Related Experiment Video
Updated: Aug 17, 2026

Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Gene-expression profile analysis to disclose diagnostics and therapeutics biomarkers for thyroid carcinoma
Sabkat Mahmud1, Alvira Ajadee1, Md Bayazid Hossen2
1Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh.
Abstract:
The most frequent endocrine cancer of the head and neck is thyroid carcinoma (THCA). Although there is increasing evidence linking THCA to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. There is still much to learn about THCA's molecular roots and genetic biomarkers. Though drug therapies are the best choice after metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving them for a few years. Therefore, multi-targeted different variants of therapeutic drugs may be essential for effective treatment against THCA. To understand molecular mechanisms of THCA development and progression and explore multi-targeted different variants of therapeutic drugs, we detected 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples from six microarray gene expression datasets using the statistical LIMMA approach. Through protein-protein interaction (PPI) network analysis, we identified the top-ranked eight differentially expressed genes (TIMP1, FN1, THBS1, RUNX2, SHANK2, TOP2A, LRP2, and ACTN1) as the THCA-causing key genes (KGs), where 6 KGs (TIMP1, TOP2A, FN1, ACTN1, RUNX2, THBS1) are upregulated and 2 KGs (LRP2, SHANK2) are downregulated. The expression pattern analysis of KGs with the independent TCGA database by Box plots also confirmed their upregulated and downregulated patterns. The expression analysis of KGs in different stages of THCA development indicated that these KGs might be utilized as early diagnostic and prognostic biomarkers. The pan-cancer analysis of KGs indicated a substantial correlation of KGs with multiple cancers, including THCA. Some transcription factors (TFs) and microRNAs were detected as the key transcriptional and post-transcriptional regulators of KGs using gene regulatory network (GRN) analysis. The enrichment analysis of the cDEGs revealed several key molecular functions, biological processes, cellular components, and pathways significantly associated with THCA. These findings highlight critical mechanisms influenced by the identified key genes (KGs), providing deeper insight into their roles in THCA development. Then we detected 6 repurposable drug molecules (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, and Pazopanib) by molecular docking with KGs-mediated receptor proteins, ADME/T analysis, and cross-validation with the independent receptors. Therefore, these findings might be useful resources for wet lab researchers and clinicians to consider an effective treatment strategy against THCA.
Insights
This study identifies key genes and potential drug targets for thyroid carcinoma (THCA). It reveals eight crucial genes involved in THCA development and suggests six repurposable drugs for effective treatment strategies.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Thyroid carcinoma (THCA) is the most common endocrine cancer.
- The molecular mechanisms and genetic biomarkers of THCA are not fully understood.
- Drug resistance is a significant challenge in THCA treatment.
Purpose of the Study:
- To elucidate the molecular mechanisms of THCA development and progression.
- To identify key genes (KGs) associated with THCA.
- To explore potential multi-targeted therapeutic drug variants for THCA.
Main Methods:
- Differential gene expression analysis using LIMMA on six microarray datasets.
- Protein-protein interaction (PPI) network analysis to identify key genes.
- Gene regulatory network (GRN) analysis to detect regulators.
- Pan-cancer analysis and TCGA database validation.
- Molecular docking and ADME/T analysis for drug repurposing.
Main Results:
- Identified 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples.
- Eight key genes (KGs) were identified, with six upregulated (TIMP1, FN1, THBS1, RUNX2, TOP2A, ACTN1) and two downregulated (LRP2, SHANK2).
- KGs showed potential as early diagnostic and prognostic biomarkers for THCA.
- Significant correlation of KGs with multiple cancers was observed.
- Six repurposable drugs (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, Pazopanib) were identified.
Conclusions:
- The identified KGs play critical roles in THCA development and progression.
- These KGs can serve as potential biomarkers for early diagnosis and prognosis.
- The identified drugs offer promising therapeutic strategies for THCA treatment.
- Findings provide valuable resources for researchers and clinicians in developing effective THCA treatment strategies.

