Opposite Roles of the JMJD1A Interaction Partners MDFI and MDFIC in Colorectal Cancer

Yuan, Shushan; Li, Yongming; Oh, Sangphil; Zhang, Bin; Freeman, Willard M.; Shin, Sook; Janknecht, Ralf

doi:10.1038/s41598-020-65536-6

Cited by 20 publications

(22 citation statements)

References 66 publications

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“…Macartney-Coxson DP et al found that GFRA2 was remarkably down-regulated in the process of CRC and possibly related to liver metastasis [ 21 ]. In mice, the function inhibition of MyoD family inhibitor ( MDFI ) promotes the regeneration of the gastrocnemius muscle after injury [ 22 ]. In addition, MDFI is over expressed in CRC tumors and high expression of MDFI is associated with tumor metastasis [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

“…In mice, the function inhibition of MyoD family inhibitor ( MDFI ) promotes the regeneration of the gastrocnemius muscle after injury [ 22 ]. In addition, MDFI is over expressed in CRC tumors and high expression of MDFI is associated with tumor metastasis [ 22 ]. In this study, we found that down-regulated GFRA2 and up-regulated MDFI were differentially expressed-methylated genes in CRC.…”

Section: Discussionmentioning

confidence: 99%

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Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database

et al. 2022

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Background Colorectal cancer (CRC) is major cancer-related death. The aim of this study was to identify differentially expressed and differentially methylated genes, contributing to explore the molecular mechanism of CRC. Methods Firstly, the data of gene transcriptome and genome-wide DNA methylation expression were downloaded from the Gene Expression Omnibus database. Secondly, functional analysis of differentially expressed and differentially methylated genes was performed, followed by protein-protein interaction (PPI) analysis. Thirdly, the Cancer Genome Atlas (TCGA) dataset and in vitro experiment was used to validate the expression of selected differentially expressed and differentially methylated genes. Finally, diagnosis and prognosis analysis of selected differentially expressed and differentially methylated genes was performed. Results Up to 1958 differentially expressed (1025 up-regulated and 993 down-regulated) genes and 858 differentially methylated (800 hypermethylated and 58 hypomethylated) genes were identified. Interestingly, some genes, such as GFRA2 and MDFI, were differentially expressed-methylated genes. Purine metabolism (involved IMPDH1), cell adhesion molecules and PI3K-Akt signaling pathway were significantly enriched signaling pathways. GFRA2, FOXQ1, CDH3, CLDN1, SCGN, BEST4, CXCL12, CA7, SHMT2, TRIP13, MDFI and IMPDH1 had a diagnostic value for CRC. In addition, BEST4, SHMT2 and TRIP13 were significantly associated with patients’ survival. Conclusions The identified altered genes may be involved in tumorigenesis of CRC. In addition, BEST4, SHMT2 and TRIP13 may be considered as diagnosis and prognostic biomarkers for CRC patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database

et al. 2022

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“…While overexpression of MDFI and MDFIC were observed in the brain, gastric and pancreatic tumors. This implicated that MDFI might perform tumor-promoting activities (Sui et al, 2020). Further investigation in colorectal cancer also showed that DNA methylation of MDF1 gene could be considered as an epigenetic biomarker in colorectal cancer (Li et al, 2017).…”

Section: Discussionmentioning

confidence: 94%

ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis

Vafaeie

Nomiri

Ranjbaran

et al. 2022

Asian Pac J Cancer Prev

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Background: Gastric cancer (GC) is a complex disorder with an inadequate response to treatment. Although many efforts have been made to clarify the development of GC, the exact etiology and molecular mechanisms of this malignancy remain unclear. This study was designed to identify and characterize essential associated genes with GC to construct a prognostic model. Methods: In this Insilco study, the gene expression microarray dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO). The raw data were processed and quantile-normalized with the edgeR package of R ver.3.5.3. The module-trait relationship and hub-genes associated with GC were analyzed with Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Cluepedia and Enrichr Database. Finally, hubgenes were screened and validated by GEPIA online database. Results: According to the WGCNA results, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57). DEGs analysis was performed by edgeR package of R and indicated a total of 47 genes as hub-genes. Verifying the hub-genes expression using GEPIA online database showed a significantly increased level of ACAN gene expression in primary cancer cell line compared to metastatic cell line. On the other hand, the expression of MDFI and CHST1 genes in primary cell lines were lower compared to metastatic cancer cell lines. Conclusions: This study provides a framework of the co-expression gene modules ACAN, MDFI, and CHST1 as hub-genes. These hub-genes might offer candidate biomarkers to targeted therapy against GC. Further experiment validation and animal models are needed to reveal the exact mechanism of the above-mentioned genes in the pathogenesis and prognoses of GC.

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“…MDFIC also influences signal transduction pathways including the Wnt/β-catenin and JNK pathways [ 76 , 77 ]. MDFIC is epigenetically silenced in cancerous hematopoietic cell lines, suggesting it may function as a tumor suppressor [ 78 ], an idea supported by the observation that ectopic expression of MDFIC suppresses the growth of a colorectal cancer cell line [ 79 ]. Yet the impact of MDFIC on cancer cells may be cancer cell-specific, as MDFIC expression enhanced the chemoresistance of cancer stem cells in a lung cancer cell model [ 80 ].…”

Section: Resultsmentioning

confidence: 99%

RELT stains prominently in B-cell lymphomas and binds the hematopoietic transcription factor MDFIC

Cusick

Alhomsy

Wong

et al. 2020

Biochemistry and Biophysics Reports

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Receptor Expressed in Lymphoid Tissues (RELT) is a human tumor necrosis factor receptor superfamily member (TNFRSF) that is expressed most prominently in cells and tissues of the hematopoietic system. RELL1 and RELL2 are two homologs that physically interact with RELT and co-localize with RELT at the plasma membrane. This study sought to further elucidate the function of RELT by identifying novel protein interactions with RELT family members. The transcription factor MyoD family inhibitor domain-containing (MDFIC) was identified in a yeast two-hybrid genetic screen using RELL1 as bait. MDFIC co-localizes with RELT family members at the plasma membrane; this co-localization was most prominently observed with RELL1 and RELL2. In vitro co-immunoprecipitation (Co-IP) was utilized to demonstrate that MDFIC physically interacts with RELT, RELL1, and RELL2. Co-IP using deletion mutants of MDFIC and RELT identified regions important for physical association between MDFIC and RELT family members and a computational analysis revealed that RELT family members are highly disordered proteins. Immunohistochemistry of normal human lymph nodes revealed RELT staining that was most prominent in macrophages. Interestingly, the level of RELT staining significantly increased progressively in low and high-grade B-cell lymphomas versus normal lymph nodes. RELT co-staining with CD20 was observed in B-cell lymphomas, indicating that RELT is expressed in malignant B cells. Collectively, these results further our understanding of RELT-associated signaling pathways, the protein structure of RELT family members, and provide preliminary evidence indicating an association of RELT with B-cell lymphomas.

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Opposite Roles of the JMJD1A Interaction Partners MDFI and MDFIC in Colorectal Cancer

Cited by 20 publications

References 66 publications

Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database

Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database

ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis

RELT stains prominently in B-cell lymphomas and binds the hematopoietic transcription factor MDFIC

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