| Literature DB >> 25669975 |
Libing Xiang1, Jiajia Li1, Wei Jiang1, Xuxia Shen2, Wentao Yang2, Xiaohua Wu1, Huijuan Yang1.
Abstract
Mutations in 16 targetable oncogenic genes were examined using reverse transcription polymerase chain reaction (RT-PCR) and direct sequencing in 285 Chinese cervical cancers. Their clinicopathological relevance and prognostic significance was assessed. Ninety-two nonsynonymous somatic mutations were identified in 29.8% of the cancers. The mutation rates were as follows: PIK3CA (12.3%), KRAS (5.3%), HER2 (4.2%), FGFR3-TACC3 fusions (3.9%), PTEN (2.8%), FGFR2 (1.8%), FGFR3 (0.7%), NRAS (0.7%), HRAS (0.4%) and EGFR (0.4%). No mutations were detected in AKT1 or BRAF, and the fusions FGFR1-TACC1, EML4-ALK, CCDC6-RET and KIF5B-RET were not found in any of the cancers. RTK and RAS mutations were more common in non-squamous carcinomas than in squamous carcinomas (P=0.043 and P=0.042, respectively). RAS mutations were more common in young patients (<45 years) (13.7% vs. 7.7%, P=0.027). RTK mutations tended to be more common in young patients, whereas PIK3CA/PTEN/AKT mutations tended to be more common in old patients. RAS mutations were significantly associated with disease relapse. To our knowledge, this is the first comprehensive analysis of major targetable oncogenic mutations in a large cohort of cervical cancer cases. Our data reveal that a considerable proportion of patients with cervical cancers harbor known druggable mutations and might benefit from targeted therapy.Entities:
Keywords: PI3K pathway genes; RAS genes; RTK genes; cervical cancers; oncogenic mutation
Mesh:
Substances:
Year: 2015 PMID: 25669975 PMCID: PMC4467127 DOI: 10.18632/oncotarget.3212
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Distribution of mutations of the 16 tested genes in the 285 Chinese cervical cancers
Figure 2Mutation rates of the 16 tested genes in 285 Chinese cervical cancers
Figure 3FGFR3-TACC3 fusion variants
The prevalence of the 16 oncogenic mutations in different groups according to different clinicopathological features
| Characteristics | PIK3CA/PTEN/AKT | RTKs | RAS/RAF | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Wild-type | Mutation | P | Wild-type | mutation | P | Wild-type | mutation | P | |
| Age(years) | 0.065 | 0.114 | |||||||
| <45 | 105 | 12 | 101 | 16 | 105 | 12 | |||
| ≥45 | 137 | 31 | 155 | 13 | 162 | 6 | |||
| Menopause status | 0.078 | 0.209 | 0.441 | ||||||
| Yes | 73 | 19 | 86 | 6 | 88 | 4 | |||
| No | 169 | 24 | 170 | 23 | 179 | 14 | |||
| Histological type | 0.122 | ||||||||
| SCC | 147 | 32 | 166 | 13 | 172 | 7 | |||
| AC+ASC+Others | 95 | 11 | 90 | 16 | 95 | 11 | |||
| Tumor size | 0.716 | 1.000 | 0.595 | ||||||
| >4cm | 67 | 13 | 72 | 8 | 74 | 6 | |||
| ≤4cm | 175 | 30 | 184 | 21 | 193 | 12 | |||
| Depth of myometrial invasion | 0.066 | 0.829 | 1.000 | ||||||
| >1/2 | 167 | 36 | 183 | 20 | 190 | 13 | |||
| ≤1/2 | 75 | 7 | 73 | 9 | 77 | 5 | |||
| LVSI | 1.000 | 0.209 | 0.604 | ||||||
| Yes | 78 | 14 | 86 | 6 | 85 | 7 | |||
| No | 164 | 29 | 170 | 23 | 182 | 11 | |||
| Regional lymph node metastasis | 0.194 | 0.658 | 1.000 | ||||||
| Yes | 61 | 15 | 67 | 9 | 71 | 5 | |||
| No | 181 | 28 | 189 | 20 | 196 | 13 | |||
| Parametrial involvement | 0.674 | 1.000 | 0.519 | ||||||
| Yes | 9 | 2 | 10 | 1 | 10 | 1 | |||
| No | 233 | 41 | 246 | 28 | 257 | 17 | |||
| Distant metastasis | 0.279 | 0.193 | 1.000 | ||||||
| Yes | 1 | 1 | 1 | 1 | 2 | 0 | |||
| No | 241 | 42 | 255 | 28 | 265 | 18 | |||
RTKs included EGFR, HER2, FGFR2,FGFR3 mutations and FGFR3-TACC3 fusions.
Fisher's exact test was employed to assess the difference between groups.
Figure 4Disease-free survival (RFS) curves plotted by Kaplan-Meier method for the 285 patients based on the mutation status of the 16 tested genes
A. Comparison of RFS in the patients with mutations and the patients without mutations. B. Comparison of RFS in patients with different mutations