Expression of desmogleins 1-3 and their clinical impacts on human lung cancer

Desmoglein-2 as a cancer modulator: friend or foe?

Desmoglein-2 (DSG2) is a calcium-binding single pass transmembrane glycoprotein and a member of the large cadherin family. Until recently, DSG2 was thought to only function as a cell adhesion protein embedded within desmosome junctions designed to enable cells to better tolerate mechanical stress. However, additional roles for DSG2 outside of desmosomes are continuing to emerge, particularly in cancer. Herein, we review the current literature on DSG2 in cancer and detail its impact on biological functions such as cell adhesion, proliferation, migration, invasion, intracellular signaling, extracellular vesicle release and vasculogenic mimicry. An increased understanding of the diverse repertoire of the biological functions of DSG2 holds promise to exploit this cell surface protein as a potential prognostic biomarker and/or target for better patient outcomes. This review explores the canonical and non-canonical functions of DSG2, as well as the context-dependent impacts of DSG2 in the realm of cancer.

Diagnosis of acute myeloid leukaemia on microarray gene expression data using categorical gradient boosted trees

We define an iterative method for dimensionality reduction using categorical gradient boosted trees and Shapley values and created four machine learning models which potentially could be used as diagnostic tests for acute myeloid leukaemia (AML). For the final Catboost model we use a dataset of 2177 individuals using as features 16 probe sets and the age in order to classify if someone has AML or is healthy. The dataset is multicentric and consists of data from 27 organizations, 25 cities, 15 countries and 4 continents. The performance of our last model is specificity: 0.9909, sensitivity: 0.9985, F1-score: 0.9976 and its ROC-AUC: 0.9962 using ten fold cross validation. On an inference dataset the perormance is: specificity: 0.9909, sensitivity: 0.9969, F1-score: 0.9969 and its ROC-AUC: 0.9939. To the best of our knowledge the performance of our model is the best one in the literature, as regards the diagnosis of AML using similar or not data. Moreover, there has not been any bibliographic reference which associates AML or any other type of cancer with the 16 probe sets we used as features in our final model.

Desmoglein-2 and COVID-19 complications: insights into its role as a biomarker, pathogenesis and clinical implications

Desmoglein-2 (DSG2) has emerged as a potential biomarker for coronavirus disease 2019 (COVID-19) complications, particularly cardiac and cardiovascular involvement. The expression of DSG2 in lung tissues has been detected at elevated levels, and circulating DSG2 levels correlate with COVID-19 severity. DSG2 may contribute to myocardial injury, cardiac dysfunction and vascular endothelial dysfunction in COVID-19. Monitoring DSG2 levels could aid in risk stratification, early detection and prognostication of COVID-19 complications. However, further research is required to validate DSG2 as a biomarker. Such research will aim to elucidate its precise role in pathogenesis, establishing standardized assays for its measurement and possibly identifying therapeutic targets.

Telomere-related prognostic biomarkers for survival assessments in pancreatic cancer

Human telomeres are linked to genetic instability and a higher risk of developing cancer. Therefore, to improve the dismal prognosis of pancreatic cancer patients, a thorough investigation of the association between telomere-related genes and pancreatic cancer is required. Combat from the R package "SVA" was performed to correct the batch effects between the TCGA-PAAD and GTEx datasets. After differentially expressed genes (DEGs) were assessed, we constructed a prognostic risk model through univariate Cox regression, LASSO-Cox regression, and multivariate Cox regression analysis. Data from the ICGC, GSE62452, GSE71729, and GSE78229 cohorts were used as test cohorts for validating the prognostic signature. The major impact of the signature on the tumor microenvironment and its response to immune checkpoint drugs was also evaluated. Finally, PAAD tissue microarrays were fabricated and immunohistochemistry was performed to explore the expression of this signature in clinical samples. After calculating 502 telomere-associated DEGs, we constructed a three-gene prognostic signature (DSG2, LDHA, and RACGAP1) that can be effectively applied to the prognostic classification of pancreatic cancer patients in multiple datasets, including TCGA, ICGC, GSE62452, GSE71729, and GSE78229 cohorts. In addition, we have screened a variety of tumor-sensitive drugs targeting this signature. Finally, we also found that protein levels of DSG2, LDHA, and RACGAP1 were upregulated in pancreatic cancer tissues compared to normal tissues by immunohistochemistry analysis. We established and validated a telomere gene-related prognostic signature for pancreatic cancer and confirmed the upregulation of DSG2, LDHA, and RACGAP1 expression in clinical samples, which may provide new ideas for individualized immunotherapy.

An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification

Non-Small Cell Lung Cancer (NSCLC) exhibits intrinsic heterogeneity at the molecular level that aids in distinguishing between its two prominent subtypes - Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). This paper proposes a novel explainable AI (XAI)-based deep learning framework to discover a small set of NSCLC biomarkers. The proposed framework comprises three modules - an autoencoder to shrink the input feature space, a feed-forward neural network to classify NSCLC instances into LUAD and LUSC, and a biomarker discovery module that leverages the combined network comprising the autoencoder and the feed-forward neural network. In the biomarker discovery module, XAI methods uncovered a set of 52 relevant biomarkers for NSCLC subtype classification. To evaluate the classification performance of the discovered biomarkers, multiple machine-learning models are constructed using these biomarkers. Using 10-Fold cross-validation, Multilayer Perceptron achieved an accuracy of 95.74% (±1.27) at 95% confidence interval. Further, using Drug-Gene Interaction Database, we observe that 14 of the discovered biomarkers are druggable. In addition, 28 biomarkers aid the prediction of the survivability of the patients. Out of 52 discovered biomarkers, we find that 45 biomarkers have been reported in previous studies on distinguishing between the two NSCLC subtypes. To the best of our knowledge, the remaining seven biomarkers have not yet been reported for NSCLC subtyping and could be further explored for their contribution to targeted therapy of lung cancer.

Up-regulation of Dsg2 confered stem cells with malignancy through wnt/β-catenin signaling pathway

In the previous study, we originally developed cancer stem cells (CSCs) models from mouse induced pluripotent stem cells (miPSCs) by culturing miPSCs in the conditioned medium of cancer cell lines, which mimiced as carcinoma microenvironment. However, the molecular mechanism of conversion in detail remains to be uncovered. Microarray analysis of the CSCs models in this study revealed Dsg2, one of the members of the desmosomal cadherin family, was up-regulated when compared with the original miPSCs. Moreover, the expression of key factors in Wnt/β-catenin signaling pathway were also found up-regulated in one of the CSCs models, named miPS-LLCcm. An autocrine loop was implied between Dsg2 and Wnt/β-catenin signaling pathway when miPSCs were treated with Wnt/β-catenin signaling pathway activators, Wnt3a and CHIR99021, and when the CSCs model were treated with inhibitors, IWR-1 and IWP-2. Furthermore, the ability of proliferation and self-renewal in the CSCs model was markedly decreased in vitro and in vivo when Dsg2 gene was knocked down by shRNA. Our results showed that the Wnt/β-catenin signaling pathway is activated by the up-regulation of Dsg2 expresssion during the conversion of miPSCs into CSCs implying a potential mechanism of the tranformation of stem cells into malignant phenotype.

Filaggrin and cytokines in respiratory samples of preterm infants at risk for respiratory viral infection

Respiratory viral infections (RVIs) are frequent in preterm infants possibly inducing long-term impact on respiratory morbidity. Immune response and respiratory barriers are key defense elements against viral insults in premature infants admitted to Neonatal Intensive Care Units (NICUs). Our main goals were to describe the local immune response in respiratory secretions of preterm infants with RVIs during NICU admission and to evaluate the expression and synthesis of lung barrier regulators, both in respiratory samples and in vitro models. Samples from preterm infants that went on to develop RVIs had lower filaggrin gene and protein levels at a cellular level were compared to never-infected neonates (controls). Filaggrin, MIP-1α/CCL3 and MCP-1 levels were higher in pre-infection supernatants compared to controls. Filaggrin, HIF-1α, VEGF, RANTES/CCL5, IL-17A, IL-1β, MIP-1α and MIP-1β/CCL5 levels were higher during and after infection. ROC curve and logistic regression analysis shows that these molecules could be used as infection risk biomarkers. Small airway epithelial cells stimulated by poly:IC presented reduced filaggrin gene expression and increased levels in supernatant. We conclude that filaggrin gene and protein dysregulation is a risk factor of RVI in newborns admitted at the NICU.

Comparative proteomic analysis of exhaled breath condensate between lung adenocarcinoma and CT-detected benign pulmonary nodule patients

BACKGROUND

Lung cancer is the leading cause of cancer mortality worldwide. The collection of exhaled breath condensate (EBC) is a non-invasive method that may have enormous potential as a biomarker for the early detection of lung cancer.

OBJECTIVE

To investigate the proteomic differences of EBC between lung cancer and CT-detected benign nodule patients, and determine whether these proteins could be potential biomarkers.

METHODS

Proteomic analysis was performed on individual samples from 10 lung cancer patients and 10 CT-detected benign nodule patients using data-independent acquisition (DIA) mass spectrometry.

RESULTS

A total of 1,254 proteins were identified, and 21 proteins were differentially expressed in the lung adenocarcinoma group compared to the benign nodule group (p< 0.05). The GO analysis showed that most of these proteins were involved in neutrophil-related biological processes, and the KEGG analysis showed these proteins were mostly annotated to pyruvate and propanoate metabolism. Through protein-protein interactions (PPIs) analysis, ME1 and LDHB contributed most to the interaction-network of these proteins.

CONCLUSION

Significantly differentially expressed proteins were detected between lung cancer and the CT-detected benign nodule group from EBC samples, and these proteins might serve as potential novel biomarkers of EBC for early lung cancer detection.

DSG2 expression is low in colon cancer and correlates with poor survival

Background

Desmoglein2 (DSG2) is a transmembrane protein that helps regulate intercellular connections and contributes to desmosome assembly. Desmosome are associated with cell adhesion junctions, which play an important role in cancer progression specially cancer cell migration and invasion. However, DSG2 expression in colon cancer (CC) and its association with CC patients’ overall survival (OS) are still unclear.

Methods

We collected 587 CC samples, 41 colitis tissues and 114 pericarcinomatous tissues, as well as corresponding clinicopathological data about the patients who contributed them. All samples were tested immunohistochemically in tissue microarrays. Kaplan–Meier method was used for calculating patient survival. Univariate and multivariate analyses was used for investigating DGS2 link with CC patient’s clinicopathological factors. Bioinformatics analysis was also used in study.

Results

The results showed that DSG2 expression was lower in CC tissues than in pericarcinomatous tissues (P < 0.001). DSG2 expression was associated with differentiation (P = 0.033), lymph node metastasis (P = 0.045), distant metastasis (P = 0.006) and AJCC stage (P < 0.001). Univariate analysis indicated that poor OS in patients with CC was associated with low DSG2 expression (P < 0.001), tumor size (P < 0.001), lymph node metastasis (P < 0.001), distant metastasis (P < 0.001), AJCC stage (P < 0.001) and venous invasion (P < 0.001). In multivariate analysis, low DSG2 expression (P < 0.001), distant metastasis (P < 0.001), AJCC stage (P = 0.002), venous invasion (P < 0.001) were independent prognostic factors for CC patients. Bioinformatics analysis indicated that low DSG2 expression affects protein activation, regulates the P53-related pathway in CC, and activates the EGFR pathway.

Conclusions

The results suggest that low DSG2 expression is associated with poor survival for CC patients. DSG2 could be a prognostic biomarker for CC.

Co-Expression of Coxsackievirus/Adenovirus Receptors and Desmoglein 2 in Lung Adenocarcinoma: A Comprehensive Analysis of Bioinformatics and Tissue Microarrays

Introduction: Coxsackievirus/adenovirus receptors (CARs) and desmoglein-2 (DSG2) are similar molecules to adenovirus-based vectors in the cell membrane. They have been found to be associated with lung epithelial cell tumorigenesis and can be useful markers in predicting survival outcome in lung adenocarcinoma (LUAD). Methods: A gene ontology enrichment analysis disclosed that DSG2 was highly correlated with CAR. Survival analysis was then performed on 262 samples from the Cancer Genome Atlas, forming “Stage 1A” or “Stage 1B”. We therefore analyzed a tissue microarray (TMA) comprised of 108 lung samples and an immunohistochemical assay. Computer counting software was used to calculate the H-score of the immune intensity. Cox regression and Kaplan–Meier analyses were used to determine the prognostic value. Results: CAR and DSG2 genes are highly co-expressed in early stage LUAD and associated with significantly poorer survival (p = 0.0046). TMA also showed that CAR/DSG2 expressions were altered in lung cancer tissue. CAR in the TMA was correlated with proliferation, apoptosis, and epithelial–mesenchymal transition (EMT), while DSG2 was associated with proliferation only. The Kaplan–Meier survival analysis revealed that CAR, DSG2, or a co-expression of CAR/DSG2 was associated with poorer overall survival. Conclusions: The co-expression of CAR/DSG2 predicted a worse overall survival in LUAD. CAR combined with DSG2 expression can predict prognosis.

Dysregulation of Key Proteins Associated with Sperm Motility and Fertility Potential in Cancer Patients

Cancer has adverse effects on male reproductive health. Conventional semen analysis does not explain the molecular changes in the spermatozoa of cancer patients. Currently, proteomics is being widely used to identify the fertility-associated molecular pathways affected in spermatozoa. The objective of this study was to evaluate the sperm proteome of patients with various types of cancer. Cryopreserved semen samples from patients (testicular cancer, n = 40; Hodgkin’s disease, n = 32; lymphoma, n = 20; leukemia, n = 17) before starting therapy were used for proteomic analysis, while samples from fertile donors (n = 19) were included as controls. The proteomic profiling of sperm was carried out by liquid chromatography-tandem mass spectrometry, and differentially expressed proteins involved in the reproductive processes were validated by Western blotting. Bioinformatic analysis revealed that proteins associated with mitochondrial dysfunction, oxidative phosphorylation, and Sirtuin signaling pathways were dysregulated in cancer patients, while oxidative phosphorylation and tricarboxylic acid cycle were predicted to be deactivated. Furthermore, the analysis revealed dysregulation of key proteins associated with sperm fertility potential and motility (NADH:Ubiquinone oxidoreductase core subunit S1, superoxide dismutase 1, SERPINA5, and cytochrome b-c1 complex subunit 2) in the cancer group, which were further validated by Western blot. Dysfunctional molecular mechanisms essential for fertility in cancer patients prior to therapy highlight the potential impact of cancer phenotype on male fertility.

Negative Expression of DSG1 and DSG2, as Prognostic Biomarkers, Impacts on the Overall Survival in Patients with Extrahepatic Cholangiocarcinoma

Aims

To evaluate the expression of DSG1 and DSG2 and investigate their clinicopathological significance in EHCC.

Method

The protein expression of DSG1 and DSG2 was measured by EnVision immunohistochemistry in 15 normal biliary tract tissues, 10 biliary tract adenoma tissues, 30 peritumoral tissues, and 100 EHCC tumour tissues.

Result

The expression of the DSG1 and DSG2 proteins was significantly lower in EHCC tumour tissues than in normal biliary tract tissues, biliary tract adenoma, and peritumoral tissues (P < 0.05). Adenoma and peritumoral tissues with negative DSG1 and/or DSG2 protein expression exhibited atypical hyperplasia. DSG1 expression was positively correlated with DSG2 expression in EHCC (P < 0.01). In patients with good differentiation, no invasion, no lymph metastasis, TNM I + II stage, and radical surgery, the positive expression of DSG1 and DSG2 proteins was higher (P < 0.05). In comparison to patients with negative DSG1 and/or DSG2 expression, the average overall survival time of those with positive expression was significantly longer (P = 0.000). Cox multivariate analysis revealed that negative DSG1 and DSG2 expressions were independent of poor prognosis factors in EHCC patients. The AUC calculated for DSG1 was 0.681 (95% confidence interval: 0.594–0.768) and that for DSG2 was 0.645 (95% confidence interval: 0.555–0.734), while that for DSG1 and DSG2 was 0.772 (95% confidence interval: 0.609-0.936).

Conclusions

Negative protein expression of DSG1 and DSG2 is closely related to the pathogenesis, severe clinicopathological characteristics, aggressive biological behaviours, and dismal prognosis in EHCC.

DSG2 expression is correlated with poor prognosis and promotes early-stage cervical cancer

Background

The pathogenesis and developmental mechanism of early-stage (FIGO 2009 IA2-IIA2) cervical cancer (CC) remain unclear. Seeking novel molecular biomarkers based on The Cancer Genome Atlas (TCGA) will facilitate the understanding of CC pathogenesis and help evaluate early-stage CC prognosis.

Methods

To identify prognosis-related genes in early-stage CC, we analyzed TCGA mRNA-seq data and clinical data by univariate Cox and Kaplan-Meier plotter analyses. Differential expression analysis identified upregulated genes in early-stage CC. Combined with the genes correlated with unfavorable prognosis, we selected desmoglein-2 (DSG2) for further investigation. To detect DSG2 expression in early-stage CC, we used immunohistochemistry (IHC), quantitative real-time PCR (qRT-PCR) and western blotting. The relationship between the expression of DSG2 and clinical features was analyzed by the Chi square test. Cox analysis was applied to assess the relationship between CC overall survival (OS) and risk factors. The correlations between DSG2 expression and CC cell line proliferation and migration were investigated with Cell Counting Kit-8 (CCK-8) and migration assays.

Results

There were 416 prognosis-related genes in early-stage CC. DSG2, matrix metallopeptidase 1 (MMP1), carbonic anhydrase IX (CA9), homeobox A1 (HOXA1), and serine protease inhibitor B3 (SERPINB3) were upregulated in early-stage CC compared with adjacent noncancerous tissue (ANT) and correlated with unfavorable prognosis. Among them, DSG2 was most significantly correlated with patient survival. Coexpression analysis indicated that DSG2 was probably involved in cell division, positive regulation of transferase activity, positive regulation of cell migration, EGFR upregulation pathway and regulation of lymphangiogenesis. IHC, qRT-PCR and western blotting showed that DSG2 expression was higher in CC than in normal tissue. Significant correlations were identified between DSG2 expression and several aggressive clinical features, including pelvic lymph node metastasis (PLNM). Multivariate Cox analysis showed that DSG2 and PLNM were independent prognostic factors for OS. DSG2 knockdown inhibited CC cell proliferation and migration.

Conclusions

DSG2 is a biomarker that promotes tumor proliferation and metastasis and is correlated with poor prognosis in early-stage CC.

Desmoglein-2 modulates tumor progression and osimertinib drug resistance through the EGFR/Src/PAK1 pathway in lung adenocarcinoma

Desmoglein-2 (DSG2), a member of the cadherin superfamily, has been implicated in cell-cell adhesion and tumorigenesis. Here, we demonstrate that high DSG2 expression in both lung adenocarcinoma (LUAD) cell lines and tissues is associated with poor prognosis in LUAD patients. Notably, DSG2 overexpression promoted cell proliferation and migration, and increased resistance to the EGFR tyrosine kinase inhibitor osimertinib, whereas DSG2 silencing could reverse these results. Moreover, direct interaction between DSG2 and EGFR in the cell membrane stimulated EGFR signaling to promote tumorigenesis, and loss of DSG2 resulted in EGFR translocation into the cytoplasm. In addition, DSG2 was required for EGFR binding to Src; consequently, DSG2 silencing inhibited tumor cell malignancy via suppression of the EGFR-Src-Rac1-PAK1 signaling pathway. Consistent with these findings, a nude mouse xenograft model using H1975 cells demonstrated that DSG2 promoted LUAD cell growth in vivo and increased osimertinib resistance. Collectively, these observations are the first to elucidate a unique role for DSG2 in the development and progression of lung adenocarcinoma via EGFR signaling.

Identification of Key Genes in Association with Progression and Prognosis in Cervical Squamous Cell Carcinoma

Cervical cancer remains a primary cause of female death in developing countries, but its prognosis can be greatly improved if patients are diagnosed earlier. In the present study, we screened the common differentially expressed genes (DEGs) of cervical squamous cell carcinoma (CESC) from dataset GSE7803, Gene Expression Omnibus, and The Cancer Genome Atlas databases. An integrated bioinformatics analysis was performed based on these DEGs for their enrichment in functions and pathways, interaction network, prognostic signature, and candidate molecular drugs. As a result, 164 (114 upregulated and 47 downregulated) DEGs of CESC were identified for further investigation. We then conducted the gene ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes Pathway analyses to reveal the underlying functions and pathways of these DEGs. In the protein-protein interaction network, hub module and hub genes were identified. Five genes of significant prognostic value-DSG2, ITM2A, CENPM, RIBC2, and MEIS2-were identified by prognostic signature analysis and used to construct a risk linear model. Further validation and investigation suggested DSG2 might be a key gene in CESC prognosis. We then identified two candidate small molecules (trichostatin A and tanespimycin) against CESC. Further validation and exploration of these hub genes are warranted for future prospect in clinical applications.

Upregulation of desmoglein 2 and its clinical value in lung adenocarcinoma: a comprehensive analysis by multiple bioinformatics methods

Background

Desmoglein-2 (DSG2), a desmosomal adhesion molecule, is found to be closely related to tumorigenesis in recent years. However, the clinical value of DSG2 in lung adenocarcinoma remains unclear.

Methods

Real-time reverse transcription-quantitative polymerase chain reaction (qRT-PCR) was utilized to detect the expression of DSG2 in 40 paired lung adenocarcinoma tissues and corresponding non-cancerous tissues. Data from The Cancer Genome Atlas (TCGA) and Oncomine datasets were also downloaded and analyzed. The correlation between DSG2 and clinicopathological features was investigated. The expression of DSG2 protein by immunohistochemical was also detected from tissue microarray and the Human Protein Atlas database. Integrated meta-analysis combining the three sources (qRT-PCR data, TCGA data and Oncomine datasets) was performed to evaluate the clinical value of DSG2. Univariate and multivariate Cox regression analyses were used to explore the prognostic value of DSG2. Then, co-expressed genes were calculated by Pearson correlation analysis. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to investigate the underlying molecular mechanism. The expression level in lung adenocarcinoma and prognostic significance of the top ten co-expressed genes were searched from Gene Expression Profiling Interactive Analysis (GEPIA) online database.

Results

DSG2 was highly expressed in lung adenocarcinoma tissues based on qRT-PCR, TCGA and Oncomine datasets. The protein expression of DSG2 was also higher in lung adenocarcinoma. According to qRT-PCR and TCGA, high DSG2 expression was positively associated with tumor size (p = 0.027, p = 0.001), lymph node metastasis (p = 0.014, p < 0.001) and TNM stage (p = 0.023, p < 0.001). The combined standard mean difference values of DSG2 expression based on the three sources were 1.30 (95% confidence interval (CI): 1.08–1.52) using random effect model. The sensitivity and specificity were 0.73 (95% CI [0.69–0.76]) and 0.96 (95% CI [0.89–0.98]). The area under the curve based on summarized receiver operating characteristic (SROC) curve was 0.79 (95% CI [0.75–0.82]). Survival analysis revealed that high DSG2 expression was associated with a short overall survival (hazard ratio [HR] = 1.638; 95% CI [1.214–2.209], p = 0.001) and poor progression-free survival (HR = 1.475; 95% CI [1.102–1.974], p < 0.001). A total of 215 co-expressed genes were identified. According to GO and KEGG analyses, these co-expressed genes may be involved in “cell division”, “cytosol”, “ATP binding” and “cell cycle”. Based on GEPIA database, seven of the top ten co-expressed genes were highly expressed in lung adenocarcinoma (DSC2, SLC2A1, ARNTL2, ERO1L, ECT2, ANLN and LAMC2). High expression of these genes had shorter overall survival.

Conclusions

The expression of DSG2 is related to the tumor size, lymph node metastasis and TNM stage. Also, DSG2 predicts poor prognosis in lung adenocarcinoma.

A Chinese Prescription Yu-Ping-Feng-San Administered in Remission Restores Bronchial Epithelial Barrier to Inhibit House Dust Mite-Induced Asthma Recurrence

Clinically, the treatments against asthma like β₂ agonist focus on controlling the symptoms rather than inhibiting recurrence radically. This study aims to evaluate the efficacy and mechanism of a potent Chinese prescription Yu-Ping-Feng-San (YPFS) against asthma recurrence. We here established an optimized house dust mite (HDM)-induced asthma recurrence mice model with typical asthmatic responses such as significantly augmented airway hyperresponsiveness (AHR), elevated serum IgE, pulmonary type 2 cytokines IL-5 and IL-13 levels, pathological changes including thickening bronchial wall, inflammatory infiltration of lung tissue, etc. Moreover, all typical asthmatic pathological features were prominently alleviated by YPFS applied during remission phase ahead of second elicitation, which was even more effective than three different types of medications dexamethasone, montelukast and salbutamol, which were commonly applied in clinical practice, administered during recurrence phase. Besides, we found that desmoglein 1 (DSG1) remained deficient when asthmatic responses regressed whereas tight junction (TJ) claudin 1 (CLDN1) or adherin junction (AJ) E-cadherin restored spontaneously. In vitro, DSG1 interference resulted in increased thymic stromal lymphopoietin (TSLP) secretion, and epithelial barrier compromise evidenced by significantly elevated transepithelial electrical resistance (TEER) and increased 4-kDa FITC-dextran influx. YPFS could downregulate TSLP production and restore HDM-induced DSG1 deficiency and barrier destruction, which was further reversed by shDSG1. Collectively, administration of YPFS in remission prominently alleviated HDM-induced asthma relapse by restoring DSG1 and decreasing TSLP overexpression, which might be the key factors contributing to chronic asthma relapse. Our data not only demonstrated the pivotal role of DSG1 in asthma pathogenesis, but also provided a novel and potent therapeutic strategy against chronic asthma.

Altered Cell-Cycle Control, Inflammation, and Adhesion in High-Risk Persistent Bronchial Dysplasia

Persistent bronchial dysplasia is associated with increased risk of developing invasive squamous cell carcinoma (SCC) of the lung. In this study, we hypothesized that differences in gene expression profiles between persistent and regressive bronchial dysplasia would identify cellular processes that underlie progression to SCC. RNA expression arrays comparing baseline biopsies from 32 bronchial sites that persisted/progressed to 31 regressive sites showed 395 differentially expressed genes [ANOVA, FDR ≤ 0.05). Thirty-one pathways showed significantly altered activity between the two groups, many of which were associated with cell-cycle control and proliferation, inflammation, or epithelial differentiation/cell-cell adhesion. Cultured persistent bronchial dysplasia cells exhibited increased expression of Polo-like kinase 1 (PLK1), which was associated with multiple cell-cycle pathways. Treatment with PLK1 inhibitor induced apoptosis and G2-M arrest and decreased proliferation compared with untreated cells; these effects were not seen in normal or regressive bronchial dysplasia cultures. Inflammatory pathway activity was decreased in persistent bronchial dysplasia, and the presence of an inflammatory infiltrate was more common in regressive bronchial dysplasia. Regressive bronchial dysplasia was also associated with trends toward overall increases in macrophages and T lymphocytes and altered polarization of these inflammatory cell subsets. Increased desmoglein 3 and plakoglobin expression was associated with higher grade and persistence of bronchial dysplasia. These results identify alterations in the persistent subset of bronchial dysplasia that are associated with high risk for progression to invasive SCC. These alterations may serve as strong markers of risk and as effective targets for lung cancer prevention.Significance: Gene expression profiling of high-risk persistent bronchial dysplasia reveals changes in cell-cycle control, inflammatory activity, and epithelial differentiation/cell-cell adhesion that may underlie progression to invasive SCC. Cancer Res; 78(17); 4971-83. ©2018 AACR.

SOX30 is a key regulator of desmosomal gene suppressing tumor growth and metastasis in lung adenocarcinoma

Background

The expression of desmosomal genes in lung adenocarcinoma and lung squamous carcinoma is different. However, the regulatory mechanism of desmosomal gene expression in lung adenocarcinoma and lung squamous carcinoma remains unknown.

Methods

The correlation between expression of desmosomal gene expression and SOX30 expression were analyzed by bioinformatics. The expression of SOX30, DSP, JUP and DSC3 were detected in lung cancer cell lines, lung tissues of mice and patients’ tissues by qPCR, WB, Immunofluorescence and Immunohistochemistry. A chromatin Immunoprecipitation assay was used to investigate the mechanisms of the SOX30 regulation on desmosomal gene expression. In vitro proliferation, migration and invasion assays, and an in vivo nude mice model were utilized to assess the important role of desmosomal genes on SOX30-induced tumor suppression. A WB assay and TOP/FOP flash reporter assay was used to investigate the downstream pathway regulated by the SOX30-desmosomal gene axis. A chemical carcinogenic model of SOX30-knockout mice was generated to confirm the role of the SOX30-desmosomal gene axis in tumorigenesis.

Results

The expression of desmosomal genes were upregulated by SOX30 in lung adenocarcinoma but not in lung squamous carcinoma. Further mechanism studies showed that SOX30 acts as a key transcriptional regulator of desmosomal genes by directly binding to the ACAAT motif of desmosomal genes promoter region and activating their transcription in lung adenocarcinoma. Knockdown of the expression of related desmosomal genes by miRNA significantly attenuated the inhibitory effect of SOX30 on cell proliferation, migration and invasion in vitro and on tumor growth and metastasis in vivo. In addition, knockout of SOX30 promotes lung tumor development and loss the inhibition of desmosomal genes on downstream Wnt and ERK signal in urethane-induced lung carcinogenesis in SOX30-knockout mice.

Conclusions

Overall, these findings demonstrate for the first time that SOX30 acts as a master switch of desmosomal genes, inhibits lung adenocarcinoma cell proliferation, migration and invasion by activating the transcription of desmosomal genes. This study provides novel insights on the regulatory mechanism of desmosomal genes in lung adenocarcinoma.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0778-3) contains supplementary material, which is available to authorized users.

Pinin facilitated proliferation and metastasis of colorectal cancer through activating EGFR/ERK signaling pathway

Increasing emphasis has been put on the influence of desmosome related proteins on progress of colorectal cancer (CRC). Pinin (PNN) is a desmosome-associated molecule that has been reported its overexpression could increase desmoglein 2 (DSG2) and E-cadherin (E-ca) levels. However, it was documented that DSG2 and E-ca had opposite functions in CRC. Thus, we attempted to elucidate function and mechanism of PNN in CRC. Herein, we revealed that overexpression of PNN was significantly correlated with the aggressive characteristics and indicated poor overall survival of CRC patients. In addition, the proliferation, invasion in vitro, and tumorigenic growth, metastasis in vivo were also promoted by the up-regulation of PNN. It was also verified that up-regulation of PNN increased the expression of DSG2 and activated the EGFR/ERK signaling pathway. Our findings suggested that PNN, as a valuable marker of prognosis, has important influence on the progression of CRC.

Cell-surface marker discovery for lung cancer

Lung cancer is the leading cause of cancer deaths in the United States. Novel lung cancer targeted therapeutic and molecular imaging agents are needed to improve outcomes and enable personalized care. Since these agents typically cannot cross the plasma membrane while carrying cytotoxic payload or imaging contrast, discovery of cell-surface targets is a necessary initial step. Herein, we report the discovery and characterization of lung cancer cell-surface markers for use in development of targeted agents. To identify putative cell-surface markers, existing microarray gene expression data from patient specimens were analyzed to select markers with differential expression in lung cancer compared to normal lung. Greater than 200 putative cell-surface markers were identified as being overexpressed in lung cancers. Ten cell-surface markers (CA9, CA12, CXorf61, DSG3, FAT2, GPR87, KISS1R, LYPD3, SLC7A11 and TMPRSS4) were selected based on differential mRNA expression in lung tumors vs. non-neoplastic lung samples and other normal tissues, and other considerations involving known biology and targeting moieties. Protein expression was confirmed by immunohistochemistry (IHC) staining and scoring of patient tumor and normal tissue samples. As further validation, marker expression was determined in lung cancer cell lines using microarray data and Kaplan–Meier survival analyses were performed for each of the markers using patient clinical data. High expression for six of the markers (CA9, CA12, CXorf61, GPR87, LYPD3, and SLC7A11) was significantly associated with worse survival. These markers should be useful for the development of novel targeted imaging probes or therapeutics for use in personalized care of lung cancer patients.

Desmoglein-2 is overexpressed in non-small cell lung cancer tissues and its knockdown suppresses NSCLC growth by regulation of p27 and CDK2

PURPOSE

Desmoglein-2 (Dsg2) is a cell adhesion protein of the cadherin superfamily. Altered Dsg2 expression is associated with tumorigenesis. This study determined Dsg2 expression in non-small cell lung cancer (NSCLC) tissue specimens for association with clinicopathological and survival data and then assessed the effect of Dsg2 knockdown on regulation of NSCLC cell malignant behaviors in vitro and in nude mouse xenografts.

METHODS

qRT-PCR and Western blot were used to detect Dsg2 expression in 28 paired NSCLC and normal tissue samples. Immunohistochemistry was used to detect Dsg2 expression in 70 cases of paraffin-embedded NSCLC tissues. NSCLC A549, H1703, and H1299 cells were cultured with Dsg2 knockdown performed using Dsg2 siRNA. Cell viability, cell cycle, apoptosis, and colony formation were assessed. siRNA-transfected A549 cells were also used to generate tumor xenografts in nude mice.

RESULTS

Both Dsg2 mRNA and protein were highly expressed in NSCLC tissues and associated with NSCLC size, but not with overall survival of patients. Moreover, knockdown of Dsg2 expression reduced NSCLC cell proliferation and arrested them at the G1 phase of the cell cycle, but did not significantly affect NSCLC cell apoptosis. Dsg2 knockdown downregulated cyclin-dependent kinase 2 expression and upregulated p27 expression. Nude mouse xenograft assays showed that Dsg2 knockdown inhibited NSCLC xenograft growth in vivo.

CONCLUSION

This study revealed the importance of Dsg2 in suppression of NSCLC development and progression. Further studies will explore whether restoration of Dsg2 expression is a novel strategy in control of NSCLC.

Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma

BACKGROUND

Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy.

METHODS

Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining.

RESULTS

A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers.

CONCLUSIONS

The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data.