Gene Expression Profiling Interactive Analysis Research Articles

Exploring the therapeutic mechanisms and prognostic targets of Biochanin A in glioblastoma via integrated computational analysis and in vitro experiments

Glioblastoma (GBM) is the most aggressive brain tumor and is characterized by a poor prognosis and high recurrence and mortality rates. Biochanin A (BCA) exhibits promising clinical anti-tumor effects. In this study, we aimed to explore the pharmacological mechanisms by which BCA acts against GBM. Network pharmacology was employed to identify overlapping target genes between BCA and GBM. Differentially expressed genes from the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database were visualized using VolcaNose. Interactions among these overlapping genes were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Protein–protein interaction networks were constructed using Cytoscape 3.8.1. The Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Survival analyses for these genes were performed using the GEPIA2 database. The Chinese Glioma Genome Atlas database was used to study the correlations between key prognostic genes. Molecular docking was confirmed using the DockThor database and visualized with PyMol software. Cell viability was assessed via the CCK-8 assay, apoptosis and the cell cycle stages were examined using flow cytometry, and protein expression was detected using western blotting. In all, 63 genes were initially identified as potential targets for BCA in treating GBM. Enrichment analysis suggested that the pharmacological mechanisms of BCA primarily involved cell cycle inhibition, induction of cell apoptosis, and immune regulation. Based on these findings, AKT1, EGFR, CASP3, and MMP9 were preliminarily predicted as key prognostic target genes for BCA in GBM treatment. Furthermore, molecular docking analysis suggested stable binding of BCA to the target protein. In vitro experiments revealed the efficacy of BCA in inhibiting GBM, with an IC50 value of 98.37 ± 2.21 μM. BCA inhibited cell proliferation, induced cell apoptosis, and arrested the cell cycle of GBM cells. Furthermore, the anti-tumor effects of BCA on U251 cells were linked to the regulation of the target protein. We utilized integrated bioinformatics analyses to predict targets and confirmed through experiments that BCA possesses remarkable anti-tumor activities. We present a novel approach for multi-target treatment of GBM using BCA.

Validation of serum cystatin SN detection for diagnosis and poor prognosis of esophageal squamous cell carcinoma.

The identification of effective tumor markers is of paramount importance for the early diagnosis, treatment, and prognosis of esophageal squamous cell carcinoma (ESCC). The present study endeavors to identify efficacious serological markers that can differentiate patients with early-stage ESCC from those with benign esophageal lesions and healthy controls (HC). Cystatin-SN (CST1), an active cysteine protease inhibitor belonging to the Cystatin (CST) superfamily, is implicated in the pathogenesis of inflammation and tumorigenesis. The objective of this investigation is to assess the diagnostic, therapeutic, and prognostic potential of serum CST1 in ESCC. In our prior RNA sequencing and screening endeavors, we have identified ten genes that are up-regulated in relation to esophageal cancer. Subsequently, we have verified the gene CST1 from the transcriptome data of the The Cancer Genome Atlas Program (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) database. Following this, we conducted an enzyme-linked immunosorbent assay (ELISA) to ascertain the expression levels of CST1 in serum samples from clinical cohorts. The study revealed a significant elevation in serum CST1 levels among patients with early-stage esophageal squamous cell carcinoma (ESCC) (7.41 ± 4.32 ng/ml) compared to those with esophageal benign lesions (4.67 ± 2.43 ng/ml) (p < 0.0001) and healthy controls (4.87 ± 2.77 ng/ml) (p < 0.0001). The diagnostic sensitivity of CST1 for ESCC was 75.68% (specificity 70.83%, AUC 0.775). Combination of CST1 and SCC-Ag exhibited the AUC up to 0.819. Additionally, serum CST1 levels exhibited a significant decrease at 1-2 weeks post-surgery (4.49 ± 3.31 ng/ml) compared to pre-surgery levels (7.68 ± 3.71 ng/ml) (p<0.0001). Survival analysis demonstrated a strong association between high (844/415-1543 d) or low (1490/645-1710 d) serum CST1 levels at diagnosis and overall survival time (p < 0.001). Furthermore, multivariate regression analysis confirmed CST1 (p=0.024, HR=2.023, 95%CI 1.099-3.725) as an independent prognostic factor. Serum CST1 has the potential to function as a diagnostic indicator for distinguishing early-stage esophageal squamous cell carcinoma (ESCC) from individuals with benign esophageal lesions and healthy individuals. Additionally, it could serve as a prognostic predictor and therapeutic efficacy indicator for patients with ESCC.

Prognosis and clinical significance of Piezo2 in tumor: a meta-analysis and database validation.

The objective of this study is to assess the correlation between Piezo2 and tumors through a comprehensive meta-analysis and database validation. Case-control studies investigating the association between Piezo2 and tumors were obtained from various databases, including China National Knowledge Infrastructure (CNKI), SinoMed, Embase, Web of Science, The Cochrane Library, and PubMed. The search was performed from the inception of each database up until May 2023. Two researchers independently screened the literature, extracted data, and assessed the quality of the included studies. Metaanalysis of the included literature was conducted using Stata 12.0 software. Additionally, the Gene Expression Profiling Interactive Analysis (GEPIA) database predicted a correlation between Piezo2 expression and prognostic value in tumor patients. A total of three studies, involving a combined sample size of 392 participants, were included in the meta-analysis. The findings revealed that the expression level of Piezo2 in tumor patients was not significantly associated with age, gender, or tumor size. However, it was found to be positively correlated with lymphatic invasion (OR = 7.89, 95%CI: 3.96-15.73) and negatively correlated with invasion depth (OR = 0.17, 95%CI: 0.06-0.47), TNM stage (OR = 0.48, 95%CI: 0.27-0.87), and histological grade (OR = 0.40, 95%CI: 0.21-0.77). Confirming these findings, the GEPIA database indicated that high expression of Piezo2 was associated with poor prognosis of disease-free survival in patients with colon adenocarcinoma (HR = 1.6, P = 0.049) and gastric cancer (HR = 1.6, P = 0.017). Piezo2 may be associated with poor prognosis and clinicopathological parameters in tumor patients.

A pan-cancer analysis uncovering the function of CRHBP in tumor immunity, prognosis and drug response: especially its function in LIHC

Corticotropin-releasing hormone-binding protein (CRHBP) is involved in many physiological processes. However, it is still unclear what role CRHBP has in tumor immunity and prognosis prediction. Using databases such as the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Tumor Protein Database, Timer Database, and Gene Expression Profiling Interactive Analysis (GEPIA), we evaluated the potential role of CRHBP in diverse cancers. Further research looked into the relationships between CRHBP and tumor survival prognosis, immune infiltration, immune checkpoint (ICP) indicators, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), DNA methylation, tumor microenvironment (TME), and drug responsiveness. The anticancer effect of CRHBP in liver hepatocellular carcinoma (LIHC) was shown by Western blotting, EdU staining, JC-1 staining, transwell test, and wound healing assays. CRHBP expression is significantly low in the majority of tumor types and is associated with survival prognosis, ICP markers, TMB, and microsatellite instability (MSI). The expression of CRHBP was found to be substantially related to the quantity of six immune cell types, as well as the interstitial and immunological scores, showing that CRHBP has a substantial impact in the TME. We also noticed a link between the IC50 of a number of anticancer medicines and the degree of CRHBP expression. CRHBP-related signaling pathways were discovered using functional enrichment. Cox regression analysis showed that CRHBP expression was an independent prognostic factor for LIHC. CRHBP has a tumor suppressor function in LIHC, according to cell and molecular biology trials. CRHBP has a significant impact on tumor immunity, treatment, and prognosis, and has the potential as a cancer treatment target and prognostic indicator.

Clinical significance of KRT7 in bladder cancer prognosis.

Typically, the overexpressed keratin 7 (KRT7) is considered a validated therapeutic target and prognosis marker in bladder cancer. However, the crucial roles of KRT7 in the clinical prognosis and immune microenvironment in bladder cancer remain unclear. Initially, the expression levels of KRT7 in public databases were analyzed that is,Tumor Immune Estimation Resource (TIMER) 2.0 and Gene Expression Profiling Interactive Analysis (GEPIA). Further, the clinical tissue samples from patients (n = 10 pairs) were collected to confirm the expression trends of KRT7 and detected by immunohistochemistry (IHC) analysis. Meanwhile, the relationship between KRT7 and the prognosis of bladder cancer patients was analyzed by Kaplan-Meier plotter estimation and Cox regression analysis. Finally, TIMER 2.0 and IHC staining analyses were performed to calculate the infiltration abundances of three kinds of immune cells in eligible bladder tumor samples. The TIMER 2.0 and GEPIA datasets suggested the differences in the expression levels of KRT7 in tumors, in which KRT7 was significantly upregulated in bladder cancer. The KRT7 expression was closely associated with patients' gender, tumor histologic subtypes, T status, and American Joint Committee on Cancer stages. Notably, the increased KRT7 indicated poor overall survival and disease-free survival rates. Moreover, KRT7 expression could be responsible for immune infiltration in the cancer microenvironment of the bladder. Finally, the high expression level of KRT7 increased the presence of regulatory T cells (Tregs) but reduced the infiltration of CD8+ T and natural killer cells. KRT7 as a biomarker potentiated the prediction of bladder cancer prognosis and the immune microenvironment.

Identification of prognostic biomarkers of smoking-related lung cancer.

The early diagnosis and effective prognostic treatment measures for lung cancer are still limited, leading to a 5-year survival rate of less than 15% for these patients. Smoking is one of the causes of lung cancer, but it is not the initial carcinogenic factor. It is not clear what specific mechanism cigarette induces lung cancer, and there is a lack of research on the relationship between related genes and the prognosis of patients with smoking lung cancer. The objective of this study was to provide new theoretical evidence and potential therapeutic targets for the mechanisms of smoking-related lung cancer formation. The gene expression profile data from the GSE12428 dataset which includes 63 lung cancer and normal tissue pairs were downloaded from the Gene Expression Omnibus (GEO) database, and data from smokers with lung cancer [both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)] from The Cancer Genome Atlas (TCGA) database were analyzed. The differential genes in smokers with lung cancer were screened using the linear model for microarray data via R software. The differential gene enrichment analysis was performed using the online analysis software Database for Annotation, Visualization and Integrated Discovery (DAVID). The expression levels of differential genes and their correlation with patient tumor clinical stage were analyzed using gene expression profiling interactive analysis (GEPIA). The overall survival rate was analyzed using Kaplan-Meier curves. In the GSE12428 dataset, 225 upregulated genes and 565 downregulated genes were identified in cancer tissues; based on smoking status, 1 upregulated gene and 4 downregulated genes were identified. Among smokers who also had lung cancer, 4 genes were downregulated, namely CSH1, BPIFA1, SLPI, and SCGB3A1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these genes were mainly associated with biological functions such as antibacterial response, humoral immune response, and response to external stimuli. Among them, BPIFA1, SLPI, and SCGB3A1 expression was decreased in lung cancer tissues, with SCGB3A1 showing significant differences. Additionally, high expression of SCGB3A1 was associated with favorable prognosis in patients with lung cancer. Three genes BPIFA1, SLPI and SCGB3A1, were identified as being associated with smokers with lung cancer, with SCGB3A1 showing a close correlation with patient prognosis. These findings provide potential new targets for the treatment of lung cancer. Certainly, this study needs to more investigate the mechanism of these genes regulation.

Construction of an exosome-associated miRNA-mRNA regulatory network and validation of FYCO1 and miR-17-5p as potential biomarkers associated with ovarian cancer.

The occurrence and development of several human physiological processes are significantly influenced by the competing endogenous RNA (ceRNA) network. The aim of the present study was to construct a microRNA (miRNA)-mRNA network associated with exosomes in ovarian cancer (OV), and experimental validation of key target genes. By exploring the Gene Expression Omnibus (GEO) database, we analyzed the RNAs from 226 samples to identify differentially expressed miRNAs (DEMs) and genes (DEGs) that showed differential expression as OV progressed. Subsequently, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on the DEGs. Furthermore, we constructed a miRNA-mRNA network that pertains to exosomes in OV using DEMs and DEGs. Moreover, we validated the expression levels of mRNAs in the miRNA-mRNA network using Gene Expression Profiling Interactive Analysis (GEPIA2). Ultimately, luciferase reporter assay was used to identify the potential target relationship between FYVE and coiled-coil domain containing 1 (FYCO1) and miRNAs. Our analysis screened a total of 14 DEMs and 101 DEGs, and the DEGs were mainly enriched in DNA replication or repair, amino acid biosynthesis and carbon metabolism. Furthermore, a miRNA-mRNA network was constructed including 3 miRNAs (hsa-miR-17-5p, hsa-miR-20b-5p and hsa-miR-20a-5p) and 2 mRNAs, FYCO1 and purine rich element binding protein A (PURA). Finally, the 2 mRNAs in this miRNA-mRNA network were verified by GEPIA2 using The Cancer Genome Atlas (TCGA) database. Among them, only FYCO1 showed significant different expression of mRNA in OV and normal tissue, while the prognosis of FYCO1 in OV remains controversial due to different database. Interestingly, FYCO1 was identified as the target of hsa-miR-17-5p. By constructing a novel network of miRNA-mRNA, we can gain new understanding of the molecular mechanisms that drive exosomes in OV. Targeting FYCO1, which originates from exosomes, may hold promise as a diagnostic marker for OV.

B7-H3 promotes proliferation and migration of lung cancer cells by modulating PI3K/AKT pathway via ENO1 activity.

B7-H3 (CD276) is overexpressed in diverse malignant tumors and plays critical roles in tumorigenesis and metastasis. However, the mechanism of B7-H3 in lung cancer remains unclear. This study aimed to explore the mechanism of interaction between B7-H3 and α-enolase (ENO1) in lung cancer progression. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) and Gene Expression Profiling Interactive Analysis 2 (GEPIA 2) databases were used to analyze the B7-H3 messenger RNA (mRNA) expression levels in lung cancer. The Kaplan-Meier (KM) plotter was used to analyze the correlation between B7-H3 and prognosis. Immunoprecipitation and glutathione S-transferase (GST) pull-down were used to verify the B7-H3 and ENO1 interaction. Cell counting kit-8 (CCK-8) and wound healing assays were used to investigate the effect of B7-H3 on the lung cancer growth. Based on the public databases, the analysis showed that B7-H3 mRNA expression levels were up-regulated and correlated with patient prognosis in lung cancer. By using B7-H3 gain and off cell model, we concluded that B7-H3 overexpression promoted proliferation and migration of SBC5 cells. Subsequently, we found that both B7-H3 and ENO1 knockdown could inhibit cell proliferation and migration, in the meanwhile, and the phosphorylation levels of PI3K-p85α, and AKT were significantly reduced. Interestingly, we determined that B7-H3 regulated ENO1 activity rather than changing its expression levels. Furthermore, we used an AP-III-a4 to block ENO1 activity in the experiments, which attenuated the roles of B7-H3 not only on phosphorylation levels of those molecules, but also on cell growth and migration. B7-H3 directly interacts with ENO1 in lung cancer cells. B7-H3 can promote proliferation and migration of lung cancer cells by modulating PI3K/AKT pathway via ENO1 activity.

Depleted-MLH1 Expression Predicts Prognosis and Immunotherapeutic Efficacy in Uterine Corpus Endometrial Cancer: An In Silico Approach

Uterine corpus endometrial carcinoma (UCEC) poses significant clinical challenges due to its high incidence and poor prognosis, exacerbated by the lack of effective screening methods. The standard treatment for UCEC typically involves surgical intervention, with radiation and chemotherapy as potential adjuvant therapies. In recent years, immunotherapy has emerged as a promising avenue for the advanced treatment of UCEC. This study employs a multi-omics approach, analyzing RNA-sequencing data and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA), and GeneMANIA databases to investigate the prognostic value of MutL Homolog 1 (MLH1) gene expression in UCEC. The dysregulation of MLH1 in UCEC is linked to adverse prognostic outcomes and suppressed immune cell infiltration. Gene Set Enrichment Analysis (GSEA) data reveal MLH1’s involvement in immune-related processes, while its expression correlates with tumor mutational burden (TMB) and microsatellite instability (MSI). Lower MLH1 expression is associated with poorer prognosis, reduced responsiveness to Programmed cell death protein 1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors, and heightened sensitivity to anti-cancer agents. This comprehensive analysis establishes MLH1 as a potential biomarker for predicting prognosis, immunotherapy response, and drug sensitivity in UCEC, offering crucial insights for the clinical management of patients.

A study on the role of Taxifolin in inducing apoptosis of pancreatic cancer cells: screening results using weighted gene co-expression network analysis.

Pancreatic adenocarcinoma (PAAD) is a frequent malignant tumor in the pancreas. The incomplete understanding of cancer etiology and pathogenesis, as well as the limitations in early detection and diagnostic methods, have created an urgent need for the discovery of new therapeutic targets and drugs to control this disease. As a result, the current therapeutic options are limited. In this study, the weighted gene co-expression network analysis (WGCNA) method was employed to identify key genes associated with the progression and prognosis of pancreatic adenocarcinoma (PAAD) patients in the Gene Expression Profiling Interactive Analysis (GEPIA) database. To identify small molecule drugs with potential in the treatment of pancreatic adenocarcinoma (PAAD), we compared key genes to the reference dataset in the CMAP database. First, we analyzed the antitumor properties of small molecule drugs using cell counting kit-8 (CCK-8), AO/EB and Transwell assays. Subsequently, we integrated network pharmacology with molecular docking to explore the potential mechanisms of the identified molecules' anti-tumor effects. Our findings indicated that the progression and prognosis of PAAD patients in pancreatic cancer were associated with 11 genes, namely, DKK1, S100A2, CDA, KRT6A, ITGA3, GPR87, IL20RB, ZBED2, PMEPA1, CST6, and MUC16. These genes were filtered based on their therapeutic potential through comparing them with the reference dataset in the CMAP database. Taxifolin, a natural small molecule drug with the potential for treating PAAD, was screened by comparing it with the reference dataset in the CMAP database. Cell-based experiments have validated the potential of Taxifolin to facilitate apoptosis in pancreatic cancer cells while restraining their invasion and metastasis. This outcome is believed to be achieved via the HIF-1 signaling pathway. In conclusion, this study provided a theoretical basis for screening genes related to the progression of pancreatic cancer and discovered potentially active small molecule drugs. The experimental results confirm that Taxifolin has the ability to promote apoptosis in pancreatic cancer cells.

Comprehensive analysis of the effects of the cuprotosis-associated gene SLC31A1 on patient prognosis and tumor microenvironment in human cancer.

Solute carrier family 31 (copper transporter), member 1 (SLC31A1) is a key factor in maintaining intracellular copper concentration and an important factor affecting cancer energy metabolism. Therefore, exploring the potential biological function and value of SLC31A1 could provide a new direction for the targeted therapy of tumors. This study assessed gene expression levels, survival, clinicopathology, gene mutations, methylation levels, the tumor mutational burden (TMB), microsatellite instability (MSI), and the immune cell infiltration of SLC31A1 in pan-cancer using the Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham CANcer (UALCAN) data analysis portal, and cBioPortal databases. To further understand the potential biological mechanisms of SLC31A1 in different cancers, single-cell level sequencing and a Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis of SLC31A1 were also performed. Finally, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting (WB) were used to validate the expression of SLC31A1 in cancers, such as gastric cancer. SLC31A1 was expressed in most cancer tissues. In kidney renal clear cell carcinoma (KIRC), the high expression of SLC31A1 was associated with good overall survival (OS), while in adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), lower grade glioma (LGG), mesothelioma (MESO), and skin cutaneous melanoma (SKCM), the low expression of SLC31A1 was associated with good OS. The highest frequency of SLC31A1 amplification was observed in ACC. In addition, missense mutations accounted for a major portion of the mutation types. The truncation mutation S105Y may be a putative cancer driver. SLC31A1 affected methylation levels in cancer and was associated with the TMB, MSI, and the level of infiltration of various immune cells. Additionally, the single-cell sequencing results showed that SLC31A1 was associated with multiple biological functions in cancer. Finally, the SLC31A1 enrichment analysis revealed that the SLC31A1-related genes were mainly enriched in the mitochondrial matrix and envelope vesicles. The RT-qPCR and WB results were consistent with the predicted results. SLC31A1 may be a potential target related to cancer energy metabolism and may have prognostic value.

Periostin is associated with prognosis and immune cell infiltration in pancreatic adenocarcinoma based on integrated bioinformatics analysis.

Pancreatic cancer is one of the most aggressive human malignancies. Previous research has shown that periostin (POSTN) promotes pancreatic cancer cell proliferation, migration, and invasion. Further, POSTN is involved in tumor microenvironment remodeling during tumor progression. However, the relationship between POSTN expression, immune cell infiltration, and the efficacy of immunotherapy in pancreatic cancer is unclear. We conducted a comprehensive evaluation of POSTN differential expression, examining mRNA and protein levels. To gather data, we utilized various databases including gene expression profiling interactive analysis 2 (GEPIA2), gene expression omnibus (GEO), and the human protein atlas (HPA). To investigate the correlation between POSTN expression and clinical characteristics, we analyzed data from the Kaplan-Meier plotter database and clinical data sourced from the cancer genome atlas (TCGA). Furthermore, we performed gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). Additionally, we explored the relationship between POSTN expression and immune cell infiltration, as well as the immunophenoscore (IPS), by leveraging the cancer immunome atlas (TCIA) database. Lastly, we examined the tumor mutational burden (TMB) in pancreatic cancer in relation to POSTN expression. When compared with healthy pancreatic tissues, pancreatic cancer tissues displayed significantly higher levels of POSTN, which was indicative of a worse prognosis. POSTN expression was closely associated with extracellular matrix (ECM) organization, ECM-receptor interaction, and focal adhesion by GO, KEGG pathway, and GSEA analyses. Higher expression of POSTN was associated with increased infiltration of M2 macrophages. Additionally, increased IPS was linked to lower POSTN expression. IPS scores for CTLA4, PD-1/PDL1, and CTLA4/PD-1/PDL1 immune checkpoint inhibitors were also higher in the POSTN-low expression group, suggesting that lower expression of POSTN is associated with a better outcome with checkpoint inhibitor treatment. POSTN is related to pancreatic cancer prognosis, and may influence immune cell infiltration. High expression of POSTN is predicted to correlate with lower sensitivity to immunotherapy with checkpoint inhibitors in pancreatic cancer.

Identification of potential biomarkers in follicular thyroid carcinoma: bioinformatics and immunohistochemical analyses

Abstract Objectives The prevalence of thyroid cancer has shown a progressive rise over time. This study aimed to explore the expression and underlying mechanisms of decorin (DCN) in follicular thyroid carcinoma (FTC), employing bioinformatics analysis and immunohistochemistry techniques. Methods The GSE27155 dataset was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and core DEGs were identified through data mining and analysis using the R language and online databases. The expression of core DEGs was validated using The Cancer Genome Atlas database. Additionally, the correlation between DCN and clinicopathological stage, tumor-infiltrating lymphocytes, and hotspot molecules in thyroid cancer was assessed using the Gene Expression Profiling Interactive Analysis and TIMER databases. Immunohistochemical (IHC) analysis was then conducted to verify the differential expression of core DCN in FTC and adjacent tissues. Results We confirmed the downregulation of three DEGs (DCN, GPC3, and PDGFRA). Furthermore, the analysis revealed a significant association between DCN expression and the clinical stage of patients with thyroid cancer (p&lt;0.0001). DCN expression and the infiltration of several immune cells were positively correlated (p&lt;0.01). A significant positive correlation was also noted between DCN and the NRAS and KRAS genes (partial cor&gt;0, p&lt;0.05). Immunohistochemical analyses revealed a significantly lower staining score (3.071 ± 2.493) for DCN protein in cancer tissues than that in adjacent tissues (8.643 ± 2.094) (p&lt;0.0001). Conclusions DCN is underexpressed and contributes to tumor progression in FTC. Thus, DCN serves as a tumor suppressor gene in FTC and a promising therapeutic target.

CX3CR1 is a potential biomarker of immune microenvironment and prognosis in epithelial ovarian cancer.

Immunotherapy is less efficient for epithelial ovarian cancer and lacks ideal biomarkers to select the best beneficiaries for immunotherapy. CX3CR1 as chemokine receptor mainly expressed on immune cell membranes, and combined with its unique ligand CX3CL1, mediates tissue chemotaxis and adhesion of immune cells. However, the immune functional and prognostic value of CX3CR1 in epithelial ovarian cancer has not been clarified. A comprehensive retrospective analysis was performed by using the online database to identify the underlying immunological mechanisms and prognostic value of CX3CR1. The Human Protein Atlas, gene expression profiling interactive analysis, and TISIDB (an integrated repository portal for tumor-immune system interactions) database showed that CX3CR1 expressed higher in epithelial ovarian cancer than that in normal ovarian tissue. Four hundred twenty-two cases from Gene Expression Profiling Interactive Analysis and 1656 cases from Kaplan-Meier plotter database showed higher expression of CX3CR1 (above median) was associated with unfavorable overall survival. TIMER, UALCAN, and TISIDB database were applied to validate CX3CR1 negative impact on overall survival. In addition, correlation analysis showed that the expression level of CX3CR1 was positive association with infiltrating levels of B cells (R = 0.31, P = 3.10e-12), CD8+ T cells (R = 0.26, P = 7.93e-09), CD4+ T cells (R = 0.11, P = 1.41e-02), macrophages (R = 0.32, P = 4.29e-13), dendritic cells (R = 0.27, P = 2.98e-09), and neutrophil (R = 0.25, P = 3.25e-08) in epithelial ovarian cancer. Therefore, CX3CR1 involved in reshaping the immune microenvironment for epithelial ovarian cancer and maybe a potential immunotherapy target and prognostic marker for ovarian cancer.

ZC3H12A inhibits tumor growth and metastasis of breast cancer under hypoxic condition via the inactivation of IL-17 signaling pathway

ABSTRACT Hypoxia is a major contributor to tumor microenvironment (TME) and metastasis in most solid tumors. We seek to screen hypoxia-related genes affecting metastasis in breast cancer and to reveal relative potential regulatory pathway. Based on gene expression profiling of GSE17188 dataset, differential expressed genes (DEGs) were identified between highly metastatic breast cancer cells under hypoxia and samples under normoxia. The protein–protein interaction (PPI) network was utilized to determine hub genes. The gene expression profiling interactive analysis database (GEPIA2) and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) were employed to quantify hub genes. Moreover, overexpression of zinc finger CCCH-type containing 12A (ZC3H12A) was performed both in breast cancer cells and xenograft mouse model to determine the role of ZC3H12A. We identified 134 DEGs between hypoxic and normoxic samples. Based on PPI analysis, 5 hub genes interleukin (IL)-6, GALN (GAL), CD22 molecule (CD22), ZC3H12A and TNF receptor associated factor 1 (TRAF1) were determined; the expression levels of TRAF1, IL-6, ZC3H12A and GAL were remarkably downregulated while CD22 was upregulated in breast cancer cells. Besides, patients with higher expression of ZC3H12A had favorable prognosis. Overexpression of ZC3H12A could inhibit metastasis and tumor growth of breast cancer; overexpression of ZC3H12A downregulated the expression of IL-17 signaling pathway-related proteins such as IL-17 receptor A (IL-17RA), IL-17A and nuclear factor κB activator 1 (Act1). This study reveals ZC3H12A and IL-17 signaling pathway as potential therapeutic targets for hypoxic breast cancer.

Mechanism of the Effect of Scopolamine on Breast Cancer: Determination by Network Pharmacology and Bioinformatics.

To a certain extent, traditional Chinese medicine (TCM)-based anesthesia has replaced opiate administration in recent years. Preliminary drug screening has revealed that scopolamine may affect breast cancer (BC) metastasis by an unknown mechanism. Network pharmacology, bioinformatics, and protein-protein interaction (PPI) topological analysis were implemented to identify the core genes linking scopolamine and BC. The core genes were then subjected to gene expression profiling interactive analysis (GEPIA). The top ten pathways were detected by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The impact of immune infiltration on the core gene difference and survival analyses was then determined. Molecular docking was then performed on the core genes and the main active components. Protein kinase 1 (AKT1), epidermal growth factor receptor (EGFR), heat shock protein 90 alpha class A (HSP90AA1), caspase 3 (CASP3), and estrogen receptor 1 (ESR1) were the key genes in the interaction between scopolamine and BC cells. The KEGG enrichment analysis disclosed that the top ten pathways significantly associated with the scopolamine response in BC included "protein glycosylation," "phosphoinositide 3-kinase (PI3K)-Akt signaling," "mitogen- activated protein kinase (MAPK) signaling" and others. The AKT1, EGFR, and especially the HSP90AA1 expression levels were correlated with survival in patients with BC. Immune infiltration also influenced the survival outcome. Molecular docking demonstrated that scopolamine bound and formed stable complexes with the protein products of all five aforementioned genes. Scopolamine has multiple targets regulating BC cell function and may increase the risk of metastasis during treatment. Therefore, it should be preoperatively administered with caution to patients with BC.

Systems biology approach to identify biomarkers and therapeutic targets for colorectal cancer

BackgroundColorectal cancer (CRC), is the third most prevalent cancer across the globe, and is often detected at advanced stage. Late diagnosis of CRC, leave the chemotherapy and radiotherapy as the main options for the possible treatment of the disease which are associated with severe side effects. In the present study, we seek to explore CRC gene expression data using a systems biology framework to identify potential biomarkers and therapeutic targets for earlier diagnosis and treatment of the disease. MethodsThe expression data was retrieved from the gene expression omnibus (GEO). Differential gene expression analysis was conducted using R/Bioconductor package. The PPI network was reconstructed by the STRING. Cystoscope and Gephi software packages were used for visualization and centrality analysis of the PPI network. Clustering analysis of the PPI network was carried out using k-mean algorithm. Gene-set enrichment based on Gene Ontology (GO) and KEGG pathway databases was carried out to identify the biological functions and pathways associated with gene groups. Prognostic value of the selected identified hub genes was examined by survival analysis, using GEPIA. ResultsA total of 848 differentially expressed genes were identified. Centrality analysis of the PPI network resulted in identification of 99 hubs genes. Clustering analysis dissected the PPI network into seven interactive modules. While several DEGs and the central genes in each module have already reported to contribute to CRC progression, survival analysis confirmed high expression of central genes, CCNA2, CD44, and ACAN contribute to poor prognosis of CRC patients. In addition, high expression of TUBA8, AMPD3, TRPC1, ARHGAP6, JPH3, DYRK1A and ACTA1 was found to associate with decreased survival rate. ConclusionOur results identified several genes with high centrality in PPI network that contribute to progression of CRC. The fact that several of the identified genes have already been reported to be relevant to diagnosis and treatment of CRC, other highlighted genes with limited literature information may hold potential to be explored in the context of CRC biomarker and drug target discovery.

Clinical utility of keratin 14 expression measurement in reflecting the tumor properties and prognosis in patients with renal cell carcinoma: a study with long-term follow-up.

Keratin 14 (KRT14) is hypothesized to be involved in the pathogenesis of renal cell carcinoma (RCC) based on its tumorigenic role in various cancers and its relationship with the prognosis of other urinary system malignancies. This study aimed to evaluate the correlation of KRT14 with tumor properties and prognosis in RCC patients. Data from 180 RCC patients who received tumor resection were retrospectively reviewed. The KRT14 was assessed by immunohistochemistry (IHC) staining in tumor tissues and non-tumor tissues. KRT14 was insufficiently expressed in both tumor and non-tumor tissues, with median (interquartile range) IHC score of 2.0 (0.0-3.4) and 1.0 (0.0-2.0), respectively. While it was relatively higher in tumor versus non-tumor tissues (P < 0.001). Besides, tumor KRT14 was positively correlated with the pathological grade (P = 0.038), tumor size (P = 0.012), T stage (P = 0.006), and TNM stage (P = 0.018). Interestingly, tumor KRT14 high predicted shorter accumulating recurrence-free survival (RFS) (P = 0.003) and accumulating overall survival (OS) (P = 0.001), which was further verified by the multivariate Cox's regression analysis (both P < 0.05). Furthermore, tumor KRT14 high estimated shorter RFS and OS from the Gene Expression Profiling Interactive Analysis and Human Protein ATLAS databases (all P < 0.05). Subgroup analyses indicated that the correlation of tumor KRT14 with accumulating RFS and accumulating OS was more pronounced in RCC patients with better physical status (such as age < 65years and better eastern cooperative oncology group performance status) and higher tumor stages (such as higher pathological grade). High KRT14 in tumor tissue could reflect an advanced tumor features and unsatisfying survival in RCC patients.

Catalase expression is an independent prognostic marker in liver hepatocellular carcinoma

Abstract Objectives Liver hepatocellular carcinoma (LIHC) is the most common type of primary liver cancer and originates from hepatocytes, the main functional cells of the liver. It is a serious and aggressive cancer with a generally poor prognosis, especially when diagnosed at advanced stages. Reactive oxygen species (ROS) have been detected in LIHC and are involved in carcinogenesis and tumor progression. Here, a comprehensive analysis was performed to evaluate the effects of ROS-related genes on the prognosis of LIHC. Methods Using bioinformatical tools including Gene Expression Profiling Interactive Analysis (GEPIA2) and Q-omics, a comprehensive analysis was performed to evaluate the effects of ROS-related genes, including superoxide dismutases (SODs), glutathione peroxidases (GPXs), peroxiredoxins (PRDXs) and catalase (CAT) on the prognosis of LIHC using The Cancer Genome Atlas (TCGA) dataset and identified the most appropriate candidate genes. Then we further explored their effects on LIHC cell proliferation and drug selection for LIHC treatment. Results We found that CAT expression was significantly downregulated in late stage’s LIHC tissues compared to normal liver or early stage’s LIHC tissues, and high CAT expression was correlated with a favorable survival prognosis in LIHC. The expression of the CAT gene was associated with an inhibition of the “cell cycle” pathway. HepG2 and Hep3B cells’ growth was increased with a decrease in CAT expression by silencing its mRNA. As silencing of CAT in HepG2 and Hep3B cells, and its association with an increase in the expression of PLK1, CCNB1, CDC20, and PTTG1. A comparative 426 drug response in LIHC cells with different CAT expression, SU11274, a Met inhibitor, could serve as a therapeutic option when CAT levels are low in LIHC cells. Conclusions Our findings revealed that Met inhibitors could potentially control tumor progression and be used as a therapeutic option against LIHC with low CAT.

Identification of Novel Prognostic Biomarkers for Colorectal Cancer by Bioinformatics Analysis.

Colorectal cancer (CRC) ranks third among malignancies in terms of global incidence and has a poor prognosis. The identification of effective diagnostic and prognostic biomarkers is critical for CRC treatment. This study intends to explore novel genes associated with CRC progression via bioinformatics analysis. Dataset GSE184093 was selected from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between CRC and noncancerous specimens. Functional enrichment analyses were implemented for probing the biological functions of DEGs. Gene Expression Profiling Interactive Analysis and Kaplan-Meier plotter databases were employed for gene expression detection and survival analysis, respectively. Western blotting and real-time quantitative polymerase chain reaction were employed for detecting molecular protein and messenger RNA levels, respectively. Flow cytometry, Transwell, and CCK-8 assays were utilized for examining the effects of GBA2 and ST3GAL5 on CRC cell behaviors. There were 6464 DEGs identified, comprising 3005 downregulated DEGs (dDEGs) and 3459 upregulated DEGs (uDEGs). Six dDEGs were significantly associated with the prognoses of CRC patients, including PLCE1, PTGS1, AMT, ST8SIA1, ST3GAL5, and GBA2. Upregulating ST3GAL5 or GBA2 repressed the malignant behaviors of CRC cells. We identified 6 genes related to CRC progression, which could improve the disease prognosis and treatment.