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Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature.

Chen SJ, Liu H, Liao CT, Huang PJ, Huang Y, Hsu A, Tang P, Chang YS, Chen HC, Yen TC - Oncotarget (2015)

Bottom Line: Mutations in 14 genes were found to predict DFS.Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005).Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Sciences, Chang Gung University, Taoyuan, 33302, Taiwan.

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.

No MeSH data available.


Related in: MedlinePlus

Extent of genetic disruption in advanced OSCCA. Prevalence of tumors harboring tumor suppressor gene variants in the Chang Gung cohort and in the TCGA HNSCC cohort. B. Prevalence of tumors harboring oncogenic variants in the Chang Gung cohort and in the TCGA HNSCC cohort. C. Distribution of TP53 mutations in the Chang Gung cohort and in the TCGA HNSCC cohort. D. Distribution of PIK3CA mutations in the Chang Gung cohort and in the TCGA cohort.
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Figure 3: Extent of genetic disruption in advanced OSCCA. Prevalence of tumors harboring tumor suppressor gene variants in the Chang Gung cohort and in the TCGA HNSCC cohort. B. Prevalence of tumors harboring oncogenic variants in the Chang Gung cohort and in the TCGA HNSCC cohort. C. Distribution of TP53 mutations in the Chang Gung cohort and in the TCGA HNSCC cohort. D. Distribution of PIK3CA mutations in the Chang Gung cohort and in the TCGA cohort.

Mentions: The 1,269 non-synonymous mutations identified in the current study were located in 44 genes (Figure 2). The most frequently mutated genes were TP53 (65%), PIK3CA (16.8%), CDKN2A (12.8%), HRAS (9.3%), BRAF (9.0%), EGFR (6.7%) and FGFR3 (5.8%). Genetic mutations in the ten most frequently mutated genes were identified in 263 (76.2%) samples (Figure 2). As only the hotspot regions of 45 cancer-related genes were sequenced in our study, we analyzed whether our targeted sequencing approach could distort the observed mutation spectra. We therefore compared our findings with the mutational patterns reported in The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) dataset (containing the whole-exome sequencing data of 279 tumors). The frequency of genetic variations in TSG detected in our study was largely similar to that observed in TCGA dataset, the only exceptions being CDKN2A (12.8% vs. 22.6% in the TCGA data) and NOTCH1 (3.2% vs. 18.6% in the TCGA data) which showed a significantly lower degree of sequence variation in our study (Figure 3A). In contrast, mutations in several oncogenes (including potential drug targets) were more commonly observed in our study than in the TCGA (Figure 3B). Notably, several oncogenes had a 3-fold higher mutation rates in the current report compared with the TCGA data, including AKT1 (3.2% vs. 0.7%), BRAF (9% vs. 1.4%), CTNNB1 (2.3% vs. 0.7%), FGFR1 (1.4% vs. 0.4%), FGFR2 (4.3% vs. 0.7%), KIT (4.1% vs. 1.1%), KRAS (2.3% vs. 0.4%), and MET (4.3% vs. 1.1%; Figure 3B). Moreover, we also detected 11 samples with ABL1 (3.2%) mutations and 11 cases with SMO (3.2%) mutations. No such mutations were reported in the TCGA dataset. Mutations in the PI3K pathway, including PIK3CA, AKT1 and PTEN, were identified in 68 (19.7%) tumors, suggesting that these patients may benefit from AKT-PI3K-mTOR inhibitors.


Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature.

Chen SJ, Liu H, Liao CT, Huang PJ, Huang Y, Hsu A, Tang P, Chang YS, Chen HC, Yen TC - Oncotarget (2015)

Extent of genetic disruption in advanced OSCCA. Prevalence of tumors harboring tumor suppressor gene variants in the Chang Gung cohort and in the TCGA HNSCC cohort. B. Prevalence of tumors harboring oncogenic variants in the Chang Gung cohort and in the TCGA HNSCC cohort. C. Distribution of TP53 mutations in the Chang Gung cohort and in the TCGA HNSCC cohort. D. Distribution of PIK3CA mutations in the Chang Gung cohort and in the TCGA cohort.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4621868&req=5

Figure 3: Extent of genetic disruption in advanced OSCCA. Prevalence of tumors harboring tumor suppressor gene variants in the Chang Gung cohort and in the TCGA HNSCC cohort. B. Prevalence of tumors harboring oncogenic variants in the Chang Gung cohort and in the TCGA HNSCC cohort. C. Distribution of TP53 mutations in the Chang Gung cohort and in the TCGA HNSCC cohort. D. Distribution of PIK3CA mutations in the Chang Gung cohort and in the TCGA cohort.
Mentions: The 1,269 non-synonymous mutations identified in the current study were located in 44 genes (Figure 2). The most frequently mutated genes were TP53 (65%), PIK3CA (16.8%), CDKN2A (12.8%), HRAS (9.3%), BRAF (9.0%), EGFR (6.7%) and FGFR3 (5.8%). Genetic mutations in the ten most frequently mutated genes were identified in 263 (76.2%) samples (Figure 2). As only the hotspot regions of 45 cancer-related genes were sequenced in our study, we analyzed whether our targeted sequencing approach could distort the observed mutation spectra. We therefore compared our findings with the mutational patterns reported in The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) dataset (containing the whole-exome sequencing data of 279 tumors). The frequency of genetic variations in TSG detected in our study was largely similar to that observed in TCGA dataset, the only exceptions being CDKN2A (12.8% vs. 22.6% in the TCGA data) and NOTCH1 (3.2% vs. 18.6% in the TCGA data) which showed a significantly lower degree of sequence variation in our study (Figure 3A). In contrast, mutations in several oncogenes (including potential drug targets) were more commonly observed in our study than in the TCGA (Figure 3B). Notably, several oncogenes had a 3-fold higher mutation rates in the current report compared with the TCGA data, including AKT1 (3.2% vs. 0.7%), BRAF (9% vs. 1.4%), CTNNB1 (2.3% vs. 0.7%), FGFR1 (1.4% vs. 0.4%), FGFR2 (4.3% vs. 0.7%), KIT (4.1% vs. 1.1%), KRAS (2.3% vs. 0.4%), and MET (4.3% vs. 1.1%; Figure 3B). Moreover, we also detected 11 samples with ABL1 (3.2%) mutations and 11 cases with SMO (3.2%) mutations. No such mutations were reported in the TCGA dataset. Mutations in the PI3K pathway, including PIK3CA, AKT1 and PTEN, were identified in 68 (19.7%) tumors, suggesting that these patients may benefit from AKT-PI3K-mTOR inhibitors.

Bottom Line: Mutations in 14 genes were found to predict DFS.Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005).Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Sciences, Chang Gung University, Taoyuan, 33302, Taiwan.

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.

No MeSH data available.


Related in: MedlinePlus