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Comprehensive Profile Analysis Identifies Three Key Genes Related to Stemness in Thyroid Carcinoma

Author(s):

Tonglong Zhang, Chunhong Yan, Zhengdu Ye, Xingling Yin and Tian-an Jiang*   Pages 1 - 12 ( 12 )

Abstract:


Background: Tumor heterogeneity imposes great challenges on cancer treatment. Cancer stem cells (CSCs) are a primary factor in initiating tumor occurrence. However, the mechanisms stem cells in the growth of thyroid cancer (TCHA) are still unclear.

Methods: Key genes regulating the stemness characteristics of THCA were identified by combining gene expressions of samples from the Cancer Genome Atlas (TCGA) and machine learning-based methods to establish an mRNA expression stemness index (mRNAsi). The relationships between mRNAsi, THCA clinical features and molecular subtypes were analyzed. Next, mRNAsi-related gene modules were obtained from Weighted Gene Co-Expression Network Analysis (WGCNA) and used to determine mRNAsi-related differentially co-expressed genes. Key genes related to mRNAsi were acquired through protein interaction network. Functional analysis was performed and expressions of key genes were verified using multiple external data sets.

Results: The mRNAsi score in TCHA tissues was lower than that in normal tissues (p<0.05), and a lower mRNAsi score was positively correlated with a slow progression of tumor prognosis (p=0.0085). 83 differentially co-expressed genes were screened related to mRNAsi and were associated with multiple tumor pathways such as apoptosis, tight junction, cytokinecytokine receptor interaction, and cAMP signaling pathway (p<0.05). Finally, 28 protein interaction networks involving 32 genes were established, and 3 key genes were identified through network mining. The 3 genes were found closely related to each other, with their low expressions correlating strongly with the progression of THCA.

Conclusion: The study found that NGF, FOS, GRIA1 are closely related to the characteristics of THCA stem cells. These genes, especially FOS, are significantly predictive of the prognostic progression of THCA patients. Thus, screening therapy could be use to inhibit the stemness characteristics of TCHA.

Keywords:

Bioinformatics, stemness, prognostic markers, TCGA, thyroid carcinoma.

Affiliation:

Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou , Zhejiang, Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou , Zhejiang, Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou , Zhejiang, Micrometer Biotech, Micrometer Biotech, Hangzhou, Zhejiang, Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou , Zhejiang



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