OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma

TIMM9 as a prognostic biomarker in multiple cancers and its associated biological processes

TIMM9 has been identified as a mediator of essential functions in mitochondria, but its association with pan-cancer is poorly understood. We herein employed bioinformatics, computational chemistry techniques and experiments to investigate the role of TIMM9 in pan-cancer. Our analysis revealed that overexpression of TIMM9 was significantly associated with tumorigenesis, pathological stage progression, and metastasis. Missense mutations (particularly the S49L variant), copy number variations (CNV) and methylation alterations in TIMM9 were found to be associated with poor cancer prognosis. Moreover, TIMM9 was positively related with cell cycle progression, mitochondrial and ribosomal function, oxidative phosphorylation, TCA cycle activity, innate and adaptive immunity. Additionally, we discovered that TIMM9 could be regulated by cancer-associated signaling pathways, such as the mTOR pathway. Using molecular simulations, we identified ITFG1 as the protein that has the strongest physical association with TIMM9, which show a promising structural complement.

hOGG1: A novel mediator in nitrosamine-induced esophageal tumorigenesis

BACKGROUND

The effect of human 8-Oxoguanine DNA Glycosylase (hOGG1) on exogenous chemicals in esophageal squamous cell carcinoma (ESCC) remain unclear. The study plans to determine hOGG1 expression levels in ESCC and possible interactions with known environmental risk factors in ESCC.

MATERIAL AND METHODS

We analyzed levels of exposure to urinary nitrosamines in volunteers from high and low prevalence areas by GC-MS. And we performed the interaction between hOGG1 gene and nitrosamine disinfection by-products by analyzing hOGG1 gene expression in esophageal tissues.

RESULTS

In ESCC, nitrosamine levels were significantly increased and hOGG1 mRNA expression levels were significantly decreased. There was a statistically significant interaction between reduced hOGG1 mRNA levels and non-tap drinking water sources in ESCC. The apparent indirect association between ESCC and NMEA indicated that 33.4% of the association between ESCC and NMEA was mediated by hOGG1.

CONCLUSION

In populations which exposed to high levels of environmental pollutants NDMA, low expression of hOGG1 may promote the high incidence of esophageal cancer in Huai'an. hOGG1 may be a novel mediator in nitrosamine-induced esophageal tumorigenesis.

OSppc: A web server for online survival analysis using proteome of pan-cancers

Prognostic biomarker, as a feasible and objective indicator, is valuable in the assessment of cancer risk. With the development of high-throughput sequencing technology, the screening of prognostic biomarkers has become easy, but it is difficult to screen prognostic markers based on proteomic data. In this study we developed a tool named Online consensus Survival analysis web server based on Proteome of Pan-cancers, abbreviated as OSppc, to evaluate the prognostic values of protein biomarkers. >8000 cancer cases with proteomic data, transcriptomic data and clinical follow-up information were collected from TCGA and CPTAC. 14,038 proteins (including proteins and their phosphorylated forms) analyzed by reverse-phase protein arrays and mass spectrometry in 33 types of cancers were collected. In OSppc, three analysis modules are provided, including Survival Analysis, Differential Analysis and Correlation Analysis. Survival analysis module exhibits HR with 95% CI and KM curves with log-rank p value of protein and mRNA levels of input genes. Differential analysis module shows the box plots of protein expression levels in different tissues. Correlation analysis module provides scatter plot with pearson's and spearman's correlation coefficient of the protein and its corresponding mRNA. OSppc can be accessed at http://bioinfo.henu.edu.cn/Protein/OSppc.html. SIGNIFICANCE: OSppc can analyze the association between protein, mRNA and prognosis, the correlation between proteome data and gene expression profiles, the differential expression of proteome data between subgroups such as normal and cancer as well. OSppc is registration-free and very valuable to evaluate the prognostic potency of protein of interests. OSppc is very valuable for researchers and clinicians to screen, develop and validate potential protein prognostic biomarkers in pan-cancers, and offers the opportunities to investigate the clinical important functional genes and therapeutic targets of cancers.

ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients

BACKGROUND

Esophageal cancer (EC) is considered as one of the deadliest malignancies with respect to incidence and mortality rate, and numerous risk factors may affect the prognosis of EC patients. For better understanding of the risk factors associated with the onset and prognosis of this malignancy, we develop an interactive web-based tool for the convenient analysis of clinical and survival characteristics of EC patients.

METHODS

The clinical data were obtained from The Surveillance, Epidemiology, and End Results (SEER) database. Seven analysis and visualization modules were built with Shiny.

RESULTS

The Esophageal Cancer Clinical Data Interactive Analysis (ECCDIA, http://webapps.3steps.cn/ECCDIA/ ) was developed to provide basic data analysis, visualization, survival analysis, and nomogram of the overall group and subgroups of 77,273 EC patients recorded in SEER. The basic data analysis modules contained distribution analysis of clinical factor ratios, Sankey plot analysis for relationships between clinical factors, and a map for visualizing the distribution of clinical factors. The survival analysis included Kaplan-Meier (K-M) analysis and Cox analysis for different subgroups of EC patients. The nomogram module enabled clinicians to precisely predict the survival probability of different subgroups of EC patients.

CONCLUSION

ECCDIA provides clinicians with an interactive prediction and visualization tool for visualizing invaluable clinical and prognostic information of individual EC patients, further providing useful information for better understanding of esophageal cancer.

Comprehensive analysis of two potential novel SARS-CoV-2 entries, TMPRSS2 and IFITM3, in healthy individuals and cancer patients

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2, with acute respiratory failure as the most significant symptom, has led to a global pandemic. Angiotensin-converting enzyme 2 (ACE2) is considered as the most important receptor of SARS-CoV-2 and wildly expressed in human tissues. Whereas, the extremely low expression of ACE2 in lung could hardly interpret the severe symptom of pneumonia in COVID-19 patients. Here we profiled two SARS-CoV-2 infection related genes, the transmembrane serine protease 2 (TMPRSS2) and the interferon-inducible transmembrane protein 3 (IFITM3), in human tissues and organs. Consistent with the expression and distribution of ACE2, TMPRSS2 was also highly expressed in digestive, urinary and reproductive systems, but low expressed in lung. Notably, the anti-virus protein IFITM3 also expressed much lower in lung than other tissues, which might be related to the severe lung symptoms of COVID-19. In addition, the low expression of IFITM3 in immune cells suggested that SARS-CoV-2 might attack lymphocytes and induce the cytokine release syndrome (CRS). Furthermore, cancer patients were considered as more susceptible to SARS-CoV-2 infection. Our data supposed that fourteen types of tumors might have different susceptibility to the virus according to ACE2, TMPRSS2 and IFITM3 expression patterns. Interestingly the prognosis of six types of cancers including breast carcinoma (BRCA), lung adenocarcinoma (LUAD), uterine corpus endometrial carcinoma (UCEC), renal clear cell carcinoma (KIRC), prostate adenocarcinoma (PRAD), and hepatocellular carcinoma (LIHC) were closely related to these gene expressions. Our study explored the expression and distribution profiles of two potential novel molecules that might participate in SARS-CoV-2 infection and involved in immunity, which may provide a functional basis for preventing infection of SARS-CoV-2.

Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is a deadly cancer with high mortality rate, especially in economically advanced countries, while Barrett's esophagus (BE) is reported to be a precursor that strongly increases the risk of EAC. Due to the complexity of these diseases, their molecular mechanisms have not been revealed clearly. This study aims to explore the gene signatures shared between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 from the Gene Expression Omnibus and ArrayExpress using systematic meta-analysis. These data were accompanied by clinical data and RNAseq data from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to explore the relationship between gene sets and clinical traits as well as to discover the key relationships behind the co-expression modules. A differentially expressed gene-based protein-protein interaction (PPI) complex was used to extract hub genes through Cytoscape plugins. As a result, 403 DEGs were excavated, comprising 236 upregulated and 167 downregulated genes, which are involved in the cell cycle and replication pathways. Forty key genes were identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark-gray module with 207 genes was identified which having a high correlation with phenotype (gender) in the WGCNA. Furthermore, five shared hub gene signatures (SHGS), namely, pre-mRNA processing factor 4 (PRPF4), serine and arginine-rich splicing factor 1 (SRSF1), heterogeneous nuclear ribonucleoprotein M (HNRNPM), DExH-Box Helicase 9 (DHX9), and origin recognition complex subunit 2 (ORC2), were identified between BE and EAC. SHGS enrichment denotes that RNA metabolism and splicosomes play a key role in esophageal cancer development and progress. We conclude that the PPI complex and WGCNA co-expression network highlight the importance of phenotypic identifying hub gene signatures for BE and EAC.