Microarray Expression Profiling Research Articles

Clinical Value Screening, Prognostic Significance, and Key Gene Identification of TrkB in Laryngeal Carcinoma.

Purpose Using human gene chip expression profiling technology to screen out downstream genes related to TrkB regulation in laryngeal cancer cells. Methods Using the Hep-2 TrkB shRNA cell line, divide it into an experimental group (shNTRK2) and a control group (PLKO1), and use the human gene expression microarray to screen out the differential genes. Then, select 10 upregulated genes and 10 downregulated genes from the differential genes, and use RT-PCR to verify whether the screening results of human gene expression microarray profiles are reliable. Use GO, KEGG, and miRNA enrichment analyses, PPI network diagram, etc., to analyze the differential genes and further screen out the key genes. Results A total of 318 differential genes (87 upregulated genes and 231 downregulated genes) were screened in laryngeal cancer cells. Use RT-PCR for the 10 upregulated differential genes (DMKN, FHL1, FOXN4, GGNBP1, HOXB9, ABCB1, TNFAI, RGS2, LINC01133, and FGG) and 10 downregulated differential genes (CHI3L1, FMOD, IGFBP1, IRF5, SPARC, NPAS4, TRPS1, TRAP, COL8A1, and DNER), and the results are consistent with the chip results, confirming the accuracy of the chip results; GO analysis results show that the downstream differential genes (DEGs) regulated by TrkB are mainly involved in biological processes such as retinol metabolic process, diterpenoid metabolic process, and regulation of cell-substrate adhesion. DEGs mainly affect cytoskeletal protein binding, serotonin-activated cation-selective channel activity, and sphingosine molecular functions. DEGs are mainly enriched in the cell periphery, secretory granule, cytoplasmic membrane-bounded vesicle lumen, blood microparticle, and other molecular components. The results of disease enrichment analysis show that the downstream differential genes regulated by TrkB are mainly involved in atypical hemolytic uremic syndrome, hematologic disease, meningococcal disease, lung cancer, susceptibility, asthma, and other diseases. The PPI network diagram results showed 7 hub genes, and then, we used GO analysis and KEGG enrichment analysis to see the biological process, cell component, molecular functions, and biological pathways. Conclusion Gene chip technology was used to screen out the differential genes of TrkB epigenetic modification in the Hep-2 cell line, and seven key genes (ALDH1A1, SDR16C5, PIK3R1, PLCG2, IL2RG, PIK3CD, and SPARC) were further screened using bioinformatics technology.

Genotype-to-Phenotype Associations in the Aggressive Variant Prostate Cancer Molecular Profile (AVPC-m) Components.

Simple SummaryWe treat prostate cancer like it is one disease, but it is clear that it behaves like different diseases in different patients, with some having excellent responses to hormonal therapies and prolonged survivals, and others having virulent, aggressive courses and short survivals. These differences reflect different tumor biologies and therapeutic sensitivities, but the absence of molecular markers that identify each of these subsets makes it difficult to develop treatments specific to each. We found that alterations in two or more of the tumor suppressors TP53, RB1 and PTEN characterize the more virulent prostate cancers, and that patients with this molecular profile (called the aggressive variant prostate cancer molecular profile) appear to benefit more from combination chemotherapies than those without. The alterations in these markers can be determined either by staining tumor tissues or by examining their DNA. In this study, we used 28 mouse models of the human disease to assess the performance of various assays in determining these alterations. We found that although both staining and DNA sequencing are complementary, staining (which is a broadly available technique) is likely sufficient to make these determinations. Our results will inform the use of this molecular signature in clinical research and clinical practice.The aggressive variant prostate cancer molecular profile (AVPC-m), composed of combined defects in TP53, RB1 and PTEN, characterizes a subset of prostate cancers linked to androgen indifference and platinum sensitivity. To contribute to the optimization of the AVPC-m assessment for inclusion in prospective clinical trials, we investigated the status of the AVPC-m components in 28 patient tumor-derived xenografts (PDXs) developed at MDACC. We subjected single formalin-fixed, paraffin-embedded (FFPE) blocks from each PDX to immunohistochemistry (IHC), targeted next-generation genomic sequencing (NGS) and Clariom-S Affymetrix human microarray expression profiling. Standard validated IHC assays and a 10% labeling index cutoff resulted in high reproducibility across three separate laboratories and three independent readers for all tumor suppressors, as well as strong correlations with loss-of-function transcriptional scores (LOF-TS). Adding intensity assessment to labeling indices strengthened the association between IHC results and LOF-TS for TP53 and RB1, but not for PTEN. For TP53, genomic alterations determined by NGS had slightly higher agreement scores with LOF-TS than aberrant IHC, while for RB1 and PTEN, NGS and IHC determinations resulted in similar agreement scores with LOF-TS. Nonetheless, our results indicate that the AVPC-m components can be assessed reproducibly by IHC using various widely available standardized assays.

Identification and Assessment of Necroptosis-Related Genes in Clinical Prognosis and Immune Cells in Diffuse Large B-Cell Lymphoma.

BackgroundWith the unveiling of new mechanisms and the advent of new drugs, the prognosis of diffuse large B-cell lymphoma (DLBCL) becomes promising, but some patients still progress to the relapse or refractory stage. Necroptosis, as a relatively novel programmed cell death, is involved in the development of multiple tumors. There are no relevant studies on the prognostic significance of necroptosis in DLBCL to date.MethodsWe identified the differential necroptosis-related genes (NRGs) by comparing the DLBCL and normal control in GSE12195 and GSE56315 datasets. TCGA DLBC and GSE10846 containing clinical information and microarray expression profiling were merged as the entire cohort. We performed consensus clusters based on NRGs and two clusters were obtained. Kaplan–Meier (K-M) survival analysis, GSVA, GO, KEGG, and ssGSEA were used to analyze the survival, function, and immune microenvironment between two clusters. With LASSO and proportional hazard model construction, we identified differentially expressed genes (DEGs) between NRG clusters, calculated the risk score, established a prognostic model, and validated its value by calibration and ROC curves. The entire cohort was divided into the training and test cohort, and GSE87371 was included as an external validation cohort. K-M, copy number variation, tumor mutation burden, and drug sensitivity were also analyzed.ResultsWe found significant differences in prognosis between the two NRG clusters. Cluster A with a poor prognosis had a decreased expression of NRGs and a relatively suppressed immune microenvironment. GSVA analysis indicated that cluster A was related to the downregulation of the TGF-β signaling pathway and the activation of the Notch signaling pathway. The risk score had an accurate predictive ability. The nomogram could help predict the survival probability of DLBCL patients in the entire cohort and the external validation cohort. The area under the curve (AUC) of the nomogram, risk score, and International Prognostic Index was 0.723, 0.712, and 0.537, respectively. γ/δ T cells and Macrophage 1 cells decreased while Macrophage 2 cells and Natural Killer resting cells increased in the high-risk group. In addition, the high-risk group was more sensitive to the PI3K inhibitor and the PDK inhibitor.ConclusionWe explored the potential role of necroptosis in DLBCL from multiple perspectives and provided a prognostic nomogram for the survival prediction of DLBCL. Necroptosis was downregulated and was correlated with an immunosuppressed tumor microenvironment and poor prognosis in DLBCL. Our study may deepen the understanding and facilitate the development of new therapy targets for DLBCL.

The Bioinformatic Study Uncovers Probable Critical Genes Involved in the Pathophysiology of Biliary Atresia.

Background Biliary atresia (BA) is an uncommon illness that causes the bile ducts outside and within the liver to become clogged in babies. If left untreated, the cholestasis causes increasing conjugated hyperbilirubinemia, cirrhosis, and hepatic failure. BA has a complicated aetiology, and the mechanisms that drive its development are unknown. The objective of this study was to show the role of probable critical genes involved in the pathophysiology of biliary atresia. Methods We utilised the public Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE46960 to find differentially expressed genes (DEGs) in 64 biliary atresia newborns, 14 infants with various causes of intrahepatic cholestasis, and 7 deceased-donor children as control subjects in our study. The relevant information was looked into. The important modules were identified after functional enrichment, GO and KEGG pathway analyses, protein-protein interaction (PPI) network analyses, and GSEA analysis. Results The differential expression analysis revealed a total of 22 elevated genes. To further understand the biological activities of the DEGs, we run functional enrichment analyses on them. Meanwhile, KEGG analysis has revealed significant enrichment of pathways involved in activating cross-talking with inflammation and fibrosis in BA. SERPINE1, THBS1, CCL2, MMP7, CXCL8, EPCAM, VCAN, ITGA2, AREG, and HAS2, which may play a significant regulatory role in the pathogenesis of BA, were identified by PPI studies. Conclusion Our findings suggested 10 hub genes and probable mechanisms of BA in the current study through bioinformatic analysis.

Epigenetic Silencing of PTEN and Epi-Transcriptional Silencing of MDM2 Underlied Progression to Secondary Acute Myeloid Leukemia in Myelodysplastic Syndrome Treated with Hypomethylating Agents.

In myelodysplastic syndrome (MDS), resistance to hypomethylating agents (HMA) portends a poor prognosis, underscoring the importance of understanding the molecular mechanisms leading to HMA-resistance. In this study, P39 and Kasumi-1 cells and their azacitidine-resistant and decitabine-resistant sublines were evaluated comparatively with transcriptomic and methylomic analyses. Expression profiling and genome-wide methylation microarray showed downregulation of PTEN associated with DNA hypermethylation in P39 cell lines resistant to azacitidine and decitabine. This pattern of PTEN dysregulation was also confirmed in a cohort of patients failing treatment with HMA. DNA hypomethylation of MDM2 was detected with downregulation of MDM2 in HMA resistant cell lines. Long-read sequencing revealed significant RNA hypomethylation of MDM2 resulting in alternative splicing and production of a truncated MDM2 transcript in azacitidine-resistant P39 cells. The expression of this MDM2 truncated transcript was also significantly increased in HMA-resistant patients compared with HMA-responsive patients. In conclusion, epigenetic and epi-transcriptomic dysregulation of PTEN and MDM2 were associated with resistance to hypomethylating agents.

SIAH1 promotes senescence and apoptosis of nucleus pulposus cells to exacerbate disc degeneration through ubiquitinating XIAP

BackgroundUsing clinical samples and database analysis, this study aimed to investigate the signaling pathways that mediated degeneration of nucleus pulposus cells (NPCs) in patients with intervertebral disc degeneration (IDD). MethodsNPCs were extracted from enucleated intervertebral discs of IDD patients, and the senescence, apoptosis, and extracellular matrix (ECM) synthesis levels of cells were confirmed by β-galactosidase (SA-β-gal), Western blot, and measurement of superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione (GSH). The microarray expression profile of GSE56081 was downloaded to screen differentially expressed mRNAs. CO-IP and ubiquitination assays were used to determine the targeted regulation of XIAP by SIAH1. Methylation of mRNA was verified by m6A RIP and actinomycin D assays. ResultsNPCs extracted from the enucleated intervertebral discs of IDD patients exhibited marked senescence, apoptosis, elevated levels of inflammation, and decreased ECM synthesis. The expression of SIAH1 was significantly elevated in NPCs of IDD patients, and SIAH1 knockdown reversed senescence, apoptosis, elevated levels of inflammation, and decreased ECM synthesis in NPCs of IDD patients. CO-IP and ubiquitination assays indicated that SIAH1 can target and ubiquitinate XIAP. Besides, MeRIP-qPCR and actinomycin experiments showed that METTL3-mediated m6A can methylate SIAH1 mRNA. ConclusionIn IDD patients, SIAH1 can target and ubiquitinate XIAP, thereby mediating senescence, apoptosis, increased inflammation, and decreased ECM synthesis of NPCs, while METTL3-mediated m6A can methylate SIAH1 mRNA, producing harmful effects.

Identification and Validation of Autophagy-Related Genes in Diabetic Retinopathy.

BackgroundDiabetic retinopathy (DR) is one of the most common microvascular complications of diabetes, which is associated with damage of blood-retinal barrier and ischemia of retinal vasculature. It devastates visual acuity due to leakage of retinal vessels and aberrant pathological angiogenesis in diabetic patients. The etiology of DR is complex, accumulated studies have shown that autophagy plays an important role in the pathogenesis of DR, but its specific mechanism needs to be further studied.MethodsThis study chose the online Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE146615 to carry on the research. Autophagy-related genes that were potentially differentially expressed in DR were screened by R software. Then, the differentially expressed autophagy-related genes were analyzed by correlation analysis, tissue-specific gene expression, gene-ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network analysis. Finally, retinal pigment epithelial cell line (ARPE-19) incubated with high glucose (HG) was used to mimic the DR model, and the mRNA level of key genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR) in vitro.ResultsA total of 23 differentially expressed autophagy-related genes (9 up-regulated genes and 14 down-regulated genes) were identified by differential expression analysis. The analysis of tissue-specific gene expression showed that these differentially expressed autophagy-related genes were enriched in the retina. GO and KEGG enrichment analysis showed that differentially expressed autophagy-related genes were significantly enriched in autophagy-related pathways such as regulation of autophagy and macroautophagy. Then 10 hub genes were identified by PPI network analysis and construction of key modules. Finally, qRT-PCR confirmed that the expression of MAPK3 in the DR model was consistent with the results of bioinformatics analysis of mRNA chip.ConclusionThrough bioinformatics analysis, we identified 23 potential DR autophagy-related genes, among which the down-regulated expression of MAPK3 may affect the occurrence and development of DR by regulating autophagy. It provides a novel insight into the pathogenesis of DR.

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates.

Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood–brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecular drivers of disease progression is valuable. In this study, we aimed to investigate the molecular drivers responsible for glioblastoma progression and identify valid biomarkers. Three microarray expression profiles GSE90604, GSE50601, and GSE134470 containing healthy and glioblastoma-affected samples revealed overlapping differentially expressed genes (DEGs). The interrelational pathway enrichment analysis elucidated the halt of cell cycle checkpoints and activation of signaling pathways and led to the identification of 6 predominant hub genes. Validation of hub genes in comparison with The Cancer Genome Atlas datasets identified the potential biomarkers of glioblastoma. The study evaluated two significantly upregulated genes, SPARC (secreted protein acidic and rich in cysteine) and VIM (vimentin) for glioblastoma. The genes CACNA1E (calcium voltage-gated channel subunit alpha1 e), SH3GL2 (SH3 domain-containing GRB2-like 2, endophilin A1), and DDN (dendrin) were identified as under-expressed genes as compared to the normal and pan-cancer tissues along with prominent putative prognostic biomarker potentials. The genes DDN and SH3GL2 were found to be upregulated in the proneural subtype, while CACNA1E in the mesenchymal subtype of glioblastoma exhibits good prognostic potential. The mutational analysis also revealed the benign, possibly, and probably damaging substitution mutations. The correlation between the DEG and survival in glioblastoma was evaluated using the Kaplan–Meier plots, and VIM had a greater life expectancy of 60.25 months. Overall, this study identified key candidate genes that might serve as predictive biomarkers for glioblastoma.

Development and Validation of a Novel Gene Signature for Predicting the Prognosis of Idiopathic Pulmonary Fibrosis Based on Three Epithelial-Mesenchymal Transition and Immune-Related Genes.

Background: Increasing evidence has revealed that epithelial–mesenchymal transition (EMT) and immunity play key roles in idiopathic pulmonary fibrosis (IPF). However, correlation between EMT and immune response and the prognostic significance of EMT in IPF remains unclear. Methods: Two microarray expression profiling datasets (GSE70866 and GSE28221) were downloaded from the Gene Expression Omnibus (GEO) database. EMT- and immune-related genes were identified by gene set variation analysis (GSVA) and the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the functions of these EMT- and immune-related genes. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen prognostic genes and establish a gene signature. Gene Set Enrichment Analysis (GSEA) and Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) were used to investigate the function of the EMT- and immune-related signatures and correlation between the EMT- and immune-related signatures and immune cell infiltration. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to investigate the mRNA expression of genes in the EMT- and immune-related signatures. Results: Functional enrichment analysis suggested that these genes were mainly involved in immune response. Moreover, the EMT- and immune-related signatures were constructed based on three EMT- and immune-related genes (IL1R2, S100A12, and CCL8), and the K–M and ROC curves presented that the signature could affect the prognosis of IPF patients and could predict the 1-, 2-, and 3-year survival well. Furthermore, a nomogram was developed based on the expression of IL1R2, S100A12, and CCL8, and the calibration curve showed that the nomogram could visually and accurately predict the 1-, 2-, 3-year survival of IPF patients. Finally, we further found that immune-related pathways were activated in the high-risk group of patients, and the EMT- and immune-related signatures were associated with NK cells activated, macrophages M0, dendritic cells resting, mast cells resting, and mast cells activated. qRT-PCR suggested that the mRNA expression of IL1R2, S100A12, and CCL8 was upregulated in whole blood of IPF patients compared with normal samples. Conclusion: IL1R2, S100A12, and CCL8 might play key roles in IPF by regulating immune response and could be used as prognostic biomarkers of IPF.

Integrated bioinformatic analysis of gene expression profiling data to identify combinatorial biomarkers in inflammatory skin disease

Selection of appropriate biomarker to identify inflammatory skin diseases is complicated by the involvement of thousands of differentially expressed genes (DEGs) across multiple cell types and organs. This study aimed to identify combinatorial biomarkers in inflammatory skin diseases. From one gene expression microarray profiling dataset, we performed bioinformatic analyses on dataset from lesional skin biopsies of patients with inflammatory skin diseases (atopic dermatitis [AD], contact eczema [KE], lichen planus [Li], psoriasis vulgaris [Pso]) and healthy controls to identify the involved pathways, predict upstream regulators, and potential measurable extracellular biomarkers. Overall, 434, 629, 581, and 738 DEGs were mapped in AD, KE, Li, and Pso, respectively; 238 identified DEGs were shared among four different inflammatory skin diseases. Bioinformatic analysis on four inflammatory skin diseases showed significant activation of pathways with known pathogenic relevance. Common upstream regulators, with upregulated predicted activity, identified were CNR1 and BMP4. We found the following common serum biomarkers: ACR, APOE, ASIP, CRISP1, DKK1, IL12B, IL9, MANF, MDK, NRTN, PCSK5, and VEGFC. Considerable differences of gene expression changes, involved pathways, upstream regulators, and biomarkers were found in different inflammatory skin diseases. Integrated bioinformatic analysis identified 12 potential common biomarkers of inflammatory skin diseases requiring further evaluation.

A microarray expression profile and bioinformatic analysis of circular RNA in human esophageal carcinoma

Recent studies indicate that non-coding circular RNAs (circRNAs) are involved in the development of esophageal carcinoma (EC). This study aimed to identify differential expression of circRNAs in EC, which can provide potential biomarkers and therapeutic targets for EC treatment and improve the understanding of tumorigenesis mechanism. First, samples (n=5) of EC tissues and adjacent normal tissue were sent for circRNA microarray detection, Second, further bioinformatic analysis was performed, including circRNA-microRNA (miRNA), co-expression network analysis, Spearman correlation test, and cancer-related circRNA-miRNA axis analysis. Finally, the expression of circRNA that our analysis predicted to be hub genes was verified in samples (n=15) of EC tissues and adjacent normal tissue by real-time polymerase chain reaction (RT-PCR). Microarray identified 102 upregulated and 67 significantly downregulated circRNAs were in EC patients' tumors relative to adjacent normal tissue. One upregulated circRNA (hsa_circRNA_401955) showed the most connection with MREs, therefore was regarded as the hub gene by the Spearman correlation test. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that four primary pathways (mRNA surveillance, cytoskeleton actin regulation, spliceosome, and the NOD-like receptor signaling pathway) were predicted in the hub circRNA's five connected miRNA response elements (MREs). Furthermore, cancer-related circRNA-miRNA axis analyses showed that hsa_circRNA_100375 and its four connected MREs participated in the cancer-related pathway. RT-PCR showed that hsa_circRNA_100375 and hsa_circRNA_401955 were significantly increased in the tumor tissues of EC patients. Abnormal expression of circRNAs was involved in the tumorigenesis of EC. Key circRNAs, namely hsa_circRNA_401955 and hsa_circRNA_100375, may be as potential biomarkers and therapeutic targets for the treatment of EC.

Gene Expression Transcriptome Profile Validation: A Critical Appraisal of Methods and Signature Analyses

<h3>Purpose</h3> The aim of our study is to assess the reliability of transcriptome profile platform outcomes between different tissue preservation conditions, RNA extraction methods and heart-failure-related genes, minimizing intra- and inter-experimental variability. <h3>Methods</h3> Our cohort of study is composed by 6 FFPE endomyocardial biopsies (EMBs) and 6 fresh frozen (FF) heart tissues samples belonging to the same adult end-stage heart failure patient, limiting inter-patient variability bias. Two major RNA extraction procedure were tested for FF and FFPE tissues. Then, we performed a high-throughput microarray expression profiling without a bias of transcript selection. We analyzed mRNAs expression through R programming and transcriptome analysis software, exploring >20000 transcripts. We refined the transcriptome analysis selecting, from a literature systematic review appraisal 30 heart-failure related genes, coupling the overlapping genes in the differential expression and network analysis. <h3>Results</h3> We compared the analysis of up- and down-regulated genes between the groups, addressing both the different RNA extraction procedure and tissue preservation, while sharing the same transcriptome platform. The differential expressed genes (DEG) analyzed had fold change set at 2 and -2, and a cut-off threshold of FDR adjusted p-value < 0,05. Heatmap showed a great samples' clusterization according to preservation and extraction methods. Only 284 genes passed filter criteria in FFPE inter-groups comparison of extraction methods, while 52 differed in FFPE vs. FF, showing a great overlap of transcriptome signature, corroborated by the heart-failure related set of genes. The network analysis highlighted that most of the DEG are strongly associated (p-value adjusted <0.004) to the dysregulation of reticulum and collagen related cell component, in accordance with heart failure stage. <h3>Conclusion</h3> To the best of our knowledge, this is the first study in heart transplantation fields comparing genetic extraction and preservation methods for microarray expression profile evaluation correlated with pathophysiological mechanism. A proof of concept that RNAs from FFPE-EMBs, and not only FF, are feasible for microarray expression profile evaluation, and derived transcriptome profiles have a strong potential for research and diagnostic clinical application.

Paclitaxel Resistance Modulated by the Interaction between TRPS1 and AF178030.2 in Triple-Negative Breast Cancer.

Paclitaxel is a chemotherapeutic agent that acts as an inhibitor of cellular mitosis and has been widely used in the treatment of triple-negative breast cancer (TNBC). However, paclitaxel resistance is one of the major reasons that contribute to the high failure rates of chemotherapy and the relapse of TNBC. Accumulating studies have demonstrated that long noncoding RNA (lncRNA) plays a role in the paclitaxel resistance and positively correlated with progression and metastasis of breast cancers. In the present study, microarray expression profile analysis of lncRNA was performed between paclitaxel-resistant TNBC cell line MDA-MB-231 and their parental cells. After verification with quantitative PCR, we identified that AF178030.2, an orphan lncRNA, was significantly upregulated in paclitaxel-resistant TNBC cells. Overexpression of AF178030.2 greatly attenuated the sensitivity of TNBC to paclitaxel, whereas knockdown of AF178030.2 enhanced the sensitivity of TNBC cells to paclitaxel. Furthermore, bioinformatic analysis and RNA binding protein immunoprecipitation assay reveal that AF178030.2 can directly bind with trichorhinophalangeal syndrome-1 (TRPS1), an oncogene in breast cancer, and downregulate its expression in paclitaxel-resistant TNBC cells. TRPS1 overexpression effectively increased the sensitivity of paclitaxel-resistant TNBC cells to paclitaxel. Taking together, high AF178030.2 expression contributed to paclitaxel resistance in TNBC through TRPS1 and poor clinical outcomes, which may provide a new treatment strategy for paclitaxel-resistant TNBC patients.

Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease.

Background: Coronary artery disease (CAD) exerts a global challenge to public health. Genetic heritability is one of the most vital contributing factors in the pathophysiology of CAD. Co-expression network analysis is an applicable and robust method for the interpretation of biological interaction from microarray data. Previous CAD studies have focused on peripheral blood samples since the processes of CAD may vary from tissue to blood. It is therefore necessary to find biomarkers for CAD in heart tissues; their association also requires further illustration. Materials and Methods: To filter for causal genes, an analysis of microarray expression profiles, GSE12504 and GSE22253, was performed with weighted gene co-expression network analysis (WGCNA). Co-expression modules were constructed after batch effect removal and data normalization. The results showed that 7 co-expression modules with 8,525 genes and 1,210 differentially expressed genes (DEGs) were identified. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Four major pathways in CAD tissue and hub genes were addressed in the Hybrid Mouse Diversity Panel (HMDP) and Human Protein Atlas (HPA), and isoproterenol (ISO)/doxycycline (DOX)-induced heart toxicity models were used to validate the hub genes. Lastly, the hub genes and risk variants were verified in the CAD cohort and in genome-wide association studies (GWAS). Results: The results showed that RNF181 and eight other hub genes are perturbed during CAD in heart tissues. Additionally, the expression of RNF181 was validated using RT-PCR and immunohistochemistry (IHC) staining in two cardiotoxicity mouse models. The association was further verified in the CAD patient cohort and in GWAS. Conclusion: Our findings illustrated for the first time that the E3 ubiquitination ligase protein RNF181 may serve as a potential biomarker in CAD, but further in vivo validation is warranted.

Nicotine treatment regulates PD-L1 and PD-L2 expression via inhibition of Akt pathway in HER2-type breast cancer cells.

The immune checkpoint molecules such as PD-L1 and PD-L2 have a substantial contribution to cancer immunotherapy including breast cancer. Microarray expression profiling identified several molecular subtypes, namely luminal-type (with a good-prognosis), HER2-type (with an intermediate-prognosis), and triple-negative breast cancer (TNBC)-type (with a poor-prognosis). We found that PD-L1 and PD-L2 mRNA expressions were highly expressed in TNBC-type cell lines (HCC1937, MDA-MB-231), moderately expressed in HER2-type cell line (SK-BR-3), and poorly expressed in luminal-type cell lines (MDA-MB-361, MCF7). The PD-L1 and PD-L2 expression in SK-BR-3 cells, but not those in HCC1937 and MDA-MB-231 cells, decreased by nicotine stimulation in a dose-dependent manner. In addition, nicotine treatment decreased the phosphorylation of Akt in SK-BR-3 cells, but not in other cell lines. These results show that nicotine regulates the expression of immune checkpoint molecules, PD-L1 and PD-L2, via inhibition of Akt phosphorylation. This findings may provide the new therapeutic strategies for the treatment of breast cancer.

Identification of common susceptibility genes and drug target genes in multiple sclerosis, systemic lupus erythematosus, and rheumatoid arthritis and its value to guide clinical treatment

BackgroundMultiple sclerosis (MS) is an autoimmune-mediated demyelinating disease of the white matter in the central nervous system (CNS). In clinical practice, it was found that MS is associated with a variety of autoimmune diseases, such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA). The aim of this study was to identify common susceptibility genes and drug target genes in MS, SLE, and RA and to provide new insights into treatment. MethodsThe common susceptibility genes of MS, SLE, and RA were obtained by searching the GWAS database and using microarray data to validate. The Genome Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, and the common KEGG pathways were selected. All the genes enriched in the common pathways were obtained and intersected with the susceptibility genes of MS, SLE, and RA to obtain the pathway genes of them respectively, and found the common pathogenesis-related genes of the three diseases. By reviewing the literature and the DrugBank database, the drugs and drug target genes that have been approved for the treatment of the three diseases were obtained. Finally, the DGIdb database was searched to predict potential drugs or molecular compounds that interact with susceptibility genes common to MS, SLE, and RA. ResultsIn MS, SLE, and RA, there were 46 common susceptibility genes, of which 23 were significantly differentially expressed in the microarray expression profile. Then, 2117 genes were obtained in the 42 common pathways, among which 17 pathogenesis-related genes were common in MS, SLE, and RA. The Drugbank database was used to obtain 29 drug target genes for MS, 43 drug target genes for RA, and 20 drug target genes for SLE. DHODH is a common drug target gene for MS, SLE, and RA, and its corresponding drugs are Leflunomide and Teriflunomide. A total of 13 genes and 366 potential drugs or molecular compounds were predicted to have interaction relationships after searching the DGIdb database. ConclusionThe common susceptibility genes and drug target genes among MS, SLE, and RA provide a theoretical basis for the co-morbidity phenomenon of the three diseases in clinical practice and may guide the clinical treatment.

MicroRNA Profile Associated with Positive Lymph Node Metastasis in Early-Stage Cervical Cancer.

Lymph node metastasis (LNM) is an important prognostic factor in cervical cancer (CC). In early stages, the risk of LNM is approximately 3.7 to 21.7%, and the 5-year overall survival decreases from 80% to 53% when metastatic disease is identified in the lymph nodes. Few reports have analyzed the relationship between miRNA expression and the presence of LNM. The aim of this study was to identify a subset of miRNAs related to LNM in early-stage CC patients. Formalin-fixed paraffin-embedded tissue blocks were collected from patients with early-stage CC treated by radical hysterectomy with lymphadenectomy. We analyzed samples from two groups of patients—one group with LNM and the other without LNM. Global miRNA expression was identified by microarray analysis, and cluster analysis was used to determine a subset of miRNAs associated with LNM. Microarray expression profiling identified a subset of 36 differentially expressed miRNAs in the two groups (fold change (FC) ≥ 1.5 and p < 0.01). We validated the expression of seven miRNAs; miR-487b, miR-29b-2-5p, and miR-195 were underexpressed, and miR-92b-5p, miR-483-5p, miR-4534, and miR-548ac were overexpressed according to the microarray experiments. This signature exhibited prognostic value for identifying early-stage CC patients with LNM. These findings may help detect LNM that cannot be observed in imaging studies.

738 Role of non-coding RNA uc.194 and uc.443+A in the intrastent restenosis

Abstract Aims Vascular smooth muscle cells (VSMCs) play a key role in the vessel wall, being active partaker in vascular remodelling and influencing multiple pathophysiological phenomena, such as progression of atherosclerosis, in-stent restenosis and vascular reactivity. Recently antisense oligonucleotides have shown promising results as a therapeutic option. The aim of this study was to analyse the expression profile and function of T-UCRs in vascular smooth muscle cells (VSMCs)—both in vitro and in vivo—and to evaluate the effects of their inhibition by the use of specific antisense oligonucleotides. Methods After obtaining cell cultures of vascular smooth muscle cells, we modified their phenotype varying growth conditions. A microarray and qRT-PCR expression profile analysis and a cell cycle analysis with cell proliferation/apoptosis/migration assay were performed. In vivo studies were performed on rat carotids after cell damage and administration of specific antisense oligonucleotides. Results There were significant differences in the expression of T-UCRs in VSMCs with a proliferating and quiescent phenotype. In particular, 5 T-UCRs were found to be upregulated in VSMCs. These types of cells were subsequently transfected with specific antisense oligonucleotides obtaining a reduction in their proliferative activity in particular with the inhibition of the T-UCRs uc.194 and uc.443 + A. MiR-10A and miR-34b-5p were identified with complementary sequences respectively to uc.194 and uc.443 + A. The increase of these miRs following the inhibition of the T-UCRs were closely related to the inhibition of the proliferative signals of VSMCs. Similarly, the same results were obtained in vivo. Conclusions The expression levels of non-coding RNAs uc.194 and uc. 443 + A increase in proliferating smooth muscle cells in vitro and in the vascular wall following damage, suggesting an important role of these molecules in the phenomenon of intra-stent restenosis. Through the inhibition of uc.194 and uc.443 + A using an antisense strategy, we demonstrated a reduction in cell proliferation and migration processes and, consequently, in the formation of neointima. A possible relationship was also highlighted between the aforementioned non-coding RNAs and some micro-RNAs (miR-10A and miR-34b-5p), negative regulators of the proliferative phenotype of VSMCs. The inhibition of the analysed T-UCRs would allow the maintenance of the contractile phenotype thanks to the activity of the miRs analysed in this study. Our results might pave the way for the identification of new therapeutic targets in order to prevent and reduce the incidence of intra-stent restenosis.

Bulk and Single-Cell Profiling of Breast Tumors Identifies TREM-1 as a Dominant Immune Suppressive Marker Associated With Poor Outcomes.

BackgroundTriggering receptor expressed on myeloid cells (TREM)-1 is a key mediator of innate immunity previously associated with the severity of inflammatory disorders, and more recently, the inferior survival of lung and liver cancer patients. Here, we investigated the prognostic impact and immunological correlates of TREM1 expression in breast tumors.MethodsBreast tumor microarray and RNAseq expression profiles (n=4,364 tumors) were analyzed for associations between gene expression, tumor immune subtypes, distant metastasis-free survival (DMFS) and clinical response to neoadjuvant chemotherapy (NAC). Single-cell (sc)RNAseq was performed using the 10X Genomics platform. Statistical associations were assessed by logistic regression, Cox regression, Kaplan-Meier analysis, Spearman correlation, Student’s t-test and Chi-square test.ResultsIn pre-treatment biopsies, TREM1 and known TREM-1 inducible cytokines (IL1B, IL8) were discovered by a statistical ranking procedure as top genes for which high expression was associated with reduced response to NAC, but only in the context of immunologically “hot” tumors otherwise associated with a high NAC response rate. In surgical specimens, TREM1 expression varied among tumor molecular subtypes, with highest expression in the more aggressive subtypes (Basal-like, HER2-E). High TREM1 significantly and reproducibly associated with inferior distant metastasis-free survival (DMFS), independent of conventional prognostic markers. Notably, the association between high TREM1 and inferior DMFS was most prominent in the subset of immunogenic tumors that exhibited the immunologically hot phenotype and otherwise associated with superior DMFS. Further observations from bulk and single-cell RNAseq analyses indicated that TREM1 expression was significantly enriched in polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and M2-like macrophages, and correlated with downstream transcriptional targets of TREM-1 (IL8, IL-1B, IL6, MCP-1, SPP1, IL1RN, INHBA) which have been previously associated with pro-tumorigenic and immunosuppressive functions.ConclusionsTogether, these findings indicate that increased TREM1 expression is prognostic of inferior breast cancer outcomes and may contribute to myeloid-mediated breast cancer progression and immune suppression.

SYT7 acts as an oncogene and a potential therapeutic target and was regulated by \u0394Np63\u03b1 in HNSCC

BackgroundHead and neck squamous cell carcinoma (HNSCC) are one of the most common types of head and neck cancer, and it is urgent to find effective treatment for advanced patients. Exploring developing and progressing mechanisms of HNSCC could provide a theoretical basis to find new therapeutic targets.MethodsIn our research, we performed a whole-gene expression profile microarray analysis to identify differential expression genes between squamous cell carcinoma cells and ΔNp63 alpha (ΔNp63α) knockdown cells. As a result, an important gene Synaptotagmin VII (SYT7) was screened out.ResultsSYT7 knockdown affected the proliferation, apoptosis and cell cycle of squamous cell carcinoma cells. The rescue experiment in vitro with ΔNp63α and SYT7 double knockdown resulted in partial reversion of ΔNp63α-induced phenotypes. This was also confirmed by experiments in vivo.ConclusionsTaken together, we found that ΔNp63α could inhibit the occurrence and progression of HNSCC throughout downregulating the expression of SYT7. Therefore, SYT7/ΔNp63α axis could be a potential therapeutic target for clinical treatment of HNSCC.