Cargando…

Identification of Potential BRAF Inhibitor Joint Therapy Targets in PTC based on WGCAN and DCGA

As the most common mutation in papillary thyroid cancer (PTC), B-type Raf kinase V600E mutation (BRAF(V600E)) has become an important target for the clinical treatment of PTC. However, the clinical application still faces the problem of resistance to BRAF inhibitors (BRAFi). Therefore, exploring BRA...

Descripción completa

Detalles Bibliográficos
Autores principales: Han, YaLi, Yu, XiaQing, Yin, YuZhen, Lv, Zhongwei, Jia, ChengYou, Liao, Yina, Sun, Hongyan, Liu, Tie, Cong, Lele, Fei, ZhaoLiang, Fu, Da, Cong, Xianling, Qu, Shen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890315/
https://www.ncbi.nlm.nih.gov/pubmed/33613767
http://dx.doi.org/10.7150/jca.51551
Descripción
Sumario:As the most common mutation in papillary thyroid cancer (PTC), B-type Raf kinase V600E mutation (BRAF(V600E)) has become an important target for the clinical treatment of PTC. However, the clinical application still faces the problem of resistance to BRAF inhibitors (BRAFi). Therefore, exploring BRAF(V600E)-associated prognostic factors to providing potential joint targets is important for combined targeted therapy with BRAFi. In this study, we combined transcript data and clinical information from 199 BRAF wild-type (BRAF(WT)) patients and 283 BRAF(V600E) mutant patients collected from The Cancer Genome Atlas (TCGA), and screened 455 BRAF(V600E)- associated genes through differential analysis and weighted gene co-expression network analysis. Based on these BRAF(V600E)-associated genes, we performed functional enrichment analysis and co-expression differential analysis and constructed a core co-expression network. Next, genes in the differential co-expression network were used to predict drugs for therapy in the crowd extracted expression of differential signatures (CREEDS) database, and the key genes were selected based on the hub co-expression network through survival analyses and receiver operating characteristic (ROC) curve analyses. Finally, we obtained eight BRAF(V600E)-associated biomarkers with both prognostic and diagnostic values as potential BRAFi joint targets, including FN1, MET, SLC34A2, NGEF, TBC1D2, PLCD3, PROS1, and NECTIN4. Among these genes, FN1, MET, PROS1, and TBC1D2 were validated through GEO database. Two novel biomarkers, PROS1 and TBC1D2, were further validated by qRT-PCR experiment. Besides, we obtained four potential targeted drugs that could be used in combination with BRAFi to treat PTC, including MET inhibitor, ERBB3 inhibitor, anti-NaPi2b antibody-drug conjugate, and carboplatin through literature review. The study provided potential drug targets for combination therapy with BRAFi for PTC to overcome the drug resistance for BRAFi.