32 hub genes between NSS patients and healthy volunteers. Among of them, the top 10 hub genes including STAT1, ISG15, HERC1, EIF2AK2, RPL27, LY6E, IFI44L, XAF1, RSAD2 and HERC6 were studied, which predict sepsis based on receiver operator characteristic curve analysis. These hub genes were enriched in positive regulation of biomedical process including translation, response to virus and suppression of mitochondrial depolarization, etc.; cell component including mitochondrial inner membrane; molecular function containing ligase activity, etc. These hub genes are also enriched in influenza A infection and leukocyte trans-endothelial migration. The expression of these hub genes is better involved in a diagnosis of NSS, such as HERC6 (AUC = 0.9753, p = .0007), RPL27 (AUC = 0.9691, p = .0008), ISG15 (AUC = 0.9630, p = .0009), STAT1 (AUC = 0.9383, p = .0017), HERC1 (AUC = 0.9259, p = .0023), and XAF1 (AUC = 0.9259, p = .0023). Furthermore, 20 mg/kg of LPS injection up-regulated the expression of ISG15, RPL27, LY6E and HERC6 in the lung tissues compared with control mice. Conclusion: These identified 188 DEGs and 10 hub genes were associated with NSS, especially ISG15, RPL27, LY6E and HERC6 genes expressed in the lung as the most vulnerable organ.

Widely Targeted Metabolomic Profiling Combined with Transcriptome Analysis Provides New Insights into Lipid Biosynthesis in Seed Kernels of Pinus koraiensis.

Lipid-rich Pinus koraiensis seed kernels are highly regarded for their nutritional and health benefits. To ascertain the molecular mechanism of lipid synthesis, we conducted widely targeted metabolomic profiling together with a transcriptome analysis of the kernels in P. koraiensis cones at various developmental stages. The findings reveal that 148 different types of lipid metabolites, or 29.6% of total metabolites, are present in kernels. Among those metabolites, the concentrations of linoleic acid, palmitic acid, and α-linolenic acid were higher, and they steadily rose as the kernels developed. An additional 10 hub genes implicated in kernel lipid synthesis were discovered using weighted gene co-expression network analysis (WGCNA), gene interaction network analysis, oil body biosynthesis, and transcriptome analysis. This study used lipid metabolome and transcriptome analyses to investigate the mechanisms of key regulatory genes and lipid synthesis molecules during kernel development, which served as a solid foundation for future research on lipid metabolism and the creation of P. koraiensis kernel food.

Genome-wide identification of xylan glucuronosyltransferase family in cotton and function characterization of GhGUX5 in regulating Verticillium wilt resistance

Xylan glucuronosyltransferase (GUX) is widely involved in a variety of physiological processes in plants, including plant development, growth and the defense response to pathogens. However, the function of GUX regulators in Verticillium dahliae (V. dahliae) infection has not been considered previously in cotton. Overall, 119 GUX genes were identified from multiple species and were phylogenetically categorized into seven classes. Duplication event analysis indicated that GUXs in Gossypium hirsutum primarily originated from segmental duplication. GhGUXs promoter analysis indicated cis-regulatory elements capable of reacting to several different stresses. RNA-Seq data and qRT-PCR analysis both indicated that most GhGUXs were associated with V. dahliae infection. Gene interaction network analysis showed that GhGUX5 interacted with 11 proteins, and the relative expression of these 11 proteins changed significantly following V. dahliae infection. In addition, silencing and overexpression of GhGUX5 results to enhance and reduce plant's susceptibility to V. dahliae. Further study showed that TRV:GhGUX5 silenced cotton plants exhibited a decrease in the degree of lignification, total lignin content, gene expression levels involved in lignin biosynthesis, and enzyme activity compared with TRV:00. The above results indicate that GhGUX5 enhances Verticillium wilt resistance through the lignin biosynthesis pathway.

Unveiling the role of hub proteins in controlling quorum sensing regulated virulence through analogues in Pseudomonas aeruginosa PAO1: A functional protein-protein network biology approach

The protein-protein interaction (PPI) network analysis of specific genes identified for biofilm production and virulence/secretion system mediated by quorum sensing. The PPI depicted 13 hub proteins (namely rhlR, lasR, pscU, vfr, exsA, lasI, gacA, toxA, pilJ, pscC, fleQ, algR, and chpA) out of 160 nodes involving 627 edges. The PPI network analysis based on topographical features depicted pcrD with the highest degree value and vfr gene with the greatest betweenness centrality and closeness centrality (BC and CC) values. Based on in silico results, curcumin used as an Acyl homo-serine lactone (AHL) mimicker in P. aeruginosa, was also found effective in suppressing the quorum sensing regulated virulence factors such as elastase and pyocyanin. Based on in vitro experiment, curcumin suppressed biofilm formation at 62 μg/ml concentration. Host-pathogen interaction experiment showed that curcumin was also proved to be efficient in saving C. elegans from paralysis and killing effects of P. aeruginosa PAO1.

Abstract 2403: Divergent evolutionary response to multiple fractions of radiation (MF2) therapy in cervical cancer cell lines (CCCL)

Abstract Introduction: Treatment for locally-advanced cervical cancer is not currently tailored based on genomic markers of treatment response. We aim to explore the potential for differential evolutionary trajectories of radiation (RT) resistance throughout treatment using two in vitro models. Methods: Sixteen cervical cancer cell lines ( CCCL) were exposed to 1.8 Gy fractions of RT radiation for five sequential days and the surviving fraction (MF2) calculated. Differential gene expression (DGE) was performed on pre and post - treatment samples. Partial least squares (PLS) regression was completed with MF2 as the endpoint . Protein-protein interaction (PPI) network and overrepresentation analysis of genes was also performed. Four CCCL (BOKU, SKG II SF, ME180, and HeLa) were serially exposed to 50 Gy of gamma radiation RT given in 2Gy fractions. Five evolutionary replicates and three passage-controls were maintained. The mean integral survival as a function of dose (AUC) was calculated and ANOVA analysis performed. Results: MF2 as the phenotypic endpoint identified 19 DE genes. PLS identified histones (H4C8, H2BC18, H2BC4) as positively associated and transcriptional regulators (NR2F1, KALRN) as negatively associated with MF2 (Figure 1AB). PPI and Reactome Pathways also highlighted histone deacetylase pathways, nucleosome assembly and regulation of membrane potentials (Figure 1BC). Longitudinal treatment RT identified differential evolutionary trajectories between CCCL replicates. Two BOKU (p = 0.005 and 0.0090), one SKG II SF (p = 0.0146), and one ME180 (p = 0.0384) replicates became resistant. Four SKG II SF (p &amp;lt; 0.0001), and two HeLa (p = 0.0005 and p = 0.0068) became more sensitive to radiationRT (1C). Conclusion: Divergent evolutionary trajectories under therapeutic stress can be elicited using in vitro evolutionary experimentation with cervical cancer cell linesCCCL. Genomic correlation with divergent evolutionary trajectories may allow for the identification of real-time markers of resistance or sensitivity and allow for true RT radiotherapy personalization. Citation Format: Johanna Kelley, Arda Durmaz, Michelle Kuznicki, Aaron Petty, Jacob Scott, Roberto Vargas. Divergent evolutionary response to multiple fractions of radiation (MF2) therapy in cervical cancer cell lines (CCCL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2403.

Abstract 6537: Single cell transcriptomics uncovers cellular and molecular differences in PBMCs of responders and non-responders to the MUC1 cancer vaccine given in the preventative setting

Abstract Introduction: A single arm trial (NCT007773097) and a double-blind, placebo controlled randomized trial (NCT02134925) were conducted in patients with newly diagnosed advanced colonic adenomas to test the safety and immunogenicity of the MUC1 antigen vaccine and its potential to prevent new adenoma formation. These are the first trials of a non-viral cancer vaccine administered in the absence of cancer. In both trials, the vaccine was safe and strongly immunogenic in 43% and 25% of participants (Responders), respectively. The lack of robust response in a significant number of participants suggested, for the first time, that even in a premalignant setting, the immune system may have already been exposed to regulatory influences that, in the case of the vaccine, determine who does and who does not respond. We hypothesized that there could be molecular and cellular differences in the immune competence between vaccine responders and non-responders, and that they could be identified by studying their pre-vaccination peripheral blood mononuclear cells (PBMCs). Methods: The two MUC1 vaccine trials are described in https://doi.org/10.1101/2022.10.05.22280474 and https://doi.org/10.1158%2F1940-6207.CAPR-12-0275. We performed single cell RNA-sequencing (scRNAseq) on banked pre-vaccination PBMCs from 16 Responders and 16 Non-Responders, determined by anti-MUC1 IgG response. Using differential gene expression (DGE), pathway enrichment, and network estimation analyses, we identified specific cell types, genes, and pathways that differ between responders and non-responders. Results: Pre-vaccination PBMCs from Responders contained a significantly higher percentage of CD4+ naive T cells, while Non-Responders showed significantly higher percentage of CD8+ T effector memory (TEM) cells and a higher percentage of CD16+ monocytes. DGE and gene interaction network analysis showed a higher level of expression of T cell activation genes, such as Fos and Jun, in the CD4+ naive T cells in Responders. Further network analysis showed that these genes were directly connected to response. We also found pre-vaccination specific gene ontology (GO) pathways for translational and transcriptional activity enriched in all cell types in Responders compared to Non-Responders. Conclusion: Our analyses identified candidate biomarkers that are predictive of a preventative cancer vaccine response. Thus, our results can be used for patient selection for vaccine administration. Furthermore, we identified cell type differences and transcriptional pathways that provide information of possible mechanisms of vaccine response. Citation Format: Daniel Y. Yuan, Michelle L. McKeague, Matthew T. Dracz, Olivera J. Finn, Panayiotis V. Benos. Single cell transcriptomics uncovers cellular and molecular differences in PBMCs of responders and non-responders to the MUC1 cancer vaccine given in the preventative setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6537.

Role of ALOX5 in non-small cell lung cancer: A potential therapeutic target associated with immune cell infiltration.

The efficacy of immunotherapy for lung cancer is closely related to immune cell infiltration. Arachidonic acid 5-lipoxygenase (ALOX5) can activate inflammatory responses and trigger various cell death patterns; however, the relevance of ALOX5 to immune cell infiltration in lung cancer is unclear. The expression of ALOX5 in non-small cell lung cancer (NSCLC) is analyzed using an online database to explore the correlation between ALOX5 and immune cell infiltration in NSCLC and its relationship with prognosis. Differences in ALOX5 expression in NSCLC and normal lung tissues were analyzed by online databases such as TIMER, GEPIA and HPA; the UALCAN database was used to reveal the relationship between ALOX5 and clinical features; Kaplan-Meier database was applied to explore the prognostic value of ALOX5; GeneMANIA and String Website was used to explore genes and proteins associated with ALOX5 expression, respectively; the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to analyze ALOX5 differential genes which were picked up through the TCGA database; GSEA software was applied to predict the signal pathways that ALOX5 may be involved in; and the TIMER database was used to analyze the effect of ALOX5 expression on the level of immune cell infiltration. Compared with the normal lung tissues, the ALOX5 expression was low in NSCLC tissues (P<0.05), and which affected the prognosis of lung cancer patients. The expression level of ALOX5 was related to clinical features such as sex, age, metastasis, and pathological staging in NSCLC patients (all P<0.05). The gene interaction network analysis found that the genes interacting with ALOX5 mainly included the genes related to lipid oxidation and pro-inflammatory mediators such as coactosin like protein 1 (COTL1), leukotriene C4 synthase (LTC4S), and prostaglandin endoperoxide synthase 2 (PTGS2), and the protein-protein interaction analysis results were consistent. GO and KEGG analysis found that ALOX5 was involved in the biological process of activation of immune cell function and was involved in immune response function pathways. The GSEA analysis showed that ALOX5 may activate immune responses and mediate immune-related prognosis by affecting the cytokine-cytokine receptor interactions, natural killer-mediated cytotoxicity, and T cell receptor signaling pathways. The ALOX5 mRNA expressions in lung adenocarcinoma and lung squamous cell carcinoma were positively correlated with the tumor infiltration immune cells (B cells, CD8+ T cells, CD4+ T cells, etc.) (all P<0.05), and the ALOX5 mRNA expression was positively correlated with the expression of classic T cell immune checkpoint inhibitor genes (P<0.001). The ALOX5 gene expression in NSCLC is significantly downregulated, and which can affect NSCLC prognosis and immune cell infiltration levels. ALOX5 gene may be a potential biomarker of NSCLC prognosis associated with immune cell infiltration.

Genetic diagnosis of microcephaly

Objective: To explore the diagnostic value of chromosome karyotype analysis, chromosomal microarray analysis (CMA) and whole exome sequencing (WES) in microcephaly. Methods: A total of 9 cases of microcephaly fetuses diagnosed by prenatal ultrasound or children with microcephaly diagnosed after birth were selected from the Sixth Affiliated Hospital of Guangzhou Medical University from January 2014 to August 2022.Karyotype analysis and/or CMA were used to detect. The cases with negative karyotype analysis and CMA results were further sequenced by trio-based WES (Trio-WES). Then the coding genes contained in the pathogenic copy number variation (CNV) fragments were analyzed by gene ontology (GO) enrichment. The genes related to the development of the central nervous system contained in the pathogenic CNV and the pathogenic genes found by Trio-WES were combined for gene interaction network analysis. Results: In this study, 9 cases of microcephaly were recruited, with the time of diagnosis ranged from 23 weeks of gestation to 7 years after birth, and the head circumference of fetus or children ranged from 18.3 to 42.5 cm (-7SD to -2SD). Karyotype analysis was detected in all 9 cases and no abnormality result was found. Eight cases were detected by CMA, and one abnormal was found. Five cases were detected by Trio-WES, and two cases were detected with likely pathogenic genes. The GO enrichment analysis of the coding gene in the 4p16.3 microdeletion (pathogenic CNV) region showed that: in biological process, it was mainly concentrated in phototransduction, visible light; in terms of molecular function, it was mainly concentrated in fibroblast growth factor binding; in terms of cell components, it was mainly concentrated in rough endoplasmic reticulum. Gene interaction network analysis suggested that CDC42 gene could interact with CTBP1, HTT and ASPM gene. Conclusions: CMA could be used as a first-line detection technique for microcephaly. When the results of chromosome karyotype analysis and/or CMA are negative, Trio-WES could improve the detection rate of pathogenicity of microcephaly.

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis.

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

Low expression of NR1H3 correlates with macrophage infiltration and indicates worse survival in breast cancer.

Background: Nuclear receptor NR1H3 is a key regulator of macrophage function and lipid homeostasis. Here, we aimed to visualize the prognostic value and immunological characterization of NR1H3 in breast cancer. Methods: The expression pattern and prognostic value of NR1H3 were analyzed via multiple databases, including TIMER2, GEPIA2 and Kaplan-Meier Plotter. TISIDB, TIMER2 and immunohistochemical analysis were used to investigate the correlation between NR1H3 expression and immune infiltration. GO enrichment analysis, KEGG analysis, Reactome analysis, ConsensusPathDB and GeneMANIA were used to visualize the functional enrichment of NR1H3 and signaling pathways related to NR1H3. Results: We demonstrated that the expression of NR1H3 was significantly lower in breast cancer compared with adjacent normal tissues. Kaplan-Meier survival curves showed shorter overall survival in basal breast cancer patients with low NR1H3 expression, and poorer prognosis of relapse-free survival in breast cancer patients with low NR1H3 expression. NR1H3 was mainly expressed in immune cells, and its expression was closely related with infiltrating levels of tumor-infiltrating immune cells in breast cancer. Additionally, univariate and multivariate analysis indicated that the expression of NR1H3 and the level of macrophage infiltration were independent prognostic factors for breast cancer. Gene interaction network analysis showed the function of NR1H3 involved in regulating of innate immune response and macrophage activation. Moreover, NR1H3 may function as a predictor of chemoresponsiveness in breast cancer. Conclusion: These findings suggest that NR1H3 serves as a prognostic biomarker and contributes to the regulation of macrophage activation in breast cancer.

The Skeletal Muscle Transcriptome Profile of Elderly Men with Metabolic Syndrome Based on Weighted Gene Co-Expression Network Analysis

Introduction: This study aimed to understand the transcriptome characteristics of the skeletal muscle of elderly (EL) men with metabolic syndrome (MS) and to find the hub genes and insight into the molecular mechanisms of skeletal muscle in the occurrence and development of MS. Methods: In this study, the limma package of R software was used to analyze the differentially expressed genes in the skeletal muscle of healthy young (YO) adult men, healthy EL men, and EL men diagnosed with MS (SX) for at least 10 years. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis, and gene interaction network analysis, were used to explore the biological functions of differentially expressed genes, and weighted gene coexpression network analysis (WGCNA) was used to cluster differentially expressed genes into modules. Results: Among the YO group, EL group, and SX group, 65 co-differentially expressed genes were found maybe regulated by age factor and MS factor. Those co-differentially expressed genes were enriched into 25 biological process terms and 3 KEGG pathways. Based on the WGCNA results, a total of five modules were identified. Fifteen hub genes may play an essential role in regulating the function of skeletal muscle of EL men with MS. Conclusions: 65 differentially expressed genes and 5 modules may regulate the function of skeletal muscle of EL men with MS, among which fifteen hub genes may play an essential role in the occurrence and development of MS.

Identification of key genes and miRNAs related to polycystic ovary syndrome by comprehensive analysis of microarray

BackgroundWe aimed to explore mechanisms of development and progression of polycystic ovary syndrome (PCOS).MethodsThe microRNA expression microarray GSE37914 and gene expression profiles GSE43264 and GSE98421 were downloaded from the Gene Expression Omnibus database. The differentially expressed miRNAs (DEmiRNAs) and genes (DEGs) were screened using Limma package. Then, the DEGs and DEmiRNAs were combined to use for the subsequent analysis, including the functional enrichment analysis, protein–protein interaction (PPI) network and module analysis, drug–gene interaction network analysis, and DEmiRNAs–DEGs interactive network construction.ResultsA total of 26 DEmiRNAs and 80 DEGs were screened. The PPI network contained 68 nodes and 259 interactions. A significant clustering module with 8 nodes and 25 interactions was obtained. Three PCOS-related overlapping pathways were obtained based on PPI-degree top10 and module genes, including prion diseases, Staphylococcus aureus infection, and Chagas disease (American trypanosomiasis). A total of 44 drug–gene interaction pairs were obtained, which included 2 up-regulated genes (LDLR and VCAM1), 4 down-regulated genes (C1QA, C1QB, IL6 and ACAN) and 26 small molecules drugs. A total of 52 nodes and 57 interactions were obtained in the DEmiRNA–DEGs regulatory network, LDLR was regulated by miR-152-3p, miR-1207-5p, miR-378a-5p and miR-150-5p.ConclusionsOur research has identified several key genes and pathways related to PCOS. These results can improve our understanding of PCOS and provide new basis for drug target research.