Characterization of BRAF mutation in patients older than 45 years with well-differentiated thyroid carcinoma

Barreno, Luis Rene Quiroa; Mello, Julia Bette Homem de; Barros-Filho, Mateus Camargo; Francisco, Ana Lúcia Noronha; Chulam, Thiago Celestino; Pinto, Clóvis Antônio Lopes; Gonçalves-Filho, João; Kowalski, Luiz Paulo

doi:10.1016/j.bjorl.2020.07.007

Cited by 5 publications

(1 citation statement)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the histological classification, follicular thyroid cell-derived tumors can be classified as papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), poorly differentiated thyroid carcinoma, and anaplastic thyroid carcinoma (ATC) [2]. Approximately 30% of the well-differentiated thyroid cancers (WDTC) progress to dedifferentiated thyroid cancers (DeTCs) and develop recurrence and metastasis [3]. Hence, the dedifferentiation status of DeTC and ATC indicates a more invasive approach and worse prognosis.…”

Section: Introductionmentioning

confidence: 99%

Targeting the inward rectifier potassium channel 5.1 in thyroid cancer: artificial intelligence-facilitated molecular docking for drug discovery

Yang

et al. 2022

Preprint

View full text Add to dashboard Cite

Purpose: Recurrent and metastatic thyroid cancer is more invasive and can transform to dedifferentiated thyroid cancer, thus leading to a severe decline in the 10-year survival. The thyroid-stimulating hormone receptor (TSHR) plays an important role in differentiation process. We aim to find a therapeutic target in redifferentiation strategies for thyroid cancer. Methods: Our study integrated the differentially expressed genes acquired from the Gene Expression Omnibus database by comparing TSHR expression levels in the Cancer Genome Atlas database. We conducted functional enrichment analysis and verified the expression of these genes by RT-PCR in 68 pairs of thyroid tumor and paratumor tissues. Artificial intelligence-enabled virtual screening was combined with the VirtualFlow platform for deep docking. Results: We identified five genes (KCNJ16, SLC26A4, T.G., TPO, and SYT1) as potential cancer treatment targets. TSHR and KCNJ16 were downregulated in the thyroid tumor tissues, compared with paired normal tissues. In addition, KCNJ16 was lower in the vascular/capsular invasion group. Enrichment analyses revealed that KCNJ16 may play a significant role in cell growth and differentiation. The inward rectifier potassium channel 5.1 (Kir5.1, encoded by KCNJ16) emerged as an interesting target in thyroid cancer. Artificial intelligence-facilitated molecular docking identified Z2087256678_2, Z2211139111_1, Z2211139111_2, and PV-000592319198_1 (-7.3 kcal/mol) as the most potent commercially available molecular targeting Kir5.1. Conclusion: This study may provide greater insights into the differentiation features associated with TSHR expression in thyroid cancer, and Kir5.1 may be a potential therapeutic target in the redifferentiation strategies for recurrent and metastatic thyroid cancer.

show abstract

Section: Introductionmentioning

confidence: 99%