Network based analyses of gene expression profile of LCN2 overexpression in esophageal squamous cell carcinoma

Lipocalin 2 receptors: facts, fictions, and myths

The human 25-kDa Lipocalin 2 (LCN2) was first identified and purified as a protein that in part is associated with gelatinase from neutrophils. This protein shows a high degree of sequence similarity with the deduced sequences of rat α2-microglobulin-related protein and the mouse protein 24p3. Based on its typical lipocalin fold, which consists of an eight-stranded, anti-parallel, symmetrical β-barrel fold structure it was initially thought that LCN2 is a circulating protein functioning as a transporter of small lipophilic molecules. However, studies in Lcn2 null mice have shown that LCN2 has bacteriostatic properties and plays a key role in innate immunity by sequestering bacterial iron siderophores. Numerous reports have further shown that LCN2 is involved in the control of cell differentiation, energy expenditure, cell death, chemotaxis, cell migration, and many other biological processes. In addition, important roles for LCN2 in health and disease have been identified in Lcn2 null mice and multiple molecular pathways required for regulation of Lcn2 expression have been identified. Nevertheless, although six putative receptors for LCN2 have been proposed, there is a fundamental lack in understanding of how these cell-surface receptors transmit and amplify LCN2 to the cell. In the present review we summarize the current knowledge on LCN2 receptors and discuss inconsistencies, misinterpretations and false assumptions in the understanding of these potential LCN2 receptors.

The Expression Pattern and Clinical Significance of Lysyl Oxidase Family in Gliomas

LOX (Lysyl oxidase) family participates in the catalysis of collagen and elastin to maintain ECM homeostasis. Glioma is the most common primary brain tumor and LOX family has not been systemic studied in glioma. In this study, we found LOX family members are upregulated expressed in gliomas samples. A protein-protein interaction network (PPIN) was construct to visualize and understand the differential expression pattern, as well as functional annotation, for LOX family and their interacting proteins, which involved in collagen fibril organization and MAPK signaling pathway. Through subcellular localization distribution, the LOX family members distribute both intracellular and extracellular. All five LOX members are consistently significantly correlate with dendritic cell both in immune infiltrate of GBM and LGG. Survival analysis showed that high expression of LOX family is associated with a poor prognosis of gliomas patients. These analyses provide important clues to identify the potential biological roles for LOX family in gliomas, which might serve as diagnosis markers.

Pepsinogen/Proton Pump Co-Expression in Barrett's Esophageal Cells Induces Cancer-Associated Changes

EDUCATIONAL OBJECTIVE

At the conclusion of this presentation, participants should better understand the carcinogenic potential of pepsin and proton pump expression in Barrett's esophagus.

OBJECTIVE

Barrett's esophagus (BE) is a well-known risk factor for esophageal adenocarcinoma (EAC). Gastric H⁺ /K⁺ ATPase proton pump and pepsin expression has been demonstrated in some cases of BE; however, the contribution of local pepsin and proton pump expression to carcinogenesis is unknown. In this study, RNA sequencing was used to examine global transcriptomic changes in a BE cell line ectopically expressing pepsinogen and/or gastric H⁺ /K⁺ ATPase proton pumps.

STUDY DESIGN

In vitro translational.

METHODS

BAR-T, a human BE cell line devoid of expression of pepsinogen or proton pumps, was transduced by lentivirus-encoding pepsinogen (PGA5) and/or gastric proton pump subunits (ATP4A, ATP4B). Changes relative to the parental line were assessed by RNA sequencing.

RESULTS

Top canonical pathways associated with protein-coding genes differentially expressed in pepsinogen and/or proton pump expressing BAR-T cells included those involved in the tumor microenvironment and epithelial-mesenchymal transition. Top upstream regulators of coding transcripts included TGFB1 and ERBB2, which are associated with the pathogenesis and prognosis of BE and EAC. Top upstream regulators of noncoding transcripts included p300-CBP, I-BET-151, and CD93, which have previously described associations with EAC or carcinogenesis. The top associated disease of both coding and noncoding transcripts was cancer.

CONCLUSIONS

These data support the carcinogenic potential of pepsin and proton pump expression in BE and reveal molecular pathways affected by their expression. Further study is warranted to investigate the role of these pathways in carcinogenesis associated with BE.

LEVEL OF EVIDENCE

NA Laryngoscope, 133:59-69, 2023.

Anti-tumor effects of dual PI3K-HDAC inhibitor CUDC-907 on activation of ROS-IRE1α-JNK-mediated cytotoxic autophagy in esophageal cancer

Background

PI3K-Akt pathway activation and the expression of histone deacetylases (HDACs) are highly increased in esophageal cancer, suggesting that inhibition of such targets may be a viable therapeutic strategy. Herein, we aimed to evaluate the anti-tumor effect of CUDC-907, a dual PI3K-HDAC inhibitor, in esophageal squamous cell carcinoma (ESCC).

Methods

The anti-tumor effects of CUDC-907 in ESCC were evaluated using cell counting kit-8, flow cytometry, and western blot. mRNA-sequencing was used to explore the mechanism underlying CUDC-907 anti-tumor effects. The relations of reactive oxygen species (ROS), lipocalin 2 (LCN2), and CUDC-907 were determined by flow cytometry, rescue experiments, and western blot. The activation of the IRE1α-JNK-CHOP signal cascade was confirmed by western blot. The in vivo inhibitory effects of CUDC-907 were examined by a subcutaneous xenograft model in nude mice.

Results

CUDC-907 displayed effective inhibition in the proliferation, migration, and invasion of ESCC cells. Through an mRNA-sequencing and functional enrichment analysis, autophagy was found to be associated with cancer cells death. CUDC-907 not only inhibited the PI3K-Akt-mTOR pathways to result in autophagy, but also induced ROS accumulation to activate IRE1α-JNK-CHOP-mediated cytotoxic autophagy by downregulating LCN2 expression. Consistently, the in vivo anti-tumor effects of CUDC-907 accompanied by the downregulated expression of p-mTOR and LCN2 and upregulated expression of p-IRE1α and LC3B-II were evaluated in a xenograft mouse model.

Conclusion

Our findings suggested the clinical development and administration of CUDC-907 might act as a novel treatment strategy for ESCC. A more in-depth understanding of the anti-tumor effect of CUDC-907 in ESCC will benefit the clinically targeted treatment of ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00855-x.

Identification of Novel Choroidal Neovascularization-Related Genes Using Laplacian Heat Diffusion Algorithm

Choroidal neovascularization (CNV) is a type of eye disease that can cause vision loss. In recent years, many studies have attempted to investigate the major pathological processes and molecular pathogenic mechanisms of CNV. Because many diseases are related to genes, the genes associated with CNV need to be identified. In this study, we proposed a network-based approach for identifying novel CNV-associated genes. To execute such method, we first employed a protein-protein interaction network reported in STRING. Then, we applied a network diffusion algorithm, Laplacian heat diffusion, on this network by selecting validated CNV-related genes as the seed nodes. As a result, some novel genes that had unknown but strong relationships with validated genes were identified. Furthermore, we used a screening procedure to extract the most essential genes. Eleven latent CNV-related genes were finally obtained. Extensive analyses were performed to confirm that these genes are novel CNV-related genes.

Lipocalin 2 as a link between ageing, risk factor conditions and age-related brain diseases

Chronic (neuro)inflammation plays an important role in many age-related central nervous system (CNS) diseases, including Alzheimer's disease, Parkinson's disease and vascular dementia. Inflammation also characterizes many conditions that form a risk factor for these CNS disorders, such as physical inactivity, obesity and cardiovascular disease. Lipocalin 2 (Lcn2) is an inflammatory protein shown to be involved in different age-related CNS diseases, as well as risk factor conditions thereof. Lcn2 expression is increased in the periphery and the brain in different age-related CNS diseases and also their risk factor conditions. Experimental studies indicate that Lcn2 contributes to various neuropathophysiological processes of age-related CNS diseases, including exacerbated neuroinflammation, cell death and iron dysregulation, which may negatively impact cognitive function. We hypothesize that increased Lcn2 levels as a result of age-related risk factor conditions may sensitize the brain and increase the risk to develop age-related CNS diseases. In this review we first provide a comprehensive overview of the known functions of Lcn2, and its effects in the CNS. Subsequently, this review explores Lcn2 as a potential (neuro)inflammatory link between different risk factor conditions and the development of age-related CNS disorders. Altogether, evidence convincingly indicates Lcn2 as a key constituent in ageing and age-related brain diseases.

Network Analyses of the Differential Expression of Heat Shock Proteins in Glioma

Heat shock protein (HSP) is a family of highly conserved protein, which exists widely in various organisms and has a variety of important physiological functions. Currently, there is no systematic analysis of HSPs in human glioma. The aim of this study was to investigate the characteristics of HSPs through constructing protein-protein interaction network (PPIN) considering the expression level of HSPs in glioma. After the identification of the differentially expressed HSPs in glioma tissues, a specific PPIN was constructed and found that there were many interactions between the differentially expressed HSPs in glioma. Subcellular localization analysis shows that HSPs and their interacting proteins distribute from the cell membrane to the nucleus in a multilayer structure. By functional enrichment analysis, gene ontology analysis, and Kyoto Encyclopedia of Genes and Genomes pathway analysis, the potential function of HSPs and two meaningful enrichment pathways was revealed. In addition, nine HSPs (DNAJA4, DNAJC6, DNAJC12, HSPA6, HSP90B1, DNAJB1, DNAJB6, DNAJC10, and SERPINH1) are prognostic markers for human brain glioma. These analyses provide a full view of HSPs about their expression, biological process, as well as clinical significance in glioma.

LCN2-interacting proteins and their expression patterns in brain tumors

Lipocalin 2 (LCN2) is a member of the lipocalin family. Elevated expression of LCN2 has been observed in many human tumors, suggesting it might be a potential biomarker and/or therapeutic target in malignancies. In this study, we aimed to explore LCN2 interacting proteins through bioinformatics, as well as their biological functions. Protein-protein interaction networks (PPIN) were constructed using LCN2 and its interacting proteins as the core node. These PPINs were scale free biological networks in which LCN2 and its interacting proteins could connect or cross-talk with at least one partner protein. Both functional and KEGG pathway enrichment analyses identified the known and potential biological functions of the PPIN, such as cell migration and cancer-related pathways. Expression levels of the PPIN proteins, as well as their expression correlations, in five types of brain tumor, were analyzed and integrated into the PPIN to illustrate a dynamic change. A significant correlation was found between the survival time of glioblastoma patients and the expression level of 10 genes (LCN2, MMP9, MMP2, PDE4DIP, L2HGDH, HNRNPA1, DDX31, LOXL2, FAM60A and RNF25). Taken together, our results suggest that LCN2 and its interacting proteins are mostly differentially expressed and have a distinguishing co-expression pattern. They might promote proliferation and migration via cell migration signaling and cancer-related pathways. LCN2 and its interacting proteins might be potential biomarkers in glioblastoma.

The analyses of SRCR genes based on protein-protein interaction network in esophageal squamous cell carcinoma

The scavenger receptor cysteine-rich (SRCR) proteins, with one to several SRCR domains, play important roles in human diseases. A full view of their functions in esophageal squamous cell carcinoma (ESCC) remain unclear. Sequence alignment and phylogenetic tree for all human SRCR domains were performed. Differentially-expressed SRCR genes were identified in ESCC, followed by protein-protein interaction (PPI) network construction, topological parameters, subcellular distribution, functional enrichment and survival analyses. The variation of conserved cysteines in each SRCR domain suggested a requirement for new classification of the SRCR family. Six genes (LGALS3BP, MSR1, CD163, LOXL2, LOXL3 and LOXL4) were upregulated, and four genes (DMBT1, PRSS12, TMPRSS2 and SCARA5) were downregulated in ESCC. These 10 SRCR genes form a unique biological network. Functional enrichment analyses provided important clues to investigate the biological functions for SRCR gene network in ESCC, such as extracellular structure organization and the PI3K-Akt signaling pathway. Kaplan-Meier curves confirmed that high expression of SCARA5, LOXL2, LOXL3, LOXL4 were related to poor survival, whereas high expression of DMBTI and PRSS12 showed the opposite result. SRCR genes promote the development of ESCC through its network and could serve as potential prognostic factors and therapy targets of ESCC.

The protein-protein interaction network and clinical significance of heat-shock proteins in esophageal squamous cell carcinoma

Heat-shock proteins (HSPs), one of the evolutionarily conserved protein families, are widely found in various organisms, and play important physiological functions. Nevertheless, HSPs have not been systematically analyzed in esophageal squamous cell carcinoma (ESCC). In this study, we applied the protein-protein interaction (PPI) network methodology to explore the characteristics of HSPs, and integrate their expression in ESCC. First, differentially expressed HSPs in ESCC were identified from our previous RNA-seq data. By constructing a specific PPI network, we found differentially expressed HSPs interacted with hundreds of neighboring proteins. Subcellular localization analyses demonstrated that HSPs and their interacting proteins distributed in multiple layers, from membrane to nucleus. Functional enrichment annotation analyses revealed known and potential functions for HSPs. KEGG pathway analyses identified four significant enrichment pathways. Moreover, three HSPs (DNAJC5B, HSPA1B, and HSPH1) could serve as promising targets for prognostic prediction in ESCC, suggesting these HSPs might play a significant role in the development of ESCC. These multiple bioinformatics analyses have provided a comprehensive view of the roles of heat-shock proteins in esophageal squamous cell carcinoma.

Integrative network analyses of wilt transcriptome in chickpea reveal genotype dependent regulatory hubs in immunity and susceptibility

Host specific resistance and non-host resistance are two plant immune responses to counter pathogen invasion. Gene network organizing principles leading to quantitative differences in resistant and susceptible host during host specific resistance are poorly understood. Vascular wilt caused by root pathogen Fusarium species is complex and governed by host specific resistance in crop plants, including chickpea. Here, we temporally profiled two contrasting chickpea genotypes in disease and immune state to better understand gene expression switches in host specific resistance. Integrative gene-regulatory network elucidated tangible insight into interaction coordinators leading to pathway determination governing distinct (disease or immune) phenotypes. Global network analysis identified five major hubs with 389 co-regulated genes. Functional enrichment revealed immunome containing three subnetworks involving CTI, PTI and ETI and wilt diseasome encompassing four subnetworks highlighting pathogen perception, penetration, colonization and disease establishment. These subnetworks likely represent key components that coordinate various biological processes favouring defence or disease. Furthermore, we identified core 76 disease/immunity related genes through subcellular analysis. Our regularized network with robust statistical assessment captured known and unexpected gene interaction, candidate novel regulators as future biomarkers and first time showed system-wide quantitative architecture corresponding to genotypic characteristics in wilt landscape.

Differences in reproductive toxicology between alopecia drugs: an analysis on adverse events among female and male cases

Alopecia is a dermatological condition with limited therapeutic options. Only two drugs, finasteride and minoxidil, are approved by FDA for alopecia treatment. However, little is known about the differences in adverse effects between these two drugs. We examined the clinical reports submitted to the FDA Adverse Event Reporting System (FAERS) from 2004 to 2014. For both female and males, finasteride was found to be more associated with reproductive toxicity as compared to minoxidil. Among male alopecia cases, finasteride was significantly more concurrent with several forms of sexual dysfunction. Among female alopecia cases, finasteride was significantly more concurrent with harm to fetus and disorder of uterus. In addition, drug-gene network analysis indicated that finasteride could profoundly disturb pathways related to sex hormone signaling and oocyte maturation. These findings could provide clues for subsequent toxicological research. Taken together, this analysis suggested that finasteride could be more liable to various reproductive adverse effects. Some of these adverse effects have yet to be warned in FDA-approved drug label. This information can help improve the treatment regimen of alopecia and post-marketing regulation of drug products.

STAT1, IGF1, RAC1, and MDM2 Are Associated with Recurrence of Giant Cell Tumor of Bone

BACKGROUND

In our previous study, mouse double minute 2 homolog (MDM2), insulin-like growth factor 1 (IGF1), signal transducer and activator of transcription 1 (STAT1), and Rac family small GTPase 1 (RAC1) were correlated with the recurrence of giant cell tumor of bone (GCT). The aim of this study is to use a large cohort study to confirm the involvement of these four genes in GCT recurrence.

METHODS

The expression of these four genes was detected and compared between GCT patients with or without recurrence. The correlation between the expression of these four genes and clinical characteristics was evaluated. Protein-protein interaction (PPI) network was constructed for functional enrichment analysis.

RESULTS

It showed that the expression levels of MDM2, IGF1, STAT1, and RAC1 in GCT patients with recurrence were significantly higher than those in GCT patients without recurrence (P < 0.05). Multivariate logistic regression analysis suggested that several clinical characteristics may influence prognosis. A PPI network was constructed using the four genes as hub genes. Functional enrichment analysis showed that this network involves many important biological progress mediated by these four genes, including immune response.

CONCLUSION

MDM2, IGF1, STAT1, and RAC1 are associated with GCT recurrence, which might serve as biomarkers for GCT recurrence.

Network-Based Differential Analysis to Identify Molecular Features of Tumorigenesis for Esophageal Squamous Carcinoma

Esophageal cancer has a poor prognosis and high mortality rate across the world. The diagnosis and treatment of esophageal cancer are hindered by the limited knowledge about the pathogenesis mechanisms of esophageal cancer. Esophageal cancer has two major subtypes, squamous and adenocarcinoma. In this work, we proposed a method to select candidate biomarkers of esophageal squamous carcinoma based on the topological differential analysis between the gene–gene interaction networks for esophageal squamous carcinoma and normal cells. We established the gene–gene interaction networks for esophageal squamous carcinoma and normal based on the correlation of genes. For each gene, we firstly calculated and compared five centrality measures, which could reflect the topological property of a network. According to five centrality measures, the genes with large differences between the two networks were regarded as candidate biomarkers for esophageal squamous carcinoma. A total of 21 candidate biomarkers were identified for esophageal squamous carcinoma, and seven of them have been confirmed to be biomarkers of esophageal-12 squamous carcinoma by previous research. In addition, six genes (RBPMS2, PDK4, IGK, SBSN, IFIT3 and HSPB6) were likely to be the biomarkers of tumorigenesis for esophageal squamous carcinoma due to the fact that the biological processes in which they participate are closely related with the development of esophageal squamous carcinoma. Statistical analysis indicates that effectiveness of the detected biomarkers of esophageal squamous carcinoma. The proposed method could be extended to other complex diseases for detecting the molecular features of pathopoiesis and targets for targeted therapy.

Network analyses elucidate the role of SMYD3 in esophageal squamous cell carcinoma

SMYD3 is a member of the SET and myeloid-Nervy-DEAF-1 (MYND) domain-containing protein family of methyltransferases, which are known to play critical roles in carcinogenesis. Expression of SMYD3 is elevated in various cancers, including esophageal squamous cell carcinoma (ESCC), and is correlated with the survival time of patients with ESCC. Here, we dissect gene expression data, from a previously described KYSE150 ESCC cell line in which SMYD3 had been knocked down, by integration with the protein-protein interaction (PPI) network, to find the new potential biological roles of SMYD3 and subsequent target genes. By construction of a specific PPI network, differentially expressed genes (DEGs), following SMYD3 knockdown, were identified as interacting with thousands of neighboring proteins. Enrichment analyses from the DAVID Functional Annotation Chart found significant Gene Ontology (GO) terms associated with transcription activities, which were closely related to SMYD3 function. For example, YAP1 and GATA3 might be a target gene for SMYD3 to regulate transcription. Enrichment annotation of the total DEG PPI network by GO 'Biological Process' generated a connected functional map and found 532 significant terms, including known and potential biological roles of SMYD3 protein, such as expression regulation, signal transduction, cell cycle, cell metastasis, and invasion. Subcellular localization analyses found that DEGs and their interacting proteins were distributed in multiple layers, which might reflect the intricate biological processes at the spatial level. Our analysis of the PPI network has provided important clues for future detection of the biological roles and mechanisms, as well as the target genes of SMYD3.

Identifying gene subnetworks associated with clinical outcome in ovarian cancer using Network Based Coalition Game

The problem of identifying interacting genes that jointly are associated with a phenotype is considered. When the number of features are extremely large compared to the number of samples, there may be several subsets of features that provide acceptable levels of predictability. This is particularly true in cancer genomics, where we are interested in finding functionally related gene sets likely to jointly drive cancer phenotypes. In this paper, a novel game theoretic solution is proposed by modeling genes as players of a Coalition Game. This method discovers and develops informative gene subnetworks by integrating gene expression profiling of cancer tissues with protein-protein interaction (PPI) networks. These subnetworks are gradually developed by selective addition of candidate genes that present maximal Shapely values in coalition with subnetworks of genes. We applied the proposed algorithm to an ovarian cancer dataset (N = 201), in order to identify optimal subnetworks that can predict cancer progression risk in response to platinum-based therapy. We show improved predictive power of the proposed method when compared to state-of-the-art feature selection methods, with the added advantage of identifying potentially functional gene subnetworks that may provide insights into the mechanisms underlying cancer progression.

Network analysis reveals potential markers for pediatric adrenocortical carcinoma

Pediatric adrenocortical carcinoma (ACC) is a rare malignancy with a poor outcome. Molecular mechanisms of pediatric ACC oncogenesis and advancement are not well understood. Accurate and timely diagnosis of the disease requires identification of new markers for pediatric ACC. Differentially expressed genes (DEGs) were identified from the gene expression profile of pediatric ACC and obtained from Gene Expression Omnibus. Gene Ontology functional and pathway enrichment analysis was implemented to recognize the functions of DEGs. A protein–protein interaction (PPI) and gene–gene functional interaction (GGI) network of DEGs was constructed. Hub gene detection and enrichment analysis of functional modules were performed. Furthermore, a gene regulatory network incorporating DEGs–microRNAs–transcription factors was constructed and analyzed. A total of 431 DEGs including 228 upregulated and 203 downregulated DEGs were screened. These genes were largely involved in cell cycle, steroid biosynthesis, and p53 signaling pathways. Upregulated genes, CDK1, CCNB1, CDC20, and BUB1B, were identified as the common hubs of PPI and GGI networks. All the four common hub genes were also part of modules of the PPI network. Moreover, all the four genes were also present in the largest module of GGI network. A gene regulatory network consisting of 82 microRNAs and 100 transcription factors was also constructed. CDK1, CCNB1, CDC20, and BUB1B may serve as potential biomarker of pediatric ACC and as potential targets for therapeutic approach, although experimental studies are required to authenticate our findings.

Structural similarities of human and mammalian lipocalins, and their function in innate immunity and allergy

Owners and their domestic animals via skin shedding and secretions, mutually exchange microbiomes, potential pathogens and innate immune molecules. Among the latter especially lipocalins are multifaceted: they may have an immunomodulatory function and, furthermore, they represent one of the most important animal allergen families. The amino acid identities, as well as their structures by superposition modeling were compared among human lipocalins, hLCN1 and hLCN2, and most important animal lipocalin allergens, such as Can f 1, Can f 2 and Can f 4 from dog, Fel d 4 from cats, Bos d 5 from cow's milk, Equ c 1 from horses, and Mus m 1 from mice, all of them representing major allergens. The β-barrel fold with a central molecular pocket is similar among human and animal lipocalins. Thereby, lipocalins are able to transport a variety of biological ligands in their highly conserved calyx-like cavity, among them siderophores with the strongest known capability to complex iron (Fe(3+) ). Levels of human lipocalins are elevated in nonallergic inflammation and cancer, associated with innate immunoregulatory functions that critically depend on ligand load. Accordingly, deficient loading of lipocalin allergens establishes their capacity to induce Th2 hypersensitivity. Our similarity analysis of human and mammalian lipocalins highlights their function in innate immunity and allergy.

A powerful score-based statistical test for group difference in weighted biological networks

BACKGROUND

Complex disease is largely determined by a number of biomolecules interwoven into networks, rather than a single biomolecule. A key but inadequately addressed issue is how to test possible differences of the networks between two groups. Group-level comparison of network properties may shed light on underlying disease mechanisms and benefit the design of drug targets for complex diseases. We therefore proposed a powerful score-based statistic to detect group difference in weighted networks, which simultaneously capture the vertex changes and edge changes.

RESULTS

Simulation studies indicated that the proposed network difference measure (NetDifM) was stable and outperformed other methods existed, under various sample sizes and network topology structure. One application to real data about GWAS of leprosy successfully identified the specific gene interaction network contributing to leprosy. For additional gene expression data of ovarian cancer, two candidate subnetworks, PI3K-AKT and Notch signaling pathways, were considered and identified respectively.

CONCLUSIONS

The proposed method, accounting for the vertex changes and edge changes simultaneously, is valid and powerful to capture the group difference of biological networks.

Teeth loss, teeth brushing and esophageal carcinoma: a systematic review and meta-analysis

Esophageal carcinoma (EC) is a serious malignancy, and its epidemiologic etiology is not fully explained. We performed this review to investigate the association between teeth loss and teeth brushing and the risk of EC. A systematic search was conducted to identify all relevant studies. The Q test and I(2) statistic were used to examine between-study heterogeneity. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were considered by fixed or random effects models. Furthermore, we conducted subgroup analyses based on study design, the studies' geographic regions and case type of origin. Modified Egger linear regression test was used to estimate publication bias. Ten articles were included. Pooled analyses indicated that teeth loss was associated with an increased risk of EC for Asians (OR, 1.52; 95% CI: 1.30, 1.78), and high frequency of teeth brushing was associated with a lower incidence of EC (OR, 0.62; 95%CI: 0.43, 0.89). Subgroup analyses showed consistent results and no publication bias existed. Teeth loss and teeth brushing play potential roles in the progressing of EC. People should take care of their oral health in daily life. And large well-designed researches are needed to fully describe the association between teeth health and EC risk.

A systematic analysis of human lipocalin family and its expression in esophageal carcinoma

The lipocalin proteins (lipocalins) are a large family of small proteins characterized by low sequence similarity and highly conserved crystal structures. Lipocalins have been found to play important roles in many human diseases. For this reason, a systemic analysis of the molecular properties of human lipocalins is essential. In this study, human lipocalins were found to contain four structurally conserved regions (SCRs) and could be divided into two subgroups. A human lipocalin protein-protein interaction network (PPIN) was constructed and integrated with their expression data in esophageal carcinoma. Many lipocalins showed obvious co-expression patterns in esophageal carcinoma. Their subcellular distributions also suggested these lipocalins may transfer signals from the extracellular space to the nucleus using the pathway-like paths. These analyses also expanded our knowledge about this human ancient protein family in the background of esophageal carcinoma.

Functional analysis of the mRNA profile of neutrophil gelatinase‑associated lipocalin overexpression in esophageal squamous cell carcinoma using multiple bioinformatic tools

Neutrophil gelatinase-associated lipocalin (NGAL) is a member of the lipocalin superfamily; dysregulated expression of NGAL has been observed in several benign and malignant diseases. In the present study, differentially expressed genes, in comparison with those of control cells, in the mRNA expression profile of EC109 esophageal squamous cell carcinoma (ESCC) cells following NGAL overexpression were analyzed by multiple bioinformatic tools for a comprehensive understanding. A total of 29 gene ontology (GO) terms associated with immune function, chromatin structure and gene transcription were identified among the differentially expressed genes (DEGs) in NGAL overexpressing cells. In addition to the detected GO categories, the results from the functional annotation chart revealed that the differentially expressed genes were also associated with 101 functional annotation category terms. A total of 59 subpathways associated locally with the differentially expressed genes were identified by subpathway analysis, a markedly greater total that detected by traditional pathway enrichment analysis only. Promoter analysis indicated that the potential transcription factors Snail, deltaEF1, Mycn, Arnt, MNB1A, PBF, E74A, Ubx, SPI1 and GATA2 were unique to the downregulated DEG promoters, while bZIP910, ZNF42 and SOX9 were unique for the upregulated DEG promoters. In conclusion, the understanding of the role of NGAL overexpression in ESCC has been improved through the present bioinformatic analysis.