Gene Set Enrichment Analysis Pathway Research Articles

The chemokine CCL14 is a potential biomarker associated with immune cell infiltration in lung adenocarcinoma

BackgroundChemokine ligand 14, which has a C–C motif (CCL14), mediates the immunological milieu around tumors. However, its role in the progression of lung adenocarcinoma (LUAD) is still unknown. Our objectives were to study the association between CCL14 and tumor-infiltrating immune cells (TIICs) as well as the predictive significance of CCL14 in LUAD.MethodsThe expression of CCL14 in LUAD was examined by using the Oncomine, The Cancer Genome Atlas (TCGA), The University of Alabama at Birmingham CANcer data analysis Portal (UALCAN), and Human Protein Atlas databases. To determine the prognostic significance of CCL14 in LUAD, researchers used the Kaplan‒Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA, version 2). We utilized TIMER and GEPIA2 to investigate the connection between CCL14 and TIICs. Gene set enrichment analysis (GSEA) was used to test for functional enrichment of genes. We used RT‒qPCR to measure CCL14 expression and Cell Counting Kit-8, Transwell, and wound healing assays to investigate the biological role of CCL14.ResultsThe prognosis of patients with LUAD was worse when CCL14 expression was low. Statistical analysis revealed that CCL14 mRNA expression was significantly greater in lung epithelial cells than in LUAD cell lines in vitro. Enhancing CCL14 expression reduced cell migration, invasion, and proliferation. The results of the immune infiltration research showed that CCL14 and TIICs were positively correlated. Different immune infiltration patterns associated with CCL14 were also shown by TIIC markers. According to GSEA, histone deacetylases, G2/M checkpoints, and Notch signaling pathways were associated with low CCL14 expression.ConclusionsCCL14 is anticipated to emerge as a prognostic marker and therapeutic target for LUAD due to its role in regulating TIICs, suggesting that it may be an antioncogene.

Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke.

Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3m, GSE137482-18m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.

Transcriptomic profiling analysis of the effect of palmitic acid on 3D spheroids of β-like cells derived from induced pluripotent stem cells

Type 2 diabetes (T2D) is posing a serious public health concern with a considerable impact on human life and health expenditures worldwide. The disease develops when insulin plasma level is insufficient for coping insulin resistance, caused by the decline of pancreatic β-cell function and mass. In β-cells, the lipotoxicity exerted by saturated free fatty acids in particular palmitate (PA), which is chronically elevated in T2D, plays a major role in β-cell dysfunction and mass. However, there is a lack of human relevant in vitro model to identify the underlying mechanism through which palmitate induces β-cell failure. In this frame, we have previously developed a cutting-edge 3D spheroid model of β-like cells derived from human induced pluripotent stem cells. In the present work, we investigated the signaling pathways modified by palmitate in β-like cells derived spheroids. When compared to the 2D monolayer cultures, the transcriptome analysis (FDR set at 0.1) revealed that the 3D spheroids upregulated the pancreatic markers (such as GCG, IAPP genes), lipids metabolism and transporters (CD36, HMGSC2 genes), glucose transporter (SLC2A6). Then, the 3D spheroids are exposed to PA 0.5 mM for 72 h. The differential analysis demonstrated that 32 transcription factors and 135 target genes were mainly modulated (FDR set at 0.1) including the upregulation of lipid and carbohydrates metabolism (HMGSC2, LDHA, GLUT3), fibrin metabolism (FGG, FGB), apoptosis (CASP7). The pathway analysis using the 135 selected targets extracted the fibrin related biological process and wound healing in 3D PA treated conditions. An overall pathway gene set enrichment analysis, performed on the overall gene set (with pathway significance cutoff at 0.2), highlighted that PA perturbs the citrate cycle, FOXO signaling and Hippo signaling as observed in human islets studies. Additional RT-PCR confirmed induction of inflammatory (IGFBP1, IGFBP3) and cell growth (CCND1, Ki67) pathways by PA. All these changes were associated with unaffected glucose-stimulated insulin secretion (GSIS), suggesting that they precede the defect of insulin secretion and death induced by PA. Overall, we believe that our data demonstrate the potential of our spheroid 3D islet-like cells to investigate the pancreatic-like response to diabetogenic environment.

Abstract 66: A new mechanism of tumor immune escape: TCF19 promotes the development of novel terminally exhausted T cells through E2F and MYC transcription family

Abstract Introduction: ICB (immune checkpoint blocking) has been a promising therapy in cancer treatment, but there are still some patients do not response to this therapy. And it is well known that the majority cells reactivated to ICB are TCF1+ precursor exhausted T cells. Thus, studying the formation and heterogeneity of exhausted T cells are very necessary for improving the efficacy of ICB therapy. In this research, we identified a new population as TCF19+PD1+TIM3+ exhausted CD8+ T cells, which blocked the responds to ICB therapy. Methods: We collected single cell sequencing data, including colorectal cancer, gastric cancer, melanoma, and lung cancer, and drew tumor immune cells map through cluster analysis. Then using bioinformatics tools CytoTRACE. T and CCAT. A to calculate the differentiation of exhausted T cell populations, which discovered a new subset of highly proliferative and poorly differentiated terminal exhausted T cells. Subsequently, the existence of this group of cells was verified through in vitro experiments, and their formation mechanism and correlation with immunotherapy were further studied. Results: We utilized CytoTRACE.T and CCAT.A to predict differentiation states of terminally exhausted T cells. Then GEO and KEGG pathway gene set enrichment analysis were used. After analyzing, we found out that there was a subset of cells in terminally exhausted T cells defined as TCF19+PD1+TIM3+ Tex cells, which presented low differentiated and high proliferative potential.Then we performed multiple immunofluorescence staining and flow cytometry to verified the existence of TCF19+PD1+TIM3+ Tex cells in vitro. Clarifing the generation of these cell subset through regulating the expression of E2F and MYC transcription factor families.By collecting pathological sections of patients with immunotherapy information, we found that the amount of TCF19+PD1+TIM3+ Tex cells was inversely proportional to the efficacy of ICB, through immunofluorescence staining and immunohistochemical analysis as well as organoid models cocultured with T cells. Conclusion: In this research, we found a new subpopulation of terminal Tex cells, which showed high proliferation and low differentiation. For cells, TCF19 mediated the generation of stemness terminal Tex cells may through regulating the expression of E2F and MYC. Finally, we discovered that the existence of TCF19+PD1+TIM3+ Tex cells can predict the efficacy of ICB, that the more TCF19+PD1+TIM3+ Tex cells contained, the less efficacy of ICB in patients.This finding may provide a new research direction for immunotherapy. Thus, more attention should be paid to this new cell subset. Citation Format: Fuhui Wang, Nan Dong, Changhua Zhang. A new mechanism of tumor immune escape: TCF19 promotes the development of novel terminally exhausted T cells through E2F and MYC transcription family [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 66.

Abstract 762: The combination of EPA and naproxen suppresses colon tumorigenesis via altering the TME, and promoting epithelial maturation in cancerous crypts

Abstract Introduction: Colorectal cancer (CRC) is a leading cause of cancer-associated mortality. Our recent study in Pirc rats revealed that the combination of eicosapentaenoic acid and sodium naproxen exhibited additive tumor protection. While the results from this preclinical study were impressive, showing tumor suppression in excess of 95%, potential mechanisms underlying this tumor protection remain unclear. The purpose of this study was to determine the transcriptomic changes resulting in the tumor suppression afforded by the combination of EPA and naproxen supplementation in the diet. Methods: Six week-old Pirc rats were fed either a control AIN-93G diet, or AIN-93G diet supplemented with 2% EPA combined with 200 ppm naproxen, for a total of 20 weeks. Global transcriptomic analysis was performed using RNA sequencing (RNA-Seq) of colon tumors and tumor-adjacent normal tissue from 26-week-old Pirc rats. 100-bp paired-end sequencing was performed on an Illumina NovaSeq to a depth of 25 million reads per sample. Reads were trimmed with Trimmomatic-v0.39, and reads were mapped to the mRatBN7.2.105 rat reference genome using HISAT2. Differentially expressed genes were calculated using DESeq2, and gene set enrichment analysis (GSEA) were performed using Rstudio. Results: DESeq2 identified 809 differentially expressed genes (DEGs, 2-fold change > 1, FDR < 0.05) between large tumors from AIN-93G fed rats versus suppressed tumors from rats fed the combination of EPA and naproxen (490 up-regulated, 319 down-regulated). GSEA analysis revealed activation of inflammatory pathways including IL-17 signaling, JAK-STAT signaling, complement activation, cytokine signaling, ribosome biogenesis, and cell cycle were enriched in untreated control. In contrast, suppressed tumors from animals supplemented with EPA and naproxen were enriched in pathways including negative regulation of Wnt signaling, cell fate specification, ion channel complexes, and nutrient absorption. Furthermore, suppressed tumors shared significant GSEA pathway overlap with normal tissue, leading us to believe the combination of EPA and naproxen may be preventing tumorigenesis in part by maintaining cells in a differentiated state. Conclusion and Future directions: Inflammation plays a key role in tumorigenesis and promoting cancer stem cell niches in tumors. According to our analysis, the combination of EPA and naproxen attenuated cancer-associated inflammation and reduced proliferation in part by augmenting tumor differentiation. Future studies will utilize single-nuclei RNA-Seq (snRNA-Seq) to determine at a single cell resolution the transcriptomic changes of epithelial and stromal populations within the TME. This work was supported by National Cancer Institute task order 75N91019F00132. Citation Format: Ryan Beach, Michael Martinez, Vignesh Gunasekharan, Daniel W. Rosenberg. The combination of EPA and naproxen suppresses colon tumorigenesis via altering the TME, and promoting epithelial maturation in cancerous crypts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 762.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling.

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Comprehensive analysis revealed the immunoinflammatory targets of rheumatoid arthritis based on intestinal flora, miRNA, transcription factors, and RNA-binding proteins databases, GSEA and GSVA pathway observations, and immunoinfiltration typing

ObjectiveRheumatoid arthritis (RA) is a chronic inflammatory arthritis. This study aimed to identify potential biomarkers and possible pathogenesis of RA using various bioinformatics analysis tools.MethodsThe GMrepo database provided a visual representation of the analysis of intestinal flora. We selected the GSE55235 and GSE55457 datasets from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) separately. With the intersection of these DEGs with the target genes associated with RA found in the GeneCards database, we obtained the DEGs targeted by RA (DERATGs). Subsequently, Disease Ontology, Gene Ontology, and the Kyoto Encyclopedia of Genes and Genomes were used to analyze DERATGs functionally. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed on the data from the gene expression matrix. Additionally, the protein-protein interaction network, transcription factor (TF)-targets, target-drug, microRNA (miRNA)-mRNA networks, and RNA-binding proteins (RBPs)-DERATGs correlation analyses were built. The CIBERSORT was used to evaluate the inflammatory immune state. The single-sample GSEA (ssGSEA) algorithm and differential analysis of DERATGs were used among the infiltration degree subtypes.ResultsThere were some correlations between the abundance of gut flora and the prevalence of RA. A total of 54 DERATGs were identified, mainly related to immune and inflammatory responses and immunodeficiency diseases. Through GSEA and GSVA analysis, we found pathway alterations related to metabolic regulations, autoimmune diseases, and immunodeficiency-related disorders. We obtained 20 hub genes and 2 subnetworks. Additionally, we found that 39 TFs, 174 drugs, 2310 miRNAs, and several RBPs were related to DERATGs. Mast, plasma, and naive B cells differed during immune infiltration. We discovered DERATGs’ differences among subtypes using the ssGSEA algorithm and subtype grouping.ConclusionsThe findings of this study could help with RA diagnosis, prognosis, and targeted molecular treatment.

Diurnal gene expression patterns in retina and choroid distinguish myopia progression from myopia onset.

The world-wide prevalence of myopia (nearsightedness) is increasing, but its pathogenesis is incompletely understood. Among many putative mechanisms, laboratory and clinical findings have implicated circadian biology in the etiology of myopia. Consistent with a circadian hypothesis, we recently reported a marked variability in diurnal patterns of gene expression in two crucial tissues controlling post-natal refractive development - the retina and choroid-at the onset of form-deprivation myopia in chick, a widely studied and validated model. To extend these observations, we assayed gene expression by RNA-Seq in retina and choroid during the progression of established unilateral form-deprivation myopia of chick. We assayed gene expression every 4 hours during a single day from myopic and contralateral control eyes. Retinal and choroidal gene expression in myopic vs. control eyes during myopia progression differed strikingly at discrete times during the day. Very few differentially expressed genes occurred at more than one time in either tissue during progressing myopia. Similarly, Gene Set Enrichment Analysis pathways varied markedly by time during the day. Some of the differentially expressed genes in progressing myopia coincided with candidate genes for human myopia, but only partially corresponded with genes previously identified at myopia onset. Considering other laboratory findings and human genetics and epidemiology, these results further link circadian biology to the pathogenesis of myopia; but they also point to important mechanistic differences between the onset of myopia and the progression of established myopia. Future laboratory and clinical investigations should systematically incorporate circadian mechanisms in studying the etiology of myopia and in seeking more effective treatments to normalize eye growth in children.

Signaling Pathway Gene Set Enrichment Analysis in Whole Exome Sequencing Data from Discordant Identical Twins Unveils Relevant Pathways As a Clue to Understand Somatic Mutation Acquisition and Clonal Evolution in Myeloproliferative Neoplasms

Although the role of classic driver mutations (i.e., JAK2, MPL, and CALR) in myeloproliferative neoplasm (MPN) development is well characterized, additional somatic mutations likely modulate the phenotype. Recurrent somatic mutations, such as those in TET2, DNMT3A, ASXL1 genes are commonly identified in MPN using targeted myeloid panels, however identification of somatic mutations using an unbiased approach may unveil novel pathways involved in MPN pathogenesis. We performed whole exome sequencing of blood samples of three sets of discordant identical twins in which one twin has MPN and the other twin is unaffected. The twin sets included all MPN subtypes (1 polycythemia vera, 1 essential thrombocythemia, 1 primary myelofibrosis). We also performed whole exome sequencing on additional family members, including the mother and father of the PV twin and the brother of the ET twin. Sequencing information from the discordant identical twins is a unique opportunity to identify somatic mutations in the affected twin that may contribute to MPN pathogenesis, and also to potentially identify clonal hematopoiesis in the unaffected twin. We mapped all the identified genetic variants to the affected genes, and we filtered all the genes mapped to those variants depending on whether they were present either in the MPN-affected twin or in the unaffected counterpart for further gene set enrichment pathway analysis. The gene set enriched signaling pathways from identified genetic variants for each condition-exclusive (either MPN or unaffected twin) allows us to identify and prioritize key pathways in MPN development in terms of somatic mutations acquisition. Furthermore, besides performing the analysis within each single MPN set, we analyzed the gene sets resulting from combining the different families allowing us not only to identify pathways at each single MPN type level but also among the different MPN diseases (PV, ET, and MF). We divided all the enrichment analyses into coding and silent variants to obtain a higher degree of pathway refinement. In single discordant twin sets we identified several pathways that may play an important role within MPN pathogenesis such as defective mismatch DNA repair, facilitated mitotic progression, extracellular matrix degradation, MAPK signaling, FGFR signaling, O-glycosylation of proteins, collagen metabolism and laminin interactions, neutrophil degranulation, interleukin-33 signaling, Rho GTPases and cGMP regulation, and nuclear pore complex (NPC) assembly. Interestingly, only when we analyze all the MPN-types together all the statistically significant pathways resulting from coding variants correspond only to DNA repair, specifically defective mismatch repair (PMS2, MLH1, MutSα, MutSβ, and TP53). Our findings reveal that DNA repair genes might occupy a central role within MPN acquisition and development, whereas at the same time each single MPN clinical entity might possess its own distinct mechanisms differentiating each one from the others.

Sigma-1 receptor expression in a subpopulation of lumbar spinal cord microglia in response to peripheral nerve injury

Sigma-1 Receptor has been shown to localize to sites of peripheral nerve injury and back pain. Radioligand probes have been developed to localize Sigma-1 Receptor and thus image pain source. However, in non-pain conditions, Sigma-1 Receptor expression has also been demonstrated in the central nervous system and dorsal root ganglion. This work aimed to study Sigma-1 Receptor expression in a microglial cell population in the lumbar spine following peripheral nerve injury. A publicly available transcriptomic dataset of 102,691 L4/5 mouse microglial cells from a sciatic-sural nerve spared nerve injury model and 93,027 age and sex matched cells from a sham model was used. At each of three time points—postoperative day 3, postoperative day 14, and postoperative month 5—gene expression data was recorded for both spared nerve injury and Sham cell groups. For all cells, 27,998 genes were sequenced. All cells were clustered into 12 distinct subclusters and gene set enrichment pathway analysis was performed. For both the spared nerve injury and Sham groups, Sigma-1 Receptor expression significantly decreased at each time point following surgery. At the 5-month postoperative time point, only one of twelve subclusters showed significantly increased Sigma-1 Receptor expression in spared nerve injury cells as compared to Sham cells (p = 0.0064). Pathway analysis of this cluster showed a significantly increased expression of the inflammatory response pathway in the spared nerve injury cells relative to Sham cells at the 5-month time point (p = 6.74e−05). A distinct subcluster of L4/5 microglia was identified which overexpress Sigma-1 Receptor following peripheral nerve injury consistent with neuropathic pain inflammatory response functioning. This indicates that upregulated Sigma-1 Receptor in the central nervous system characterizes post-acute peripheral nerve injury and may be further developed for clinical use in the differentiation between low back pain secondary to peripheral nerve injury and low back pain not associated with peripheral nerve injury in cases where the pain cannot be localized.

Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer.

Gastric cancer (GC) is one of the most common malignant tumors with poor prognosis in terms of advanced stage. However, the survival-associated biomarkers for GC remains unclear. To investigate the potential biomarkers of the prognosis of patients with GC, so as to provide new methods and strategies for the treatment of GC. RNA sequencing data from The Cancer Genome Atlas (TCGA) database of STAD tumors, and microarray data from Gene Expression Omnibus (GEO) database (GSE19826, GSE79973 and GSE29998) were obtained. The differentially expressed genes (DEGs) between GC patients and health people were picked out using R software (x64 4.1.3). The intersections were underwent between the above obtained co-expression of differential genes (co-DEGs) and the DEGs of GC from Gene Expression Profiling Interactive Analysis database, and Gene Ontology (GO) analysis, Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), Protein-protein Interaction (PPI) analysis and Kaplan-Meier Plotter survival analysis were performed on these DEGs. Using Immunohistochemistry (IHC) database of Human Protein Atlas (HPA), we verified the candidate Hub genes. With DEGs analysis, there were 334 co-DEGs, including 133 up-regulated genes and 201 down-regulated genes. GO enrichment analysis showed that the co-DEGs were involved in biological process, cell composition and molecular function pathways. KEGG enrichment analysis suggested the co-DEGs pathways were mainly enriched in ECM-receptor interaction, protein digestion and absorption pathways, etc. GSEA pathway analysis showed that co-DEGs mainly concentrated in cell cycle progression, mitotic cell cycle and cell cycle pathways, etc. PPI analysis showed 84 nodes and 654 edges for the co-DEGs. The survival analysis illustrated 11 Hub genes with notable significance for prognosis of patients were screened. Furtherly, using IHC database of HPA, we confirmed the above candidate Hub genes, and 10 Hub genes that associated with prognosis of GC were identified, namely BGN, CEP55, COL1A2, COL4A1, FZD2, MAOA, PDGFRB, SPARC, TIMP1 and VCAN. The 10 Hub genes may be the potential biomarkers for predicting the prognosis of GC, which can provide new strategies and methods for the diagnosis and treatment of GC.

Retinal transcriptome of neonatal mice after optic nerve injury.

The axonal growth capacity of retinal ganglion cells decreases dramatically within the first day of birth, and the axonal regeneration after injury in mature mammals is very limited. Here, this study aimed to delineate the transcriptomic changes associated with altered axonal growth capacity and to identify the key genes associated with axonal regeneration by the RNA sequencing (RNA-Seq) analysis. The whole retinas from the mice of embryonic day (E) 20, postnatal day (P) 1 and P3 were collected at 6 hours after optic nerve crush (ONC). Differentially expressed genes (DEGs) for ONC or ages were identified by the RNA-Seq analysis. K-means analysis was conducted for the clustering of DEGs based on expression patterns. Enrichment of functions and signaling pathways analysis were performed based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and Gene Set Enrichment analysis (GSEA). Quantitative real time polymerase chain reaction (qRT-PCR) was used to validate the DEGs selected from the RNA-Seq analysis. In total, 5,408 DEGs were identified for ages, and 2,639 DEGs in neonatal mouse retina after ONC. K-means analysis revealed 7 clusters in age-DEGs and 11 clusters in ONC-DEGs. The GO, KEGG and GSEA pathway analyses identified significantly enrichment of DEGs in the visual perception and phototransduction for the age effect, and the break repair, neuron projection guidance, and immune system pathway for the ONC. PPI analysis identified hub genes in the axon-related gene cluster. The expressions of Mlc1, Zfp296, Atoh7, Ecel1, Creb5, Fosb, and Lcn2, thought to be involved in RGC death and axonal growth were validated by qRT-PCR. This study, for the first time, delineated the gene expression changes following ON injury in embryonic and neonatal mice, providing a new resource of age- and injury-driven data on axonal growth capacity.

MRNA Expression Profiles and Molecular Biomarkers Involved in Inflammatory Response for Essential Hypertension in Kazakh Population From Xinjiang

Abstract Background To identify hypertensive inflammation-related mRNA in peripheral blood mononuclear cells (PBMCs) from patients with essential hypertension (EH) of Kazakh Chinese population in Xinjiang, and offer theoretical foundation for further understanding the immune mechanisms that contribute to EH in Kazakh and provide specific molecular biomarkers for clinical diagnosis and targeted-specific treatments of this disorder. Methods Thirty Kazakh patients with EH and 30 age-matched healthy Kazakh people were divided into EH group and control group. After performing blood pressure measurement and determination of serum lipids and blood glucose, total RNA was isolated from PBMCs of hypertensive Kazakh patients and healthy Kazakh subjects, and differentially expressed mRNA in 6 randomly selected samples from each group were identified with human lncRNA/mRNA V4.0 microarray. Gene set enrichment analysis (GSEA), disease process, the Gene Ontology (GO), and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of differentially expressed mRNA were carried out using R language and ClusterProfiler software package. Reverse transcription quantitative real-time PCR (qRT-PCR) was used to validate the differential expression pattern of inflammation-related genes in the mRNA microarray data and results of bioinformatics analysis. Results The average blood pressure was significantly higher in the EH group than those in the control group (P < 0.01), while there was no statistical significance for the levels of serum lipids and blood glucose between the 2 groups. Compared with healthy Kazakh controls, a total of 522 mRNA were significantly differentially expressed from PBMCs of hypertensive Kazakh patients with fold change of ≥1.5 and P value <5% in expression. Among them, 411 were upregulated and 111 were downregulated. GO enrichment analysis of upregulated mRNA identified numerous inflammation-related biological processes and molecular functions. Many of these processes and molecular function were mainly involved in immune response-regulating signaling pathway, immune response-activating signal transduction, antigen binding, immunoglobulin receptor binding and peptide antigen binding, etc. GSEA and KEGG pathway analysis for the upregulated mRNA indicated several positively enriched gene sets and pathways related to inflammatory response, such as focal adhesion, cell adhesion molecules, chemokine signaling pathway, leukocyte transendothelial migration, cytokine–cytokine receptor interaction, and B-cell receptor signaling pathway. qRT-PCR validation results of 14 mRNA related to inflammatory response were consistent with the microarray data. Conclusions This is the first study to identify gene expression profile involved in hypertensive inflammation in Kazakh Chinese population in Xinjiang with EH, and not only provides specific molecular biomarkers for predicting and diagnosing progression of EH, but also will provide targeted-specific treatments of this disorder in Kazakh Chinese population in Xinjiang.

IPSC-derived retinal pigmented epithelial cells from patients with macular telangiectasia show decreased mitochondrial function.

Patient-derived induced pluripotent stem cells (iPSCs) provide a powerful tool for identifying cellular and molecular mechanisms of disease. Macular telangiectasia type 2 (MacTel) is a rare, late-onset degenerative retinal disease with an extremely heterogeneous genetic architecture, lending itself to the use of iPSCs. Whole-exome sequencing screens and pedigree analyses have identified rare causative mutations that account for less than 5% of cases. Metabolomic surveys of patient populations and GWAS have linked MacTel to decreased circulating levels of serine and elevated levels of neurotoxic 1-deoxysphingolipids (1-dSLs). However, retina-specific, disease-contributing factors have yet to be identified. Here, we used iPSC-differentiated retinal pigmented epithelial (iRPE) cells derived from donors with or without MacTel to screen for novel cell-intrinsic pathological mechanisms. We show that MacTel iRPE cells mimicked the low serine levels observed in serum from patients with MacTel. Through RNA-Seq and gene set enrichment pathway analysis, we determined that MacTel iRPE cells are enriched in cellular stress pathways and dysregulation of central carbon metabolism. Using respirometry and mitochondrial stress testing, we functionally validated that MacTel iRPE cells had a reduction in mitochondrial function that was independent of defects in serine biosynthesis and 1-dSL accumulation. Thus, we identified phenotypes that may constitute alternative disease mechanisms beyond the known serine/sphingolipid pathway.

COL12A1 as a prognostic biomarker links immunotherapy response in breast cancer.

Immunotherapy has shown promising efficacy for breast cancer (BC) patients. Yet the predictive biomarkers for immunotherapy response remain lacking. Based on two GEO datasets, 53 differentially expressed genes associated with durvalumab treatment response were identified. Using least absolute shrinkage and selection operator (LASSO) and univariate Cox regression, four genes (COL12A1, TNN, SCUBE2, and FDCSP) revealed prognostic value in the TCGA BC cohort. COL12A1 outperformed the others, without overlap in its survival curve. Survival analysis by Kaplan-Meier plotter demonstrated that COL12A1 was negatively associated with BC patients' prognosis. A COL12A1-based nomogram was further developed to predict the overall survival in BC patients. The calibration plot revealed an optimal agreement between nomogram prediction and actual observation. Moreover, COL12A1 expression was significantly up-regulated in BC tissues and COL12A1 knockdown impaired the proliferation of MDA-MB-231 and BT549 cells. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment analysis pathway indicated that the function of COL12A1 was related to immunity-related pathways. Immunological analyses illustrated that COL12A1 was correlated with M2 macrophage infiltration and M2 macrophage markers (transforming growth factor beta 1 (TGFB1), interleukin-10, colony stimulating factor 1 receptor (CSF1R) and CD163) in BC. Immunohistochemistry staining further revealed a highly positive relationship of COL12A1 with TGF-β1. The co-incubated models of BC cells and M2 macrophges showed COL12A1 knockdown suppressed M2 macrophage infiltration. Additionally, silencing COL12A1 suppressed TGF-B1 protein expression, and treating with TGFB1 could reverse the inhibitory effects on M2 macrophage infiltration by COL12A1 knockdown. Using immunotherapy datasets, we also found elevated expression of COL12A1 predicted poor response to anti-PD-1/PD-L1 therapy. These results reinforce the current understanding of COL12A1's roles in tumorigenesis and immunotherapy response in BC.

Functional networks of the human bromodomain-containing proteins.

Background: Bromodomains are a structurally conserved epigenetic reader domain that bind to acetylated lysine residues in both histone and non-histone proteins. Bromodomain-containing proteins (BRD proteins) often function as scaffolding proteins in the assembly of multi-protein complexes to regulate diverse biological processes. BRD proteins have been classified based on biological and functional similarity, however the functions of many BRD proteins remains unknown. PPI network analysis is useful for revealing organizational roles, identifying functional clusters, and predicting function for BRD proteins. Results: We used available data to construct protein-protein interaction networks (PPINs) to study the properties of the human bromodomain protein family. The network properties of the BRD PPIN establishes that the BRD proteins serve as hub proteins that are enriched near the global center to form an inter-connected PPIN. We identified dense subgraphs formed by BRD proteins and find that different BRD proteins share topological similarity and functional associations. We explored the functional relationships through clustering and Hallmark pathway gene set enrichment analysis and identify potential biological roles for different BRD proteins. Conclusion: In our network analysis we confirmed that BRD proteins are conserved central nodes in the human PPI network and function as scaffolds to form distinctive functional clusters. Overall, this study provides detailed insight into the predictive functions of BRD proteins in the context of functional complexes and biological pathways.

High RRM2 expression has poor prognosis in specific types of breast cancer.

RRM2 plays an important role in different malignant tumors, but there are few studies in breast cancer. Public databases were used to analyze the expression of RRM2 in breast cancer and its prognostic value. A total of 2,509 breast cancer samples were downloaded from the METABRIC database. The relationship between RRM2 expression and clinical pathology was evaluated. Using the BCIP database and real-time-PCR, and western blotting, RRM2 mRNA and protein expression of RRM2 in breast cancer tissues and cell lines were evaluated. Univariate and multivariate analysis defined independent prognostic factors that affected the overall survival of patients with breast cancer. The Kaplan-Meier method was used to study the relationship between the high expression of RRM2 and overall survival and distant metastasis-free survival (DMFS) of breast cancer patients. Finally, We performed Gene Set Enrichment Analysis (GSEA) and obtained the relevant pathways associated with high expression of RRM2 potentially influencing breast cancer progression. RRM2 expression was significantly correlated with age, tumor size, grade, menopausal status, molecular typing, ER, PR, and Her-2 of patients with breast cancer(P<0.05). Univariate and multivariate regression analysis showed that RRM2, the number of positive lymph nodes, ER, Her-2, tumor size, and tumor stage can be used as independent prognostic factors for overall survival of patients with breast cancer. Kaplan-Meier analysis showed that in patients with Luminal A and Normal like breast cancers and Stage1 and stage2 breast cancers, patients with high expression of RRM2 had worse overall survival and DMFS. The analysis of the GSEA pathway showed that RRM2 is mainly enriched in the ERBB signaling pathway and other pathways. The high expression of RRM2 has a worse prognosis in patients with breast cancer with specific features. It can be used as a biomarker for the prognosis of breast cancer.

Identification and Validation of an EMT-Related LncRNA Signature for HNSCC to Predict Survival and Immune Landscapes.

Long noncoding RNAs (lncRNAs) are increasingly recognized as decisive factors in the progression of head and neck squamous cell carcinoma (HNSCC), and they participate in the epithelial–mesenchymal transformation (EMT) of HNSCC. LncRNAs are closely related to the prognosis of patients with HNSCC; thus, it is essential to identify EMT-related lncRNAs with prognostic value for HNSCC. The coexpression network of EMT-related lncRNAs was constructed using The Cancer Genome Atlas (TCGA). An EMT-related eight-lncRNA-based prognostic signature was constructed using LASSO Cox regression and Cox proportional hazards analyses. Univariate and multivariate analyses and stratified prognosis confirmed that the prognostic signature was an independent predictive factor. Subsequently, we performed immune cell infiltration analysis, gene set enrichment analysis (GSEA), and single-sample GSEA (ssGSEA) pathway enrichment analysis to uncover the potential molecular mechanisms of prognostic differences in the high- and low-risk groups. Next, we discussed the relationship between the prognostic signature and immune checkpoint-related genes, their TIDE scores, and the sensitivity of common chemotherapeutics. Finally, we further verified the expression differences in lncRNAs that were included in our signature via RT–qPCR in eighteen paired tissues. In summary, this prognostic signature provides powerful prognostic biomarkers for HNSCC and could serve as a predictor for the sensitivity of common chemotherapeutics and immunotherapy responses as well as providing a reference for further personalized treatment.

WGCNA and LASSO algorithm constructed an immune infiltration-related 5-gene signature and nomogram to improve prognosis prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common immunogenic malignant tumor. Although the new strategies of immunotherapy and targeted therapy have made considerable progress in the treatment of HCC, the 5-year survival rate of patients is still very low. The identification of new prognostic signatures and the exploration of the immune microenvironment are crucial to the optimization and improvement of molecular therapy strategies. We studied the potential clinical benefits of the inflammation regulator miR-93-3p and mined its target genes. Weighted gene co-expression network analysis (WGCNA), univariate and multivariate COX regression and the LASSO COX algorithm are employed to identify prognostic-related genes and construct multi-gene signature-based risk model and nomogram for survival prediction. Support vector machine (SVM) based Cibersort’s deconvolution algorithm and gene set enrichment analysis (GSEA) is used to evaluate the changes in tumor immune microenvironment and pathway differences. The study found the favorable prognostic performance of miR-93-3p and identified 389 prognostic-related target genes. The risk model based on a novel 5-gene signature (cct5, cdk4, cenpa, dtnbp1 and flvcr1) was developed and has prominent prognostic significance in the training cohort (P < 0.0001) and validation cohort (P = 0.0016). The nomogram constructed by combining the gene signature and the AJCC stage further improves the survival prediction ability of the gene signature. The infiltration level of multiple immune cells (especially T cells, B cells and macrophages) were positively correlated with the expression of prognostic signature. In addition, we found that gene markers of T cells and B cells is monitored and regulated by prognostic signature. Meanwhile, several GSEA pathways related to the immune system are enriched in the high-risk group. In general, we integrated the WGCNA, LASSO COX and SVM algorithms to develop and verify 5-gene signatures and nomograms related to immune infiltration to improve the survival prediction of patients.

Thyrotrophin and thyroxine support immune homeostasis in humans.

SummaryThe endocrine and the immune systems interact by sharing receptors for hormones and cytokines, cross‐control and feedback mechanisms. To date, no comprehensive study has assessed the impact of thyroid hormones on immune homeostasis. By studying immune phenotype (cell populations, antibody concentrations, circulating cytokines, adipokines and acute‐phase proteins, monocyte–platelet interactions and cytokine production capacity) in two large independent cohorts of healthy volunteers of Western European descent from the Human Functional Genomics Project (500FG and 300BCG cohorts), we identified a crucial role of the thyroid hormone thyroxin (T4) and thyroid‐stimulating hormone (TSH) on the homeostasis of lymphocyte populations. TSH concentrations were strongly associated with multiple populations of both effector and regulatory T cells, whereas B‐cell populations were significantly associated with free T4 (fT4). In contrast, fT4 and TSH had little impact on myeloid cell populations and cytokine production capacity. Mendelian randomization further supported the role of fT4 for lymphocyte homeostasis. Subsequently, using a genomics approach, we identified genetic variants that influence both fT4 and TSH concentrations and immune responses, and gene set enrichment pathway analysis showed enrichment of fT4‐affected gene expression in B‐cell function pathways, including the CD40 pathway, further supporting the importance of fT4 in the regulation of B‐cell function. In conclusion, we show that thyroid function controls the homeostasis of the lymphoid cell compartment. These findings improve our understanding of the immune responses and open the door for exploring and understanding the role of thyroid hormones in the lymphocyte function during disease.