Genetic evidence reveals a causal relationship between rheumatoid arthritis and interstitial lung disease.

Background/purpose: Previous epidemiological studies have associated interstitial lung disease (ILD) with rheumatoid arthritis (RA), yet the causality of this relationship remains uncertain. This study aimed to investigate the genetic causal link between ILD and RA. Methods: Genome-wide association study (GWAS) statistics for ILD and RA were collected from public datasets. Relevant single-nucleotide polymorphisms (SNPs) were selected by executing quality control steps from the GWAS summary results. A two-sample bidirectional Mendelian randomization (MR) analysis was performed to assess the causal relationship between the two conditions. The MR analysis primarily used the inverse variance weighting (IVW), weighted median (WM), and MR-Egger regression methods. Sensitivity analyses, including MR-Egger, leave-one-out, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), were conducted to evaluate the heterogeneity and pleiotropy. Replication analyses using Asian datasets were also conducted to enhance the robustness of our findings. Results: In the European population, RA was found to increase the risk of ILD by 9.6% (OR: 1.096, 95% CI: 1.023-1.174, p = 0.009). Conversely, ILD was associated with a 12.8% increased risk of RA (OR: 1.128, 95% CI: 1.013-1.256, p = 0.029). Replication analyses from Asian GWAS further supported these findings, particularly the increased risk of ILD attributable to RA (OR: 1.33, 95% CI: 1.18-1.49, p-value <0.001). Conclusion: Our findings underscore the clinical importance of screening for ILD in RA patients and suggest that effective management of RA could significantly benefit ILD patients. The potential applicability of novel RA treatments to ILD warrants further exploration. Additionally, racial disparities in the manifestation of these diseases should not be overlooked, as they may offer new perspectives for targeted therapies in diverse populations.

The hypoxia-associated genes in immune infiltration and treatment options of lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is a common lung cancer with a poor prognosis under standard chemotherapy. Hypoxia is a crucial factor in the development of solid tumors, and hypoxia-related genes (HRGs) are closely associated with the proliferation of LUAD cells. Methods: In this study, LUAD HRGs were screened, and bioinformatics analysis and experimental validation were conducted. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to gather LUAD RNA-seq data and accompanying clinical information. LUAD subtypes were identified by unsupervised cluster analysis, and immune infiltration analysis of subtypes was conducted by GSVA and ssGSEA. Cox regression and LASSO regression analyses were used to obtain prognosis-related HRGs. Prognostic analysis was used to evaluate HRGs. Differences in enrichment pathways and immunotherapy were observed between risk groups based on GSEA and the TIDE method. Finally, RT-PCR and in vitro experiments were used to confirm prognosis-related HRG expression in LUAD cells. Results: Two hypoxia-associated subtypes of LUAD were distinguished, demonstrating significant differences in prognostic analysis and immunological characteristics between subtypes. A prognostic model based on six HRGs (HK1, PDK3, PFKL, SLC2A1, STC1, and XPNPEP1) was developed for LUAD. HK1, SLC2A1, STC1, and XPNPEP1 were found to be risk factors for LUAD. PDK3 and PFKL were protective factors in LUAD patients. Conclusion: This study demonstrates the effect of hypoxia-associated genes on immune infiltration in LUAD and provides options for immunotherapy and therapeutic strategies in LUAD.

Evaluation of metoprolol standard dosing pathway in Chinese patients with acute coronary syndrome: a prospective multicenter single-arm interventional study.

OBJECTIVE: To evaluate the feasibility and tolerability of metoprolol standard dosing pathway (MSDP) in Chinese patients with acute coronary syndrome (ACS). METHODS: In this multicenter, prospective, open label, single-arm and interventional study that was conducted from February 2018 to April 2019 in fifteen Chinese hospitals. A total of 998 hospitalized patients aged ≥ 18 years and diagnosed with ACS were included. The MSDP was applied to all eligible ACS patients based on the standard treatment recommended by international guidelines. The primary endpoint was the percentage of patients achieving the target dose at discharge (V2). The secondary endpoints included the heart rate and blood pressure at V2 and four weeks after discharge (V4), and percentage of patients experiencing bradycardia (heart rate < 50 beats/min), hypotension (blood pressure < 90/60 mmHg) and transient cardiac dysfunction at V2 and V4. RESULTS: Of the 998 patients, 29.46% of patients achieved the target dose (≥ 95 mg/d) at V2. The total population was divided into two groups: target group (patients achieving the target dose at V2) and non-target group (patients not achieving the target dose at V2). There was significant difference in the reduction of heart rate from baseline to discharge in the two groups (-4.97 ± 11.90 beats/min vs. -2.70 ± 9.47 beats/min, P = 0.034). There was no significant difference in the proportion of bradycardia that occurred in the two groups at V2 (0 vs. 0, P = 1.000) and V4 (0.81% vs. 0.33%, P = 0.715). There was no significant difference in the proportion of hypotension between the two groups at V2 (0.004% vs. 0.004%, P = 1.000) and V4 (0 vs. 0.005%, P = 0.560). No transient cardiac dysfunction occurred in two groups during the study. A total of five adverse events (1.70%) and one serious adverse event (0.34%) were related to the pathway in target group. CONCLUSIONS: In Chinese ACS patients, the feasibility and tolerability of the MSDP have been proved to be acceptable.

eccDB: a comprehensive repository for eccDNA-mediated chromatin contacts in multi-species.

SUMMARY: We developed the eccDB database to integrate available resources for extrachromosomal circular DNA (eccDNA) data. eccDB is a comprehensive repository for storing, browsing, searching, and analyzing eccDNAs from multispecies. The database provides regulatory and epigenetic information on eccDNAs, with a focus on analyzing intrachromosomal and interchromosomal interactions to predict their transcriptional regulatory functions. Moreover, eccDB identifies eccDNAs from unknown DNA sequences and analyzes the functional and evolutionary relationships of eccDNAs among different species. Overall, eccDB offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher the molecular regulatory mechanisms of eccDNAs. AVAILABILITY AND IMPLEMENTATION: eccDB is freely available at http://www.xiejjlab.bio/eccDB.

Drug screening and biomarker gene investigation in cancer therapy through the human transcriptional regulatory network.

A complex and vast biological network regulates all biological functions in the human body in a sophisticated manner, and abnormalities in this network can lead to disease and even cancer. The construction of a high-quality human molecular interaction network is possible with the development of experimental techniques that facilitate the interpretation of the mechanisms of drug treatment for cancer. We collected 11 molecular interaction databases based on experimental sources and constructed a human protein-protein interaction (PPI) network and a human transcriptional regulatory network (HTRN). A random walk-based graph embedding method was used to calculate the diffusion profiles of drugs and cancers, and a pipeline was constructed by using five similarity comparison metrics combined with a rank aggregation algorithm, which can be implemented for drug screening and biomarker gene prediction. Taking NSCLC as an example, curcumin was identified as a potentially promising anticancer drug from 5450 natural small molecules, and combined with differentially expressed genes, survival analysis, and topological ranking, we obtained BIRC5 (survivin), which is both a biomarker for NSCLC and a key target for curcumin. Finally, the binding mode of curcumin and survivin was explored using molecular docking. This work has a guiding significance for antitumor drug screening and the identification of tumor markers.

Use of oral anticoagulants and its associated factors among nonvalvular atrial fibrillation patients with new-onset acute ischemic stroke: A report from the China Atrial Fibrillation Registry study.

BACKGROUND: The adherence of oral anticoagulant (OAC) therapy among nonvalvular atrial fibrillation (NVAF) patients with acute ischemic stroke (AIS) in China during recent years was unclear, and the possible factors that influenced the initiation and persistent use of OAC were needed to be explored. METHODS: A total of 1085 NVAF patients, who experienced new-onset and nonfatal AIS from August 2011 to December 2020 during follow-ups in the China Atrial Fibrillation Registry (China-AF), were enrolled. Information including patients' demographic characteristics, medical history, medication usage, which were collected before and after the index stroke, were used in the analysis. RESULTS: OAC was initiated in 40% (434/1085) NVAF patients within 3 months after new-onset AIS. High-reimbursement-rate insurance coverage (odds ratio [OR]: 1.51, 95% confidence interval [CI]: 1.03-2.22, p = .036), 3-month-peri-stroke AF episodes (OR: 2.63, 95% CI: 1.88-3.69, p < .001), and pre-stroke OAC usage (OR: 8.92, 95% CI: 6.01-13.23, p < .001), were positively associated with initiation of OAC within 3 months after new-onset AIS, while age (OR: 0.98, 95% CI: 0.96-1.00, p = .024), female (OR: 0.63, 95% CI: 0.44-0.90, p = .012) and higher modified HASBLED score (OR: 0.45, 95% CI: 0.37-0.55, p < .001) were negatively associated with it. Among 3-month-post-stroke OAC users, history of radiofrequency ablation (hazard ratio: 1.65, 95% CI: 1.16-2.35; p = .006) was positively associated with non-persistence of OAC usage. CONCLUSIONS: In China, the proportion of NVAF patients who initiated OAC therapy since new-onset AIS was still low. More efforts are needed on improving patients' adherence to anticoagulant therapy.

A Study on Weak Edge Detection of COVID-19's CT Images Based on Histogram Equalization and Improved Canny Algorithm.

The coronavirus disease 2019 (COVID-19) is a substantial threat to people's lives and health due to its high infectivity and rapid spread. Computed tomography (CT) scan is one of the important auxiliary methods for the clinical diagnosis of COVID-19. However, CT image lesion edge is normally affected by pixels with uneven grayscale and isolated noise, which makes weak edge detection of the COVID-19 lesion more complicated. In order to solve this problem, an edge detection method is proposed, which combines the histogram equalization and the improved Canny algorithm. Specifically, the histogram equalization is applied to enhance image contrast. In the improved Canny algorithm, the median filter, instead of the Gaussian filter, is used to remove the isolated noise points. The K-means algorithm is applied to separate the image background and edge. And the Canny algorithm is improved continuously by combining the mathematical morphology and the maximum between class variance method (OTSU). On selecting four types of lesion images from COVID-CT date set, MSE, MAE, SNR, and the running time are applied to evaluate the performance of the proposed method. The average values of these evaluation indicators are 1.7322, 7.9010, 57.1241, and 5.4887, respectively. Compared with other three methods, these values indicate that the proposed method achieves better result. The experimental results prove that the proposed algorithm can effectively detect the weak edge of the lesion, which is helpful for the diagnosis of COVID-19.

Real world effectiveness of PCSK-9 inhibitors combined with statins versus statins-based therapy among patients with very high risk of atherosclerotic cardiovascular disease in China (RWE-PCSK study).

BACKGROUND: The efficacy and safety of proprotein convertase subtilisin/kexin type 9 (PCSK-9) inhibitors were confirmed by several clinical trials, but its effectiveness in routine clinical practice in China has not been evaluated. This study aims to describe the real world effectiveness of PCSK-9 inhibitors combined with statins compared with statins-based therapy among patients with very high risk of atherosclerotic cardiovascular disease (ASCVD). METHODS: This is a multi-center observational study, enrolled patients from 32 hospitals who underwent percutaneous coronary intervention (PCI) from January to June in 2019. There are 453 patients treated with PCSK-9 inhibitors combined with statins in PCSK-9 inhibitor group and 2,610 patients treated with statins-based lipid lowering therapies in statins-based group. The lipid control rate and incidence of major adverse cardiovascular events (MACE) over six months were compared between two groups. A propensity score-matched (PSM) analysis was used to balance two groups on confounding factors. Survival analysis using Kaplan-Meier methods was applied for MACE. RESULTS: In a total of 3,063 patients, 89.91% of patients had received moderate or high-intensity statins-based therapy before PCI, but only 9.47% of patients had low-density lipoprotein cholesterol (LDL-C) levels below 1.4 mmol/L at baseline. In the PSM selected patients, LDL-C level was reduced by 42.57% in PCSK-9 inhibitor group and 30.81% (P < 0.001) in statins-based group after six months. The proportion of LDL-C ≤ 1.0 mmol/L increased from 5.29% to 29.26% in PCSK-9 inhibitor group and 0.23% to 6.11% in statins-based group, and the proportion of LDL-C ≤ 1.4 mmol/L increased from 10.36% to 47.69% in PCSK-9 inhibitor group and 2.99% to 18.43% in statins-based group ( P < 0.001 for both). There was no significant difference between PCSK-9 inhibitor and statins-based treatment in reducing the risk of MACE (hazard ratio = 2.52, 95% CI: 0.49-12.97, P = 0.250). CONCLUSIONS: In the real world, PCSK-9 inhibitors combined with statins could significantly reduce LDL-C levels among patients with very high risk of ASCVD in China. The long-term clinical benefits for patients received PCSK-9 inhibitor to reduce the risk of MACE is still unclear and requires further study.

Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients.

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed. Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan-Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed. Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P < 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P < 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis. Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

A robust two-gene signature for glioblastoma survival prediction.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan-Meier analysis, t-distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two-gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2-RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64-0.98, vs median: 0.98, 95% CI: 0.65-1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70-1.18, vs median: 1.21, 95% CI: 0.95-2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86-1.24, vs median: 1.23, 95% CI: 1.04-1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two-gene signature was a robust prognostic model to predict GBM survival.

Identification of key genes by integrating DNA methylation and next-generation transcriptome sequencing for esophageal squamous cell carcinoma.

Aberrant DNA methylation leads to abnormal gene expression, making it a significant regulator in the progression of cancer and leading to the requirement for integration of gene expression with DNA methylation. Here, we identified 120 genes demonstrating an inverse correlation between DNA methylation and mRNA expression in esophageal squamous cell carcinoma (ESCC). Sixteen key genes, such as SIX4, CRABP2, and EHD3, were obtained by filtering 10 datasets and verified in paired ESCC samples by qRT-PCR. 5-Aza-dC as a DNA methyltransferase (DNMT) inhibitor could recover their expression and inhibit clonal growth of cancer cells in seven ESCC cell lines. Furthermore, 11 of the 16 genes were correlated with OS (overall survival) and DFS (disease-free survival) in 125 ESCC patients. ChIP-Seq data and WGBS data showed that DNA methylation and H3K27ac histone modification of these key genes displayed inverse trends, suggesting that there was collaboration between DNA methylation and histone modification in ESCC. Our findings illustrate that the integrated multi-omics data (transcriptome and epigenomics) can accurately obtain potential prognostic biomarkers, which may provide important insight for the effective treatment of cancers.

A P53-related microRNA model for predicting the prognosis of hepatocellular carcinoma patients.

Studies have shown that microRNAs (miRNAs) play a vital role in tumor progression and patients' prognosis. Therefore, we aimed to construct a miRNA model for forecasting the survival of hepatocellular carcinoma (HCC) patients. The gene expression data of 433 patients with HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus public databases were remined by survival analysis and receptor manipulation characteristic curve (ROC). A prognostic model including six miRNAs (hsa-mir-26a-1-3p, hsa-mir-188-5p, hsa-mir-212-5p, hsa-mir-149-5p, hsa-mir-105-5p, and hsa-mir-132-5p) were constructed in the training dataset (TCGA, n = 333). HCC patients were stratified into a high-risk group and a low-risk group with significantly different survival (median: 2.75 vs. 8.93 years, log-rank test p < .001). Then we proved its performance of stratification in another independent dataset (GSE116182, median: 2.55 vs 6.96 years, log-rank test p = .008). Cox regression analysis showed that the prognostic model was an independent prognostic indicator for HCC patients. Then time-dependent ROC analyses were performed to test the prognostic ability of the model with that of TNM staging, we found the model had a better performance, especially at 5 years (AUC = 0.76). Functional prediction showed that the genes targeted by the six prognostic miRNAs in the prognostic model were highly expressed in the P53-related pathway. In conclusion, we constructed a prognostic miRNA model that could indicate the survival of HCC patients.

A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.

Flavoproteins and their interacting proteins play important roles in mitochondrial electron transport, fatty acid degradation, and redox regulation. However, their clinical significance and function in esophageal squamous cell carcinoma (ESCC) are little known. Here, using survival analysis and machine learning, we mined 179 patient expression profiles with ESCC in GSE53625 from the Gene Expression Omnibus (GEO) database and constructed a signature consisting of two flavoprotein genes (GPD2 and PYROXD2) and four flavoprotein interacting protein genes (CTTN, GGH, SRC, and SYNJ2BP). Kaplan-Meier analysis revealed the signature was significantly associated with the survival of ESCC patients (mean survival time: 26.77 months in the high-risk group vs. 54.97 months in the low-risk group, P < 0.001, n = 179), and time-dependent ROC analysis demonstrated that the six-gene signature had good predictive ability for six-year survival for ESCC (AUC = 0.86, 95% CI: 0.81-0.90). We then validated its prediction performance in an independent set by RT-PCR (mean survival: 15.73 months in the high-risk group vs. 21.1 months in the low-risk group, P=0.032, n = 121). Furthermore, RNAi-mediated knockdown of genes in the flavoprotein signature led to decreased proliferation and migration of ESCC cells. Taken together, CTTN, GGH, GPD2, PYROXD2, SRC, and SYNJ2BP have an important clinical significance for prognosis of ESCC patients, suggesting they are efficient prognostic markers and potential targets for ESCC therapy.

CNIT: a fast and accurate web tool for identifying protein-coding and long non-coding transcripts based on intrinsic sequence composition.

As more and more high-throughput data has been produced by next-generation sequencing, it is still a challenge to classify RNA transcripts into protein-coding or non-coding, especially for poorly annotated species. We upgraded our original coding potential calculator, CNCI (Coding-Non-Coding Index), to CNIT (Coding-Non-Coding Identifying Tool), which provides faster and more accurate evaluation of the coding ability of RNA transcripts. CNIT runs âˆ¼200 times faster than CNCI and exhibits more accuracy compared with CNCI (0.98 versus 0.94 for human, 0.95 versus 0.93 for mouse, 0.93 versus 0.92 for zebrafish, 0.93 versus 0.92 for fruit fly, 0.92 versus 0.88 for worm, and 0.98 versus 0.85 for Arabidopsis transcripts). Moreover, the AUC values of 11 animal species and 27 plant species showed that CNIT was capable of obtaining relatively accurate identification results for almost all eukaryotic transcripts. In addition, a mobile-friendly web server is now freely available at http://cnit.noncode.org/CNIT.

SEanalysis: a web tool for super-enhancer associated regulatory analysis.

Super-enhancers (SEs) have prominent roles in biological and pathological processes through their unique transcriptional regulatory capability. To date, several SE databases have been developed by us and others. However, these existing databases do not provide downstream or upstream regulatory analyses of SEs. Pathways, transcription factors (TFs), SEs, and SE-associated genes form complex regulatory networks. Therefore, we designed a novel web server, SEanalysis, which provides comprehensive SE-associated regulatory network analyses. SEanalysis characterizes SE-associated genes, TFs binding to target SEs, and their upstream pathways. The current version of SEanalysis contains more than 330 000 SEs from more than 540 types of cells/tissues, 5042 TF ChIP-seq data generated from these cells/tissues, DNA-binding sequence motifs for ∼700 human TFs and 2880 pathways from 10 databases. SEanalysis supports searching by either SEs, samples, TFs, pathways or genes. The complex regulatory networks formed by these factors can be interactively visualized. In addition, we developed a customizable genome browser containing >6000 customizable tracks for visualization. The server is freely available at http://licpathway.net/SEanalysis.

A novel multidimensional signature predicts prognosis in hepatocellular carcinoma patients.

The abnormal expression of microRNAs (miRNAs) or protein-coding genes (PCGs) have been found to be associated with the prognosis of hepatocellular carcinoma (HCC) patients. Using bioinformatics analysis methods including Cox's proportional hazards regression analysis, the random survival forest algorithm, Kaplan-Meier, and receiver operating characteristic (ROC) curve analysis, we mined the gene expression profiles of 469 HCC patients from The Cancer Genome Atlas (n = 379) and Gene Expression Omnibus (GSE14520; n = 90) public database. We selected a signature comprising one protein-coding gene (PCG; DNA polymerase µ) and three miRNAs (hsa-miR-149-5p, hsa-miR-424-5p, hsa-miR-579-5p) with highest accurate prediction (area under the ROC curve [AUC] = 0.72; n = 189) from the training data set. The signature stratified patients into high- and low-risk groups with significantly different survival (median 27.9 vs. 55.2 months, log-rank test, p < 0.001) in the training data set, and its risk stratification ability were validated in the test data set (median 47.4 vs. 84.4 months, log-rank test, p = 0.03) and an independent data set (median 31.0 vs. 46.0 months, log-rank test, p = 0.01). Multivariable Cox regression analysis showed that the signature was an independent prognostic factor. And the signature was proved to have a better survival prediction power than tumor-node-metastasis (TNM) stage (AUC signature = 0.72/0.64/0.62 vs. AUC TNM = 0.65/0.61/0.61; p < 0.05). Moreover, we validated the expression of these prognostic genes from the PCG-miRNA signature in Huh-7 cell by real-time polymerase chain reaction. In conclusion, we found a signature that can predict survival of HCC patients and serve as a prognostic marker for HCC.

A novel clinical multidimensional transcriptome signature predicts prognosis in bladder cancer.

A number of studies has shown that long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and protein coding genes (PCGs) are involved in various pathophysiological processes and can be used as prognostic biomarkers in cancer patients. The purpose of this study was to find a multidimensional transcriptome signature to predict clinical outcomes in bladder cancer. Using Cox's proportional hazards regression analysis and the random survival forest algorithm, we mined the expression profile data of 239 bladder cancer patients derived from The Cancer Genome Atlas (TCGA) public database. A signature comprised of two PCGs (ACADS and C1QTNF9B), two lncRNAs (RP11­60L3.1 and CTD­3195I5.3) and two microRNAs (has­miR­3913­1 and has­miR­891a) with highest accuracy prediction (AUC=0.79 in the training dataset and 0.64 in the test dataset) was selected. The signature had an ability to stratify patients into high­ and low­risk groups with significantly different survival rates (median 16.9 vs. 54.9 months, log­rank test P<0.001) in the training dataset, and its performance was validated for risk stratification in the test dataset (median 18.2 vs. 58.9 months, log­rank test P=0.002). Multivariable Cox regression analysis revealed that the signature was an independent prognostic factor for patients with bladder urothelial carcinoma (BLCA). A comparison of tumour node metastasis (TNM) stage and the signature indicated that the signature had better survival prediction power (AUCsignature=0.79/0.64 vs. AUCTNM=0.67/0.60, P<0.05). Functional analyses indicated that these prognostic genes from the signature may be involved in tumourigenesis­related biological processes and pathways. In conclusion, the multidimensional PCG­lncRNA­microRNA signature can be a novel prognostic marker to predict the survival of bladder cancer patients.

Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC. METHODS: Using Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset. RESULTS: Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients. CONCLUSIONS: The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

The interaction of lncRNA EZR-AS1 with SMYD3 maintains overexpression of EZR in ESCC cells.

EZR, a member of the ezrin-radixin-moesin (ERM) family, is involved in multiple aspects of cell migration and cancer. SMYD3, a histone H3-lysine 4 (H3-K4)-specific methyltransferase, regulates EZR gene transcription, but the molecular mechanisms of epigenetic regulation remain ill-defined. Here, we show that antisense lncRNA EZR-AS1 was positively correlated with EZR expression in both human esophageal squamous cell carcinoma (ESCC) tissues and cell lines. Both in vivo and in vitro studies revealed that EZR-AS1 promoted cell migration through up-regulation of EZR expression. Mechanistically, antisense lncRNA EZR-AS1 formed a complex with RNA polymerase II to activate the transcription of EZR. Moreover, EZR-AS1 could recruit SMYD3 to a binding site, present in a GC-rich region downstream of the EZR promoter, causing the binding of SMYD3 and local enrichment of H3K4me3. Finally, the interaction of EZR-AS1 with SMYD3 further enhanced EZR transcription and expression. Our findings suggest that antisense lncRNA EZR-AS1, as a member of an RNA polymerase complex and through enhanced SMYD3-dependent H3K4 methylation, plays an important role in enhancing transcription of the EZR gene to promote the mobility and invasiveness of human cancer cells.

L1CAM drives oncogenicity in esophageal squamous cell carcinoma by stimulation of ezrin transcription.

L1 cell adhesion molecule (L1CAM) is highly expressed in various types of human cancers, displaying yet unknown molecular mechanisms underlying their oncogenic potential. Here, we found that L1CAM expression was significantly increased in esophageal squamous cell carcinoma (ESCC; n = 157) lesions compared with non-cancerous tissues. High tumorous L1CAM expression significantly correlated with reduced overall survival. Experimentally, L1CAM knockdown led to decreased cell growth, migration, and invasiveness in vitro, whereas overexpression of L1CAM showed the opposite effect. In nude mice, L1CAM depletion attenuated tumorigenesis and ability to penetrate the tissues surrounding ESCC cells. Gene set enrichment analysis (GSEA) and SubpathwayMiner analysis on gene expression profiles (microarray data on ESCC tissues, GSE53625; cDNA microarray data on L1CAM-knockdown ESCC cell line, GSE86268) suggested that L1CAM-co-expression genes were related to cell motility, cell proliferation, and regulation of actin cytoskeleton, validating the above experimental findings. Further mechanistical analysis showed that L1CAM upregulated the expression of the cytoskeletal protein ezrin via activating integrin ß1/MAPK/ERK/AP1 signaling and thus led to the malignant phenotypes of ESCC cells. Together, our findings suggest that L1CAM may be employed as a valuable prognosis marker and a therapeutic target for ESCC patients and that L1CAM promotes ESCC tumorigenicity by upregulating ezrin expression. KEY MESSAGES: L1CAM promotes growth and invasiveness of ESCC cells in vitro and in vivo. L1CAM upregulates the expression of ezrin by integrin α5ß1/MAPK/ERK/AP1 pathway. Ezrin is a key downstream effector in the L1CAM-promoted malignant phenotypes. High expression levels of both L1CAM and ezrin significantly correlated with reduced overall survival. Nuclear L1CAM is an independent prognosis marker for esophageal squamous cell carcinoma.