2015
Chen, S. -J.; Liu, H.; Liao, C. -T.; Huang, P. -J.; Huang, Y.; Hsu, A.; Tang, P.; Chang, Y. -S.; Chenx, H. -C.; Yen, T. -C.
Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature Journal Article
In: Oncotarget, 6 (20), pp. 18066-18080, 2015, ISSN: 19492553, (cited By 37).
Abstract | Links | BibTeX | 標籤: 4, 5 trisphosphate 3 phosphatase; protein p53; protein tyrosine phosphatase SHP 2; Smad4 protein; tumor marker, Adult; Aged; Biomarkers, B Raf kinase; cyclin dependent kinase inhibitor 2A; fibroblast growth factor receptor 3; Notch1 receptor; phosphatidylinositol 3, Tumor; Carcinoma
@article{Chen201518066,
title = {Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature},
author = {S. -J. Chen and H. Liu and C. -T. Liao and P. -J. Huang and Y. Huang and A. Hsu and P. Tang and Y. -S. Chang and H. -C. Chenx and T. -C. Yen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938613758&doi=10.18632%2foncotarget.3768&partnerID=40&md5=e401b9db26d05a7c7dea4e6761bcb03b},
doi = {10.18632/oncotarget.3768},
issn = {19492553},
year = {2015},
date = {2015-01-01},
journal = {Oncotarget},
volume = {6},
number = {20},
pages = {18066-18080},
publisher = {Impact Journals LLC},
abstract = {Background: Patients with advanced oral squamous cell carcinoma (OSCC) have heterogeneous outcomes that limit the implementation of tailored treatment options. Genetic markers for improved prognostic stratification are eagerly awaited. Methods: Herein, next-generation sequencing (NGS) was performed in 345 formalin-fixed paraffin-embedded (FFPE) samples obtained from advanced OSCC patients. Genetic mutations on the hotspot regions of 45 cancer-related genes were detected using an ultra-deep (>1000×) sequencing approach. Kaplan-Meier plots and Cox regression analyses were used to investigate the associations between the mutation status and disease-free survival (DFS). Results: We identified 1269 non-synonymous mutations in 276 OSCC samples. TP53, PIK3CA, CDKN2A, HRAS and BRAF were the most frequently mutated genes. Mutations in 14 genes were found to predict DFS. A mutation-based signature affecting ten genes (HRAS, BRAF, FGFR3, SMAD4, KIT, PTEN, NOTCH1, AKT1, CTNNB1, and PTPN11) was devised to predict DFS. Two different resampling methods were used to validate the prognostic value of the identified gene signature. Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005). Conclusions: Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.},
note = {cited By 37},
keywords = {4, 5 trisphosphate 3 phosphatase; protein p53; protein tyrosine phosphatase SHP 2; Smad4 protein; tumor marker, Adult; Aged; Biomarkers, B Raf kinase; cyclin dependent kinase inhibitor 2A; fibroblast growth factor receptor 3; Notch1 receptor; phosphatidylinositol 3, Tumor; Carcinoma},
pubstate = {published},
tppubtype = {article}
}
Background: Patients with advanced oral squamous cell carcinoma (OSCC) have heterogeneous outcomes that limit the implementation of tailored treatment options. Genetic markers for improved prognostic stratification are eagerly awaited. Methods: Herein, next-generation sequencing (NGS) was performed in 345 formalin-fixed paraffin-embedded (FFPE) samples obtained from advanced OSCC patients. Genetic mutations on the hotspot regions of 45 cancer-related genes were detected using an ultra-deep (>1000×) sequencing approach. Kaplan-Meier plots and Cox regression analyses were used to investigate the associations between the mutation status and disease-free survival (DFS). Results: We identified 1269 non-synonymous mutations in 276 OSCC samples. TP53, PIK3CA, CDKN2A, HRAS and BRAF were the most frequently mutated genes. Mutations in 14 genes were found to predict DFS. A mutation-based signature affecting ten genes (HRAS, BRAF, FGFR3, SMAD4, KIT, PTEN, NOTCH1, AKT1, CTNNB1, and PTPN11) was devised to predict DFS. Two different resampling methods were used to validate the prognostic value of the identified gene signature. Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005). Conclusions: Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.