Celecoxib exhibits an anti-gastric cancer effect by targeting focal adhesion and leukocyte transendothelial migration-associated genes

In Silico Drug Repurposing Against PSMB8 as a Potential Target for Acute Myeloid Leukemia Treatment

PSMB8 emerges as a prominent gene associated with cancer survival, yet its potential therapeutic role in acute myeloid leukemia (AML) remains unexplored within the existing literature. The principal aim of this study is to systematically screen an expansive library of molecular entities, curated from various databases to identify the prospective inhibitory agents with an affinity for PSMB8. A comprehensive assortment of molecular compounds obtained from the ZINC15 database was subjected to molecular docking simulations with PSMB8 by using the AutoDock tool in PyRx (version 0.9.9) to elucidate binding affinities. Following the docking simulations, a select subset of molecules underwent further investigation through comprehensive ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis employing AdmetSar and SwissADME tools. Finally, RMSD, RMSF, Rg, and H bond analyses were conducted via GROMACS to determine the best conformationally dynamic molecule that represents the candidate agent for the study. Following rigorous evaluation, Adozelesin, Fiduxosin, and Rimegepant have been singled out based on considerations encompassing bioavailability scores, compliance with filter criteria, and acute oral toxicity levels. Additionally, ligand interaction analysis indicates that Adozelesin and Fiduxosin exhibit an augmented propensity for hydrogen bond formation, a factor recognized for its facilitative role in protein-ligand interactions. After final analyses, we report that Fiduxosin may offer a treatment possibility by reversing the low survival rates caused by PSMB8 high activation in AML. This study represents a strategic attempt to repurpose readily available pharmaceutical agents, potentially obviating the need for de novo drug development, and thereby offering promising avenues for therapeutic intervention in specific diseases.

CSRP1 gene: a potential novel prognostic marker in acute myeloid leukemia with implications for immune response

BACKGROUND

Acute myeloid leukemia, constituting a majority of leukemias, grapples with a 24% 5-year survival rate. Recent strides in research have unveiled fresh targets for drug therapies. LIM-only, a pivotal transcription factor within LIM proteins, oversees cell development and is implicated in tumor formation. Among these critical LIM proteins, CSRP1, a Cysteine-rich protein, emerges as a significant player in various diseases. Despite its recognition as a potential prognostic factor and therapeutic target in various cancers, the specific link between CSRP1 and acute myeloid leukemia remains unexplored. Our previous work, identifying CSRP1 in a prognostic model for AML patients, instigates a dedicated exploration into the nuanced role of CSRP1 in acute myeloid leukemia.

METHODS

R tool was conducted to analyze the public data. qPCR was applied to evaluate the expression of CSRP1 mRNA for clinical samples and cell line. Unpaired t test, Wilcoxon Rank Sum test, KM curves, spearman correlation test and Pearson correlation test were included in this study.

RESULTS

CSRP1 displays notable expression variations between normal and tumor samples in acute myeloid leukemia (AML). It stands out as an independent prognostic factor for AML patients, showing correlations with clinical factors like age and cytogenetics risk. Additionally, CSRP1 correlates with immune-related pathways, immune cells, and immune checkpoints in AML. Furthermore, the alteration of CSRP1 mRNA levels is observed upon treatment with a DNMT1 inhibitor for THP1 cells.

CONCLUSION

The CSRP1 has potential as a novel prognostic factor and appears to influence the immune response in acute myeloid leukemia. Additionally, there is an observed association between CSRP1 and DNA methylation in acute myeloid leukemia.

Comprehensive Analyses Revealed Eight Immune Related Signatures Correlated With Aberrant Methylations as Prognosis and Diagnosis Biomarkers for Kidney Renal Papillary Cell Carcinoma

BACKGROUND

Kidney renal papillary cell carcinoma (KIRP) is a common type of renal cell carcinoma. DNA methylation plays an important role in the development of several cancers. The aim of our study was to identify differentially expressed genes associated with abnormal DNA methylation as biomarkers for predicting the outcome of KIRP.

METHOD

We downloaded KIRP methylation data, RNA sequencing (RNAseq) data, and their corresponding clinical information from the Cancer Genome Atlas (TCGA) database. ChAMP and DEGseq2 packages in R software were used to screen differentially methylated probes (DMPs) and differentially expressed genes (DEGs). Univariate and multivariate Cox regression analyses were used to identify suitable immune related genes correlated with aberrant methylations as prognosis biomarkers.

RESULTS

We identified 8 DEGs (Cysteine And Glycine Rich Protein 1 [CSRP1], major histocompatibility complex, Class II, DM Beta [HLA-DMB], LIF Receptor Subunit Alpha [LIFR], Leukotriene B4 receptor 2 [LTB4R2], Mitogen-Activated Protein Kinase Kinase Kinase 14 [MAP3K14], Nuclear Receptor Subfamily 2 Group F Member 1 [NR2F1], Secreted And Transmembrane 1 [SECTM1], and Vimentin [VIM]) that were independently associated with the overall survival (months) (OS) of KIRP. The time dependent area under the curve (AUC) for each receiver operating characteristic (ROC) of the risk assessment model at 1, 3, 5, and 10-years reached 0.8415, 0.8131, 0.7873, and 0.7667. The risk assessment model was correlated with several immune cells and factors. The AUC value of the diagnosis model using those 8 DEGs reached 0.99.

CONCLUSIONS

The risk assessment model constructed by those 8 DEGs was well able to predict the prognosis and diagnose of KIRP. However, whether the prognosis and diagnosis model could be applied in clinical practice requires further study.

Identifying a prognostic model and screening of potential natural compounds for acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is one of the most common hematologic malignancies with a poor prognosis and high recurrence rate. The discovery of new predictive models and therapeutic agents plays a crucial role.

Methods

The differentially expressed gene that was explicitly highly expressed in The Cancer Genome Atlas (TCGA) and GSE9476 transcriptome databases were screened and included in the least absolute shrinkage and selection operator (LASSO) regression model to derive risk coefficients and build a risk score model. Functional enrichment analysis was conducted on the screened hub genes to explore the potential mechanisms. Subsequently, critical genes were incorporated into a nomogram model based on risk scores to analyze prognostic value. Finally, this study combined network pharmacology to find potential natural compounds for hub genes and used molecular docking to verify the binding ability of molecular structures to natural compounds to explore drug development for possible efficacy in AML.

Results

A total of 33 highly expressed genes may be associated with poor prognosis of AML patients. After LASSO and multivariate Cox regression analysis of 33 critical genes, Rho-related BTB domain containing 2 (RHOBTB2), phospholipase A2 (PLA2G4A), interleukin-2 receptor-α (IL2RA), cysteine and glycine-rich protein 1 (CSRP1), and olfactomedin-like 2A (OLFML2A) were found to played a significant role in the prognosis of AML patients. CSRP1 and OLFML2A were independent prognostic factors of AML. The predictive power of these 5 hub genes in combination with clinical features was better than clinical data alone in predicting AML in the column line graphs and had better predictive value at 1, 3, and 5 years. Finally, through network pharmacology and molecular docking, this study found that diosgenin in Guadi docked well with PLA2G4A, beta-sitosterol in Fangji docked well with IL2RA, and OLFML2A docked well with 3,4-di-O-caffeoylquinic acid in Beiliujinu.

Conclusions

The predictive model of RHOBTB2, PLA2G4A, IL2RA, CSRP1, and OLFML2A combined with clinical features can better guide the prognosis of AML. In addition, the stable docking of PLA2G4A, IL2RA, and OLFML2A with natural compounds may provide new options for treating AML.

Harnessing interventions during the immediate perioperative period to improve the long-term survival of patients following radical gastrectomy

Although the incidence and mortality of gastric cancer (GC) have been decreasing steadily worldwide, especially in East Asia, the disease burden of this malignancy is still very heavy. Except for tremendous progress in the management of GC by multidisciplinary treatment, surgical excision of the primary tumor is still the cornerstone intervention in the curative-intent treatment of GC. During the relatively short perioperative period, patients undergoing radical gastrectomy will suffer from at least part of the following perioperative events: Surgery, anesthesia, pain, intraoperative blood loss, allogeneic blood transfusion, postoperative complications, and their related anxiety, depression and stress response, which have been shown to affect long-term outcomes. Therefore, in recent years, studies have been carried out to find and test interventions during the perioperative period to improve the long-term survival of patients following radical gastrectomy, which will be the aim of this review.

The Long Noncoding RNA Gm9866/Nuclear Factor-κB Axis Promotes Macrophage Polarization

Macrophages are a type of immune cells with high levels of plasticity and heterogeneity. They can polarize into M1 or M2 functional phenotypes. These two phenotypes exhibit a dynamic balance during polarization-related diseases and play opposing roles. Long noncoding RNAs (lncRNAs) play an important role in biological processes such as cell proliferation, death, and differentiation; however, how long noncoding RNAs affect the cellular functionality of macrophages remains to be studied. Long noncoding RNA Gm9866 was found to be closely related to macrophage polarization through bioinformatics analysis. In this study, by conducting real-time polymerase chain reaction analysis, it was observed that long noncoding RNA Gm9866 expression significantly increased after treatment with interleukin-4 but significantly decreased after treatment with lipopolysaccharide. Fluorescence in situ hybridization revealed that long noncoding RNA Gm9866 was expressed mainly in the nucleus. Real-time polymerase chain reaction analysis showed that overexpression of long noncoding RNA Gm9866 in RAW264.7 cells further promoted the expression of M2 markers MRC1 (macrophage mannose receptor 1) and MRC2 (macrophage mannose receptor 2). Western blotting analysis demonstrated inhibition of nuclear factor-κB (NF-κB) expression. EdU (5-ethynyl-2'-deoxyuridine) and TUNEL (TdT-mediated dUTP nick-end labeling) staining assays revealed that overexpression of long noncoding RNA Gm9866 promoted cell proliferation and inhibited apoptosis. These findings thus indicated that long noncoding RNA Gm9866 promoted macrophage polarization and inhibited the nuclear factor-κB signaling pathway. Thus, long noncoding RNA Gm9866 may serve as a potential diagnostic and therapeutic target for polarization-related diseases such as infectious diseases, inflammatory diseases, liver fibrosis, and tumors.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

CSRP1 Promotes Colon Adenocarcinoma Growth and Serves as an Independent Risk Biomarker for Worse Prognosis

Background

Cysteine and Glycine Rich Protein 1 (CSRP1) belongs to the cysteine-rich protein family, which contains a unique double-zinc finger motif and is important for development and cellular differentiation. Abnormal expression of CSRP1 was reported within several malignancies such as prostate cancer and acute myeloid leukemia. Here, we explored function of CSRP1 within colon adenocarcinoma (COAD) for the first time.

Methods

The mRNA levels of CSRP1 in COADs were obtained from TCGA datasets. CSRP1 protein expressions in COADs were tested via immunohistochemistry staining. Patients' prognosis was evaluated using both univariate analysis and multivariate analysis. Two human COAD originated cancer cell lines, Caco-2, and HT-29, were used for cellular experiments including shRNA knockdown, proliferation assay, and migration assay. In vivo model was established using nude mice xenografts to further validate the role of CSRP1 in COAD progression.

Results

The mRNA levels of CSRP1 are elevated in COAD specimens from patients with more advanced tumor stages and higher Carcinoembryonic Antigen (CEA) levels. In addition, higher CSRP1 mRNA level indicates worse COAD prognosis. Consistently, higher CSRP1 protein expression is correlated with worse overall survival according to both univariate and multivariate analysis, indicating that CSRP1 is a new COAD prognostic factor. Furthermore, COAD cells transfected with CSRP1-shRNAs exhibit attenuated proliferation and migration capacities. Finally, growth of xenografts originated from CSRP1-knockdown cells is inhibited comparing to the control ones.

Conclusions

Expression of CSRP1 is positively correlated with COAD progression, which can promote tumor growth and migration. Higher CSRP1 can is a novel independent prognostic factor of COAD.

RILPL2 is associated with the progression and prognosis of cervical squamous cell carcinoma and endocervical adenocarcinoma

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is one of the most common tumors among females worldwide. RILPL2 was recently reported to be a promising biomarker for the treatment of breast cancer. This study aimed to investigate the potential role of RILPL2 in CESC. Totally 302 CESC patients' data were downloaded from The Cancer Genome Atlas database. All patients were divided into high or low RILPL2 groups according to the median expression of RILPL2. Subsequently, survival analysis, multivariate Cox regression, and experimental validation were performed on all CESC patient data. The Ualcan database was used to analyze the expression level and prognostic value of RILPL2 in pan-cancer. The Gene Set Cancer Analysis database was used for drug sensitivity analysis. Functional KEGG pathways were analyzed using gene set enrichment analysis. RILPL2 was generally down-regulated in a variety of tumors, and a high level of RILPL2 was associated with a better prognosis in CESC patients. Immunohistochemistry, western blotting, and qRT-PCR results showed that RILPL2 was significantly down-regulated in CESC cells and tissues. Besides, along with the increase of TNM Stage, the RILPL2 expression tended to decrease gradually. Patients with high RILPL2 expression showed lower resistance to small molecule drugs used in CESC progressions, such as Methotrexate, AZD7762, and Vinblastine, and a higher response rate to immunotherapy. Additionally, we identified 267 co-expressing genes of RILPL2, all of which jointly affected CESC progression through 15 complex pathways. Low RILPL2 expression was closely associated with the onset, progression, and poor prognosis of CESC. RILPL2 might be a promising optional biomarker for CESC patients' diagnosis and prognosis.

Drug repurposing-an emerging strategy in cancer therapeutics

Cancer is a complex disease affecting millions of people around the world. Despite advances in surgical and radiation therapy, chemotherapy continues to be an important therapeutic option for the treatment of cancer. The current treatment is expensive and has several side effects. Also, over time, cancer cells develop resistance to chemotherapy, due to which there is a demand for new drugs. Drug repurposing is a novel approach that focuses on finding new applications for the old clinically approved drugs. Current advances in the high-dimensional multiomics landscape, especially proteomics, genomics, and computational omics-data analysis, have facilitated drug repurposing. The drug repurposing approach provides cheaper, effective, and safe drugs with fewer side effects and fastens the process of drug development. The review further delineates each repurposed drug's original indication and mechanism of action in cancer. Along with this, the article also provides insight upon artificial intelligence and its application in drug repurposing. Clinical trials are vital for determining medication safety and effectiveness, and hence the clinical studies for each repurposed medicine in cancer, including their stages, status, and National Clinical Trial (NCT) identification, are reported in this review article. Various emerging evidences imply that repurposing drugs is critical for the faster and more affordable discovery of anti-cancerous drugs, and the advent of artificial intelligence-based computational tools can accelerate the translational cancer-targeting pipeline.

Identification of key genes with prognostic value in gastric cancer by bioinformatics analysis

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis.

Methods: The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein–protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets.

Results: In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (MYLK, MYL9, LUM, and CAV1) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients.

Conclusion: We found that MYLK, MYL9, LUM, and CAV1 are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.

Construction and validation of a novel coagulation-related 7-gene prognostic signature for gastric cancer

Background: Gastric cancer (GC) is the most common malignant tumor. Due to the lack of practical molecular markers, the prognosis of patients with advanced gastric cancer is still poor. A number of studies have confirmed that the coagulation system is closely related to tumor progression. Therefore, the purpose of this study was to construct a coagulation-related gene signature and prognostic model for GC by bioinformatics methods.

Methods: We downloaded the gene expression and clinical data of GC patients from the TCGA and GEO databases. In total, 216 coagulation-related genes (CRGs) were obtained from AmiGO 2. Weighted gene co-expression network analysis (WGCNA) was used to identify coagulation-related genes associated with the clinical features of GC. Last absolute shrinkage and selection operator (LASSO) Cox regression was utilized to shrink the relevant predictors of the coagulation system, and a Coag-Score prognostic model was constructed based on the coefficients. According to this risk model, GC patients were divided into high-risk and low-risk groups, and overall survival (OS) curves and receiver operating characteristic (ROC) curves were drawn in the training and validation sets, respectively. We also constructed nomograms for predicting 1-, 2-, and 3-year survival in GC patients. Single-sample gene set enrichment analysis (ssGSEA) was exploited to explore immune cells’ underlying mechanisms and correlations. The expression levels of coagulation-related genes were verified by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results: We identified seven CRGs employed to construct a Coag-Score risk model using WGCNA combined with LASSO regression. In both training and validation sets, GC patients in the high-risk group had worse OS than those in the low-risk group, and Coag-Score was identified as an independent predictor of OS, and the nomogram provided a quantitative method to predict the 1-, 2-, and 3-year survival rates of GC patients. Functional analysis showed that Coag-Score was mainly related to the MAPK signaling pathway, complement and coagulation cascades, angiogenesis, epithelial–mesenchymal transition (EMT), and KRAS signaling pathway. In addition, the high-risk group had a significantly higher infiltration enrichment score and was positively associated with immune checkpoint gene expression. Conclusion: Coagulation-related gene models provide new insights and targets for the diagnosis, prognosis prediction, and treatment management of GC patients.

Celecoxib Reverse Invasion and Metastasis of Gastric Cancer through Lnc_AC006548.28-miR-223-LAMC2 Pathway

Celecoxib, a specific cyclooxygenase-2 (COX-2) inhibitor, is a traditional nonsteroidal antipyretic analgesic and anti-inflammatory drug commonly used in clinic, which has inhibitory effect on colorectal cancer, gastric cancer, and other malignant tumors. This study showed that Celecoxib could significantly reverse the invasion and metastasis of gastric cancer and improved the pathological changes due to GC. We collected the clinical specimens to analyze the correlation between the expression of Lnc_AC006548.28, miR-223, and LAMC2. In the mouse model, Celecoxib can slowdown the growth of GC tumor and the occurrence of this effect may depend on Lnc_AC006548.28-miR-223-LAMC2 pathway, in vitro transfection, RT-PCR, western blot, CCK8, small chamber assay, flow cytometry, and immunohistochemistry to retest the protective effect of celecoxib. Our results showed that Celecoxib could reverse invasion and metastasis of gastric cancer through Lnc_AC006548.28-miR-223-LAMC2 pathway.

Proteomic Signatures of Diffuse and Intestinal Subtypes of Gastric Cancer

Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7448 or 4846 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 124 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.

Research progress in myosin light chain 9 in malignant tumors

Myosin light chain 9 (MYL9) is a regulatory light chain of myosin, which plays an important role in various biological processes including cell contraction, proliferation and invasion. MYL9 expresses abnormally in several malignancies including lung cancer, breast cancer, prostate cancer, malignant melanoma and others, which is closely related to the poor prognosis, but the clinical significance for its expression varies with different types of cancer tissues. Further elucidating the molecular mechanism of MYL9 in various types of malignant tumor metastasis is of great significance for cancer prevention and treatment. At the same time, as a molecular marker and potential target, MYL9 may have great clinical value in the early diagnosis, prognosis prediction, and targeted treatment of malignant tumors.

Identification of key miRNA-gene pairs in gastric cancer through integrated analysis of mRNA and miRNA microarray

Nowadays, the current bioinformatic methods have been increasingly applied in the field of oncological research. In this study, we expect a better understanding of the molecular mechanism of gastric cancer from the bioinformatic methods. By systematically addressing the differential expression of microRNAs (miRNAs) and mRNAs between gastric cancer specimens and normal gastric specimens with the application of bioinformatics tools, A total of 206 DEGs and 38 DEMs were identified. The Gene Ontology (GO) analysis of Annotation, Visualization and Integrated Discovery (DAVID) database revealed that the differentially expressed genes (DEGs) were significantly enriched in biological process, molecular function and cellular component, while Kyoto Encyclopedia of Genes and Genomes (KEGG) database showed DEGs were significantly enriched in 8 signal pathways. The miRNA-gene regulatory network was constructed based on 385 miRNA-gene (DEM-DEG) pairs, consisting of 35 miRNAs and 107 target genes. In the regulatory network, the top 5 up-regulated genes were Transmembrane Protease, Serine 11B (TMPRSS11B), regulator of G protein signaling 1 (RGS1), cysteine rich angiogenic inducer 61 (CYR61), inhibin subunit beta A (INHBA), syntrophin gamma 1 (SNTG1), and the top 5 down-regulated genes were tumor necrosis factor receptor superfamily, member 19 (TNFRSF19), pleckstrin homology domain containing B2 (PLEKHB2), Tax1 binding protein 3 (TAX1BP3), presenilin enhancer, gamma-secretase subunit (PSENEN), NME/NM23 nucleoside diphosphate kinase 3 (NME3). Based on the gastric cancer patient database from Kaplan-Meier Plotter tools, we found that 8 of 10 genes with most significant changes in the miRNA-gene regulatory network possessed a prognostic value for survival time of gastric cancer patients. Patients with higher level of RGS1, PLEKHB2, TAX1BP3 and PSENEN in gastric cancer had a longer survival time compared with the patients with lower level of these genes. On the contrary, patients with higher level of INHBA, SNTG1, TNFRSF19 and NME3 were found associated with a shorter survival time. In conclusion, our findings provided several potential targets regarding gastric cancer, which may result in a new strategy to treat gastric cancer from a system rather than a single-gene perspective.

Identification of Gene Modules and Hub Genes Involved in Mastitis Development Using a Systems Biology Approach

Objective

Mastitis is defined as the inflammation of the mammary gland, which impact directly on the production performance and welfare of dairy cattle. Since, mastitis is a multifactorial complex disease and the molecular pathways underlying this disorder have not been clearly understood yet, a system biology approach was used in this study to a better understanding of the molecular mechanisms behind mastitis.

Methods

Publicly available RNA-Seq data containing samples from milk of five infected and five healthy Holstein cows at five time points were retrieved. Gene Co-expression network analysis (WGCNA) approach and functional enrichment analysis were then applied with the aim to find the non-preserved module of genes that their connectivity were altered under infected condition. Hub genes were identified in the non-preserved modules and were subjected to protein-protein interactions (PPI) network construction.

Results

Among the 25 modules identified, eight modules were non-preserved and were also biologically associated with inflammation, immune response and mastitis development. Interestingly most of the hub genes in the eight modules were also densely connected in the PPI network. Of the hub genes, 250 genes were hubs in both co-expression and PPI networks and most of them were reported to play important roles in immune response or inflammatory pathways. The blue module was highly enriched in inflammatory responses and STAT1 was suggested to play an important role in mastitis development by regulating the immune related genes in this module. Moreover, a set of highly connected genes were identified such as BIRC3, PSMA6, FYN, F11R, NFKBIZ, NFKBIA, GRO1, PHB, CD3E, IL16, GSN, SOCS2, HCK, VAV1 and TLR6, which have been established to be critical for mastitis pathogenesis.

Conclusion

This study improved the understanding of the mechanisms underlying bovine mastitis and suggested eight non-preserved modules along with several most important genes with promising potential in etiology of mastitis.

Bioinformatic screening and identification of downregulated hub genes in adrenocortical carcinoma

The molecular mechanisms of adrenocortical carcinoma (ACC) carcinogenesis and progression remain unclear. In the present study, three microarray datasets from the Gene Expression Omnibus database were screened, which identified a total of 96 differentially expressed genes (DEGs). A protein-protein interaction network (PPI) was established for these DEGs and module analysis was performed using STRING and Cytoscape. A total of eight hub genes were identified from the most significant module; namely, calponin 1 (CNN1), myosin light chain kinase (MYLK), cysteine and glycine rich protein 1 (CSRP1), myosin heavy chain 11 (MYH11), fibulin extracellular matrix protein 2 (EFEMP2), fibulin 1 (FBLN1), microfibril associated protein 4 (MFAP4) and fibulin 5 (FBLN5). The biological functions of these hub genes were analyzed using the DAVID online tool. Changes in the expression of hub genes did not affect overall survival; however, downregulated EFEMP2 decreased disease-free survival. CSRP1 and MFAP4 expression levels were associated with adverse clinicopathological features. In conclusion, although all eight hub genes were downregulated in ACC, they appeared to have important functions in ACC carcinogenesis and progression. Identification of these genes complements the genetic expression profile of ACC and provides insight for the diagnosis, treatment and prognosis of ACC.

Screening of a Novel Upregulated lncRNA, A2M-AS1, That Promotes Invasion and Migration and Signifies Poor Prognosis in Breast Cancer

Understanding of prognostic factors and therapeutic targets for breast cancer is imperative for guidance of patient care. We studied 1203 tumour samples from the Gene Expression Omnibus (GEO) to evaluate potential genes related to breast cancer. R software was used to analyse differentially expressed long noncoding RNAs (lncRNAs) in the RNA microarray expression profiles GSE45827 and GSE65216 and to identify a series of differentially expressed lncRNAs associated with human breast cancer. Of these lncRNAs, A2M-AS1, a lncRNA that has not been previously reported, was significantly upregulated in human breast cancer tissues compared with adjacent nontumour tissues. Importantly, A2M-AS1 upregulation was significantly associated with ER-negative, HER2-positive, and basal-like breast cancer and with poor recurrence-free survival and metastasis-free survival in breast cancer patients. After validating these results in 96 collected human breast cancer tissues and 64 paired adjacent noncancerous tissues, we further investigated the roles of A2M-AS1 in human ER-negative and basal-like breast cancer cells. The results revealed that A2M-AS1 significantly promotes human breast cancer cell proliferation, invasion, and migration. Additionally, bioinformatics analysis of genes coexpressed with A2M-AS1 in the context of human breast cancer combined with qRT-PCR and Western blot assays revealed that A2M-AS1 exerts regulatory effects on downstream factors in the cell adhesion molecule pathway, including CD2 and SELL. These results imply that A2M-AS1 might be a promising candidate prognostic factor and therapeutic target for breast cancer.

Identification of potential key genes in gastric cancer using bioinformatics analysis

Gastric cancer (GC) is one of the most common types of cancer worldwide. Patients must be identified at an early stage of tumor progression for treatment to be effective. The aim of the present study was to identify potential biomarkers with diagnostic value in patients with GC. To examine potential therapeutic targets for GC, four Gene Expression Omnibus (GEO) datasets were downloaded and screened for differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed to study the function and pathway enrichment of the identified DEGs. A protein-protein interaction (PPI) network was constructed. The CytoHubba plugin of Cytoscape was used to calculate the degree of connectivity of proteins in the PPI network, and the two genes with the highest degree of connectivity were selected for further analysis. Additionally, the two DEGs with the largest and smallest log Fold Change values were selected. These six key genes were further examined using Oncomine and the Kaplan-Meier plotter platform. A total of 99 upregulated and 172 downregulated genes common to all four GEO datasets were screened. The DEGs were primarily enriched in the Biological Process terms: ‘extracellular matrix organization’, ‘collagen catabolic process’ and ‘cell adhesion’. These three KEGG pathways were significantly enriched in the categories: ‘ECM-receptor interaction’, ‘protein digestion and absorption’, and ‘focal adhesion’. Based on Oncomine, expression of ATP4A and ATP4B were downregulated in GC, whereas expression of the other genes were all upregulated. The Kaplan-Meier plotter platform confirmed that upregulated expression of the identified key genes was significantly associated with worse overall survival of patients with GC. The results of the present study suggest that FN1, COL1A1, INHBA and CST1 may be potential biomarkers and therapeutic targets for GC. Additional studies are required to explore the potential value of ATP4A and ATP4B in the treatment of GC.

Transcriptome sequencing reveals genetic mechanisms of reproduction performance stimulated by dietary daidzein in laying breeder hens

Daidzein (DA) is a kind of isoflavone that is extracted primarily from soy plants and that has become increasingly popular as a dietary supplement. The objective of this study was to evaluate the effects of dietary DA supplementation for laying breeder hens on laying performance, reproductive organ development, hatching performance of seed eggs, and growth performance of offspring and to investigate the underlying molecular mechanisms. A total of 180 55-week-old laying breeder hens were randomly divided into 2 treatment groups and, after 3 weeks of acclimation, were fed either a control diet (CON) or a DA-supplemented diet (DAS, CON+30 mg/kg DA) for a total of 12 weeks. DAS treatment improved the laying rate, luteinizing hormone (LH) levels, and small yellow follicle (SYF) numbers without negative effects on the hatchability of breeder eggs or the growth performance of offspring. High-throughput RNA sequencing was utilized to identify differentially expressed genes in the SYF granulosa layer in the two groups. Transcriptome analysis showed that 161 genes (fold change ≥2 or ≤0.5; P-value<0.05) were significantly differentially expressed between the two groups, including 139 upregulated genes and 22 downregulated genes. Gene ontology (GO) functional annotation analysis revealed potential genes, processes and pathways involved in cell proliferation and differentiation related to the improvement of laying performance stimulated by DA. Dietary DA supplementation for laying breeder hens improved laying performance and reproductive performance with no negative impacts on hatchability or offspring growth. A series of differentially expressed genes in SYF granulosa cells were significantly upregulated in the DAS group relative to the CON group. This study provides insight into the genetic architecture of the transcriptome of the SYF granulosa layer in layer breeding hens and proposes candidate genes that respond to dietary DA.

Differential expression profiles of the transcriptome in bone marrow-derived cells in lung cancer revealed by next generation sequencing and bioinformatics

A pre-metastatic niche (PMN) facilitates cancer metastasis through mobilization and recruitment of bone marrow-derived cells (BMDCs) and associated factors. In bone marrow, hematogenous cells, including osteoclasts, macrophages and lymphocytes, and mesenchymal cells, including mesenchymal stem cells, osteoblasts and adipocytes, are involved in PMN formation. Patients with lung cancer and metastasis have a poor prognosis and shortened median survival time. Bone marrow has been considered fertile ground for dormant and proliferating tumor cells, and mobilizing and recruiting BMDCs and immune cells can establish a PMN. However, the role of BMDCs in PMN formation is not yet fully understood. The present study aimed to investigate the association between BMDCs and PMN in bone marrow tissue samples. The results demonstrated that bone marrow served an important role in lung cancer progression and that eight pathways were potentially involved, including ‘T-cell receptor signaling pathway’, ‘osteoclast differentiation’, ‘MAPK signaling pathway’, ‘VEGF signaling pathway’, ‘leukocyte transendothelial migration’, ‘signaling pathways regulating the pluripotency of stem cells’, ‘oxytocin signaling pathway’ and ‘cell adhesion molecules (CAMs)’. In addition, the present study investigated the role of BMDCs in facilitating lung cancer metastasis. In conclusion, the results from the present study suggested that molecular alterations in gene expression may provide a novel signature in lung cancer, which may aid in the development of novel diagnostic and therapeutic strategies for patients with lung cancer and bone metastasis.

Cell matrix adhesions in cancer: The proteins that form the glue

The main purposes of Integrin-mediated cell contacts are to interpret bi-directional signals between the extracellular environment and intracellular proteins, as well as, anchor the cell to a matrix. Many cell adhesion molecules have been discovered with a wide spectrum of responsibilities, including recruiting, activating, elongating, and maintaining. This review will perlustrate some of the key incidences that precede focal adhesion formation. Tyrosine phosphorylation is a key signaling initiation event that leads to the recruitment of multiple proteins to focal adhesion sites. Recruitment and concentration of proteins such as Paxillin and Vinculin to Integrin clutches is necessary for focal adhesion development. The assembled networks are responsible for transmitting signals back and forth from the extracellular matrix (ECM) to Actin and its binding proteins. Cancer cells exhibit highly altered focal adhesion dynamics. This review will highlight some key discoveries in cancer cell adhesion, as well as, identify current gaps in knowledge.

Cysteine and glycine-rich protein 2 (CSRP2) transcript levels correlate with leukemia relapse and leukemia-free survival in adults with B-cell acute lymphoblastic leukemia and normal cytogenetics

Relapse is the major cause of treatment-failure in adults with B-cell acute lymphoblastic leukemia (ALL) achieving complete remission after induction chemotherapy. Greater precision identifying persons likely to relapse is important. We did bio-informatics analyses of transcriptomic data to identify mRNA transcripts aberrantly-expressed in B-cell ALL. We selected 9 candidate genes for validation 7 of which proved significantly-associated with B-cell ALL. We next focused on function and clinical correlations of the cysteine and glycine-rich protein 2 (CSRP2). Quantitative real-time polymerase chain reaction (RT-qPCR) was used to examine gene transcript levels in bone marrow samples from 236 adults with B-cell ALL compared with samples from normals. CSRP2 was over-expressed in 228 out of 236 adults (97%) with newly-diagnosed B-cell ALL. A prognostic value was assessed in 168 subjects. In subjects with normal cytogenetics those with high CSRP2 transcript levels had a higher 5-year cumulative incidence of relapse (CIR) and worse relapse-free survival (RFS) compared with subjects with low transcript levels (56% [95% confidence interval, 53, 59%] vs. 19% [18, 20%]; P = 0.011 and 41% [17, 65%] vs. 80% [66–95%]; P = 0.007). In multivariate analyses a high CSRP2 transcript level was independently-associated with CIR (HR = 5.32 [1.64–17.28]; P = 0.005) and RFS (HR = 5.56 [1.87, 16.53]; P = 0.002). Functional analyses indicated CSRP2 promoted cell proliferation, cell-cycle progression, in vitro colony formation and cell migration ability. Abnormal CSRP2 expression was associated with resistance to chemotherapy; sensitivity was restored by down-regulating CSRP2 expression.

Identifying heterogeneous subtypes of gastric cancer and subtype‑specific subpaths of microRNA‑target pathways

The present study aimed to classify gastric cancer (GC) into subtypes and to screen the subtype-specific genes, their targeted microRNAs (miRNAs) and enriched pathways to explore the putative mechanism of each GC subtypes. The GSE13861 data set was downloaded from the Gene Expression Omnibus and used to screen differential expression genes (DEGs) in GC samples based on the detection of imbalanced differential signal algorithm. The specific genes in each subtype were identified with the cut-off criterion of U>0.04, pathway enrichment analysis was performed and the subtype-specific subpaths of miRNA-target pathway were determined. A total of 1,263 DEGs were identified in the primary gastric adenocarcinoma (PGD) samples, which were subsequently divided into four subtypes, according to the hierarchy cluster analysis. Identification of the subpaths of each subtype indicated that the subpath related to subtype 1 was miRNA (miR)-202/calcium voltage-gated channel subunit α1 (CACNA1E)/type II diabetes mellitus. The nuclear factor-κB signaling pathway was the most significantly specific pathway and subpath identified for subtype 2, which was regulated by miR-338-targeted suppression of C-C motif chemokine ligand 21 (CCL21). For subtype 3, significant related pathways included ubiquitin-mediated proteolysis and proteasome, and the important subpath was miR-146B/proteasome 26S subunit, non-ATPase 3 (PSMD3)/proteasome; focal adhesion was the significant pathway indicated for subtype 4, and the subpaths were miR-34A/vinculin (VCL)/focal adhesion and miR-34C/VCL/focal adhesion. In addition, Helicobacter pylori infection was higher in GC subtype 1 than in other subtypes. Specific genes, such as CACNA1E, CCL21, PSMD3 and VCL, may be used as potential feature genes to identify different subtypes of GC, and their associated subpaths may partially explain the pathogenetic mechanism of each GC subtype.