Co-expressed Gene Sets Research Articles

EPCO-18. DECIPHERING SPATIAL DIVERSITY OF GLIOBLASTOMA GENETIC ARCHITECTURE

Abstract Glioblastoma (GBM) is hallmarked by profound inter- and intratumoral heterogeneity. Current research has mapped key genetic drivers to distinct transcriptional profiles within GBM. Nevertheless, the intricate interactions between genetic alterations and spatial-transcriptional heterogeneity remain elusive. We utilized nestin-Tva C57BL/6 mice to induce de novo GBM via oncogene overexpression alongside shRNA-mediated silencing or deletion of tumor suppressors. We modeled critical driver mutations: PDGFB, NF1, and EGFR. Employing 10X Genomics platform for single-cell RNA sequencing, combined with spatially resolved transcriptomics and proteomics (Nanostring GeoMx), we integrated data using both horizontal (mutual nearest neighbors) and vertical (weighted nearest neighbors) approaches, analyzed through the SPATA2 software. Advanced computational techniques, including graph neural networks and single-cell deconvolution, were leveraged to unravel the genotypic and spatial variability within tumors and their microenvironments. Our findings uncover persistent cellular heterogeneity across diverse genetic contexts. However, specific genetic mutations precipitated distinct dominant transcriptional states: NF1 and EGFR mutations drove mesenchymal and astrocytic-like states, respectively, whereas PDGFB fostered a neural progenitor/cell-like state. These transcriptional shifts were closely linked to unique microenvironmental modifications, such as elevated neuronal signaling in PDGFB-driven GBMs and significant immune infiltration in NF1 and EGFR models. Through weighted co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA) paired with spatial-niche deconvolution, we identified a mesenchymal transition leading to an immunosuppressive microenvironment in NF1-loss driven GBMs and increased lymphocyte presence around blood vessels in EGFR-amplified GBMs. These patterns were consistent with human spatially resolved transcriptomic data, emphasizing the genetic complexity and heterogeneity of human GBMs. Our genetically engineered mouse models serve as a robust platform for dissecting GBM with defined genetic mutations. Leveraging sophisticated analytical techniques and computational modeling, this study underscores the profound interplay between genetic drivers and the tumor microenvironment, paving the way for targeted therapeutic strategies and precision medicine in GBM.

Comprehensive Analysis of the Significance of Breast Cancer Gene 1 (BRCA-1) in Bladder Cancer.

Bladder carcinoma (BLCA) is characterized by high morbidity, mortality, and treatment costs. Breast cancer gene 1 (BRCA1), a tumor suppressor gene, inhibits the development of malignant tumors. However, research on the significance of BRCA1 in BLCA is limited. This study aims to explore the importance of BRCA1 in BLCA using bioinformatic methods and immunohistochemistry. Gene expression, clinical, and survival data were collected from the TCGA databases through the UCSC Xena platform (http://xena.ucsc.edu/). The TPM data from the TCGA and GETEx databases were integrated using the GEPIA database (http://GEPIA.cancer-pku.cn). The study then explored the differential expression, survival prognosis, functional enrichment, and immune cell infiltration analyses of BRCA1 in BLCA. A PPI network of BRCA1 was constructed using the STRING database, and a BRCA1-associated gene-gene interaction network was generated using the GeneMANIA database. Immunohistochemistry (IHC) assays were performed to verify the expression levels of BRCA1 in bladder tumour tissues and adjacent normal tissues. BRCA1 is associated with BLCA. Differential analysis indicated that BRCA1 acts as a risk factor for BLCA but does not show significant expression differences across genders, stages, tumor stages, lymph node stages, or metastasis stages. Additionally, staging was based on the eighth edition of the American Joint Committee on Cancer (AJCC) for BLCA. Co-expression network and Gene Set Enrichment Analysis (GESA) confirmed that BRCA1 is involved in various BLCA pathways. Furthermore, BRCA1 expression was also linked to immune cell infiltration. However, survival prognosis analysis revealed no significant correlation between the prognosis of BLCA and BRCA1. We demonstrated that BRCA1 is a prospective predicted and immunological biomarker in BLCA, offering new avenues for potential therapies.

Dopamine Receptors and TAAR1 Functional Interaction Patterns in the Duodenum Are Impaired in Gastrointestinal Disorders.

Currently, there is a growing amount of evidence for the involvement of dopamine receptors and the functionally related trace amine-associated receptor, TAAR1, in upper intestinal function. In the present study, we analyzed their expression in the duodenum using publicly accessible transcriptomic data. We revealed the expression of DRD1, DRD2, DRD4, DRD5, and TAAR1 genes in different available datasets. The results of the gene ontology (GO) enrichment analysis for DRD2 and especially TAAR1 co-expressed genes were consistent with the previously described localization of D2 and TAAR1 in enteric neurons and secretory cells, respectively. Considering that co-expressed genes are more likely to be involved in the same biological processes, we analyzed genes that are co-expressed with TAAR1, DRD2, DRD4, and DRD5 genes in healthy mucosa and duodenal samples from patients with functional dyspepsia (FD) or diabetes-associated gastrointestinal symptoms. Both pathological conditions showed a deregulation of co-expression patterns, with a high discrepancy between DRDs and TAAR1 co-expressed gene sets in normal tissues and patients' samples and a loss of these genes' functional similarity. Meanwhile, we discovered specific changes in co-expression patterns that may suggest the involvement of TAAR1 and D5 receptors in pathologic or compensatory processes in FD or diabetes accordingly. Despite our findings suggesting the possible role of TAAR1 and dopamine receptors in functional diseases of the upper intestine, underlying mechanisms need experimental exploration and validation.

GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D Spatial Transcriptomics Data.

Gene co-expression provides crucial insights into biological functions, however, there is a lack of exploratory analysis tools for localized gene co-expression in large-scale datasets. We present GeneSurfer, an interactive interface designed to explore localized transcriptome-wide gene co-expression patterns in the 3D spatial domain. Key features of GeneSurfer include transcriptome-wide gene filtering and gene clustering based on spatial local co-expression within transcriptomically similar cells, multi-slice 3D rendering of average expression of gene clusters, and on-the-fly Gene Ontology term annotation of co-expressed gene sets. Additionally, GeneSurfer offers multiple linked views for investigating individual genes or gene co-expression in the spatial domain at each exploration stage. Demonstrating its utility with both spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas, GeneSurfer effectively identifies and annotates localized transcriptome-wide co-expression, providing biological insights and facilitating hypothesis generation and validation.

Unveiling diabetic nephropathy: a novel diagnostic model through single-cell sequencing and co-expression analysis.

Diabetic nephropathy (DN) is a severe complication of diabetes that affects the kidneys. Disulfidptosis, a newly defined type of programmed cell death, has emerged as a potential area of interest, yet its significance in DN remains unexplored. This study utilized single-cell sequencing data GSE131882 from GEO database combined with bulk transcriptome sequencing data GSE30122, GSE30528 and GSE30529 to investigate disulfidptosis in DN. Single-cell sequencing analysis was performed on samples from DN patients and healthy controls, focusing on cell heterogeneity and communication. Weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were employed to identify disulfidptosis-related gene sets and pathways. A diagnostic model was constructed using machine learning techniques based on identified genes, and immunocorrelation analysis was conducted to explore the relationship between key genes and immune cells. PCR validation was performed on blood samples from DN patients and healthy controls. The study revealed significant disulfidptosis heterogeneity and cell communication differences in DN. Specific targets related to disulfidptosis were identified, providing insights into the pathogenesis of DN. The diagnostic model demonstrated high accuracy in distinguishing DN from healthy samples across multiple datasets. Immunocorrelation analysis highlighted the complex interactions between immune cells and key disulfidptosis-related genes. PCR validation supported the differential expression of model genes VEGFA, MAGI2, THSD7A and ANKRD28 in DN. This research advances our understanding of DN by highlighting the role of disulfidptosis and identifying potential biomarkers for early detection and personalized treatment.

Value analysis of ITLN1 in the diagnostic and prognostic assessment of colorectal cancer.

Colorectal cancer (CRC) remains the leading cause of cancer death worldwide. Less than half of the patients are diagnosed when the cancer is locally advanced. Several studies have shown that intelectin-1 (ITLN1) can serve as a key prognostic and therapeutic target for CRC. The purpose of this study was to investigate the clinical value of ITLN1 in CRC and to analyse its potential as a predictive biomarker for CRC. Colon adenocarcinoma (COAD) is the main type of CRC. COAD project in The Cancer Genome Atlas (TCGA) database served as the training cohort, and GSE39582 series in the Gene Expression Omnibus (GEO) database served as the external independent validation cohort. First, the difference in the expression level of ITLN1 between COAD tissue and normal tissue was analysed, and the results were verified via immunohistochemistry. The relationship between ITLN1 expression and the prognosis of COAD patients was evaluated via the heatmap and the Kaplan-Meier (KM) curve. The ITLN1 coexpressed gene set obtained by Pearson correlation analysis was used. The prognostic signatures that were significantly correlated with survival status were screened by Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Finally, a nomogram related to ITLN1 was constructed based on the risk score of the prognostic signature and routine clinicopathological variables. ITLN1 is significantly underexpressed in tumour tissues and can be used as a valuable tool to distinguish COAD. The high-expression group of ITLN1 was verified to have a greater survival rate. ITLN1 is significantly associated with a good prognosis in COAD patients. Six candidate genes (ITLN1 and MORC2, SH2D7, LGALS4, ATOH1, and NAT2) were selected for use in the Cox-LASSO regression analysis to calculate the risk score. Finally, a nomogram was constructed with a comprehensive risk score and clinicopathologic factors to successfully predict and verify the 1-year, 3-year, and 5-year survival probability. Our study established ITLN1 as an effective tool for CRC screening, diagnosis, and prognostic assessment, provided a basis for further study of the molecular function of ITLN1, and provided new insights for the mechanistic exploration and treatment of CRC.

Higher expression of TSR2 aggravating hypertension via the PPAR signaling pathway.

Hypertension is a complex disease with unknown causes. Therefore, it's crucial to deeply study its molecular mechanism. The hypertension dataset was obtained from Gene Expression Omnibus data base (GEO), and miRNA regulating central hub genes was screened via weighted gene co-expression network (DEGs) and gene set enrichment (GSEA). Cell experiments validated TSR2's role and the PPAR signaling pathway through western blotting. 500 DEGs were identified for hypertension, mainly enriched in actin cross-linking, insulin signaling, PPAR signaling, and protein localization. Eight hub genes (SEC61G, SRP14, Liy AR, NIP7, SDAD1, POLR1D, DYNLL2, TSR2) were identified. Four hub genes (LYAR, SDAD1, POLR1D, TSR2) exhibited high expression levels in the hypertensive tissue samples, while showing low expression levels in the normal tissue samples. This led us to speculate that they may have relevant regulatory effects on hypertension. When TSR2 was knocked down in the hypertension peripheral blood mononuclear cells (PBMC) model, the critical proteins in the PPAR signaling pathway (FABP, PPAR, PLTP, ME1, SCD1, CYP27, FABP1, OLR1, CPT-1, PGAR, CAP, ADIPO, MMP1, UCP1, ILK, PDK1 UBC AQP7) were downregulated. This also occurred in the hypertension peripheral blood mononuclear cells (PBMC) + TSR2_ OV model. TSR2 is highly expressed in individuals with hypertension and may play a significant role in the development of hypertension through the PPAR signaling pathway. TSR2 could serve as a molecular target for the early diagnosis and precise treatment of hypertension, providing a valuable direction for the mechanism research of this condition.

Monocyte state 1 (MS1) cells in critically ill patients with sepsis or non-infectious conditions: association with disease course and host response

BackgroundSepsis is a life-threatening condition arising from an aberrant host response to infection. Recent single-cell RNA sequencing investigations identified an immature bone-marrow-derived CD14+ monocyte phenotype with immune suppressive properties termed “monocyte state 1” (MS1) in patients with sepsis. Our objective was to determine the association of MS1 cell profiles with disease presentation, outcomes, and host response characteristics.MethodsWe used the transcriptome deconvolution method (CIBERSORTx) to estimate the percentage of MS1 cells from blood RNA profiles of patients with sepsis admitted to the intensive care unit (ICU). We compared these profiles to ICU patients without infection and to healthy controls. Host response dysregulation was further studied by gene co-expression network and gene set enrichment analyses of blood leukocytes, and measurement of 15 plasma biomarkers indicative of pathways implicated in sepsis pathogenesis.ResultsSepsis patients (n = 332) were divided into three equally-sized groups based on their MS1 cell levels (low, intermediate, and high). MS1 groups did not differ in demographics or comorbidities. The intermediate and high MS1 groups presented with higher disease severity and more often had shock. MS1 cell abundance did not differ between survivors and non-survivors, or between patients who did or did not acquire a secondary infection. Higher MS1 cell percentages were associated with downregulation of lymphocyte-related and interferon response genes in blood leukocytes, with concurrent upregulation of inflammatory response pathways, including tumor necrosis factor signaling via nuclear factor-κB. Previously described sepsis host response transcriptomic subtypes showed different MS1 cell abundances, and MS1 cell percentages positively correlated with the “quantitative sepsis response signature” and “molecular degree of perturbation” scores. Plasma biomarker levels, indicative of inflammation, endothelial cell activation, and coagulation activation, were largely similar between MS1 groups. In ICU patients without infection (n = 215), MS1 cell percentages and their relation with disease severity, shock, and host response dysregulation were highly similar to those in sepsis patients.ConclusionsHigh MS1 cell percentages are associated with increased disease severity and shock in critically ill patients with sepsis or a non-infectious condition. High MS1 cell abundance likely indicates broad immune dysregulation, entailing not only immunosuppression but also anomalies reflecting exaggerated inflammatory responses.Graphical abstract

Differential Gene Regulatory Network Analysis between Azacitidine-Sensitive and -Resistant Cell Lines.

Azacitidine, a DNA methylation inhibitor, is employed for the treatment of acute myeloid leukemia (AML). However, drug resistance remains a major challenge for effective azacitidine chemotherapy, though several studies have attempted to uncover the mechanisms of azacitidine resistance. With the aim to identify the mechanisms underlying acquired azacitidine resistance in cancer cell lines, we developed a computational strategy that can identify differentially regulated gene networks between drug-sensitive and -resistant cell lines by extending the existing method, differentially coexpressed gene sets (DiffCoEx). The technique specifically focuses on cell line-specific gene network analysis. We applied our method to gene networks specific to azacitidine sensitivity and identified differentially regulated gene networks between azacitidine-sensitive and -resistant cell lines. The molecular interplay between the metallothionein gene family, C19orf33, ELF3, GRB7, IL18, NRN1, and RBM47 were identified as differentially regulated gene network in drug resistant cell lines. The biological mechanisms associated with azacitidine and AML for the markers in the identified networks were verified through the literature. Our results suggest that controlling the identified genes (e.g., the metallothionein gene family) and "cellular response"-related pathways ("cellular response to zinc ion", "cellular response to copper ion", and "cellular response to cadmium ion", where the enriched functional-related genes are MT2A, MT1F, MT1G, and MT1E) may provide crucial clues to address azacitidine resistance in patients with AML. We expect that our strategy will be a useful tool to uncover patient-specific molecular interplay that provides crucial clues for precision medicine in not only gastric cancer but also complex diseases.

Identification and validation of new fatty acid metabolism-related mechanisms and biomarkers for erectile dysfunction.

Erectile dysfunction (ED) is a common condition affecting middle-aged and elderly men. The study sought to investigate differentially expressed fatty acid metabolism-related genes and the molecular mechanisms of ED. The expression profiles of GSE2457 and GSE31247 were downloaded from the Gene Expression Omnibus database and merged. Differentially expressed genes (DEGs) between ED and normal samples were obtained using the R package limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of DEGs were conducted using the R package clusterProfiler. Fatty acid metabolism-related DEGs (FAMDEGs) were further identified and analyzed. Machine learning algorithms, including Lasso (least absolute shrinkage and selection operator), support vector machine, and random forest algorithms, were utilized to identify hub FAMDEGs with the ability to predict ED occurrence. Coexpression analysis and gene set enrichment analysis of hub FAMDEGs were performed. Fatty acid metabolism-related functions (such as fatty acid metabolism and degradation) may play a vital role in ED. In total, 5 hub FAMDEGs (Aldh2, Eci2, Acat1, Acadl, and Hadha) were identified and found to be differentially expressed between ED and normal samples. Gene set enrichment analysis identified key pathways associated with these genes. The area under the curve values of the 5 hub FAMDEGs for predicting ED occurrence were all >0.8. Our results suggest that these 5 key FAMDEGs may serve as biomarkers for the diagnosis and treatment of ED. The strengths of our study include the use of multiple datasets and machine learning algorithms to identify key FAMDEGs. However, limitations include the lack of validation in animal models and human tissues, as well as research on the mechanisms of these FAMDEGs. Five hub FAMDEGs were identified as potential biomarkers for ED progression. Our work may prove that fatty acid metabolism-related genes are worth further investigation in ED.

A miR-137–Related Biological Pathway of Risk for Schizophrenia Is Associated With Human Brain Emotion Processing

BackgroundmiR-137 is a microRNA involved in brain development, regulating neurogenesis and neuronal maturation. Genome-wide association studies have implicated miR-137 in schizophrenia risk but do not explain its involvement in brain function and underlying biology. Polygenic risk for schizophrenia mediated by miR-137 targets is associated with working memory, although other evidence points to emotion processing. We characterized the functional brain correlates of miR-137 target genes associated with schizophrenia while disentangling previously reported associations of miR-137 targets with working memory and emotion processing. MethodsUsing RNA sequencing data from postmortem prefrontal cortex (N = 522), we identified a coexpression gene set enriched for miR-137 targets and schizophrenia risk genes. We validated the relationship of this set to miR-137 in vitro by manipulating miR-137 expression in neuroblastoma cells. We translated this gene set into polygenic scores of coexpression prediction and associated them with functional magnetic resonance imaging activation in healthy volunteers (n1 = 214; n2 = 136; n3 = 2075; n4 = 1800) and with short-term treatment response in patients with schizophrenia (N = 427). ResultsIn 4652 human participants, we found that 1) schizophrenia risk genes were coexpressed in a biologically validated set enriched for miR-137 targets; 2) increased expression of miR-137 target risk genes was mediated by low prefrontal miR-137 expression; 3) alleles that predict greater gene set coexpression were associated with greater prefrontal activation during emotion processing in 3 independent healthy cohorts (n1, n2, n3) in interaction with age (n4); and 4) these alleles predicted less improvement in negative symptoms following antipsychotic treatment in patients with schizophrenia. ConclusionsThe functional translation of miR-137 target gene expression linked with schizophrenia involves the neural substrates of emotion processing.

Identification of neutrophil-related genes and development of a prognostic model for cholangiocarcinoma.

Cholangiocarcinoma is a prevalent gastrointestinal tumor with limited effective early diagnostic methods. The role of neutrophils in the context of cholangiocarcinoma remains largely unexplored. A comprehensive analysis was performed on a cohort of cholangiocarcinoma samples (TCGA-CHOL) from the TCGA database to investigate the relationship between cholangiocarcinoma and neutrophils. Methodologies included single-sample gene set enrichment analysis (ssGSEA), differential expression analysis, weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA). The study identified a significant decrease of neutrophils in cholangiocarcinoma via ssGSEA. WGCNA and differential expression analysis led to the identification of a neutrophil-related gene module comprised of 1059 genes. Cluster 1, showing a higher proportion of neutrophils, was linked to better survival outcomes. GSEA disclosed downregulation of complement, inflammatory response and interferon response pathways in Cluster 2, hinting at possible cholangiocarcinoma development triggers. A notable upregulation of PD1, PD-L1 and CTLA4 was observed in Cluster 1, suggesting potential benefits from immunotherapy. A prognostic model was developed based on clinical data and expression levels of three prognostic genes (SOWAHD, TNFAIP8 and EBF3) showing satisfactory discrimination, calibration and clinical benefits. An overexpression of TNFAIP8 in cholangiocarcinoma cells was found, with its knockdown significantly inhibiting cell proliferation and migration. This study elucidates a neutrophil-related gene module and prognostic genes, offering insights into the role of neutrophils in cholangiocarcinoma development and progression. It also introduces a clinical prediction model for enhanced prognosis assessment. These findings may lay the groundwork for the development of innovative therapeutic strategies in cholangiocarcinoma treatment.

Reprogramming astrocytic NDRG2/NF-κB/C3 signaling restores the diabetes-associated cognitive dysfunction.

Dementia is a serious complication in patients with diabetes-associated cognitive dysfunction (DACD). In this study, we aim to explore the protective effect of exercise on DACD in diabetic mice, and the role of NDRG2 as a potential guarder for reversing the pathological structure of neuronal synapses. Seven weeks of standardized exercise at moderate intensity was carried out using an animal treadmill in the vehicle+Run and STZ+Run groups. Based on quantitative transcriptome and tandem mass tag (TMT) proteome sequencing, weighted gene co-expression analysis (WGCNA) and gene set enrichment analysis (GSEA) were used to investigate the activation of complement cascades to injury neuronal synaptic plasticity. Golgi staining, Western blotting, immunofluorescence staining, and electrophysiology were used to verify the reliability of sequencing data. The role of NDRG2 was assessed by overexpressing or inhibiting the NDRG2 gene invivo. Moreover, we estimated the cognitive function in diabetic or normal patients using DSST scores. Exercise reversed the injury of neuronal synaptic plasticity and the downregulation of astrocytic NDRG2 in diabetic mice, which succeeded in attenuating DACD. The deficiency of NDRG2 aggravated the activation of complement C3 by accelerating the phosphorylation of NF-κB, ultimately leading to synaptic injury and cognitive dysfunction. Conversely, the overexpression of NDRG2 promoted astrocytic remodeling by inhibiting complement C3, thus attenuating synaptic injury and cognitive dysfunction. Meanwhile, C3aR blockade rescued dendritic spines loss and cognitive deficits in diabetic mice. Moreover, the average DSST score of diabetic patients was significantly lower than that of non-diabetic peers. Levels of complement C3 in human serum were elevated in diabetic patients compared to those in non-diabetic patients. Our findings illustrate the effectiveness and integrative mechanism of NDRG2-induced improvement of cognition from a multi-omics perspective. Additionally, they confirm that the expression of NDRG2 is closely related to cognitive function in diabetic mice and the activation of complement cascades accelerated impairment of neuronal synaptic plasticity. NDRG2 acts as a regulator of astrocytic-neuronal interaction via NF-κB/C3/C3aR signaling to restore synaptic function in diabetic mice. This study was supported by the National Natural Science Foundation of China (No. 81974540, 81801899, 81971290), the Key Research and Development Program of Shaanxi (Program No. 2022ZDLSF02-09) and Fundamental Research Funds for the Central Universities (Grant No. xzy022019020).

Abstract A010: ANO7 expression changes in prostate cancer progression — Association with an aggressive phenotype?

Abstract Introduction The expression level and single nucleotide polymorphisms of the prostate-specific gene ANO7 have been shown to correlate with prostate cancer (PrCa) outcome. Very little is known about ANO7, apart from its expression profile in tissues and that the protein is either a calcium-activated ion channel or a lipid scramblase. Our results suggest that ANO7 likely has a role in PrCa progression and that loss of ANO7 is associated with malignant PrCa. Materials and methods Sections of a prostate cancer formalin-fixed paraffin-embedded tissue microarray were used for ANO7 mRNA and protein detection. mRNA was detected with fluorescent in situ hybridization (FISH). Protein was detected with immunohistochemistry (IHC) using a polyclonal anti-ANO7 antibody (HPA035730). mRNA from fresh radical prostatectomy primary tumor samples were sequenced and subsequent gene expression levels were analyzed for co-expression with ANO7. The sample set consisted of a matched tumor and benign tissue sample (15+15) from each patient. Results The FISH images indicated explicitly that ANO7 mRNA is exclusively expressed in the luminal cells of the prostatic glandular epithelium. ANO7 mRNA is expressed in all cancerous lumina-forming glandular structures, but not in poorly-formed glands or sheets of cancer, in which ANO7 mRNA expression is very low or non-existent. Morphologically benign glands amidst cancerous tissue showed no expression, in contrast to tissue in which benign glands are predominating. The IHC showed a similar staining pattern to FISH.ANO7 co-expression gene set enrichment analysis resulted in 19 positively correlating and 77 negatively correlating pathways in KEGG (Kyoto Encyclopedia of Genes and Genomes) terms. Most of the positively correlating terms relate to metabolism, whereas among the negatively correlating terms, there were many signal transduction and cell growth and death-related pathways, such as Hippo, Ras, and p53 signaling pathways. Conclusions ANO7 mRNA and protein expression correlate spatially in the tissue, showing that the expression is specific to differentiated luminal cells and highly reduced in high-grade cancer. This notion is supported by the co-expressed gene-set enrichment analysis, which is showing a negative correlation of ANO7 with many pathways that are associated with aggressive PrCa. Mainly metabolism-related processes were positively correlated with ANO7, which could indicate that ANO7 is linked to the reprogramming of metabolism in the cells during cancer progression. Further research aims to identify the pathways in which ANO7 plays a significant role and to elucidate how the ANO7 protein functionally alters signaling related to PrCa progression. Citation Format: Olli Metsälä, Gudrun Wahlström, Pekka Taimen, Johanna Schleutker. ANO7 expression changes in prostate cancer progression — Association with an aggressive phenotype? [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A010.

Alzheimer's disease heterogeneity explained by polygenic risk scores derived from brain transcriptomic profiles.

Alzheimer's disease (AD) is heterogeneous, both clinically and neuropathologically. We investigated whether polygenic risk scores (PRSs) integrated with transcriptome profiles from AD brains can explain AD clinical heterogeneity. We conducted co-expression network analysis and identified gene sets (modules) that were preserved in three AD transcriptome datasets and associated with AD-related neuropathological traits including neuritic plaques (NPs) and neurofibrillary tangles (NFTs). We computed the module-based PRSs (mbPRSs) for each module and tested associations with mbPRSs for cognitive test scores, cognitively defined AD subgroups, and brain imaging data. Of the modules significantly associated with NPs and/or NFTs, the mbPRSs from two modules (M6 and M9) showed distinct associations with language and visuospatial functioning, respectively. They matched clinical subtypes and brain atrophy at specific regions. Our findings demonstrate that polygenic profiling based on co-expressed gene sets can explain heterogeneity in AD patients, enabling genetically informed patient stratification and precision medicine in AD. Co-expression gene-network analysis in Alzheimer's disease (AD) brains identified gene sets (modules) associated with AD heterogeneity. AD-associated modules were selected when genes in each module were enriched for neuritic plaques and neurofibrillary tangles. Polygenic risk scores from two selected modules were linked to the matching cognitively defined AD subgroups (language and visuospatial subgroups). Polygenic risk scores from the two modules were associated with cognitive performance in language and visuospatial domains and the associations were confirmed in regional-specific brain atrophy data.

Identification and preliminary validation of synovial tissue-specific genes and their-mediated biological mechanisms in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. It is well known that the formation of positive feedback between synovial hyperplasia and inflammatory infiltration is intimately associated with the occurrence and development of RA. However, the exact mechanisms still remain unknown, making the early diagnosis and therapy of RA difficult. This study was designed to identify prospective diagnostic and therapeutic biomarkers, as well as their-mediated biological mechanisms in RA. Three microarray datasets (GSE36700, GSE77298 and GSE153015) and two RNA-sequencing datasets (GSE89408 and GSE112656) of synovial tissues, as well as three other microarray datasets (GSE101193, GSE134087 and GSE94519) of peripheral blood were downloaded for integrated analysis. The differently expressed genes (DEGs) were identified by "limma" package of R software. Then, weight gene co-expression analysis and gene set enrichment analysis were performed to investigate synovial tissue-specific genes and their-mediated biological mechanisms in RA. The expression of candidate genes and their diagnostic value for RA were verified by quantitative real-time PCR and receiver operating characteristic (ROC) curve, respectively. Relevant biological mechanisms were explored through cell proliferation and colony formation assay. The suggestive anti-RA compounds were discovered by CMap analysis. We identified a total of 266 DEGs, which were mainly enriched in cellular proliferation and migration, infection and inflammatory immune signaling pathways. Bioinformatics analysis and molecular validation revealed 5 synovial tissue-specific genes, which exhibited excellent diagnostic value for RA. The infiltration level of immune cells in RA synovial tissue was significantly higher than that in control individuals. Moreover, preliminary molecular experiments suggested that these characteristic genes may be responsible for the high proliferation potential of RA fibroblast-like synoviocytes (FLSs). Finally, 8 small molecular compounds with anti-RA potential were obtained. We have proposed 5 potential diagnostic and therapeutic biomarkers (CDK1, TTK, HMMR, DLGAP5, and SKA3) in synovial tissues that may contribute to the pathogenesis of RA. These findings may shed light on the early diagnosis and therapy of RA.

Systematic pan-cancer analysis identifies transmembrane protein 158 as a potential therapeutic, prognostic and immunological biomarker.

The purpose of this study was to investigate the expression significance, predictive value, immunologic function, and biological role of transmembrane protein 158 (TMEM158) in the development of pan-cancer. To achieve this, we utilized data from multiple databases, including TCGA, GTEx, GEPIA, and TIMER, to collect gene transcriptome, patient prognosis, and tumor immune data. We evaluated the association of TMEM158 with patient prognosis, tumor mutational burden (TMB), and microsatellite instability (MSI) in pan-cancer samples. We performed immune checkpoint gene co-expression analysis and gene set enrichment analysis (GSEA) to better understand the immunologic function of TMEM158. Our findings revealed that TMEM158 was significantly differentially expressed between most types of cancer tissues and their adjacent normal tissues and was associated with prognosis. Moreover, TMEM158 was significantly correlated with TMB, MSI, and tumor immune cell infiltration in multiple cancers. Co-expression analysis of immune checkpoint genes showed that TMEM158 was related to the expression of several common immune checkpoint genes, especially CTLA4 and LAG3. Gene enrichment analysis further revealed that TMEM158 was involved in multiple immune-related biological pathways in pan-cancer. Overall, this systematic pan-cancer analysis suggests that TMEM158 is generally highly expressed in various cancer tissues and is closely related to patient prognosis and survival across multiple cancer types. TMEM158 may serve as a significant predictor of cancer prognosis and modulate immune responses to various types of cancer.

SPOCK1 is a Prognostic-Related Biomarker and Correlated with Immune Infiltrates in Head and Neck Squamous Cell Carcinoma

Background: To explore expression and immune infiltration of SPARC/osteonectin, cwcv, and maze-like domains proteoglycan 1 (SPOCK1) in Head and Neck squamous cell carcinoma. Methods: A total of 107 HNSC patients’ tissues and 15 adjacent normal tissues were collected in this study. Co-expressed gene and gene set enrichment analysis was detected using STRING and Linked Omics. Immune cell infiltration related to SPOCK1 was analyzed via TIMER. Results: The positive rate of SPOCK1 in HNSC tissues were significantly higher than that in normal tissues by immunohistochemical staining (p< 0.01). The expression of SPOCK1 in HNSC was a positive correlation with the level of immune infiltrating cells. In addition, we discovered that SPOCK1 was major involved in inflammatory response pathways, cancer cell proliferation regulation, cell cycle regulation, apoptosis, adhesion, cell-matrix interaction, etc. Conclusions: SPOCK1 plays a role in promoting cancer in HNSC, which was closely related to the malignant evolution of HNSC, and it was expected to become a prognostic molecular marker for HNSC patients and a potential target for immunotherapy.

Electroacupuncture alleviates perioperative hypothalamus-pituitary-adrenal axis dysfunction via circRNA-miRNA-mRNA networks.

Electroacupuncture (EA) has long been used to alleviate surgery-induced hypothalamic-pituitary-adrenal axis dysfunction. However, its downstream gene targets in the brain remain unclear. The aim of the present study was to clarify the potential targets of EA based on RNA sequencing techniques (RNA-seq). Rats were divided into normal control (NC), hepatectomy surgery (HT), HT + EA, and HT + sham EA groups followed by RNA-seq of two representative nuclei in the hypothalamus and amygdala. Weighted Gene Co-expression Network Analysis and Gene Set Enrichment Analysis identified six gene modules associated with neuroendocrine transmitters and neural remodeling in the hypothalamus. Furthermore, circRNA-miRNA-mRNA interaction networks revealed EA-related candidate miRNAs and circRNAs, of which opioid receptor mu 1 might be an EA-specific target, and showed regulation by competing endogenous RNA. We identified the neuroendocrine circRNA-miRNA-mRNA networks through which EA has an effect on HPA axis dysfunction, thus providing potential targets and future research directions for EA treatment.

KCNE4 expression is correlated with the pathological characteristics of colorectal cancer patients and associated with the radioresistance of cancer cells.

Colorectal cancer (CRC) is a common malignancy, and radioresistance limits the effectiveness of radiotherapy for rectal cancer. This study is performed to investigate the role and regulatory mechanism of Potassium Voltage-Gated Channel Subfamily E Regulatory Subunit 4 (KCNE4) in the radioresistance of CRC cells. Immunohistochemical staining results of KCNE4 in normal tissues and CRC tissues were obtained from the Human Protein Atlas (HPA) database. The UALCAN database was used for analyzing KCNE4 mRNA expression in normal tissue samples and CRC tissue samples and its relationship with tumor stage. The relationship of KCNE4 expression with prognosis was analyzed utilizing the data of GEPIA database. LinkedOmics database was searched to analyze the co-expressed gene sets of KCNE4 in CRC, and to analyze the signaling pathways related with KCNE4 in CRC. GO and KEGG enrichment analyses were carried out on the co-expressed genes of KCNE4 with DAVID database. Ionizing radiation (IR)-resistant cell lines (HCT116/IR and HT29/IR) were established; cell viability was assessed via cell counting kit-8 (CCK-8) and EdU assays, and terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) assay was performed for detecting cell apoptosis. Western blotting was carried out to detect the expressions of p-p85 and p-AKT. KCNE4 was highly expressed in CRC tissues and linked to advanced tumor stage, lymph node metastasis and poor prognosis of CRC patients. KCNE4 overexpression promoted HCT116/IR cell proliferation and inhibited the apoptosis, while KCNE4 knockdown suppressed HT29/IR cell proliferation and facilitated the apoptosis. Furthermore, high KCNE4 expression was associated with the activation of the PI3K/AKT signal pathway. KCNE4 is associated with the clinicopathological characteristics of CRC patients, and its high expression level contributes to the radioresistance of cancer cells via activating the PI3K/AKT signal pathway.