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Updated: Mar 24, 2026
Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
Published on: August 4, 2016
E2F, HSF2, and miR-26 in thyroid carcinoma: bioinformatic analysis of RNA-sequencing data
Abstract:
In this study, we examined the molecular mechanism of thyroid carcinoma (THCA) using bioinformatics. RNA-sequencing data of THCA (N = 498) and normal thyroid tissue (N = 59) were downloaded from The Cancer Genome Atlas. Next, gene expression levels were calculated using the TCC package and differentially expressed genes (DEGs) were identified using the edgeR package. A co-expression network was constructed using the EBcoexpress package and visualized by Cytoscape, and functional and pathway enrichment of DEGs in the co-expression network was analyzed with DAVID and KOBAS 2.0. Moreover, modules in the co-expression network were identified and annotated using MCODE and BiNGO plugins. Small-molecule drugs were analyzed using the cMAP database, and miRNAs and transcription factors regulating DEGs were identified by WebGestalt. A total of 254 up-regulated and 59 down-regulated DEGs were identified between THCA samples and controls. DEGs enriched in biological process terms were related to cell adhesion, death, and growth and negatively correlated with various small-molecule drugs. The co-expression network of the DEGs consisted of hub genes (ITGA3, TIMP1, KRT19, and SERPINA1) and one module (JUN, FOSB, and EGR1). Furthermore, 5 miRNAs and 5 transcription factors were identified, including E2F, HSF2, and miR-26. miR-26 may participate in THCA by targeting CITED1 and PLA2R1; E2F may participate in THCA by regulating ITGA3, TIMP1, KRT19, EGR1, and JUN; HSF2 may be involved in THCA development by regulating SERPINA1 and FOSB; and small-molecule drugs may have anti-THCA effects. Our results provide novel directions for mechanistic studies and drug design of THCA.
Insights
This study reveals key molecular mechanisms in thyroid carcinoma (THCA) by identifying differentially expressed genes and regulatory networks. Findings suggest potential therapeutic targets and small-molecule drugs for THCA treatment.
Area of Science:
- Genomics
- Bioinformatics
- Oncology
Background:
- Thyroid carcinoma (THCA) is a significant health concern.
- Understanding the molecular mechanisms of THCA is crucial for developing effective treatments.
Purpose of the Study:
- To investigate the molecular mechanisms of THCA using bioinformatics approaches.
- To identify differentially expressed genes (DEGs), regulatory networks, and potential therapeutic targets in THCA.
Main Methods:
- Downloaded and analyzed RNA-sequencing data from THCA and normal thyroid tissues.
- Utilized bioinformatics tools for gene expression analysis, DEG identification, co-expression network construction, and functional enrichment analysis.
- Identified regulatory miRNAs, transcription factors, and potential small-molecule drug interactions.
Main Results:
- Identified 254 up-regulated and 59 down-regulated DEGs in THCA.
- DEGs are enriched in biological processes including cell adhesion, death, and growth.
- Key hub genes (e.g., ITGA3, TIMP1) and regulatory elements (e.g., E2F, HSF2, miR-26) were identified.
Conclusions:
- The study provides insights into the molecular underpinnings of THCA.
- Identified potential biomarkers and therapeutic strategies, including small-molecule drugs, for THCA treatment.
- Offers novel directions for future mechanistic studies and drug design in THCA.
