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. 2017 Jan 31;8(5):8095-8104.
doi: 10.18632/oncotarget.14098.

Cervical small cell neuroendocrine tumor mutation profiles via whole exome sequencing

Soo Young Cho  1 , Minhye Choi  2 , Hyo-Jeong Ban  3   4 , Chang Hyeon Lee  5 , Soojun Park  6 , HanKyeom Kim  2 , Young-Sik Kim  2 , Young Seek Lee  3 , Ji-Yun Lee  2
Affiliations

Cervical small cell neuroendocrine tumor mutation profiles via whole exome sequencing

Soo Young Cho et al. Oncotarget. .

Abstract

Cervical small cell neuroendocrine tumors (CSCNETs) are rare, aggressive neuroendocrine tumors (NETs). Reliable diagnostic and prognostic CSCNET markers are lacking, making diagnosis and prognosis prediction difficult, and treatment strategies limited. Here we provide mutation profiles for five tumor-normal paired CSCNETs using whole exome sequencing (WES). We expanded our assessment of frequently mutated genes to include publicly available data from 55 small intestine neuroendocrine tumors, 10 pancreatic neuroendocrine tumors, 42 small cell lung cancers, six NET cell lines, and 188 cervical cancers, along with our five CSCNETs. We identified 1,968 somatic mutations, including 1,710 missense, 106 nonsense, 144 splice site, 4 lncRNA, 3 nonstop, and 1 start codon mutation. We assigned functions to the 114 most frequently mutated genes based on gene ontology. ATRX, ERBB4, and genes in the Akt/mTOR pathway were most frequently mutated. Positive cytoplasmic ERBB4 immunohistochemical staining was detected in all CSCNET tumors tested, but not in adjacent normal tissues. To our knowledge, this study is the first to utilize WES in matched CSCNET and normal tissues to identify somatic mutations. Further studies will improve our understanding of how ATRX and ERBB4 mutations and AKT/mTOR signaling promote CSCNET tumorigenesis, and may be leveraged in novel anti-cancer treatment strategies.

Keywords: AKT/mTOR; ATRX; ERBB4; cervical small cell neuroendocrine tumor; whole exome sequencing.

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Conflict of interest statement

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1. Representative histopathological analyses and somatic mutation signatures from five CSCNETs
Representative (case 10) H&E and IHC staining for chromogranin and synaptophysin in tumor and adjacent normal tissues A. Tumor tissue stains positive for chromogranin and synaptophysin. Magnifications: x40 (left) and x400 (right). T: tumor tissue; N: adjacent normal tissue. Circos plots showing 114 recurrently mutated genes within 463 missense mutations found in ≥3 CSCNETs B. Five inner circles represent five CSCNETs each and blue lines represent nonsynonymous mutations in each sample. Outer circle represents chromosome with cytoband. Colors in the cytoband indicate: centromere (red), high gene density (black), low gene density (white), and gene empty loci (sky blue).
Figure 2
Figure 2. EBRR4 mutation and protein expression
Functional domains containing five ERBB4 mutation sites from four CSCNETs A. Predictions for each mutation site indicated that p.P981S is highly conserved across species (mutationassessor.org). Representative IHC staining for ERBB4 B. Tumors, but not adjacent normal tissues, were positive for cytoplasmic ERBB4 expression. Cases 2, 10, and 11 exhibited the strongest expression, cases 13 and 16 showed medium expression, and case 3 showed the lowest expression. Original magnifications are x40 (big image) and x400 (small image). T: tumor tissue; N: adjacent normal tissue
Figure 3
Figure 3. Recurrently mutated RTK-Akt/mTOR pathway genes found in CSNCETs, other NETs, and CT
(): number of samples. *Indicated gene mutation rate was high, likely due to low sample number.
Figure 4
Figure 4. Venn diagram of frequently mutated gene(s) shared across CSCNETs, NETs and CT
Recurrently mutated genes were selected at ≥5% in CTs and other NETs, and ≥50% (≥3 samples) in our CSCNETs. Mutated genes are listed in Supplementary Table 8A.
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