CDK4 Amplification in Esophageal Squamous Cell Carcinoma Associated With Better Patient Outcome

Huang, Jie; Wang, Xiang; Zhang, Xue; Chen, Weijie; Luan, Lan; Song, Qibin; Wang, Hao; Liu, Jia; Xu, Lei; Xu, Yifan; Shen, Licheng; Tan, Lijie; Jiang, Dongxian; Su, Jieakesu; Hou, Yingyong

doi:10.3389/fgene.2021.616110

Cited by 2 publications

(2 citation statements)

References 39 publications

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“…Gao et al [ 64 ] demonstrated that High Mobility Group Box 3 ( HMBG3 ) may be a potential molecular marker for predicting the prognosis of ESCC patients. According to Huang et al [ 65 ], cyclin-dependent kinase 4 ( CDK4 ) amplification was identified as an independent prognostic factor for survival, which could be incorporated into the tumor-node-metastasis staging system to refine risk stratification of patients with esophageal squamous cell carcinoma. Ling et al [ 66 ] suggested that MutS Homolog 2 ( MSH2 ) methylation in the plasma would be a good predictor of DFS for these ESCC patients before oesophagectomy.…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Biomarkers Using Integrative Approach: A Case Study of ESCC

2022

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This paper presents a consensus-based approach that incorporates three microarray and three RNA-Seq methods for unbiased and integrative identification of differentially expressed genes (DEGs) as potential biomarkers for critical disease(s). The proposed method performs satisfactorily on two microarray datasets (GSE20347 and GSE23400) and one RNA-Seq dataset (GSE130078) for esophageal squamous cell carcinoma (ESCC). Based on the input dataset, our framework employs specific DE methods to detect DEGs independently. A consensus based function that first considers DEGs common to all three methods for further downstream analysis has been introduced. The consensus function employs other parameters to overcome information loss. Differential co-expression (DCE) and preservation analysis of DEGs facilitates the study of behavioral changes in interactions among DEGs under normal and diseased circumstances. Considering hub genes in biologically relevant modules and most GO and pathway enriched DEGs as candidates for potential biomarkers of ESCC, we perform further validation through biological analysis as well as literature evidence. We have identified 25 DEGs that have strong biological relevance to their respective datasets and have previous literature establishing them as potential biomarkers for ESCC. We have further identified 8 additional DEGs as probable potential biomarkers for ESCC, but recommend further in-depth analysis.

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Section: Discussionmentioning

confidence: 99%

Identification of Potential Biomarkers Using Integrative Approach: A Case Study of ESCC

2022

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“…There are two major subtypes of Esophageal cancer (EC), esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) (Ye et al, 2021). In China, more than 90% of esophageal cancer cases are ESCC (Zhang X. et al, 2021). EC as a whole remains a significant challenge globally, having the 8 th highest incidence and the 6th highest mortality worldwide killing over 500,000 people in 2020 (Sung et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Drug repositioning for esophageal squamous cell carcinoma

Bennett

Huang

et al. 2022

Front. Genet.

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Esophageal cancer (EC) remains a significant challenge globally, having the 8th highest incidence and 6th highest mortality worldwide. Esophageal squamous cell carcinoma (ESCC) is the most common form of EC in Asia. Crucially, more than 90% of EC cases in China are ESCC. The high mortality rate of EC is likely due to the limited number of effective therapeutic options. To increase patient survival, novel therapeutic strategies for EC patients must be devised. Unfortunately, the development of novel drugs also presents its own significant challenges as most novel drugs do not make it to market due to lack of efficacy or safety concerns. A more time and cost-effective strategy is to identify existing drugs, that have already been approved for treatment of other diseases, which can be repurposed to treat EC patients, with drug repositioning. This can be achieved by comparing the gene expression profiles of disease-states with the effect on gene-expression by a given drug. In our analysis, we used previously published microarray data and identified 167 differentially expressed genes (DEGs). Using weighted key driver analysis, 39 key driver genes were then identified. These driver genes were then used in Overlap Analysis and Network Analysis in Pharmomics. By extracting drugs common to both analyses, 24 drugs are predicted to demonstrate therapeutic effect in EC patients. Several of which have already been shown to demonstrate a therapeutic effect in EC, most notably Doxorubicin, which is commonly used to treat EC patients, and Ixazomib, which was recently shown to induce apoptosis and supress growth of EC cell lines. Additionally, our analysis predicts multiple psychiatric drugs, including Venlafaxine, as repositioned drugs. This is in line with recent research which suggests that psychiatric drugs should be investigated for use in gastrointestinal cancers such as EC. Our study shows that a drug repositioning approach is a feasible strategy for identifying novel ESCC therapies and can also improve the understanding of the mechanisms underlying the drug targets.

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CDK4 Amplification in Esophageal Squamous Cell Carcinoma Associated With Better Patient Outcome

Cited by 2 publications

References 39 publications

Identification of Potential Biomarkers Using Integrative Approach: A Case Study of ESCC

Identification of Potential Biomarkers Using Integrative Approach: A Case Study of ESCC

Drug repositioning for esophageal squamous cell carcinoma

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