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. 2020 Jun 26:8:e9294.
doi: 10.7717/peerj.9294. eCollection 2020.

Whole genome sequencing analysis identifies recurrent structural alterations in esophageal squamous cell carcinoma

Munmee Dutta  1   2 , Hidewaki Nakagawa  3 , Hiroaki Kato  4 , Kazuhiro Maejima  3 , Shota Sasagawa  3 , Kaoru Nakano  3 , Aya Sasaki-Oku  3 , Akihiro Fujimoto  5 , Raúl Nicolás Mateos  1   2 , Ashwini Patil  2 , Hiroko Tanaka  2 , Satoru Miyano  2   6 , Takushi Yasuda  4 , Kenta Nakai  1   2 , Masashi Fujita  3
Affiliations

Whole genome sequencing analysis identifies recurrent structural alterations in esophageal squamous cell carcinoma

Munmee Dutta et al. PeerJ. .

Abstract

Esophageal squamous cell carcinoma (ESCC) is the predominant type of esophageal cancer in the Asian region, including Japan. A previous study reported mutational landscape of Japanese ESCCs by using exome sequencing. However, somatic structural alterations were yet to be explored. To provide a comprehensive mutational landscape, we performed whole genome sequencing (WGS) analysis of biopsy specimens from 20 ESCC patients in a Japanese population. WGS analysis identified non-silent coding mutations of TP53, ZNF750 and FAT1 in ESCC. We detected six mutational signatures in ESCC, one of which showed significant association with smoking status. Recurrent structural variations, many of which were chromosomal deletions, affected genes such as LRP1B, TTC28, CSMD1, PDE4D, SDK1 and WWOX in 25%-30% of tumors. Somatic copy number amplifications at 11q13.3 (CCND1), 3q26.33 (TP63/SOX2), and 8p11.23 (FGFR1) and deletions at 9p21.3 (CDKN2A) were identified. Overall, these multi-dimensional view of genomic alterations improve the understanding of the ESCC development at molecular level and provides future prognosis and therapeutic implications for ESCC in Japan.

Keywords: Coding mutation; Copy number alteration; Druggable gene; Esophageal squamous cell carcinoma; FAT1; FGFR1; LRP1B; Mutational signature; Structural variation; Whole genome sequencing.

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Conflict of interest statement

Kenta Nakai is an Academic Editor for PeerJ.

Figures

Figure 1
Figure 1. The landscape of somatic alternations in ESCCs from 20 Japanese patients.
(A) Potential driver mutations by SNVs/INDELs across the 20 ESCC patients with different mutation types coded by different colors. Two genes marked with an asterisk are significantly mutated genes (q < 0.05) detected by the dNdScv method. The other 12 genes are those recurrently mutated in previous ESCC studies. (A) shows the number of mutations in all the 20 ESCC cases. The number and type of mutations for each mutated gene is also shown. Mutation types are labelled on the legend. (B) The recurrent copy number amplified and deleted regions with the important cancer-related genes detected in ESCC patients. The legend shows frequency across the ESCC patients. (C) The clinical features such as gender, smoking, alcohol drinking status, age and the tumor stages of the ESCC patients.
Figure 2
Figure 2. Mutational signatures of 20 whole genome of ESCC.
(A–F) Characterization of six mutational signatures identified across the ESCC genomes. Patterns of substitutions for each signatures W1–W6 in ESCC. The mutational signatures are presented according to the 96 substitution classifications defined by the substitution class and sequence context immediately 3’ and 5’ to the mutated base. We used the SignatureAnalyzer method to determine the six distinct mutational signatures (SNVs) out of the 20 ESCC samples. (A) Signature W1. (B) Signature W2. (C) Signature W3. (D) Signature W4. (E) Signature W5. (F) Signature W6. (G) Mutation burden and contribution of the six mutational signatures (W1-W6) across the ESCC genomes. (H) Boxplot showing the association of mutational signatures and smoking habit of patients with ESCC. Mutational signature W4 displays significant association (p-value = 0.01474) with smoking status of ESCC patients. P-value was calculated using Wilcoxon rank sum test. ns: P > 0.05.
Figure 3
Figure 3. Somatic structural variations in ESCC.
(A–L) Circos plots of SVs and somatic CNAs in 20 ESCC genome. The inner ring represents the SVs: red for intrachromosomal rearrangements, and green for interchromosomal rearrangements. The second ring next to SVs displays the CNAs: red for amplifications and blue for deletions. The outer ring shows the chromosome ideogram. (A–F) ESCCs with 100 or more SVs. (G–L) ESCCs with <100 SVs. (M) Different categories of SVs for instance inversion, translocation, deletion and tandem duplication, and their frequencies in the 20 ESCC genomes. (N) Top genes recurrently affected by SVs across the ESCC samples. Genes that were affected in two or more patients are presented.
Figure 4
Figure 4. Somatic copy number alterations in specific regions detected by GISTIC 2.0 in ESCC.
Significantly observed regions of recurrent amplifications (A) and deletions (B) across samples are shown. Numbers in the left bar in both (A) and (B) refer to the chromosome number. GISTIC scores are presented on top and, q-values (x-axis) indicating the false discovery rate at each locus are shown on a log scale in both (A) and (B). (C) Common deletions are shown at 9p21.3 region across the ESCC samples by Integrative Genomic Viewer (IGV).
Figure 5
Figure 5. Venn diagram representing the druggable genes altered by different mutation events in ESCC.
The figure shows the common druggable genes, genes having interaction with at least one drug target. These genes were affected by SNVs, SVs and CNAs in ESCC.
See this image and copyright information in PMC

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