Bioinformatics Tools (and Web Server) for Cancer Biomarker Development

Editorial

20 October 2020

Editorial: Bioinformatics Tools (and Web Server) for Cancer Biomarker Development

Longxiang Xie

Liuyang Wang

Wan Zhu

Jing Zhao

and

Xiangqian Guo

4,910 views

3 citations

Editors

Chongqing Medical University

Impact

Original Research

21 July 2020

VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis

Qingshan Ni

, 9 more and

Ying Wan

8,650 views

9 citations

Correlations between overall survival (OS)/progression-free survival (PFS) and single-nucleotide polymorphism array (SNP-A) detections in patients with myelodysplastic syndrome (MDS). Comparison of the MDS patients with and without SNP-A aberrations in OS (A) and PFS (B). Comparison of the MDS patients with abnormal SNP-A detections and without such additional SNP-A aberrations in OS (C) and PFS (D) of the normal or good cytogenetic findings by metaphase cytogenetics (MC). Comparison of the MDS patients with and without SNP-A aberrations in OS (E) and PFS (F) of the high-risk group. Comparison of the MDS patients with and without SNP-A aberrations in OS (G) and PFS (H) of the low-risk group.

Original Research

07 July 2020

Single-Nucleotide Polymorphism Array Technique Generating Valuable Risk-Stratification Information for Patients With Myelodysplastic Syndromes

Xia Xiao

, 13 more and

Zonghong Shao

3,008 views

3 citations

Correlation between the clinico-pathologic characteristics and overall survival of lung cancer in Online Consensus Survival for Lung Cancer (OSluca). (A) Correlation between histological types and OS. (B) Correlation between gender and OS. (C) Correlation between tumor stages and OS. (D) Correlation between p-TNM stages and OS. (E) Correlation between smoking status and OS. OS, overall survival; AD, adenocarcinoma; SCC, squamous cell carcinoma; LCC, large cell cancer.

Original Research

26 May 2020

OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer

Zhongyi Yan

, 12 more and

Xiangqian Guo

3,948 views

18 citations

Original Research

02 April 2020

Analysis of the Interaction Network of Hub miRNAs-Hub Genes, Being Involved in Idiopathic Pulmonary Fibers and Its Emerging Role in Non-small Cell Lung Cancer

Dong Hu Yu

, 6 more and

Sheng Li

Flow chart of data preparation, processing, analysis, and validation.

Idiopathic pulmonary fibrosis (IPF) is a fibrotic interstitial lung disease with lesions confined to the lungs. To identify meaningful microRNA (miRNA) and gene modules related to the IPF progression, GSE32537 (RNA-sequencing data) and GSE32538 (miRNA-sequencing data) were downloaded and processed, and then weighted gene co-expression network analysis (WGCNA) was applied to construct gene co-expression networks and miRNA co-expression networks. GSE10667, GSE70866, and GSE27430 were used to make a reasonable validation for the results and evaluate the clinical significance of the genes and the miRNAs. Six hub genes (COL3A1, COL1A2, OGN, COL15A1, ASPN, and MXRA5) and seven hub miRNAs (hsa-let-7b-5p, hsa-miR-26a-5p, hsa-miR-25-3p, hsa-miR-29c-3p, hsa-let-7c-5p, hsa-miR-29b-3p, and hsa-miR-26b-5p) were clarified and validated. Meanwhile, iteration network of hub miRNAs-hub genes was constructed, and the emerging role of the network being involved in non-small cell lung cancer (NSCLC) was also analyzed by several webtools. The expression levels of hub genes were different between normal lung tissues and NSCLC tissues. Six genes (COL3A1, COL1A2, OGN, COL15A1, ASPN, and MXRA5) and three miRNAs (hsa-miR-29c-3p, hsa-let-7c-5p, and hsa-miR-29b-3p) were related to the survival time of lung adenocarcinoma (LUAD). The interaction network of hub miRNAs-hub genes might provide common mechanisms involving in IPF and NSCLC. More importantly, useful clues were provided for clinical treatment of both diseases based on novel molecular advances.

8,996 views

41 citations

Correlation of CD38 expression with immune infiltration level in epithelial ovarian cancer. (A) CD38 expression is significantly negatively related to tumor purity and has significant positive correlations with infiltrating levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells from TIMER database. (B–E) CD38 expression has significant positive correlations with active CD8+ T cells, active CD4+ T cells, and active B cells, other than memory B cells.

Original Research

30 April 2020

CD38 Predicts Favorable Prognosis by Enhancing Immune Infiltration and Antitumor Immunity in the Epithelial Ovarian Cancer Microenvironment

Ying Zhu

, 3 more and

Jianwei Zhou

4,839 views

25 citations

Visualization and enrichment analysis of differentially expressed genes. (A) The heatmap of the top 50 DEGs. (B) GO enrichment analysis of differentially expressed genes. BP, biological process; CC, cellular component; MF, molecular function; (C) KEGG enrichment analysis of differentially expressed genes. The size of the dot represents the count number of genes in one KEGG term.

Original Research

31 March 2020

Integrated Analysis to Evaluate the Prognostic Value of Signature mRNAs in Glioblastoma Multiforme

Ji’an Yang

, 7 more and

Qianxue Chen

5,091 views

16 citations

Listed pictures are five representative functional gene sets enriched in CRC with MAD2L1 highly expressed.

Original Research

21 February 2020

Identification of Core Gene Expression Signature and Key Pathways in Colorectal Cancer

Xiang Ding

, 1 more and

Hesheng Luo

13,162 views

72 citations

(A) The options of input parameters used in the prognostic analysis of MGMT in OSgbm. (B) The output web page of prognosis analysis of MGMT using a combined cohort with pooling all datasets together in OSgbm. (C) The OSgbm output of gene MGMT in single cohort.

Original Research

21 February 2020

OSgbm: An Online Consensus Survival Analysis Web Server for Glioblastoma

Huan Dong

, 13 more and

Xiangqian Guo

6,401 views

20 citations

Review

05 February 2020

Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Hong Zheng

, 11 more and

Xiangqian Guo

Prognostic biomarkers are of great significance to predict the outcome of patients with cancer, to guide the clinical treatments, to elucidate tumorigenesis mechanisms, and offer the opportunity of identifying therapeutic targets. To screen and develop prognostic biomarkers, high throughput profiling methods including gene microarray and next-generation sequencing have been widely applied and shown great success. However, due to the lack of independent validation, only very few prognostic biomarkers have been applied for clinical practice. In order to cross-validate the reliability of potential prognostic biomarkers, some groups have collected the omics datasets (i.e., epigenetics/transcriptome/proteome) with relative follow-up data (such as OS/DSS/PFS) of clinical samples from different cohorts, and developed the easy-to-use online bioinformatics tools and web servers to assist the biomarker screening and validation. These tools and web servers provide great convenience for the development of prognostic biomarkers, for the study of molecular mechanisms of tumorigenesis and progression, and even for the discovery of important therapeutic targets. Aim to help researchers to get a quick learning and understand the function of these tools, the current review delves into the introduction of the usage, characteristics and algorithms of tools, and web servers, such as LOGpc, KM plotter, GEPIA, TCPA, OncoLnc, PrognoScan, MethSurv, SurvExpress, UALCAN, etc., and further help researchers to select more suitable tools for their own research. In addition, all the tools introduced in this review can be reached at http://bioinfo.henu.edu.cn/WebServiceList.html.

25,604 views

99 citations