Gene Expression Profiles Of Tissues Research Articles

Sex effects on gingival transcriptomic patterns during initiation, progression, and resolution of periodontitis.

The prevalence and severity of periodontitis demonstrates altered population distribution with age, sex, and race and ethnicity. While males exhibit greater frequency of disease, particularly with aging, the underlying basis for this observation remains obscure. This study used a nonhuman primate (Macaca mulatta) model of experimental ligature-induced periodontitis in adult animals to evaluate gingival transcriptomic differences stratified based upon sex of the animal. The 18 animals represented humans ages 40-80 years, with gingival tissue samples obtained at baseline, 0.5 months (initiation), 1 and 3 months (progression), and at 5 months that were 60 days after ligature removal for clinical disease resolution. Microarray analysis was used to quantify gene expression profiles in the gingival tissues. The results demonstrated clear gene expression differences in healthy (baseline) tissues between the sexes, with elevations in females associated with immune responses and elevation in males related to tissue structural genes. With disease initiation, fewer genes differed between the sexes, while these differences were significantly increased in progressing disease and resolution, particularly in male animals. Overexpressed biological processes showed tissue structural/functional genes at initiation, with host response pathways altered during disease progression. Resolution samples generally demonstrated biological processes of cellular metabolism that differed from baseline healthy samples. The transcriptomic findings support sex as a biological variable in periodontitis using a nonhuman primate model of experimental periodontitis.

Prognostic Values of Core Genes in Pilocytic Astrocytom

Pilocytic astrocytoma (PA) is the most common primary brain tumor in children and adolescents. Treatment strategy largely depends on its key genes and molecular mutations. This study aimed to identify potential biomarkers of PA closely related to its prognosis. The gene expression profiles (series numbers GSE50161, GSE66354, and GSE86574) of PA and normal brain tissues were downloaded from the Gene Expression Omnibus database. The Gene Expression Omnibus2R was used to identify differentially expressed genes. The overlapping differentially expressed genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. A protein-protein interaction network was constructed using Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) tool analyzed the impact of hub genes on PA prognosis based on the Kaplan-Meier curves. Compared with normal brain tissues (n= 36), a total of 37 upregulated and 144 downregulated genes were identified in PA (n= 40). In the protein-protein interaction network construction and GEPIA2 survival analysis, 2 of the top 10 hub genes were significantly associated with decreased overall survival of PA patients, namely Gamma-aminobutyric acid A receptor alpha 2 (hazard ratio = 2.8, P < 0.01) and regulating synaptic membrane exocytosis protein 1) (hazard ratio= 3.2, P < 0.01). This bioinformatics analysis reveals that low expression of Gamma-aminobutyric acid A receptor alpha 2 and regulating synaptic membrane exocytosis protein 1 is associated with a favorable prognosis for PA patients. These 2 hub genes could be novel biomarkers for prognosis assessment, furthermore a key element for treatment decisions in the future.

Expression analysis of m6A-related genes in various tissues of Meishan pigs at different developmental stages

To characterize the N6-methyladenosine (m6A)-related gene expression profiles in various tissues of Meishan pigs at different stages, m6A modification-related genes (METTL3, METTL14, METTL16, WTAP, RBM15, and FTO) were detected from newborn to physical maturity of Meishan pigs at eight important developmental stages (1, 7, 14, 21, 28, 35, 134, and 158 days old). The expression of m6A-related genes was tissue-specific. Furthermore, the level of METTL3 messenger RNA (mRNA) was higher on day 35 than in other stages in most [...]

Novel mechanisms of cadmium tolerance and Cd-induced fungal stress in wheat: Transcriptomic and metagenomic insights

Although several studies on the effects of cadmium (Cd) on wheat have been reported, the gene expression profiles of different wheat tissues in response to gradient concentrations of Cd, and whether soil microorganisms are involved in the damage to wheat remain to be discovered. To gain further insight into the molecular mechanisms of Cd-resistance in wheat, we sowed bread wheat (Triticum aestivum) in artificially Cd-contaminated soil and investigated the transcriptomic response of the wheat roots, stems, and leaves to gradient concentrations of Cd, as well as the alteration of the soil microbiome. Results indicated that the root bioaccumulation factors increased with Cd when concentrations were < 10 mg/kg, but at even higher concentrations, the bioaccumulation factors decreased, which is consistent with the overexpression of metal transporters and other genes related to Cd tolerance. In the Cd-contaminated soil, the abundance of fungal pathogens increased, and the antimicrobial response in wheat root was observed. Most of the differentially expressed genes (DEGs) of wheat changed significantly when the Cd concentration increased above 10 mg/kg, and the transcriptional response is much greater in roots than in stems and leaves. The DEGs are mainly involved in Cd transport and chelation, antioxidative stress, antimicrobial responses, and growth regulation. COPT3 and ZnT1 were identified for the first time as the major transporters responding to Cd in wheat. Overexpression of the nicotianamine synthase and pectinesterase genes suggested that nicotianamine and pectin are the key chelators in Cd detoxification. endochitinase, chitinase, and snakin2 were involved in the anti-fungal stress caused by Cd-induced cell damage. Several phytohormone-related DEGs are involved in the root’s growth and repair. Overall, this study presents the novel Cd tolerance mechanisms in wheat and the changes in soil fungal pathogens that increase plant damage.

Abstract 5559: Exploratory analysis of hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) PIK3CA mutated (mut) advanced breast cancer (aBC) treated with taselisib (TAS) and/or fulvestrant (FUL) reveals increased CCNE2 expression with poor outcome to placebo (PBO) + FUL but not TAS + FUL in SANDPIPER

Abstract PIK3CA mutations occur in ~40% of patients (pts) with HR+/HER2- aBC. TAS is a potent and selective β-sparing PI3K inhibitor that has shown modest clinical benefit when combined with FUL endocrine therapy in patients (pts) with PIK3CAmut aBC. To better understand the molecular features associated with response to TAS and/or FUL, we examined the gene expression profiles of archival tissue from pts enrolled in SANDPIPER (NCT02340221). Most patients did not have prior treatment with a CDK4/6i. RNA sequencing was performed on baseline tissue samples from 456 pts with PIK3CAmut tumors. Exploratory biomarker analyses revealed 28 genes associated with worse outcome. Of these, CCNE2 [HR=1.11 (1.04-1.19), p=0.002], RRM2 [HR=1.14 (1.07-1.22), p&amp;lt;0.0001] and TUB4A [HR=1.15 (1.05-1.26), p=0.004] are involved in the regulation of mitotic cell cycle. CCNE2 encodes CYCLIN E2, a G1 cyclin that binds and activates CDK2. Elevated expression of CCNE2 has been associated with poor outcome in ER-positive breast cancer, and has been identified as part of gene signatures that predict disease progression in tamoxifen-resistant breast cancer or advanced breast cancer. Since CCNE2 expression may be a marker of more proliferative tumors, we assessed whether the inclusion of CCNE2 gene expression would add value to a prognostic model that already includes cell cycle as a factor. Analysis of deviance after sequential addition of variables into Coxph models with stratification factors showed that elevated CCNE2 expression is significant, in addition to cell cycle signature scores, for association with worse PFS (likelihood ratio test p = 0.001). When we grouped patients based on CCNE2 expression split by quartile with the highest values (Q4) grouped as CCNE2 high vs lower values (Q1-Q3), we found that the CCNE2 high group does worse in the PBO + FUL treatment arm. Median PFS for CCNE2-high group in the placebo arm was 3.75 months compared to the other groups (log-rank p &amp;lt; 0.0001; PBO, CCNE2-low 7.3 months, TAS, CCNE2-high 7.6 months; TAS, CCNE2-low 7.3 months). A significant statistical interaction was observed between high CCNE2 gene expression and PBO + FUL treatment arm HR=1.51 (1.03-2.20), p=0.04], suggesting that CCNE2 expression may be associated with poor PFS to in 2L ER+/HER2- PIK3CAmut aBC patients that receive PBO + FUL. Our analysis revealed an association between high CCNE2 expression and worse PFS in patients that received PBO + FUL. Further, this association was not observed in the patients that received the combination of TAS+FUL, which may inform future rational combination strategies for the clinical development of PI3K inhibitors in ER+/HER2- PIK3CAmut aBC. Citation Format: Radia M. Johnson, Bonnie Liu, Javier Cortés, Susan Dent, Nadia Harbeck, Ian E. Krop, William Jacot, Robert L. Yauch, Thomas J. Stout, Frauke Schimmoller, Steven Gendreau, Timothy R. Wilson. Exploratory analysis of hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) PIK3CA mutated (mut) advanced breast cancer (aBC) treated with taselisib (TAS) and/or fulvestrant (FUL) reveals increased CCNE2 expression with poor outcome to placebo (PBO) + FUL but not TAS + FUL in SANDPIPER. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5559.

Abstract 1406: Long non-coding RNA DUXAP10 is a putative determinant of anaplastic thyroid cancer

Abstract Anaplastic Thyroid Cancer (ATC) is one of the most aggressive forms of cancer, with only a 4% survival rate with metastatic disease. ATC is highly refractory and resistant to both traditional therapeutic modalities and recently discovered small molecule inhibitors. The elucidation of molecular mechanisms that contribute to ATC’s metastatic propensity, and the identification of molecular biomarkers for early diagnosis, prognosis, and therapeutic intervention are critical unmet clinical needs-highlighting the importance of novel avenues of intervention. Recently, long non-coding RNAs (lncRNA) have been described as regulators of gene expression and cancer cell phenotypes, exhibiting the importance of identifying non-coding profiles that potentially impact ATC behavior. Publicly available datasets provided by Gene Expression Omnibus (GSE33630, GSE85457) enabled investigation of gene expression profiles of ATC vs. normal thyroid patient tissue. Bioinformatic analyses with the GEO2R program identified the lncRNA, Double Homeobox A Pseudogene 10 (DUXAP10), to be highly upregulated in ATC patient-derived tissue samples when compared to normal thyroid tissue by about 5logFC. Analysis using Gene Expression Profiling Interactive Analysis shows that high DUXAP10 expression is correlated with decreased survival in thyroid cancer patients. To recapitulate this patient data in an in vitro model, we found that the expression of DUXAP10 is also upregulated in the ATC cell line, T238, in comparison to Nthy-ori-3-1, an immortalized “normal” thyroid cell line. To understand the consequences of DUXAP10 overexpression in ATC, we used CRISPRi technology to determine the phenotypic and genotypic effects of DUXAP10 downregulation. CRISPRi knockdown of DUXAP10 significantly reduces the migratory capabilities of T238 by 50%, invasiveness by 37%, clonogenicity by 70%, cell size by 34%, and proliferation by 28%, 45%, and 36% at 24, 48, and 72 hours, respectively. This provides evidence that elevated DUXAP10 expression may increase the probability and negative consequences of metastases. Thus, targeting DUXAP10 expression may have beneficial clinical outcomes. Identification of the molecular innervations of DUXAP10 that orchestrate these pro-metastatic phenotypic changes are currently in progress. Immediate next steps are aimed toward determining if DUXAP10 can be utilized as a potential biomarker for ATC diagnosis and prognosis, as well as elucidating the full range of interactions that DUXAP10 has in shaping the ATC phenotype. Citation Format: Nicole R. DeSouza, Michelle Carnazza, Danielle Quaranto, Tara Jarboe, Kaci Kopec, Sarnath Singh, Augustine Moscatello, Jan Geliebter, Raj K. Tiwari. Long non-coding RNA DUXAP10 is a putative determinant of anaplastic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1406.

(104) Relation Between Individual Blood Gene Expression Profile (GEP) and Tissue GEP in Antibody-Mediated Rejection in Heart Transplant

(104) Relation Between Individual Blood Gene Expression Profile (GEP) and Tissue GEP in Antibody-Mediated Rejection in Heart Transplant

Prognostic value of COL10A1 and its correlation with tumor-infiltrating immune cells in urothelial bladder cancer: A comprehensive study based on bioinformatics and clinical analysis validation.

Bladder cancer (BLCA) is one of the most lethal diseases. COL10A1 is secreted small-chain collagen in the extracellular matrix associated with various tumors, including gastric, colon, breast, and lung cancer. However, the role of COL10A1 in BLCA remains unclear. This is the first research focusing on the prognostic value of COL10A1 in BLCA. In this research, we aimed to uncover the association between COL10A1 and the prognosis, as well as other clinicopathological parameters in BLCA. We obtained gene expression profiles of BLCA and normal tissues from the TCGA, GEO, and ArrayExpress databases. Immunohistochemistry staining was performed to investigate the protein expression and prognostic value of COL10A1 in BLCA patients. GO and KEGG enrichment along with GSEA analyses were performed to reveal the biological functions and potential regulatory mechanisms of COL10A1 based on the gene co-expression network. We used the "maftools" R package to display the mutation profiles between the high and low COL10A1 groups. GIPIA2, TIMER, and CIBERSORT algorithms were utilized to explore the effect of COL10A1 on the tumor immune microenvironment. We found that COL10A1 was upregulated in the BLCA samples, and increased COL10A1 expression was related to poor overall survival. Functional annotation of 200 co-expressed genes positively correlated with COL10A1 expression, including GO, KEGG, and GSEA enrichment analyses, indicated that COL10A1 was basically involved in the extracellular matrix, protein modification, molecular binding, ECM-receptor interaction, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling pathway. The most commonly mutated genes of BLCA were different between high and low COL10A1 groups. Tumor immune infiltrating analyses showed that COL10A1 might have an essential role in recruiting infiltrating immune cells and regulating immunity in BLCA, thus affecting prognosis. Finally, external datasets and biospecimens were used, and the results further validated the aberrant expression of COL10A1 in BLCA samples. In conclusion, our study demonstrates that COL10A1 is an underlying prognostic and predictive biomarker in BLCA.

Development of alternative herbals remedy for gastric cancer based on transcriptomic analysis of immune infiltration and ferroptosis.

Objective: Screening out potential herbal medicines and herbal ingredients for the treatment of gastric cancer based on transcriptomic analysis of immune infiltration and ferroptosis. Methods: Gene expression profiles of gastric tumour tissues and normal tissue samples were obtained from the GEO database and the samples were analysed for immune cell infiltration condition and differential expressed genes of ferroptosis. Key genes were screened by protein-protein interaction (PPI) and enrichment analysis, and molecular docking was used to predict and preliminary validate potential herbal and traditional Chinese medicine components for gastric cancer based on the key genes. Finally, RT-QPCR was used to validate the prediction results. Results: Immune cell infiltration analysis revealed high levels of infiltration of activated CD4 memory T cells, monocytes, M0 macrophages in gastric tumor tissues, while plasma cells and resting mast cells had higher levels of infiltration in the paraneoplastic tissues. Differential gene expression analysis identified 1,012 upregulated genes and 880 downregulated genes, of which 84 immune related differentially expressed genes such as CTSB, PGF and PLAU and 10 ferroptosis-related differentially expressed genes such as HSF1, NOX4 and NF2 were highly expressed in gastric cancer tissues. The results of enrichment analysis showed that they mainly involve 343 biological processes such as extracellular matrix organization and extracellular structural organization; 37 cellular components such as complexes of collagen trimer and basement membrane; 35 molecular functions such as signal receptor activator activity and receptor ligand activity; 19 regulatory pathways such as cytokine-cytokine receptor interactions and retinol metabolism. Finally, two key genes, TLR4 and KRAS, were selected and 12 herbal medicines such as Radix Salviae liguliobae, Rhizoma Coptidis, Rhizoma Polygoni cuspidati and 27 herbal ingredients such as resveratrol, salvianolic acid b were predicted on the basis of key genes. Molecular docking results showed that KRAS binds tightly to coumarin and magnolol, while TLR4 can bind tightly to resveratrol, curcumin, salvianolic acid b, shikonin. Subsequently, the effect of resveratrol and magnolol was experimentally verified. Conclusion: Herbal medicines such as S. liguliobae, Rhizoma Coptidis, Rhizoma P. cuspidati and herbal ingredients such as resveratrol, curcumin, salvianolic acid b may provide research directions and alternative therapeutic approaches for immunomodulation of TME and ferroptosis of tumour cells in gastric cancer.

Gene Expression Profiling of Subcutaneous Adipose Tissue Reveals New Biomarkers in Acromegaly.

Active acromegaly is characterized by lipolysis-induced insulin resistance, which suggests adipose tissue (AT) as a primary driver of metabolic aberrations. To study the gene expression landscape in AT in patients with acromegaly before and after disease control in order to understand the changes and to identify disease-specific biomarkers. RNA sequencing was performed on paired subcutaneous adipose tissue (SAT) biopsies from six patients with acromegaly at time of diagnosis and after curative surgery. Clustering and pathway analyses were performed in order to identify disease activity-dependent genes. In a larger patient cohort (n = 23), the corresponding proteins were measured in serum by immunoassay. Correlations between growth hormone (GH), insulin-like growth factor I (IGF-I), visceral AT (VAT), SAT, total AT and serum proteins were analyzed. 743 genes were significantly differentially expressed (p-adjusted < 0.05) in SAT before and after disease control. The patients clustered according to disease activity. Pathways related to inflammation, cell adhesion and extracellular matrix, GH and insulin signaling, and fatty acid oxidation were differentially expressed.Serum levels of HTRA1, METRNL, S100A8/A9, and PDGFD significantly increased after disease control (p < 0.05). VAT correlated with HTRA1 (R = 0.73) and S100A8/A9 (R = 0.55) (p < 0.05 for both). AT in active acromegaly is associated with a gene expression profile of fibrosis and inflammation, which may corroborate the hyper-metabolic state and provide a means for identifying novel biomarkers.

Human CXADR Gene – Coxsackie Virus Interaction Analysis to Identify Mutations and SNPs: An Exploratory In–Silico Approach

Coxsackie viruses belong to the enterovirus family which are usually isolated from the stomach and intestinal regions of the human body. The research we have undertook here is an exploration of the human CXADR gene using an in–silico approach to demonstrate the power and effectiveness of various online analytical tools. In this attempt to recognize the various mutations that occur in the CXADR gene, we have chosen 11 SNPs that have deleterious clinical significance. The junction expression profile reveals, the expression of CXADR gene in various tissues. In addition, gene expression profiles of various tissues have enabled us to predict the various diseases that might be caused due to the mutations with varying levels of confidence. The CXADR gene plays a very vital role in the interaction of the Coxsackie virus at the molecular level, as evidenced by their part played in causing a disease named Viral Myocarditis.

Insight into the bZIP gene family in Lagenaria siceraria: Genome and transcriptome analysis to understand gene diversification in Cucurbitaceae and the roles of LsbZIP gene expression and function under cold stress.

The basic leucine zipper (bZIP) as a well-known transcription factor family, figures prominently in diverse biological and developmental processes and response to abiotic/biotic stresses. However, no knowledge of the bZIP family is available for the important edible Cucurbitaceae crop bottle gourd. Herein, we identified 65 putative LsbZIP genes and characterized their gene structure, phylogenetic and orthologous relationships, gene expression profiles in different tissues and cultivars, and responsive genes under cold stress. The phylogenetic tree of 16 released Cucurbitaceae plant genomes revealed the evolutionary convergence and divergence of bZIP family. Based on the specific domains, LsbZIP family were classified into 12 clades (A-K, S) with similar motifs and exon-intron distribution. 65 LsbZIP genes have undergone 19 segmental and two tandem duplication events with purifying selection. The expression profiling of LsbZIP genes showed tissue-specific but no cultivar-specific pattern. The cold stress-responsive candidate LsbZIP genes were analyzed and validated by RNA-Seq and RT-PCR, providing new insights of transcriptional regulation of bZIP family genes in bottle gourd and their potential functions in cold-tolerant variety breeding.

Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response

Aims/hypothesisAlthough insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the probability of successful prevention and intervention. Moreover, treatment efficacy is affected by the genetics of the individual. We used gene expression profiles from a cross-sectional study to identify potential candidate genes for the prediction of diabetes risk and intervention response.MethodsUsing a multivariate regression model, we linked gene expression profiles of human skeletal muscle and intermuscular adipose tissue (IMAT) to fasting glucose levels and glucose infusion rate. Based on the expression patterns of the top predictive genes, we characterised and compared individual gene expression with clinical classifications using k-nearest neighbour clustering. The predictive potential of the candidate genes identified was validated using muscle gene expression data from a longitudinal intervention study.ResultsWe found that genes with a strong association with clinical measures clustered into three distinct expression patterns. Their predictive values for insulin resistance varied substantially between skeletal muscle and IMAT. Moreover, we discovered that individual gene expression-based classifications may differ from classifications based predominantly on clinical variables, indicating that participant stratification may be imprecise if only clinical variables are used for classification. Of the 15 top candidate genes, ST3GAL2, AASS, ARF1 and the transcription factor SIN3A are novel candidates for predicting a refined diabetes risk and intervention response.Conclusion/interpretationOur results confirm that disease progression and successful intervention depend on individual gene expression states. We anticipate that our findings may lead to a better understanding and prediction of individual diabetes risk and may help to develop individualised intervention strategies.Graphical abstract

Gene expression profiles and bioinformatics analysis in lung samples from ovalbumin-induced asthmatic mice

BackgroundAsthma is characterized by chronic inflammation and airway remodeling. However, limited study is conducted on the gene expression profiles of ovalbumin (OVA) induced asthma in mice. Here, we explored the gene expression profiles in lung tissues from mice with OVA-induced asthma using microarray and bioinformatics analysis.MethodsFor establishment of OVA-induced asthma model, mice first received intraperitoneal sensitization with OVA on day 0, 7 and 14, followed by atomizing inhalation of OVA 3 times a week for 8 weeks. The lung tissues were collected and subjected to microarray analysis, bioinformatics analysis and expression validation.ResultsMicroarray data of lung tissues suggested that 3754 lncRNAs and 2976 mRNAs were differentially expressed in lung tissues between control and asthmatic mice, including 1647 up-regulated and 2106 down-regulated lncRNAs, and 1201 up-regulated and 1766 down-regulated mRNAs. GO analysis displayed that the up-regulated genes were enriched in inflammatory response, leukocyte migration involved in inflammatory response, and Notch signaling pathway. KEGG pathway analysis indicated that the enriched pathway terms of the up-regulated gene included Toll-like receptor signaling pathway and Th17 cell differentiation signaling pathway. Additionally, based on the previously published literatures on asthma and inflammation, we screened out down-regulated genes, such as Smg7, Sumo2, and Stat5a, and up-regulated genes, such as Myl9, Fos and Tlr4. According to the mRNA-lncRNA co-expression network, we selected lncRNAs associated with above genes, including the down-regulated lncRNAs of NONMMUT032848, NONMMUT008873, NONMMUT009478, and NONMMUT006807, and the up-regulated lncRNAs of NONMMUT052633, NONMMUT05340 and NONMMUT042325. The expression changes of the above genes were validated in lung tissues by real-time quantitaive PCR and Western blot.ConclusionsOverall, we performed gene microarray on lung samples from OVA-induced asthmatic mice and summarized core mRNAs and their related lncRNAs. This study may provide evidence for further research on the therapeutic targets of asthma.

Estimation of cell lineages in tumors from spatial transcriptomics data

Spatial transcriptomics (ST) technology through in situ capturing has enabled topographical gene expression profiling of tumor tissues. However, each capturing spot may contain diverse immune and malignant cells, with different cell densities across tissue regions. Cell type deconvolution in tumor ST data remains challenging for existing methods designed to decompose general ST or bulk tumor data. We develop the Spatial Cellular Estimator for Tumors (SpaCET) to infer cell identities from tumor ST data. SpaCET first estimates cancer cell abundance by integrating a gene pattern dictionary of copy number alterations and expression changes in common malignancies. A constrained regression model then calibrates local cell densities and determines immune and stromal cell lineage fractions. SpaCET provides higher accuracy than existing methods based on simulation and real ST data with matched double-blind histopathology annotations as ground truth. Further, coupling cell fractions with ligand-receptor coexpression analysis, SpaCET reveals how intercellular interactions at the tumor-immune interface promote cancer progression.

Gene expression profiling of nasal inflammation induced by diesel particles using an in vivo system

Korean diesel particulate matter 20 (KDP20) is a pollutant comprising a complex mixture of carbon and chemical irritants. Although particulate matter and nasal inflammation are strongly associated, the underlying molecular mechanism based on systematic transcriptome analysis remains unknown. In this study, genome-wide gene expression profiles of mouse nasal tissues were determined following exposure to KDP20 for 5 and 10 days and compared with those of the control (n = 4/group). We identified 758 significant differentially expressed genes (DEGs) and classified them as 5-day-specific, 10-day-specific, and common among groups based on their expression patterns. The terms “regulation of alpha-beta T cell differentiation,” “macrophage differentiation,” and “cell adhesion mediated by integrin” were significantly enriched in each group. Receiver operating characteristic analysis revealed six genes as potential predictive biomarkers. The differential expression of these six genes was validated using quantitative RT-PCR (n = 3/group). Furthermore, a possible mechanism for nasal inflammation was suggested through the binding analysis between metal ions and genes. The genes identified in this study may play important roles in regulating the mechanism of nasal inflammation induced by diesel particles, especially immune cell regulation, and may function as markers for diesel particle-induced nasal inflammation.

Transcriptomic profiling revealed FZD10 as a novel biomarker for nasopharyngeal carcinoma recurrence.

Nasopharyngeal carcinoma (NPC) is a type of cancers that develops in the nasopharynx, the very upper part of the throat behind the nose. NPC is typically diagnosed in later stages of the disease and has a high rate of recurrence due to the location of the tumor growth site. In this study, we compared the gene expression profiles of NPC tissues from patients with and without recurrence to identify potential molecular biomarkers of NPC recurrence. Microarrays were used to analyze the expression of genes in 15 NPC tissues taken at the time of diagnosis and at the site of recurrence following therapeutic treatment. Pathway enrichment analysis was used to examine the biological interactions between the major differentially expressed genes. The target identified was then validated using immunohistochemistry on 86 NPC tissue samples. Our data showed that the Wnt signaling pathway was enhanced in NPC tissues with recurrence. FZD10, a component of the Wnt signaling pathway, was significantly expressed in NPC tissues, and was significantly associated with NPC recurrence. Our study provides new insights into the pathogenesis of NPC and identifies FZD10 as a potential molecular biomarker for NPC recurrence. FZD10 may be a promising candidate for NPC recurrence and a potential therapeutic target.

Actin-like Protein 6A Expression Correlates with Cancer Stem Cell-like Features and Poor Prognosis in Ovarian Cancer.

Ovarian cancer has the highest mortality rate among gynecological cancers, often diagnosed at the late stage and lacking an effective targeted therapy. Although the study of malignant features of cancer, considered to be cancer stem cells (CSCs), is emerging, the aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of ovarian cancer from a combined database with CSCs features. The common differentially expressed genes (DEGs) were selected in GSE185833 and GSE176246 datasets from the Gene Expression Omnibus (GEO). The GSE185833 dataset was created to reveal gene expression profiles of peritoneal metastasis tissues using single-cell sequencing, and the GSE176246 dataset was determined from gene expression profiles of chemotherapy-refractory ovarian cancer cell lines compared with ovarian cancer cell lines by RNA-seq analysis. By analyzing the correlation between common DEGs and prognosis of ovarian cancer and its possible pathways and functions were predicted by The Cancer Genome Atlas (TCGA) database. The expression levels of 11 genetic markers were significantly elevated in highly invasive and chemoresistant ovarian cancer. The expression of Actin-like protein 6A (ACTL6A) was found to be correlated with survival prognosis, and the total survival time of the patients with high expression of ACTL6A was shorter than those with low expression. Gene set enrichment analysis (GSEA) showed that ACTL6A positively enriched the gene set of 'Cell cycle' and ACTL6A negatively enriched the gene set of focal adhesion. CP724714, a human epidermal growth factor receptor 2 (HER2) inhibitor, could serve as a therapeutic option when ACTL6A levels are high in ovarian cancer cells. The high expression of ACTL6A is a poor prognostic factor in ovarian cancer and may serve as an effective biomarker for predicting treatment-refractory, metastasis, and prognosis of patients with ovarian cancer. The use of HER2 inhibitors is a promising therapeutic strategy against chemoresistant ovarian cancer.

Host Transcriptome Analysis of Ferret Tissues Following Henipavirus Infection.

Ferrets are commonly used as experimental models of infection for a variety of viruses due to their susceptibility to human respiratory viruses and the close resemblance of pathological outcomes found in human infections. Even though ferret-specific reagents are limited, the use of ferrets as a preclinical experimental model of infection has gained considerable interest since the publication of the ferret transcriptome and draft ferret genome. These advances have made it feasible to easily perform whole-genome gene expression analysis in the ferret infection model. Here, we describe methods for genome-wide gene expression analysis using RNA sequence (RNAseq) data obtained from the lung and brain tissues obtained from experimental infections of Hendra (HeV) and Nipah (NiV) viruses in ferrets. We provide detailed methods for RNAseq and representative data for host gene expression profiles of the lung tissues that show early activation of interferon pathways and later activation of inflammation-related pathways.

Overexpression of Mena is associated with tumor progression and poor prognosis in oral squamous cell carcinoma via EMT.

Mena, a cytoskeletal regulatory protein, is involved in actin-based regulation of cell motility and adhesion, and contributes to tumor invasion and metastasis. However, the role of Mena in oral squamous cell carcinoma remains unclear. This is the first research focusing on the prognostic value of Mena in OSCC. In this study, we aimed to investigate the correlation between Mena expression and clinicopathological significance, as well as prognostic value in OSCC. Mena gene expression profiles of OSCC and normal tissues were collected from Oncomine, TCGA, and GEO databases. Biological function was analyzed through GO, KEGG and GSEA enrichment. Further, the expression level of Mena and tumor-related markers in 151 OSCC specimens was examined by IHC staining based on tissue microarray. Kaplan-Meier analysis was used to assess the prognostic performance of Mena in OSCC. Mena was generally upregulation in various malignancies, especially OSCC. The functional analyses indicated that Mena was involved in the assembly and regulation of actin, cell movement, and EMT. IHC staining revealed that high expression of Mena in OSCC was correlated with Lymphatic metastasis, TNM stage, E-cadherin, Vimentin, and MMP-2, but insignificantly Ki67. Kaplan-Meier analysis demonstrated that elevated expression of Mena was significantly associated with poor overall survival and disease-free survival of OSCC patients. Mena could be a novel biomarker for predicting the prognosis of OSCC patients, which supports a theoretical basis for developing molecular target therapy.