A novel assessing system for predicting the prognosis of gastric cancer

Epigenomics ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1251-1266
Author(s):  
Siheng Lin ◽  
Rui Zhou ◽  
Dongqiang Zeng ◽  
Jiani Wu ◽  
Jianhua Wu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Diagnostic Tools ◽  
Expression Data ◽  
Protein Coding ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Gastric Cancer Patients

Aim: To develop novel diagnostic tools that can predict the prognosis of gastric cancer. Material & methods: Using RNA expression data from The Cancer Genome Atlas and Gene Expression Omnibus, we established protein-coding RNAs-noncoding RNAs-tumor microenvironment type (PNM) scores, which contain signatures of tumor protein coding genes (P), tumor noncoding genes (N) and immune/stroma cells in tumor microenvironment (M) to predict the prognosis of gastric cancer. Results & conclusion: Based on PNM scores, gastric cancer patients were divided into three subgroups and Kaplan–Meier survival curves revealed significant differences among the subgroups (p < 0.001). Our study showed that the PNM scores could be used as a robust predicting tool for the prognosis of gastric cancer.

scholarly journals Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Wei Han ◽  
Biao Huang ◽  
Xiao-Yu Zhao ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Metastatic Melanoma ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Subtype Identification ◽  
Cancer Genome Atlas ◽  
Immune Related Genes

Abstract Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune-related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune-related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for metastatic melanoma.

scholarly journals Downregulated SPINK4 is associated with poor survival in colorectal cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiaojie Wang ◽  
Qian Yu ◽  
Waleed M. Ghareeb ◽  
Yiyi Zhang ◽  
Xingrong Lu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Expression Data ◽  
Poor Survival ◽  
Protein Levels ◽  
Normal Tissues ◽  
Human Protein Atlas ◽  
Cancer Genome Atlas ◽  
Independent Indicator

Abstract Background SPINK4 is known as a gastrointestinal peptide in the gastrointestinal tract and is abundantly expressed in human goblet cells. The clinical significance of SPINK4 in colorectal cancer (CRC) is largely unknown. Methods We retrieved the expression data of 1168 CRC patients from 3 Gene Expression Omnibus (GEO) datasets (GSE24551, GSE39582, GSE32323) and The Cancer Genome Atlas (TCGA) to compare the expression level of SPINK4 between CRC tissues and normal colorectal tissues and to evaluate its value in predicting the survival of CRC patients. At the protein level, these results were further confirmed by data mining in the Human Protein Atlas and by immunohistochemical staining of samples from 81 CRC cases in our own center. Results SPINK4 expression was downregulated in CRC compared with that in normal tissues, and decreased SPINK4 expression at both the mRNA and protein levels was associated with poor prognosis in CRC patients from all 3 GEO datasets, the TCGA database and our cohort. Additionally, lower SPINK4 expression was significantly related to higher TNM stage. Moreover, in multivariate regression, SPINK4 was confirmed as an independent indicator of poor survival in CRC patients in all databases and in our own cohort. Conclusions We concluded that reduced expression of SPINK4 relates to poor survival in CRC, functioning as a novel indicator.

scholarly journals CPXM1: a novel biomarker for gastric cancer prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Mengxiang Zhu ◽  
Wenwu Yan ◽  
Changsheng Yao ◽  
Qingyi Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Signal Pathways ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background The molecular role of carboxypeptidase X, M14 family member (CPXM1) in oncogenesis or tumor progression remains unclear. The aim of this study was to determine whether CPXM1 can be used as a potential prognostic biomarker for gastric cancer (GC). Methods We first demonstrated the relationship between CPXM1 expression and GC in various public databases. Secondly, the expression of CPXM1 in GC tissues was further verified by immunohistochemical staining using tissue microarray containing 96 cases of GC patients. Kaplan–Meier analysis and a Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CPXM1 and the survival of GC patients. Finally, we used the expression data of CPXM1 in The Cancer Genome Atlas database to predict CPXM1-related signaling pathways through bioinformatics analysis. Results The expression level of CPXM1 in GC tissues was significantly correlated with tumor size (p = 0.041) and lymph node metastasis (p = 0.014). In addition, Kaplan–Meier analysis showed that the expression of CPXM1 in GC tissues was significantly associated with poor prognosis (p = 0.011). Multivariate analysis indicated that CPXM1 is a potential predictor of poor prognosis in GC patients (p = 0.026). The results of biosynthesis analysis demonstrated that the data set of CPXM1 high expression was mainly enriched in cancer-related signal pathways. Conclusion CPXM1 is an effective biomarker for the prognosis of GC patients and may play a key role in the occurrence and progression of GC.

scholarly journals Tumor microenvironment characterization in stage IV gastric cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xianxue Zhang ◽  
Feng Yang ◽  
Zhenbao Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stage Iv ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Stage Iv Gastric Cancer ◽  
Th 17 ◽  
Cancer Genome Atlas

Abstract Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment’s clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.

scholarly journals Reproduction of the Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) Gastric Cancer Molecular Classifications and Their Association with Clinicopathological Characteristics and Overall Survival in Moroccan Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jean Paul Nshizirungu ◽  
Sanae Bennis ◽  
Ihsane Mellouki ◽  
Mohammed Sekal ◽  
Dafr-Allah Benajah ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Research ◽  
Overall Survival ◽  
Molecular Subtypes ◽  
Clinicopathological Features ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Gastric Cancer Patients ◽  
Genome Atlas ◽  
E Cadherin

Introduction. The Cancer Genome Atlas (TCGA) project and Asian Cancer Research Group (ACRG) recently categorized gastric cancer into molecular subtypes. Nevertheless, these classification systems require high cost and sophisticated molecular technologies, preventing their widespread use in the clinic. This study is aimed to generating molecular subtypes of gastric cancer using techniques available in routine diagnostic practice in a series of Moroccan gastric cancer patients. In addition, we assessed the associations between molecular subtypes, clinicopathological features, and prognosis. Methods. Ninety-seven gastric cancer cases were classified according to TCGA, ACRG, and integrated classifications using a panel of four molecular markers (EBV, MSI, E-cadherin, and p53). HER2 status and PD-L1 expression were also evaluated. These markers were analyzed using immunohistochemistry (E-cadherin, p53, HER2, and PD-L1), in situ hybridization (EBV and HER2 equivocal cases), and multiplex PCR (MSI). Results. Our results showed that the subtypes presented distinct clinicopathological features and prognosis. EBV-positive gastric cancers were found exclusively in male patients. The GS (TCGA classification), MSS/EMT (ACRG classification), and E-cadherin aberrant subtype (integrated classification) presented the Lauren diffuse histology enrichment and tended to be diagnosed at a younger age. The MSI subtype was associated with a better overall survival across all classifications (TCGA, ACRG, and integrated classification). The worst prognosis was observed in the EBV subtype (TCGA and integrated classification) and MSS/EMT subtype (ACRG classification). Discussion/Conclusion. We reported a reproducible and affordable gastric cancer subtyping algorithms that can reproduce the recently recognized TCGA, ACRG, and integrated gastric cancer classifications, using techniques available in routine diagnosis. These simplified classifications can be employed not only for molecular classification but also in predicting the prognosis of gastric cancer patients.

scholarly journals Characterization of the prognostic values of the NDRG family in gastric cancer

2019 ◽  
Vol 12 ◽  
pp. 175628481985850 ◽  
Author(s):  
Chaoran Yu ◽  
Xiaohui Hao ◽  
Sen Zhang ◽  
Wenjun Hu ◽  
Jianwen Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Poor Prognosis ◽  
Wide Spectrum ◽  
Mitotic Cell ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Follicular Helper ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Background: The N-myc downstream-regulated gene ( NDRG) family, NDRG1-4, has been involved in a wide spectrum of biological functions in multiple cancers. However, their prognostic values remain sparse in gastric cancer (GC). Therefore, it is crucial to systematically investigate the prognostic values of the NDRG family in GC. Methods: The prognostic values of the NDRG family were evaluated by Kaplan–Meier Plotter and SurvExpress. The mRNA of the NDRG family was investigated in The Cancer Genome Atlas (TCGA). Transcription factors (TFs) and miRNAs associated with the NDRG family were predicted by NetworkAnalysis. The prognostic values of DNA methylation levels were analyzed by MethSurv. The correlation between immune cells and the NDRG family was evaluated by the Tumor Immune Estimation Resource (TIMER) database. Results: High levels of mRNA expression of NDRG2 and NDRG3 were associated with a favorable prognosis in all GCs. In HER2− GC, NDRG1 was significantly associated with a poor prognosis of GC [hazard ratio (HR) = 1.65, 95% confidence interval (CI) = 1.16–2.33, p = 0.0046]. In HER2+ GC, NDRG4 showed a poor prognosis (HR = 1.4, 95% CI: 1.06–1.85, p = 0.017). NDRG4 was an independent prognostic factor in recurrence-free survival by TCGA cohort. The low-risk NDRG-signature group displayed a significantly favorable survival outcome than the high-risk group (HR = 1.76, 95% CI: 1.2–2.59, p = 0.00385). The phosphorylated protein NDRG1 (NDRG1_pT346) displayed a favorable overall survival and was significantly associated with HER2 and phosphorylated HER2. Epidermis development was the top biological process (BP) for coexpressed genes associated with NDRG1 and NDRG4, while mitotic nuclear division and mitotic cell processes were the top BPs for NDRG2 and NDRG3, respectively. Overall, 6 CpGs of NDRG1, 4 CpGs of NDRG2, 3 CpGs of NDRG3 and 24 CpGs of NDRG4 were associated with significant prognosis. CD4+ T-cells showed the highest correlation with NDRG4 (correlation = 0.341, p = 2.14e−11). Furthermore, BCL6 in follicular helper T-cells (Tfh) cells showed the highest association with NDRG4 (correlation = 0.438, p = 00e+00). Conclusions: This study analyzed the multilevel prognostic values and biological roles of the NDRG family in GC.

scholarly journals Identification of F5 as a Prognostic Biomarker in Patients with Gastric Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yi Liu ◽  
Xi-Wen Liao ◽  
Yu-Zhou Qin ◽  
Xian-Wei Mo ◽  
Shan-Shan Luo
Keyword(s):  
Gastric Cancer ◽  
Survival Analysis ◽  
Prognostic Biomarker ◽  
Area Under The Curve ◽  
Coagulation Factor ◽  
The Cancer Genome Atlas ◽  
Factor V ◽  
Kaplan Meier ◽  
Km Plotter ◽  
Gastric Cancer Patients

Association of Coagulation factor V (F5) polymorphisms with the occurrence of many types of cancers has been widely reported, but whether it is of prognostic relevance in some cancers remain to be resolved. The RNA-sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA). The potential of F5 genes to predict the survival time of gastric cancer (GC) patients was investigated using univariate and multivariate survival analysis whereas “Kaplan-Meier plotter” (KM-plotter) online tools were employed to validate the outcomes. TCGA data revealed that F5 mRNA levels were significantly upregulated in gastric cancer samples. Survival analysis confirmed that high levels of F5 mRNA correlated with short overall survival (OS) in gastric cancer patients, and the area under the curve (AUC) values of 1-, 2-, and 5-year OS rate were 0.554, 0.593, and 0.603, respectively. Survival analysis by KM-plotter indicated that the high expression of F5 mRNA was significantly associated with a shorter OS compared with the low expression level in all patients with GC, and this was also the case for patients in stage III (hazard ratio HR=1.78, P=0.017). These findings suggest that the F5 gene is significantly upregulated in GC tumour tissues, and may be a potential prognostic biomarker for GC.

OScc: an online survival analysis web server to evaluate the prognostic value of biomarkers in cervical cancer

2019 ◽  
Vol 15 (32) ◽  
pp. 3693-3699 ◽  
Author(s):  
Qiang Wang ◽  
Lu Zhang ◽  
Zhongyi Yan ◽  
Longxiang Xie ◽  
Yang An ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Web Server ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
P Value ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
The Web

Aim: To establish a web server that can mutually validate prognostic biomarkers of cervical cancer. Methods: Four datasets including expression profiling and relative clinical follow-up data were collected from Gene Expression Omnibus and The Cancer Genome Atlas. The web server was developed by R software. Results: The web server was named OScc including 690 patients and can be accessed at http://bioinfo.henu.edu.cn/CESC/CESCList.jsp . The Kaplan–Meier survival curves with log-rank p-value and hazard ratio will be generated of interested gene in OScc. Compared with previous predictive tools, OScc had the advantages of registration-free, larger sample size and subgroup analysis. Conclusion: The OScc is highly valuable to perform the preliminary assessment and validation of new or interested prognostic biomarkers for cervical cancer.

scholarly journals OncoLnc: Linking TCGA survival data to mRNAs, miRNAs, and lncRNAs

2016 ◽  
Author(s):  
Jordan Anaya
Keyword(s):  
Survival Data ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Expression Data ◽  
Rna Seq ◽  
Kaplan Meier ◽  
Specific Cancer ◽  
Cancer Genome Atlas ◽  
Cancer Studies ◽  
Publication Quality

OncoLnc is a tool for interactively exploring survival correlations, and for downloading clinical data coupled to expression data for mRNAs, miRNAs, or lncRNAs. OncoLnc contains survival data for 8,647 patients from 21 cancer studies performed by The Cancer Genome Atlas (TCGA), along with RNA-SEQ expression for mRNAs and miRNAs from TCGA, and lncRNA expression from MiTranscriptome beta. Storing this data gives users the ability to separate patients by gene expression, and then create publication-quality Kaplan-Meier plots or download the data for further analyses. OncoLnc also stores precomputed survival analyses, allowing users to quickly explore survival correlations for up to 21 cancers in a single click. This resource allows researchers studying a specific gene to quickly investigate if it may have a role in cancer, and the supporting data allows researchers studying a specific cancer to identify the mRNAs, miRNAs, and lncRNAs most correlated with survival, and researchers looking for a novel lncRNA involved with cancer lists of potential candidates. OncoLnc is available at http://www.oncolnc.org

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