The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer

Xu, Qili; Song, Aili; Xie, Qingji

doi:10.1177/1533033820940440

Cited by 7 publications

(4 citation statements)

References 57 publications

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“…PTK2B is one of the FAKs, also known to be associated with lymph nodes, tumor size and pathologic state in thyroid cancer samples. 85 Moreover, a combinatorial drug Crizotinib (receptor tyrosine kinase targeting drug) was proven effective in reducing tumor size of triple negative breast cancer graft when used along with erlotinib (EGFR targeting drug). 86 PTK2B is also one of the targets for the drug Crizotinib.…”

Section: Discussionmentioning

confidence: 99%

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

Almansoori

Bhamidimarri

Bendardaf

et al. 2022

IJGM

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Background Thyroid cancer is the most common endocrine malignancy. However, the molecular mechanism involved in its pathogenesis is not well characterized. Purpose The objective of this study is to identify key cellular pathways and differentially expressed genes along the thyroid cancer pathogenesis sequence as well as to identify potential prognostic and therapeutic targets. Methods Publicly available transcriptomics data comprising a total of 95 samples consisting of 41 normal, 28 non-aggressive and 26 metastatic papillary thyroid carcinoma (PTC) cases were used. Transcriptomics data were normalized and filtered identifying 9394 differentially expressed genes. The genes identified were subjected to pathway analysis using absGSEA identifying PTC related pathways. Three of the genes identified were validated on 508 thyroid cancer biopsies using RNAseq and TNMplot. Results Pathway analysis revealed a total of 2193 differential pathways among non-aggressive samples and 1969 among metastatic samples compared to normal tissue. Pathways for non-aggressive PTC include calcium and potassium ion transport, hormone signaling, protein tyrosine phosphatase activity and protein tyrosine kinase activity. Metastatic pathways include growth, apoptosis, activation of MAPK and regulation of serine threonine kinase activity. Genes for non-aggressive are KCNQ1, CACNA1D, KCNN4, BCL2, and PTK2B and metastatic PTC are EGFR, PTK2B, KCNN4 and BCL2. Three of the genes identified were validated using clinical biopsies showing significant overexpression in aggressive compared to non-aggressive PTC; EGFR (p < 0.05), KCNN4 (p < 0.001) and PTK2B (p < 0.001). DrugBank database search identified several FDA approved drug targets including anti-EGFR Vandetanib used to treat thyroid cancer in addition to others that may prove useful in treating PTC. Conclusion Transcriptomics analysis identified putative prognostic targets including EGFR, PTK2B, BCL2, KCNQ1, KCNN4 and CACNA1D. EGFR, PTK2B and KCN44 were validated using thyroid cancer clinical biopsies. The drug search identified FDA approved drugs including Vandetanib in addition to others that may prove useful in treating the disease.

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Section: Discussionmentioning

confidence: 99%

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

Almansoori

Bhamidimarri

Bendardaf

et al. 2022

IJGM

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“…OTUD4, LLPH, and ECHDC1 are the three most important target genes in the miRNA-target gene regulatory network. OTUD4 is the fifth frequently mutated gene in thyroid cancer, and its mutation rate in the thyroid is 2% [ 46 ]. LLPH and ECHDC1 are new biomarkers for the development of HT.…”

Section: Discussionmentioning

confidence: 99%

Integrative Analyses of Genes Associated with Hashimoto’s Thyroiditis

Qiu

Zeng

et al. 2021

Journal of Immunology Research

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Objective. Hashimoto’s thyroiditis, also known as chronic lymphocytic thyroiditis, is a common autoimmune thyroiditis, which mostly occurs in young and middle-aged women. It can be manifested as hyperthyroidism in the early stage; hypothyroidism may appear with the progression of the disease. Studies have shown that multiple factors such as heredity, environment, and autoimmunity are involved in the pathogenesis, but the specific mechanism is not clear. In our study, we tried to find key genes and potential molecular mechanisms of Hashimoto’s thyroiditis to provide new ideas for the therapeutic targets of Hashimoto’s thyroiditis. Method. GSE138198 and GSE54958 were downloaded from the GEO database, and two datasets were combined for analysis. The combined data were normalized to identify the differentially expressed genes (DEGs), and GO and KEGG enrichment analyses were performed. Protein-protein interaction (PPI) networks and hub genes between DEGs were identified. We also used the miRWalk database to identify regulatory miRNAs associated with expressions of DEGs. Result. We identified 182 DEGs (160 upregulated and 22 downregulated) between Hashimoto’s disease patients and the healthy control group. GO analysis showed that DEGs were mostly concentrated in detection of chemical stimulus involved in sensory perception, intermediate filament cytoskeleton, and olfactory receptor activity. KEGG pathway analysis showed that DEGs were mainly related to olfactory transduction. Some members of the KRTAP family and HTR5A, KNG1, DRD3, HTR1D, TAS2R16, INSL5, TAS2R42, and GRM7 are the most important hub genes in the PPI network. In addition, we recognized that OTUD4, LLPH, and ECHDC1 were the most important hub genes in the miRNA-target gene network. Conclusion. In this study, a series of bioinformatics analyses of DEGs were performed to identify the key genes and pathways associated with Hashimoto’s thyroiditis. These genes and pathways provide a more detailed understanding of the pathogenesis of Hashimoto’s disease and provide new ideas for the therapeutic targets of Hashimoto’s thyroiditis.

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“…HYOU1 was reported to promote tumor cell proliferation and metastasis through PI3K/AKT signaling in epithelial ovarian cancer 52 . Integrin subunit alpha L was reported to be relevant to thyroid cancer by bioinformatic study 53 .…”

Section: Discussionmentioning

confidence: 99%

Identification of biomarkers and signaling pathways during the treatment of multiple myeloma

2021

Preprint

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Multiple myeloma (MM) is an incurable hematologic malignancy, which is characterized by increased bone marrow plasma cells, osteolytic lesions, and anemia. Here, our aim is to characterize significant biomarkers and signaling pathways during the treatment of MM by using bioinformatic methods. The GSE180018 dataset was generated by DNBSEQ-G400 (Homo sapiens). The KEGG and GO analyses showed the biological processes such as " Protein export”, “Protein processing in endoplasmic reticulum”, “Vibrio cholerae infection”, “Fc gamma R-mediated phagocytosis" are mainly affected in FOXM1 KO MM cells. Moreover, we identified the significant genes including CD44, NOTCH1, SELL, RAC2, HSPA8, VAV1, DDIT3, PLK1, HYOU1, ITGAL in FOXM1 KO MM cells. Therefore, our study may provide further guidance for the drug development of MM.

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The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer

Cited by 7 publications

References 57 publications

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

Integrative Analyses of Genes Associated with Hashimoto’s Thyroiditis

Identification of biomarkers and signaling pathways during the treatment of multiple myeloma

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