Impact of Acute or Chronic Acidosis and Hypoxia on Gene Expression Patterns in Tumour Cells: Potential Functional Implications.

Tumours often exhibit pronounced hypoxia and hereby extracellular acidosis due to intensified glycolysis. Since metabolic parameters can modulate gene expression, the aim of the study was to analyse changes in gene expression patterns induced by acute (24 h) acidosis or hypoxia and also in tumour cells adapted to long-term acidosis (5 weeks). Three tumour cell lines (AT1 prostate carcinoma, MCF-7, and MDA-MB-231 breast carcinoma) were exposed to acidosis (pH 6.6) or hypoxia (pO2 1.5 mmHg) for 24 h. For long-term acidosis, AT1 tumour cells were continuously cultured at pH 6.6 for 5 weeks. Gene expression was examined by total RNA-sequencing and the functional significance was assessed by gene set enrichment analysis using the Gene Ontology database. Under short-term acidosis (24 h), AT1 and MCF-7 cells showed comparable changes. 714 genes were acidosis-dependently regulated in AT1 cells (275 up, 439 down), and 221 genes in MCF-7 cells (95 up, 126 down). MDA-MB-231 cells almost did not respond to low pH (13 regulated genes). Hypoxia affected MCF-7 cells the most (1498 regulated genes), whereas fewer genes were regulated in AT1 and MDA-MB-231 cells. Concerning the function of the regulated genes by short-term acidosis, RNA processing, cell cycle regulation, DNA synthesis, and mitochondrial function were negatively affected. Chronic acidosis showed a different picture. In AT1 cells, 1160 genes were differentially expressed (638 up, 522 down) when cells exposed to low pH for 5 weeks. The putatively acidosis-induced changes in functions included tissue structural development, RNA processing, and mitochondrial activity. This study shows that both acute and chronic acidosis of tumour cells lead to altered gene expression and thus affect cell function. Long-term acidosis leads to fundamentally different changes, indicating an adaptation process of the tumour cells.

Identification biomarkers in disease progression of obstructive sleep apnea from children serum based on WGCNA and Mfuzz.

Obstructive sleep apnea (OSA) syndrome is a prevalent form of respiratory sleep disorder, with an increasing prevalence among children. The consequences of OSA include obesity, diabetes, cardiovascular disease, and neuropsychological diseases. Despite its pervasive impact, a significant proportion of individuals especially children remain unaware that they suffer from OSA. Consequently, there is an urgent need for an accessible diagnostic approach. In this study, we conducted a bioinformatic analysis to identify potential biomarkers from a proteomics dataset comprising serum samples from children with OSA in the progression stage. In the Gene Set Enrichment Analysis (GSEA), we observed that the complement and immune response pathways persisted throughout the development of OSA and could be detected in the early stages. Subsequent to soft clustering and WGCNA analysis, it was revealed that the Hippo pathway, including ITGAL and FERMT3, plays a role in mild OSA. The analysis revealed a significant alteration of the complement and coagulation pathways, including TFPI and MLB2, in moderate OSA. In severe OSA, there was an association between hypoxia and the extracellular matrix (ECM) receptor interaction and collagen binding. In summary, it can be posited that the systemic inflammation may persist throughout the progression of OSA. Furthermore, severe OSA is characterized by abnormal vascular endothelial function, which may be attributed to chronic hypoxia. Finally, four potential biomarkers (ITGAL, TFPI, TTR, ANTXR1) were identified based on LASSO regression, and a prediction model for OSA progression was constructed based on the biomarkers.

Transcriptome Profiling Associated with CARD11 Overexpression in Colorectal Cancer Implicates a Potential Role for Tumor Immune Microenvironment and Cancer Pathways Modulation via NF-κB.

The immune system plays a critical role in inflammation by initiating responses to infections or tissue damage. The nuclear factor-κB (NF-κB) pathway plays a key role in inflammation and innate immunity, as well as other cellular activities. Dysregulation of this well-choreographed pathway has been implicated in various diseases, including cancer. CARD11 is a key molecule in the BCL10-MALT1 complex, which is involved in transducing the signal downstream of the NF-κB pathway. This study aims to elucidate how CARD11 overexpression exacerbates the prognosis of colorectal cancer (CRC). To identify the cellular pathways influenced by CARD11, transcriptomic analysis in both CRC cell lines and patients was carried out on CARD11- overexpressed HCT-116 and HT-29 CRC cell lines alongside empty vector-transfected cell lines. Furthermore, a comparison of transcriptomic data from adenoma and carcinoma CRC patients with low- (CARD11-) and high-(CARD11+) CARD11 expression was carried out. Whole transcriptomics and bioinformatics analysis results indicate that CARD11 appears to play a key role in CRC progression. Absolute GSEA (absGSEA) on HCT-116 transcriptomics data revealed that CARD11 overexpression promotes cell growth and tissue remodeling and enhances immune response. Key genes co-expressed with CARD11, such as EP300, KDM5A, HIF1A, NFKBIZ, and DUSP1, were identified as mediators of these processes. In the HT-29 cell line, CARD11 overexpression activated pathways involved in chemotaxis and extracellular matrix (ECM) organization, marked by IL1RN, MDK, SPP1, and chemokines like CXCL1, CXCL3, and CCL22, which were shown to contribute to the more invasive stage of CRC. In patient samples, adenoma patients exhibited increased expression of genes associated with the tumor immune microenvironment, such as IL6ST, collagen family members, and CRC transition markers, such as GLI3 and PIEZO2, in CARD11+ adenoma patients. Carcinoma patients showed a dramatic increase in the expression of MAPK8IP2 in CARD11+ carcinoma patients alongside other cancer-related genes, including EMB, EPHB6, and CPEB4.

HPV-driven heterogeneity in cervical cancer: study on the role of epithelial cells and myofibroblasts in the tumor progression based on single-cell RNA sequencing analysis.

Background: Cervical cancer (CC) is a neoplasia with a high heterogeneity. We aimed to explore the characteristics of tumor microenvironment (TME) for CC treatment. Methods: HPV positive (+) and negative (-) samples from cervical cancer (CC) patients were sourced from the Gene Expression Omnibus (GEO) database. The single-cell RNA sequencing (scRNA-seq) data were processed and annotated for cell types utilizing the Seurat package. Following this, the expression levels and biological roles of the marker genes were analyzed applying real-time PCR (RT-PCR) and transwell assays. Furthermore, the enrichment of genes with significantly differential expressions and copy number variations was assessed by the ClusterProlifer and inferCNV software packages. Results: Seven main cell clusters were classified based on a total of 12,431 cells. The HPV- CC samples exhibited a higher immune cell infiltration level, while epithelial cells and myofibroblasts had higher proportion in the HPV+ CC samples with extensive heterogeneity. Immune pathways including antigen treatment and presentation, immunoglobulin production and T cell mediated immunity were significantly activated in the HPV- CC group with lower cell cycle and proliferation activity. However, the anti-tumor immunity of these cells was inhibited in HPV+ CC group with higher cell proliferation activity. Moreover, the amplification and loss of CNVs also supported that these cells in HPV- CC samples were prone to anti-tumor activation. Further cell validation results showed that except GZMA, the levels of APOC1, CEACAM6, FOXP3, SFRP4 and TFF3 were all higher in CC cells Hela, and that silencing TFF3 could inhibit the migration and invasion of CC cells in-vitro. Conclusion: This study highlighted the critical role of HPV infection in CC progression, providing a novel molecular basis for optimizing the current preventive screening and personalized treatment for the cancer.

Polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA) are associated with the PI3K-AKT pathway activation.

Aims: We aimed to elucidate the mechanism leading to polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA). Background: PCOS is an endocrine disorder. Patients with RSA also have a high incidence rate of PCOS, implying that PCOS and RSA may share the same pathological mechanism. Objective: The single-cell RNA-seq datasets of PCOS (GSE168404 and GSE193123) and RSA GSE113790 and GSE178535) were downloaded from the Gene Expression Omnibus (GEO) database. Methods: Datasets of PSCO and RSA patients were retrieved from the Gene Expression Omnibus (GEO) database. The "WGCNA" package was used to determine the module eigengenes associated with the PCOS and RSA phenotypes and the gene functions were analyzed using the "DAVID" database. The GSEA analysis was performed in "clusterProfiler" package, and key genes in the activated pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Real-time quantitative PCR (RT-qPCR) was conducted to determine the mRNA level. Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. Results: The modules related to PCOS and RSA were sectioned by weighted gene co-expression network analysis (WGCNA) and positive correlation modules of PCOS and RSA were all enriched in angiogenesis and Wnt pathways. The GSEA further revealed that these biological processes of angiogenesis, Wnt and regulation of cell cycle were significantly positively correlated with the PCOS and RSA phenotypes. The intersection of the positive correlation modules of PCOS and RSA contained 80 key genes, which were mainly enriched in kinase-related signal pathways and were significant high-expressed in the disease samples. Subsequently, visualization of these genes including PDGFC, GHR, PRLR and ITGA3 showed that these genes were associated with the PI3K-AKT signal pathway. Moreover, the experimental results showed that PRLR had a higher expression in KGN cells, and that knocking PRLR down suppressed cell viability and promoted apoptosis of KGN cells. Conclusion: This study revealed the common pathological mechanisms between PCOS and RSA and explored the role of the PI3K-AKT signaling pathway in the two diseases, providing a new direction for the clinical treatment of PCOS and RSA.

High infiltration of immune cells with lower immune activity mediated the heterogeneity of gastric adenocarcinoma and promoted metastasis.

Background: Gastric adenocarcinoma (GA) is a heterogeneous malignancy with high invasion and metastasis. We aimed to explore the metastatic characteristics of GA using single-cell RNA-sequencing (scRNA-seq) analysis. Methods: The scRNA-seq dataset was downloaded from the GEO database and the "Seurat" package was used to perform the scRNA-seq analysis. The CellMarker2.0 database provided gene markers. Subsequently, differentially expressed genes (DEGs) were identified using the FindMarkers function and subjected to enrichment analysis with the "ClusterProlifer". "GseaVis" package was used for visualizing the gene levels. Finally, the SCENIC analysis was performed for identifying key regulons. The expression level and functionality of the key genes were verified by quantitative real-time PCR (qRT-PCR), wound healing and transwell assays. Results: A total of 7697 cells were divided into 8 cell subsets, in which the Cytotoxic NK/T cells, Myeloid cells and Myofibroblasts had higher proportion in the metastatic tissues. Further screening of DEGs and enrichment analysis revealed that in the metastatic tissues, NK cells, monocytes and inflammatory fibroblasts with low immune levels contributed to GA metastasis. In addition, this study identified a series of key immune-related regulons that mediated the lower immune activity of immune cells. Further in vitro experiment verified that CXCL8 was a key factor mediating the proliferation and migration of GA cells. Conclusion: The scRNA-seq analysis showed that high infiltration of immune cells with lower immune activity mediated heterogeneity to contribute to GA metastasis.

Testing the Significance of Ranked Gene Sets in Genome-wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics.

Background: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Objectives: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.

Promoter mutation-independent TERT expression is related to the immune-enriched milieu in papillary thyroid cancer.

Telomerase reverse transcriptase promoter mutation (pTERT MT) promotes human carcinogenesis via aberrant expression of telomerase reverse transcriptase (TERT). However, the tumorigenic impact of TERT expression independent of pTERT MT remains unclear despite numerous mechanisms of TERT being suggested. To tackle this issue, we employed comprehensive bioinformatics to assess biological variations noticed among different TERT expression mechanisms. Papillary thyroid cancer (PTC) with pTERT MT (pTERT MT PTC) presented aggressive clinical behavior and exhibited biological profiles associated with cellular immortality and genomic instability. PTC with TERT expression but without pTERT MT (TERT (+) PTC), also exhibited poor clinicopathological characteristics and was enriched with immune responses. In accordance, c-MYC/E2F and nuclear factor kappa B (NFκB) were dominant transcription factors in pTERT MT PTC and TERT (+) PTC, respectively. Notably, we revealed TERT hypermethylated oncological region (THOR) as a potential TERT expressing mechanism in TERT (+) PTC patients. Furthermore, three unique subtypes of papillary thyroid cancer were deciphered using a combination of machine learning-based scoring systems. Our proposed scoring system was clinically significant, especially in microcarcinoma, predicting survival outcomes and inferring therapeutic responses to radioactive iodine therapy. Finally, our analysis was expanded to endocrine-related cancers, unveiling various regulatory mechanisms of TERT with poor clinical outcomes and biological behaviors.

Integrative multi-omics characterization of hepatocellular carcinoma in hispanic patients.

BACKGROUND: The incidence and mortality rates of hepatocellular carcinoma (HCC) among Hispanic individuals in the United States are much higher than in non-Hispanic white people. We conducted multi-omics analyses to elucidate molecular alterations in HCC among Hispanic patients. METHODS: Paired tumor and adjacent non-tumor samples were collected from 31 Hispanic HCCs in South Texas (STX-Hispanic) for genomic, transcriptomic, proteomic, and metabolomic profiling. Serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed HCC. RESULTS: Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in STX Hispanic HCCs, suggesting a predominant activation of the Wnt/ß-catenin pathway. TERT promoter mutations were also significantly more frequent in the Hispanic cohort (Fisher's exact test, p < .05). Cell cycles and liver function were positively and negatively enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in serum samples of HCC patients (paired t-test, p < .0001). Two HCC subtypes from our Hispanic cohort were identified and validated with the TCGA liver cancer cohort. Patients with better overall survival showed higher activity of immune and angiogenesis signatures, and lower activity of liver function-related gene signatures. They also had higher levels of immune checkpoint and immune exhaustion markers. CONCLUSIONS: Our study revealed specific molecular features of Hispanic HCC and potential biomarkers for therapeutic management. It provides a unique resource for studying Hispanic HCC.

Prognostic significance of HS2ST1 expression in patients with hepatocellular carcinoma.

BACKGROUND: Heparan sulfate 2-O-sulfotransferase 1 (HS2ST1) catalyzes the sulfation of glucuronic acid residues in heparan sulfate proteoglycans, enabling these proteoglycans to interact with numerous ligands within tumor microenvironments. However, the prognostic role of HS2ST1 expression in cancer remains unclear. OBJECTIVE: This investigated HS2ST1 expression levels and their prognostic significance in various cancer types, demonstrated the prognostic value of HS2ST1 expression in hepatocellular carcinoma (HCC) patients, and identified molecular signatures associated with HS2ST1 expression. METHODS: HS2ST1 expression and patient survival data from The Cancer Genome Atlas (TCGA) datasets were analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) portal. We obtained gene expression and clinicopathological information on HCC patients from the TCGA and the Japan and France International Cancer Genome Consortium (ICGC) databases and performed survival analyses. We also examined relevant protein networks, differentially expressed genes, gene set enrichments, and tumor immune microenvironment features associated with HS2ST1 expression. RESULTS: HS2ST1 exhibited higher expression in eight tumor types compared with normal tissues and was associated with poor prognoses in five tumors, including HCC. HS2ST1 status correlated with poor prognosis in two ICGC HCC cohorts. Elevated HS2ST1 expression in HCC tumors was associated with signaling pathways involved in cell cycle progression, protein secretion, and mTORC1 signaling. Moreover, HS2ST1 expression levels were inversely correlated with immune cell infiltration in the tumor microenvironment. CONCLUSION: Our study elucidates the prognostic significance of HS2ST1 expression in HCC patients and provides insights into the potential roles of HS2ST1 in signaling pathways and the tumor microenvironment.

Disulfidptosis-associated LncRNA signature predicts prognosis and immune response in kidney renal clear cell carcinoma.

BACKGROUND: Kidney renal clear cell carcinoma (KIRC) represents a significant proportion of renal cell carcinomas and is characterized by high aggressiveness and poor prognosis despite advancements in immunotherapy. Disulfidptosis, a novel cell death pathway, has emerged as a critical mechanism in various cellular processes, including cancer. This study leverages machine learning to identify disulfidptosis-related long noncoding RNAs (DRlncRNAs) as potential prognostic biomarkers in KIRC, offering new insights into tumor pathogenesis and treatment avenues. RESULTS: Our analysis of data from The Cancer Genome Atlas (TCGA) led to the identification of 431 DRlncRNAs correlated with disulfidptosis-related genes. Five key DRlncRNAs (SPINT1-AS1, AL161782.1, OVCH1-AS1, AC131009.3, and AC108673.3) were used to develop a prognostic model that effectively distinguished between low- and high-risk patients with significant differences in overall survival and progression-free survival. The low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qRT‒PCR confirmed the differential expression of these DRlncRNAs in KIRC cells compared to normal kidney cells, underscoring their potential functional significance in tumor biology. CONCLUSIONS: This study established a robust link between disulfidptosis-related lncRNAs and patient prognosis in KIRC, underscoring their potential as prognostic biomarkers and therapeutic targets. The differential expression of these lncRNAs in tumor versus normal tissue further highlights their relevance in KIRC pathogenesis. The predictive model not only enhances our understanding of KIRC biology but also provides a novel stratification tool for precision medicine approaches, improving treatment personalization and outcomes in KIRC patients.

Identification of molecular targets and small drug candidates for Huntington's disease via bioinformatics and a network-based screening approach.

Huntington's disease (HD) is a gradually severe neurodegenerative ailment characterised by an increase of a specific trinucleotide repeat sequence (cytosine-adenine-guanine, CAG). It is passed down as a dominant characteristic that worsens over time, creating a significant risk. Despite being monogenetic, the underlying mechanisms as well as biomarkers remain poorly understood. Furthermore, early detection of HD is challenging, and the available diagnostic procedures have low precision and accuracy. The research was conducted to provide knowledge of the biomarkers, pathways and therapeutic targets involved in the molecular processes of HD using informatic based analysis and applying network-based systems biology approaches. The gene expression profile datasets GSE97100 and GSE74201 relevant to HD were studied. As a consequence, 46 differentially expressed genes (DEGs) were identified. 10 hub genes (TPM1, EIF2S3, CCN2, ACTN1, ACTG2, CCN1, CSRP1, EIF1AX, BEX2 and TCEAL5) were further differentiated in the protein-protein interaction (PPI) network. These hub genes were typically down-regulated. Additionally, DEGs-transcription factors (TFs) connections (e.g. GATA2, YY1 and FOXC1), DEG-microRNA (miRNA) interactions (e.g. hsa-miR-124-3p and has-miR-26b-5p) were also comprehensively forecast. Additionally, related gene ontology concepts (e.g. sequence-specific DNA binding and TF activity) connected to DEGs in HD were identified using gene set enrichment analysis (GSEA). Finally, in silico drug design was employed to find candidate drugs for the treatment HD, and while the possible modest therapeutic compounds (e.g. cortistatin A, 13,16-Epoxy-25-hydroxy-17-cheilanthen-19,25-olide, Hecogenin) against HD were expected. Consequently, the results from this study may give researchers useful resources for the experimental validation of Huntington's diagnosis and therapeutic approaches.

Abnormal genes and pathways that drive muscle contracture from brachial plexus injuries: Towards machine learning approach.

In order to clarify the pathways closely linked to denervated muscle contracture, this work uses IoMT-enabled healthcare stratergies to examine changes in gene expression patterns inside atrophic muscles following brachial plexus damage. The gene expression Omnibus (GEO) database searching was used to locate the dataset GSE137606, which is connected to brachial plexus injuries. Strict criteria (|logFC|≥2 & adj.p < 0.05) were used to extract differentially expressed genes (DEGs). To identify dysregulated activities and pathways in denervated muscles, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used. Hub genes were found using Cytoscape software's algorithms, which took into account parameters like as proximity, degree, and MNC. Their expression, enriched pathways, and correlations were then examined. The results showed that 316 DEGs were predominantly concentrated in muscle-related processes such as tissue formation and contraction pathways. Of these, 297 DEGs were highly expressed in denervated muscles, whereas 19 DEGs were weakly expressed. GSEA showed improvements in the contraction of striated and skeletal muscles. In addition, it was shown that in denervated muscles, Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1 were elevated hub genes with enriched pathways such adrenergic signaling and tight junction. These results point to possible therapeutic targets for denervated muscular contracture, including Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1. This highlights treatment options for this ailment which enhances the mental state of patient.

Multiple algorithms highlight key brain genes driven by multiple anesthetics.

Anesthesia serves as a pivotal tool in modern medicine, creating a transient state of sensory deprivation to ensure a pain-free surgical or medical intervention. While proficient in alleviating pain, anesthesia significantly modulates brain dynamics, metabolic processes, and neural signaling, thereby impairing typical cognitive functions. Furthermore, anesthesia can induce notable impacts such as memory impairment, decreased cognitive function, and diminished intelligence, emphasizing the imperative need to explore the concealed repercussions of anesthesia on individuals. In this investigation, we aggregated gene expression profiles (GSE64617, GSE141242, GSE161322, GSE175894, and GSE178995) from public repositories following second-generation sequencing analysis of various anesthetics. Through scrutinizing post-anesthesia brain tissue gene expression utilizing Gene Set Enrichment Analysis (GSEA), Robust Rank Aggregation (RRA), and Weighted Gene Co-expression Network Analysis (WGCNA), this research aims to pinpoint pivotal genes, pathways, and regulatory networks linked to anesthesia. This undertaking not only enhances comprehension of the physiological changes brought about by anesthesia but also lays the groundwork for future investigations, cultivating new insights and innovative perspectives in medical practice.

Identification of key genes and pathways in duck fatty liver syndrome using gene set enrichment analysis.

High-laying ducks are often fed high-energy, nutritious feeds to maintain high productivity, which predisposes them to lipid metabolism disorders and the development of fatty liver syndrome (FLS), which seriously affects production performance and has a substantial economic impact on the poultry industry. Therefore, it is necessary to elucidate the mechanisms underlying the development of fatty liver syndrome. In this study, seven Shan Partridge ducks, each with fatty liver syndrome and normal laying ducks, were selected, and Hematoxylin Eosin staining (HE staining), Masson staining, and transcriptome sequencing were performed on liver tissue. In addition to exploring key genes and pathways using conventional analysis methods, we constructed the first Kyoto Encyclopedia of Genes and Genomes (KEGG) database-based predefined gene set containing 12,764 pathways and 16,836 genes and further performed gene set enrichment analysis (GSEA) on the liver transcriptome data. Finally, key nodes and biological processes were identified via the protein-protein interaction (PPI) network. The results showed that the liver in the FL group exhibited steatosis and fibrosis, and a total of 3,663 genes with upregulated expression versus 2,296 downregulated genes were screened by conventional analysis. GSEA analysis and PPI network analysis revealed that the liver in the FL group exhibited disruption of the mitochondrial electron transport chain, leading to decreased oxidative phosphorylation and the secretion of excessive proinflammatory factors amid the continuous accumulation of lipids. Under continuous chronic inflammation, cell cycle arrest triggers apoptosis, while fibrosis becomes more severe, and procarcinogenic genes are activated, leading to the continuous development and deterioration of the liver. In conclusion, the predefined gene set constructed in this study can be used for GSEA, and the identified hub genes provide useful reference data and a solid foundation for the study of the genetic regulatory mechanism of fatty liver syndrome in ducks.

Effect of ZIC2 on immune infiltration and ceRNA axis regulation in lung adenocarcinoma via bioinformatics and experimental studies.

OBJECTIVE: This study aimed to conclude the effect and mechanism of ZIC2 on immune infiltration in lung adenocarcinoma (LUAD). METHODS: Expression of ZIC2 in several kinds of normal tissues of TCGA data was analyzed and its correlation with the baseline characteristic of LUAD patients were analyzed. The immune infiltration analysis of LUAD patients was performed by CIBERSORT algorithm. The correlation analysis between ZIC2 and immune cell composition was performed. Additionally, the potential upstream regulatory mechanisms of ZIC2 were predicted to identify the possible miRNAs and lncRNAs that regulated ZIC2 in LUAD. In vitro and in vivo experiments were also conducted to confirm the potential effect of ZIC2 on cell proliferation and invasion ability of LUAD cells. RESULTS: ZIC2 expression was decreased in various normal tissues, but increased in multiple tumors, including LUAD, and correlated with the prognosis of LUAD patients. Enrichment by GO and KEGG suggested the possible association of ZIC2 with cell cycle and p53 signal pathway. ZIC2 expression was significantly correlated with T cells CD4 memory resting, Macrophages M1, and plasma cells, indicating that dysregulated ZIC2 expression in LUAD may directly influence immune infiltration. ZIC2 might be regulated by several different lncRNA-mediated ceRNA mechanisms. In vitro experiments validated the promotive effect of ZIC2 on cell viability and invasion ability of LUAD cells. In vivo experiments validated ZIC2 can accelerate tumor growth in nude mouse. CONCLUSION: ZIC2 regulated by different lncRNA-mediated ceRNA mechanisms may play a critical regulatory role in LUAD through mediating the composition of immune cells in tumor microenvironment.

Resource: A curated database of brain-related functional gene sets (Brain.GMT).

Transcriptional profiling has become a common tool for investigating the nervous system. During analysis, differential expression results are often compared to functional ontology databases, which contain curated gene sets representing well-studied pathways. This dependence can cause neuroscience studies to be interpreted in terms of functional pathways documented in better studied tissues (e.g., liver) and topics (e.g., cancer), and systematically emphasizes well-studied genes, leaving other findings in the obscurity of the brain "ignorome". To address this issue, we compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT") that can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret results from three species (rat, mouse, human). Brain.GMT includes brain-related gene sets curated from the Molecular Signatures Database (MSigDB) and extracted from public databases (GeneWeaver, Gemma, DropViz, BrainInABlender, HippoSeq) and published studies containing differential expression results. Although Brain.GMT is still undergoing development and currently only represents a fraction of available brain gene sets, "brain ignorome" genes are already better represented than in traditional Gene Ontology databases. Moreover, Brain.GMT substantially improves the quantity and quality of gene sets identified as enriched with differential expression in neuroscience studies, enhancing interpretation. •We compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT").•Brain.GMT can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret neuroscience transcriptional profiling results from three species (rat, mouse, human).•Although Brain.GMT is still undergoing development, it substantially improved the interpretation of differential expression results within our initial use cases.

Analysis of genes differentially expressed in the cortex of mice with the Tbl1xr1Y446C/Y446C variant.

Transducin ß-like 1 X-linked receptor 1 (mouse Tbl1xr1) or TBL1X/Y related 1 (human TBL1XR1), part of the NCoR/SMRT corepressor complex, is involved in nuclear receptor signaling. Variants in TBL1XR1 cause a variety of neurodevelopmental disorders including Pierpont syndrome caused by the p.Tyr446Cys variant. We recently reported a mouse model carrying the Tbl1xr1Y446C/Y446C variant as a model for Pierpont syndrome. To obtain insight into mechanisms involved in altered brain development we studied gene expression patterns in the cortex of mutant and wild type (WT) mice, using RNA-sequencing, differentially expressed gene (DEG) analysis, gene set enrichment analysis (GSEA), weighted gene correlation network analysis (WGCNA) and hub gene analysis. We validated results in mutated mouse cortex, as well as in BV2 and SK-N-AS cell lines, in both of which Tbl1xr1 was knocked down by siRNA. Two DEGs (adj.P. Val < 0.05) were found in the cortex, Mpeg1 (downregulated in mutant mice) and 2900052N01Rik (upregulated in mutant mice). GSEA, WGCNA and hub gene analysis demonstrated changes in genes involved in ion channel function and neuroinflammation in the cortex of the Tbl1xr1Y446C/Y446C mice. The lowered expression of ion channel genes Kcnh3 and Kcnj4 mRNA was validated in the mutant mouse cortex, and increased expression of TRIM9, associated with neuroinflammation, was confirmed in the SK-N-AS cell line. Conclusively, our results show altered expression of genes involved in ion channel function and neuroinflammation in the cortex of the Tbl1xr1Y446C/Y446C mice. These may partly explain the impaired neurodevelopment observed in individuals with Pierpont syndrome and related TBL1XR1-related disorders.

Gene Expression Reprogramming by Citrate Supplementation Reduces HepG2 Cell Migration and Invasion.

Citrate, which is obtained from oxaloacetate and acetyl-CoA by citrate synthase in mitochondria, plays a key role in both normal and cancer cell metabolism. In this work, we investigated the effect of 10 mM extracellular citrate supplementation on HepG2 cells. Gene expression reprogramming was evaluated by whole transcriptome analysis using gene set enrichment analysis (GSEA). The transcriptomic data were validated through analyzing changes in the mRNA levels of selected genes by qRT-PCR. Citrate-treated cells exhibited the statistically significant dysregulation of 3551 genes; 851 genes were upregulated and 822 genes were downregulated. GSEA identified 40 pathways affected by differentially expressed mRNAs. The most affected biological processes were related to lipid and RNA metabolism. Several genes of the cytochrome P450 family were upregulated in treated cells compared to controls, including the CYP3A5 gene, a tumor suppressor in hepatocellular carcinoma (HCC) that plays an important protective role in HCC metastasis. The citrate-induced dysregulation of cytochromes could both improve the effectiveness of chemotherapeutics used in combination and reduce the aggressiveness of tumors by diminishing cell migration and invasion.

Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork.

Low level of drip loss (DL) is an important quality characteristic of meat with high economic value. However, the key genes and regulatory networks contributing to DL in pork remain largely unknown. To accurately identify the key genes affecting DL in muscles postmortem, 12 Duroc × (Landrace × Yorkshire) pigs with extremely high (n = 6, H group) and low (n = 6, L group) DL at both 24 and 48 h postmortem were selected for transcriptome sequencing. The analysis of differentially expressed genes and weighted gene co-expression network analysis (WGCNA) were performed to find the overlapping genes using the transcriptome data, and functional enrichment and protein-protein interaction (PPI) network analysis were conducted using the overlapping genes. Moreover, we used machine learning to identify the key genes and regulatory networks related to DL based on the interactive genes of the PPI network. Finally, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK signaling pathway, the insulin signaling pathway, and the calcium signaling pathway were identified, and a single-gene set enrichment analysis (GSEA) was performed to further annotate the functions of these potential key genes. The GSEA results showed that these genes are mainly related to ubiquitin-mediated proteolysis and oxidative reactions. Taken together, our results indicate that the potential key genes influencing DL are mainly related to insulin signaling mediated differences in glycolysis and ubiquitin-mediated changes in muscle structure and improve the understanding of gene expression and regulation related to DL and contribute to future molecular breeding for improving pork quality.

A low level of drip loss (DL) is critical for the economic value of pork. However, the genetic basis underlying DL remains unclear. In this study, pigs with extremely high and low DL at both 24 and 48 h postmortem were selected, and total RNA from longissimus dorsi (LD) muscles was extracted for transcriptome sequencing. Subsequently, a variety of analytical methods, were integrated to identify the potential key genes and pathways affecting DL. As a result, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK signaling pathway, insulin signaling pathway, and calcium signaling pathway, were identified, and these genes are primarily related to ubiquitin-mediated proteolysis and oxidation reactions. This study contributes new evidence for elucidating the molecular mechanism of DL and provides potential target genes for precise genetic improvement of DL.