&lt;p&gt;A Novel Prognostic Score Based on &lt;em&gt;ZG16&lt;/em&gt; for Predicting CRC Survival&lt;/p&gt;

Wang, Wei; Sun, Jian-Fang; Wang, Xiaozhong; Ying, Hou-Qun; Sun, Fan

doi:10.2147/pgpm.s275941

Cited by 2 publications

(1 citation statement)

References 23 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The MFs terms chloride channel activity [ 95 ] was associated with CLCA4. The metallopeptidase activity [ 96 ] was associated with MMP7. Among the enriched CCs, anchored component of plasma membrane [ 98 ] was associated with CA4.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

et al. 2023

View full text Add to dashboard Cite

Background Detection of appropriate receptor proteins and drug agents are equally important in the case of drug discovery and development for any disease. In this study, an attempt was made to explore colorectal cancer (CRC) causing molecular signatures as receptors and drug agents as inhibitors by using integrated statistics and bioinformatics approaches. Methods To identify the important genes that are involved in the initiation and progression of CRC, four microarray datasets (GSE9348, GSE110224, GSE23878, and GSE35279) and an RNA_Seq profiles (GSE50760) were downloaded from the Gene Expression Omnibus database. The datasets were analyzed by a statistical r-package of LIMMA to identify common differentially expressed genes (cDEGs). The key genes (KGs) of cDEGs were detected by using the five topological measures in the protein–protein interaction network analysis. Then we performed in-silico validation for CRC-causing KGs by using different web-tools and independent databases. We also disclosed the transcriptional and post-transcriptional regulatory factors of KGs by interaction network analysis of KGs with transcription factors (TFs) and micro-RNAs. Finally, we suggested our proposed KGs-guided computationally more effective candidate drug molecules compared to other published drugs by cross-validation with the state-of-the-art alternatives of top-ranked independent receptor proteins. Results We identified 50 common differentially expressed genes (cDEGs) from five gene expression profile datasets, where 31 cDEGs were downregulated, and the rest 19 were up-regulated. Then we identified 11 cDEGs (CXCL8, CEMIP, MMP7, CA4, ADH1C, GUCA2A, GUCA2B, ZG16, CLCA4, MS4A12 and CLDN1) as the KGs. Different pertinent bioinformatic analyses (box plot, survival probability curves, DNA methylation, correlation with immune infiltration levels, diseases-KGs interaction, GO and KEGG pathways) based on independent databases directly or indirectly showed that these KGs are significantly associated with CRC progression. We also detected four TFs proteins (FOXC1, YY1, GATA2 and NFKB) and eight microRNAs (hsa-mir-16-5p, hsa-mir-195-5p, hsa-mir-203a-3p, hsa-mir-34a-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-429, and hsa-mir-335-5p) as the key transcriptional and post-transcriptional regulators of KGs. Finally, our proposed 15 molecular signatures including 11 KGs and 4 key TFs-proteins guided 9 small molecules (Cyclosporin A, Manzamine A, Cardidigin, Staurosporine, Benzo[A]Pyrene, Sitosterol, Nocardiopsis Sp, Troglitazone, and Riccardin D) were recommended as the top-ranked candidate therapeutic agents for the treatment against CRC. Conclusion The findings of this study recommended that our proposed target proteins and agents might be considered as the potential diagnostic, prognostic and therapeutic signatures for CRC.

show abstract

Section: Discussionmentioning

confidence: 99%

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

et al. 2023

View full text Add to dashboard Cite

show abstract

Comprehensive bioinformatics analysis reveals CLCA1 and ZG16 as predictive biomarkers of malignant progression in colorectal cancer

Zhang,

Wang,

Wang

et al. 2024

Preprint

View full text Add to dashboard Cite

Background Colorectal cancer (CRC) is one of the most common malignant tumors. CLCA1 and ZG16 are lowly expressed in CRC, and we wanted to investigate whether they could be prognostic biomarkers for the malignant progression of CRC. Methods 12,195 DEGs and 12,071 DEGs were identified through the GSE39582 dataset and TCGA dataset, and then 50 coexisting genes were selected for further analysis using Venn diagrams. These 50 DEGs were then subjected to GO and KEGG functional enrichment analyses, along with genome-wide GSEA. the first 5 core genes were identified and visualized using Cytoscape through the PPI network. Then the expression of ZG16 and CLCA1 in normal and tumor tissues were analyzed using GSE39582 and TCGA datasets, and correlation analysis, and survival analysis were performed. The expression of ZG16 and CLCA1 in CRC cells was verified by qRT-PCR, and cell proliferation, migration, and invasion abilities were detected by CCK-8, scratch assay, clone formation assay, and Transwell assay. Results The expression levels of ZG16 and CLCA1 were significantly lower in tissues from CRC patients than in normal tissues. Survival analysis showed that low expression of ZG16 and CLCA1 was associated with poor survival outcomes. Multifactorial analysis showed that low expression of ZG16 and CLCA1 was an independent risk factor affecting tumor prognosis. Cellular experiments showed that cell proliferation, migration, and invasion were inhibited after overexpression of ZG16 and CLCA1. Correlation analysis showed that ZG16 and CLCA1 expression levels were positively correlated and the correlation was statistically significant. GSEA enrichment analysis based on CLCA1-related genes and ZG16-related genes (FDR < 0.25, P < 0.05) revealed that the related genes of both genes were closely related to the GNRH SINALINGPATHWAYES pathway. Conclusion CLCA1 and ZG16, which are lowly expressed in CRC tissues, are associated with poor prognosis of CRC and may be one of the markers for diagnostic screening and prediction of prognostic outcome in CRC. Meanwhile, CLCA1 and ZG16 may also be new targets for tumor immunotherapy.

show abstract

<p>A Novel Prognostic Score Based on <em>ZG16</em> for Predicting CRC Survival</p>

Cited by 2 publications

References 23 publications

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

Comprehensive bioinformatics analysis reveals CLCA1 and ZG16 as predictive biomarkers of malignant progression in colorectal cancer

Contact Info

Product

Resources

About