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Published on: July 22, 2020
The Identification of Three Key Genes Related to Stemness in Thyroid Carcinoma through Comprehensive Analysis
Tonglong Zhang1, Chunhong Yan1, Zhengdu Ye1
1Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Background:
Tumor heterogeneity imposes great challenges on cancer treatment. Cancer stem cells (CSCs) are a leading factor contributing to tumor occurrence. However, the mechanisms underlying the growth of thyroid cancer (TCHA) are still unclear.
Methods:
Key genes regulating the characteristics of THCA, such as stemness were identified by combining gene expressions of samples downloaded from the Cancer Genome Atlas (TCGA) and were used to establish an mRNA expression stemness index (mRNAsi) through machine learningbased methods. The relationships of mRNAsi, THCA clinical features and molecular subtypes were analyzed. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to obtain mRNAsi-related gene modules and determine mRNAsi-related differentially co-expressed genes. Key genes related to mRNAsi were screened by protein interaction network. Functional analysis was conducted and expressions of key genes were verified in multiple external data sets.
Results:
The mRNAsi score, which was found to be lower in the TCHA tissues than that in normal tissues (p<0.05), was positively correlated with a slow progression of tumor prognosis (p=0.0085). We screened a total of 83 differentially co-expressed genes related to mRNAsi and multiple tumor pathways such as apoptosis, tight junction, cytokine-cytokine receptor interaction, and cAMP signaling pathway (p<0.05). Finally, 28 protein interaction networks incorporating 32 genes were established, and 3 key genes were identified through network mining. 3 core genes were finally determined, as their low expressions were strongly correlated with the progression of THCA.
Conclusion:
The study found that NGF, FOS, and GRIA1 are closely related to the characteristics of THCA stem cells. These genes, especially FOS, are highly indicative of the prognosis of THCA patients. Thus, screening therapy could be used to inhibit the stemness of TCHA.
Insights
Thyroid cancer stemness is linked to poor prognosis. Key genes like FOS, NGF, and GRIA1 were identified, offering potential targets for new therapies to inhibit cancer stem cell growth.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Tumor heterogeneity presents significant challenges in cancer treatment.
- Cancer stem cells (CSCs) are a primary driver of tumor development.
- Mechanisms governing thyroid cancer (THCA) growth remain incompletely understood.
Purpose of the Study:
- To identify key genes regulating thyroid cancer stemness.
- To establish an mRNA expression stemness index (mRNAsi) for THCA.
- To analyze the correlation between mRNAsi, clinical features, and molecular subtypes of THCA.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) gene expression data.
- Developed an mRNAsi using machine learning.
- Performed Weighted Gene Co-Expression Network Analysis (WGCNA) and protein-protein interaction network analysis.
- Validated key gene expressions across multiple datasets.
Main Results:
- Lower mRNAsi scores in THCA tissues correlated with better prognosis.
- Identified 83 differentially co-expressed genes linked to THCA stemness and pathways like apoptosis and cytokine-cytokine interaction.
- Discovered 3 key genes (NGF, FOS, GRIA1) whose low expression is associated with THCA progression.
Conclusions:
- NGF, FOS, and GRIA1 are crucial for THCA stem cell characteristics.
- FOS expression is a strong indicator of THCA patient prognosis.
- Targeted therapies inhibiting stemness, particularly focusing on FOS, could be a promising therapeutic strategy for THCA.
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