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

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis

PURPOSE

To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

METHODS

Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

RESULTS

There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

CONCLUSIONS

The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

In silico Screening and Validation of Achyranthes aspera as a Potential Inhibitor of BRAF and NRAS in Controlling Thyroid Cancer

BACKGROUND

Thyroid carcinoma (THCA) is one of the most prevalent endocrine tumors, accounting for 3.4% of all cancers diagnosed annually. Single Nucleotide Polymorphisms (SNPs) are the most prevalent genetic variation associated with thyroid cancer. Understanding thyroid cancer genetics will enhance diagnosis, prognosis, and treatment.

METHODS

This TCGA-based study analyzes thyroid cancer-associated highly mutated genes through highly robust in silico techniques. Pathway, gene expression, and survival studies were performed on the top 10 highly mutated genes (BRAF, NRAS, TG, TTN, HRAS, MUC16, ZFHX3, CSMD2, EIFIAX, SPTA1). Novel natural compounds from Achyranthes aspera Linn were discovered to target two highly mutated genes. The natural compounds and synthetic drugs used to treat thyroid cancer were subjected to comparative molecular docking against BRAF and NRAS targets. The ADME characteristics of Achyranthes aspera Linn compounds were also investigated.

RESULTS

The gene expression analysis revealed that the expression of ZFHX3, MCU16, EIF1AX, HRAS, and NRAS was up-regulated in tumor cells while BRAF, TTN, TG, CSMD2, and SPTA1 were down-regulated in tumor cells. In addition, the protein-protein interaction network demonstrated that HRAS, BRAF, NRAS, SPTA1, and TG proteins have strong interactions with each other as compared to other genes. The ADMET analysis shows that seven compounds have druglike properties. These compounds were further studied for molecular docking studies. The compounds MPHY012847, IMPHY005295, and IMPHY000939 show higher binding affinity with BRAF than pimasertib. In addition, IMPHY000939, IMPHY000303, IMPHY012847, and IMPHY005295 showed a better binding affinity with NRAS than Guanosine Triphosphate.

CONCLUSION

The outcomes of docking experiments conducted on BRAF and NRAS provide insight into natural compounds with pharmacological characteristics. These findings indicate that natural compounds derived from plants as a more promising cancer treatment option. Thus, the results of docking investigations conducted on BRAF and NRAS substantiate the conclusions that the molecule possesses the most suited drug-like qualities. Compared to other compounds, natural compounds are superior, and they are also druggable. This demonstrates that natural plant compounds can be an excellent source of potential anti-cancer agents. The preclinical research will pave the road for a possible anti-cancer agent.

ITGAL infers adverse prognosis and correlates with immunity in acute myeloid leukemia

Integrin subunit alpha L (ITGAL) was found aberrantly expressed in multiple cancer types, suggesting its essential role in tumorigenesis. Hence, we aimed to explore its definite role in acute myeloid leukemia and emphasize its associations with immunity. Here, we found ITGAL was highly expressed in AML patients and elevated expression was associated with poor prognosis. ITGAL was associated with age and cytogenetic risk classifications, but not relevant to AML driver gene mutations. Univariate and multivariate Cox regression analyses determined ITGAL as an independent prognostic factor. The nomogram integrating ITGAL and clinicopathologic variables was constructed to predict 1-, 3- and 5-year overall survival (OS). Functional analyses revealed that ITGAL was mainly responsible for the production and metabolic process of cytokine. As for immunity, ITGAL was positively associated with MDSCs including iDCs, and macrophages in the TCGA-LAML cohort. We also found that ITGAL was positively associated with most immune checkpoint genes and cytokines. In addition, we found that ITGAL knockdown caused substantial inhibition of cell growth and significant induction of early apoptosis in AML cells. The xenograft study indicated that ITGAL knockdown prolonged the survival of recipient mice. Overall, ITGAL is an independent prognostic factor and is closely related to the number of MDSCs and cytokine production.

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

Background

Purpose

Methods

Results

Conclusion

Integrative Analyses of Genes Associated with Hashimoto's Thyroiditis

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.