J Cancer 2021; 12(6):1779-1791. doi:10.7150/jca.51551

Research Paper

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

YaLi Han1, XiaQing Yu3, YuZhen Yin3, Zhongwei Lv3, ChengYou Jia1, Yina Liao1, Hongyan Sun2, Tie Liu2, Lele Cong2, ZhaoLiang Fei4, Da Fu5, Xianling Cong2✉, Shen Qu1✉

1. Shanghai Center for Thyroid Disease, Shanghai Tenth People's Hospital, Shanghai, China;
2. Department of biobank, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, People's Republic of China;
3. Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China;
4. Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China;
5. Central Laboratory for Medical Research, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.

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Citation:
Han Y, Yu X, Yin Y, Lv Z, Jia C, Liao Y, Sun H, Liu T, Cong L, Fei Z, Fu D, Cong X, Qu S. Identification of Potential BRAF Inhibitor Joint Therapy Targets in PTC based on WGCAN and DCGA. J Cancer 2021; 12(6):1779-1791. doi:10.7150/jca.51551. Available from https://www.jcancer.org/v12p1779.htm

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Abstract

As the most common mutation in papillary thyroid cancer (PTC), B-type Raf kinase V600E mutation (BRAFV600E) 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 BRAFV600E-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 (BRAFWT) patients and 283 BRAFV600E mutant patients collected from The Cancer Genome Atlas (TCGA), and screened 455 BRAFV600E- associated genes through differential analysis and weighted gene co-expression network analysis. Based on these BRAFV600E-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 BRAFV600E-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.

Keywords: papillary thyroid cancer, BRAF, biomarkers, targeted drugs