CRC-EBD: Epigenetic Biomarker Database for Colorectal Cancer

Liu, Xingyun; Zhang, Xueli; Chen, Jing; Ye, Benchen; Ren, Shumin; Lin, Yuxin; Sun, Xiao‐Feng; Zhang, Hong; Shen, Bairong

doi:10.3389/fgene.2020.00907

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…The ClusterR5 mainly involved in the ion transport channels, cell–cell communication and digestion and absorption‐related Reactome pathways. CA4 gene of the ClusterR5 is a known diagnostic and prognostic biomarker for CRC 32,33 . The analysis of disease‐gene associations revealed that 10 genes (FEN1, GCG, ACTG2, LY96, TPX2, AURKA, GPNMB, ITGA7, LIG1, and SCNN1B) part of the identified clustered from Reactome analysis (Figure S12).…”

Section: Resultsmentioning

confidence: 99%

Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer

Mahajan,

Sarkar,

Mondal

2024

Cancer Medicine

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IntroductionCross‐talk among biological pathways is essential for normal biological function and plays a significant role in cancer progression. Through integrated network analysis, this study explores the significance of pathway cross‐talk in colorectal cancer (CRC) development at both the pathway and gene levels.MethodsIn this study, we integrated the gene expression data with domain knowledge to construct state‐dependent pathway cross‐talk networks. The significance of the genes involved in pathway cross‐talk was assessed by analyzing their association with cancer hallmarks, disease‐gene relation, genetic alterations, and survival analysis. We also analyzed the gene regulatory network to identify the dysregulated genes and their role in CRC progression.ResultsCross‐talk was observed between immune‐related pathways and pathways associated with cell communication and signaling. The PTPRC gene was identified as a mediator, facilitating interactions within the immune system and other signaling pathways. The rewired interactions of ITGA7 were identified as influential in the epithelial‐mesenchymal transition in CRC. This study also highlighted the crucial link between cell communication and vascular smooth muscle contraction pathway in CRC progression. The survival analysis of identified gene clusters showed their significant prognostic value in distinguishing high‐risk from low‐risk CRC groups, and L1000CDS2 revealed seven potential drug molecules in CRC. Nine dysregulated genes (CTNNB1, EP300, JUN, MYC, NFKB1, RELA, SP1, STAT1, and TP53) emerge as transcription factors acting as common regulators across various pathways.ConclusionsThis study highlights the crucial role of pathway cross‐talk in CRC progression and identified the potential prognostic biomarkers and potential drug molecules.

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Section: Resultsmentioning

confidence: 99%

Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer

Mahajan,

Sarkar,

Mondal

2024

Cancer Medicine

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“…org. cn/ EBD/, Liu et al 2020) was also explored to know if the gene already has reported as a biomarker for the CRC.…”

Section: Identification and Analysis Of Modules Hub Genes And Sub-net...mentioning

confidence: 99%

Cell cycle protein BORA is associated with colorectal cancer progression by AURORA-PLK1 cascades: a bioinformatics analysis

Mahajan

Sarkar

Mondal

2022

J. Cell Commun. Signal.

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Colorectal cancer (CRC) is the third most diagnosed cancer in the world. A better understanding of the molecular mechanism of CRC is essential for making novel strategies for the CRC management and its prevention. The present study aims to explore the molecular mechanism through integrated bioinformatics analysis by analyzing genes and their co‐expression pattern in normal and CRC states. GSE110223, GSE110224 and GSE113513 gene expression profiles were analyzed in this study. The co‐expression networks for normal and tumor samples were constructed separately and analyzed to identify the modules, sub‐networks and key genes. Gene regulatory network analysis was done to understand the regulatory mechanism of selected genes. Survival analysis was performed for the identified sub‐networks and key genes to understand their role in CRC progression. A total of seven modules were detected and the KEGG pathway analysis revealed these modules were mainly enriched with cell cycle, metabolism and signaling‐related pathways. E2F6 and ETV4 transcription factors regulating the activity of multiple genes of identified modules were found to be up‐regulated in CRC. Six Sub‐networks and seven key genes, BORA, CCT7, DTL, RUVBL1, RUVBL2, THEM6 and TMEM97 associated with the CRC progression were identified. Disease‐gene association analysis identified a novel association of the BORA gene with CRC that activates and regulates the AURORA‐PLK1 cascades in the cell cycle. Survival analysis indicates that the overexpressed BORA is associated with unfavourable overall survival in CRC. The mechanistic role of BORA in the regulation of cell cycle progression suggests that BORA might act as a potential therapeutic target for CRC.

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“…Biomarkers in CBD are classified based on their biological sources into DNA, RNA, protein, and others. As a supplement to CBD, the Epigenetic Biomarker Database for Colorectal Cancer was developed in 2020 to collate epigenetic biomarkers for CRC [ 3 ]. Recently, some relevant biomarker databases have been reported, such as the MarkerDB [ 4 ] and the Cancer Biomarkers database [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

CBD2: A functional biomarker database for colorectal cancer

Zhang,

Li,

et al. 2023

iMeta

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The rapidly evolving landscape of biomarkers for colorectal cancer (CRC) necessitates an integrative, updated repository. In response, we constructed the Colorectal Cancer Biomarker Database (CBD), which collected and displayed the curated biomedicine information for 870 CRC biomarkers in the previous study. Building on CBD, we have now developed CBD2, which includes information on 1569 newly reported biomarkers derived from different biological sources (DNA, RNA, protein, and others) and clinical applications (diagnosis, treatment, and prognosis). CBD2 also incorporates information on nonbiomarkers that have been identified as unsuitable for use as biomarkers in CRC. A key new feature of CBD2 is its network analysis function, by which users can investigate the visible and topological network between biomarkers and identify their relevant pathways. CBD2 also allows users to query a series of chemicals, drug combinations, or multiple targets, to enable multidrug, multitarget, multipathway analyses, toward facilitating the design of polypharmacological treatments for CRC. CBD2 is freely available at http://www.eyeseeworld.com/cbd.

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CRC-EBD: Epigenetic Biomarker Database for Colorectal Cancer

Cited by 11 publications

References 15 publications

Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer

Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer

Cell cycle protein BORA is associated with colorectal cancer progression by AURORA-PLK1 cascades: a bioinformatics analysis

CBD2: A functional biomarker database for colorectal cancer

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