Systematic expression analysis of the CELSR family reveals the importance of CELSR3 in human lung adenocarcinoma

Flamingo participates in multiple models of cell competition

The growth and survival of cells with different fitness, such as those with a proliferative advantage or a deleterious mutation, is controlled through cell competition. During development, cell competition enables healthy cells to eliminate less fit cells that could jeopardize tissue integrity, and facilitates the elimination of pre-malignant cells by healthy cells as a surveillance mechanism to prevent oncogenesis. Malignant cells also benefit from cell competition to promote their expansion. Despite its ubiquitous presence, the mechanisms governing cell competition, particularly those common to developmental competition and tumorigenesis, are poorly understood. Here, we show that in Drosophila, the planar cell polarity (PCP) protein Flamingo (Fmi) is required by winners to maintain their status during cell competition in malignant tumors to overtake healthy tissue, in early pre-malignant cells when they overproliferate among wildtype cells, in healthy cells when they later eliminate pre-malignant cells, and by supercompetitors as they compete to occupy excessive territory within wildtype tissues. "Would-be" winners that lack Fmi are unable to over-proliferate, and instead become losers. We demonstrate that the role of Fmi in cell competition is independent of PCP, and that it uses a distinct mechanism that may more closely resemble one used in other less well-defined functions of Fmi.

Identification of an individualized therapy prognostic signature for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) are the most common cancers in the head and neck. Therapeutic response-related genes (TRRGs) are closely associated with carcinogenesis and prognosis in HNSCC. However, the clinical value and prognostic significance of TRRGs are still unclear. We aimed to construct a prognostic risk model to predict therapy response and prognosis in TRRGs-defined subgroups of HNSCC.

METHODS

The multiomics data and clinical information of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA). The profile data GSE65858 and GSE67614 chip was downloaded from public functional genomics data Gene Expression Omnibus (GEO). Based on TCGA-HNSC database, patients were divided into a remission group and a non-remission group according to therapy response, and differentially expressed TRRGs between those two groups were screened. Using Cox regression analysis and Least absolute shrinkage and selection operator (LASSO) analysis, candidate TRRGs that can predict the prognosis of HNSCC were identified and used to construct a TRRGs-based signature and a prognostic nomogram.

RESULT

A total of 1896 differentially expressed TRRGs were screened, including 1530 upregulated genes and 366 downregulated genes. Then, 206 differently expressed TRRGs that was significantly associated with the survival were chosen using univariate Cox regression analysis. Finally, a total of 20 candidate TRRGs genes were identified by LASSO analysis to establish a signature for risk prediction, and the risk score of each patient was calculated. Patients were divided into a high-risk group (Risk-H) and a low-risk group (Risk-L) based on the risk score. Results showed that the Risk-L patients had better overall survival (OS) than Risk-H patients. Receiver operating characteristic (ROC) curve analysis revealed great predictive performance for 1-, 3-, and 5-year OS in TCGA-HNSC and GEO databases. Moreover, for patients treated with post-operative radiotherapy, Risk-L patients had longer OS and lower recurrence than Risk-H patients. The nomogram involves risk score and other clinical factors had good performance in predicting survival probability.

CONCLUSIONS

The proposed risk prognostic signature and Nomogram based on TRRGs are novel promising tools for predicting therapy response and overall survival in HNSCC patients.

LncRNA SNHG5 Suppresses Cell Migration and Invasion of Human Lung Adenocarcinoma via Regulation of Epithelial-Mesenchymal Transition

Long noncoding RNAs (lncRNAs) are gradually being annotated as important regulators of multiple cellular processes. The goal of our study was to investigate the effects of the lncRNA small nucleolar RNA host gene 5 (SNHG5) in lung adenocarcinoma (LAD) and its underlying mechanisms. The findings revealed a substantial drop in SNHG5 expression in LAD tissues, which correlated with clinical-pathological parameters. Transcriptome sequencing analysis demonstrated that the inhibitory effect of SNHG5 was associated with cell adhesion molecules. Moreover, the expression of SNHG5 was shown to be correlated with epithelial-mesenchymal transition (EMT) markers in western blots and immunofluorescence. SNHG5 also had significant effects of antimigration and anti-invasion on LAD cells in vitro. Furthermore, the migration and invasion of A549 cells were suppressed by overexpressed SNHG5 in the EMT progress induced by transforming growth factor β1 (TGF-β1), and this might be due to the inhibition of the expression of EMT-associated transcription factors involving Snail, SLUG, and ZEB1. In LAD tissues, the expression of SNHG5 exhibited a positive association with E-cadherin protein expression but a negative correlation with N-cadherin and vimentin, according to the results of quantitative real-time PCR (qRT-PCR). In summary, the current work demonstrated that the lncRNA SNHG5 might limit cell migration and invasion of LAD cancer via decreasing the EMT process, indicating that SNHG5 might be used as a target for LAD therapeutic methods.

Construction and validation of a prognostic model for lung adenocarcinoma based on endoplasmic reticulum stress-related genes

Lung adenocarcinoma (LUAD) is one of the most universal types of cancer all over the world and its morbidity continues to rise year by year. Growing evidence has demonstrated that endoplasmic reticulum stress is highly activated in cancer cells and plays a key role in regulating the fate of cancer cells. However, the role and mechanism of endoplasmic reticulum stress in lung adenocarcinoma genesis and development remains unclear. In this research, we developed a prognostic model to predict the overall survival of patients with LUAD utilizing endoplasmic reticulum stress-related genes and screened out potential small molecular compounds, which could assist the clinician in making accurate decisions and better treat LUAD patients. Firstly, we downloaded 419 endoplasmic reticulum stress-related genes (ERSRGs) from Molecular Signatures Database (MSigDB). Secondly, we obtained information about the transcriptome profiling and corresponding clinical data of 59 normal samples and 535 lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database. Next, we used the DESeq2 package to identify differentially expressed genes related to endoplasmic reticulum stress. We performed univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis to establish a prognostic model for LUAD patients based on ERSRGs. Then, we carried out univariate and multivariate independent prognostic analysis of endoplasmic reticulum stress-related gene (ERSRG) score and some clinical traits of lung adenocarcinoma. Additionally, we developed a clinically applicable nomogram for predicting survival for LUAD patients over one, three, and five years. Moreover, we carried out a drug sensitivity analysis to identify novel small molecule compounds for LUAD treatment. Finally, we examined the tumor microenvironment (TME) and immune cell infiltrating analysis to explore the interactions between immune and cancer cells. 142 differentially expressed ERSRGs were identified by using the DESeq2 package. A prognostic model was built based on 7 differentially expressed ERSRGs after performing univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. According to the results of univariate and multivariate independent prognostic analysis, we found ERSRG score can be used as an independent prognostic maker. Using the Kaplan-Meier curves, we found low-risk patients had higher survival probability than high-risk patients in both training set and test set. A nomogram was drawn to predict 1-, 3-, and 5-year survival probability. The calibration curves explained good performance of the model for the prediction of survival. Phenformin, OSU-03012, GSK-650394 and KIN001-135 were identified as the drugs most likely to provide important information to clinicians about the treatment of LUAD patients. A prognostic prediction model was established based on 7 differentially expressed ERSRGs (PDX1, IGFBP1, DDIT4, PPP1R3G, CFTR, DERL3 and NUPR1), which could effectively predict the prognosis of LUAD patients and give a reference for clinical doctors to help LUAD patients to make better treatment tactics. Based on the 4 small molecule compounds (Phenformin, OSU-03012, GSK-650394 and KIN001-135) we discovered, targeting endoplasmic reticulum stress-related genes may also be a therapeutic approach for LUAD patients.

Identification and validation of a novel tumor driver gene signature for diagnosis and prognosis of head and neck squamous cell carcinoma

Objective: Head and neck squamous cell carcinoma (HNSCC) is a common heterogeneous cancer with complex carcinogenic factors. However, the current TNM staging criteria to judge its severity to formulate treatment plans and evaluate the prognosis are particularly weak. Therefore, a robust diagnostic model capable of accurately diagnosing and predicting HNSCC should be established. Methods: Gene expression and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Key prognostic genes associated with HNSCC were screened with the weighted gene co-expression network analysis and least absolute shrinkage and selection operator (LASSO) Cox regression model analysis. We used the timeROC and survival R packages to conduct time-dependent receiver operating characteristic curve analyses and calculated the area under the curve at different time points of model prediction. Patients in the training and validation groups were divided into high- and low-risk subgroups, and Kaplan-Meier (K-M) survival curves were plotted for all subgroups. Subsequently, LASSO and support vector machine algorithms were used to screen genes to construct diagnostic model. Furthermore, we used the Wilcoxon signed-rank test to compare the half-maximal inhibitory concentrations of common chemotherapy drugs among patients in different risk groups. Finally, the expression levels of eight genes were measured using quantitative real-time polymerase chain reaction and immunohistochemistry. Results: Ten genes (SSB, PFKP, NAT10, PCDH9, SHANK2, PAX8, CELSR3, DCLRE1C, MAP2K7, and ODF4) with prognostic potential were identified, and a risk score was derived accordingly. Patients were divided into high- and low-risk groups based on the median risk score. The K-M survival curves confirmed that patients with high scores had significantly worse overall survival. Receiver operating characteristic curves proved that the prognostic signature had good sensitivity and specificity for predicting the prognosis of patients with HNSCC. Univariate and multivariate Cox regression analyses confirmed that the gene signature was an independent prognostic risk factor for HNSCC. Diagnostic model was built by identifying eight genes (SSB, PFKP, NAT10, PCDH9, CELSR3, DCLRE1C, MAP2K7, and ODF4). The high-risk group showed higher sensitivity to various common chemotherapeutic drugs. DCLRE1C expression was higher in normal tissues than in HNSCC tissues. Conclusion: Our study identified the important role of tumor-driver genes in HNSCC and their potential clinical diagnostic and prognostic values to facilitate individualized management of patients with HNSCC.

Evaluated expression of CELSR3 in oral squamous cell carcinoma is associated with perineural invasion and poor prognosis

OBJECTIVE

The objective of this study was to evaluate CELSR3 expression and explore its potential mechanism in oral squamous cell carcinoma.

STUDY DESIGN

CELSR3 mRNA expression was analyzed using The Cancer Genome Atlas (TCGA) database. CELSR3 protein expression in 135 surgical oral squamous cell carcinoma specimens was observed by immunohistochemical staining. Staining results were used to investigate the association between CELSR3 expression and clinicopathologic characteristics and prognosis. Bioinformatics analyses were used to explore the potential mechanism of CELSR3 in head and neck squamous cell carcinoma.

RESULTS

CELSR3 mRNA expression was upregulated in patients with head and neck squamous cell carcinoma in the TCGA head and neck squamous cell carcinoma data set. Increased CELSR3 protein expression was associated with perineural invasion and poor clinical outcomes in patients with oral squamous cell carcinoma. Bioinformatics analyses revealed that CELSR3 is involvement in axonogenesis, neuron migration, and cell-cell adhesion, all of which are involved in the process of perineural invasion.

CONCLUSION

CELSR3 may play a pro-oncogenic role in oral squamous cell carcinoma and can predict perineural invasion and poor survival. CELSR3 may be involved in oral squamous cell carcinoma progression by modulating perineural invasion.

Systematic expression analysis of the CELSR family reveals the importance of CELSR3 in human lung adenocarcinoma

Cadherin EGF LAG seven‐pass G‐type receptors (CELSRs) are involved in the progression of various types of cancer. CELSR3, a crucial signalling molecule in the WNT/PCP pathway, is believed to be associated with tumorigenesis and metastasis. However, its role in lung adenocarcinoma (LUAD) remains unclear. In this paper, we analysed the expression of CELSR family members using the Oncomine, GEPIA and UALCAN databases. We used a Kaplan‐Meier plotter to assess the effect of CELSRs on tumour prognosis. Next, gene ontology (GO), KEGG pathway, miRNA target, kinase target and transcription factor‐target enrichment were analysed by GSEA. Simultaneously, we conducted functional assays including cell viability, colony formation and transwell assays, to determine the oncogenic role of CELSR3 in LUAD. Finally, we used the TIMER and TISIDB databases to analyse the correlation between CELSR3 and immune infiltration and the potential chemokine receptor axis causing immune cell expression. High expression of CELSR3 is in LUAD predicts poor prognosis and early progression of the tumour. KEGG and GO enrichment analysis revealed the functional relationship between CELSR3 and cell adhesion, the cell cycle, and DNA replication. Down‐regulation of CELSR3 suppressed cell proliferation to a significant extent, in addition to inhibiting invasion and migration in LUAD cells. Finally, CELSR3 expression was significantly correlated with the infiltration level of CD8+T cells through the CCL17/CCR4 axis in LUAD. These results indicate that CELSR3 can serve as a prognostic biomarker for determining prognosis and immune infiltration in LUAD.