Genetic landscape of esophageal squamous cell carcinoma

Journal name:
Nature Genetics
Volume:
46,
Pages:
1097–1102
Year published:
DOI:
doi:10.1038/ng.3076
Received
Accepted
Published online
Corrected online

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancers1. We performed exome sequencing on 113 tumor-normal pairs, yielding a mean of 82 non-silent mutations per tumor, and 8 cell lines. The mutational profile of ESCC closely resembles those of squamous cell carcinomas of other tissues but differs from that of esophageal adenocarcinoma. Genes involved in cell cycle and apoptosis regulation were mutated in 99% of cases by somatic alterations of TP53 (93%), CCND1 (33%), CDKN2A (20%), NFE2L2 (10%) and RB1 (9%). Histone modifier genes were frequently mutated, including KMT2D (also called MLL2; 19%), KMT2C (MLL3; 6%), KDM6A (7%), EP300 (10%) and CREBBP (6%). EP300 mutations were associated with poor survival. The Hippo and Notch pathways were dysregulated by mutations in FAT1, FAT2, FAT3 or FAT4 (27%) or AJUBA (JUB; 7%) and NOTCH1, NOTCH2 or NOTCH3 (22%) or FBXW7 (5%), respectively. These results define the mutational landscape of ESCC and highlight mutations in epigenetic modulators with prognostic and potentially therapeutic implications.

At a glance

Figures

  1. Genome-wide mutational landscape of ESCC identified by whole-exome sequencing.
    Figure 1: Genome-wide mutational landscape of ESCC identified by whole-exome sequencing.

    (a) Number and type of mutations. Non-silent mutations consist of missense and nonsense substitutions, exomic indels and substitutions at splice sites. (b) Key clinicopathological characteristics. Smoking status was represented by cumulative exposure doses measured by pack years. Stage was determined according to the seventh edition of the American Joint Committee on Cancer (AJCC) staging system for esophageal cancer46. (c) Middle, mutations in a selection of frequently mutated genes, arranged vertically by functional group and colored by the type of alteration. Significantly mutated genes are shown in bold. Samples are displayed as columns, arranged to emphasize mutual exclusivity among mutations. Left, the total number of somatic alterations that targeted each gene and the percentage of individuals affected. Right, heat map demonstrating a comparison of the non-silent mutation frequency in ESCC with that in EAC19. Mutation frequency was calculated as the percentage of individuals with a non-silent mutation for each gene (Supplementary Table 12). Truncating mutations include nonsense mutations, insertions or deletions that alter the reading frame and splice-site mutations. Genes located in a conserved locus at 11q13-14, including MIR548K, FGF3, FGF4, FGF19 and ORAOV1 (ref. 78), were co-amplified with CCND1 and are therefore represented by CCND1 only.

  2. Recurrent histone modifier gene mutations in ESCC.
    Figure 2: Recurrent histone modifier gene mutations in ESCC.

    (a) Schematics of protein changes in p300 with alterations identified in exome-sequenced cases (above) and by Sanger sequencing of the exons encoding the HAT domain in a multicenter validation cohort (below). (b) Alterations mapped to the structure of the p300 HAT domain bound to lysine-CoA inhibitor (cyan). Alterations are highlighted in color according to the number of mutations targeting the corresponding amino acid. In particular, Trp1436, Phe1448 and Gln1455 are located on the substrate-binding loop L1 (dark blue; UCSF Chimera v1.5)79. (c) Schematic of protein alterations of CREBBP with alterations identified and validated in the exome sequencing cohort. (d) Impact of ESCC-associated mutations of EP300 on cell proliferation. KYSE-150 or KYSE-450 cells were depleted of EP300 (by short hairpin RNA, shRNA) and subsequently reconstituted in vitro with wild-type p300 (WT) or p300 mutants, including Asp1399Tyr, Tyr1414Cys and Pro1502Leu. The data represent the mean ± s.d. of three independent experiments. *P < 0.05 (independent Student's t test). (e,f) Overall survival rates of resectable ESCC cases according to EP300 gene mutation status in the exome sequencing cohort (P = 0.014, log-rank test) (e) and the multicenter validation cohort (P = 0.031, log-rank test) (f). (g,h) Schematics of the protein alterations of KMT2D (g) and KMT2C (h) that resulted from mutations identified and validated in the exome sequencing cohort. Truncating alterations are shown in red, and synonymous alterations are shown in gray.

  3. Alterations of Hippo pathway regulators in AJUBA.
    Figure 3: Alterations of Hippo pathway regulators in AJUBA.

    (a,b) Schematics of protein alterations in AJUBA (n = 8) (a) and FAT1 (n = 12) (b) that resulted from somatic mutations identified and validated in the exome sequencing cohort. Truncating alterations are shown in red, and synonymous mutations are shown in gray.

  4. Somatically altered pathways in ESCC.
    Figure 4: Somatically altered pathways in ESCC.

    Genes are shown along with the percentage of samples with alterations, including somatic mutations (blue) and homozygous deletions (green) and amplifications (red). Somatic alterations in the Notch and PI3K-Ras pathways are shown in Supplementary Figure 9. CN, copy number.

  5. Distribution of somatic mutations detected by exome sequencing in the ESCC patient cohort.
    Supplementary Fig. 1: Distribution of somatic mutations detected by exome sequencing in the ESCC patient cohort.

    The average, median and range of mutation numbers in each category are shown.

  6. Landscape of somatic copy number alterations detected by exome sequencing in the ESCC patient cohort.
    Supplementary Fig. 2: Landscape of somatic copy number alterations detected by exome sequencing in the ESCC patient cohort.

    Chromosomes are arranged circularly end to end, with the cytobands frequently affected marked in the outer rim. The inner space displays copy number data inferred from whole-exome sequencing, with red dots indicating copy number gains and blue dots indicating copy number losses. Amplifications are arranged as inward radiations in proportion to the fold change.

  7. Substitution composition of smokers and non-smokers in the ESCC exome.
    Supplementary Fig. 3: Substitution composition of smokers and non-smokers in the ESCC exome.

    (a) Comparison of the average substitution rates at non-CpG dinucleotides and at CpG dinucleotides between smokers and non-smokers. Most of the excessive substitution of C>T over C>A/G occurred at CpG dinucleotides. (b) Comparison of the average rates of all possible single-base substitutions between ESCC smokers (n = 77) and non-smokers (n = 36). Error bars indicate s.e.m. No significant difference was found between smokers and non-smokers.

  8. Distribution of non-silent mutations or SCNAs of known cancer genes.
    Supplementary Fig. 4: Distribution of non-silent mutations or SCNAs of known cancer genes.

    (a) Mapping of cancer signaling pathways in ESCC, indicated by the number of mutations per capita and by the fraction of tumors carrying at least one mutation in the corresponding pathway. (b) Fraction of tumors carrying mutations in known oncogenes and tumor suppressor genes (TSGs). Pathway definition and gene classification are as shown in Supplementary Table 14.

  9. Recurrently mutated COSMIC Cancer Census genes in ESCC cell lines.
    Supplementary Fig. 5: Recurrently mutated COSMIC Cancer Census genes in ESCC cell lines.
  10. Somatic alterations of RB1, NOTCH1, CCND1 and MIR548K correlate with clinical features.
    Supplementary Fig. 6: Somatic alterations of RB1, NOTCH1, CCND1 and MIR548K correlate with clinical features.

    (a) Mutation spectrum of RB1 (n = 10). (b) RB1 mutation was associated with younger age of onset of ESCC (P = 0.010, Student’s t test, two-tailed). (c) Mutation spectrum of NOTCH1 (n = 16). (d) NOTCH1 mutation was associated with older age of onset of ESCC (P = 0.001, Student’s t test, two-tailed). Amplifications of (e) CCND1 and (f) MIR548K were associated with poor overall survival (P = 0.006 and P = 0.022, log-rank test).

  11. Western blot confirmation of p300 knockdown efficiency in KYSE-150 and KYSE-450 cells.
    Supplementary Fig. 7: Western blot confirmation of p300 knockdown efficiency in KYSE-150 and KYSE-450 cells.
  12. Representative fields of immunohistochemistry results.
    Supplementary Fig. 8: Representative fields of immunohistochemistry results.

    The proteins of interest are designated in rows. Immunoreactivity scores are listed above. p-YAP1, phosphorylated YAP1.

  13. Somatic alterations in the PI3K-Ras and Notch pathways in ESCC.
    Supplementary Fig. 9: Somatic alterations in the PI3K-Ras and Notch pathways in ESCC.

    Genes are shown along with the percentage of samples with alterations, including somatic mutations (blue), homozygous deletions (green) and amplifications (red).

Accession codes

Referenced accessions

NCBI Reference Sequence

Change history

Corrected online 11 September 2014
In the version of this article initially published online, the word "alternations" in the abstract should have been "alterations," in Figure 1c "30" should have been "33," in the legend to Figure 1 "MIR458K" should have been "MIR548K," labels in Figure 2h were in the wrong position, and in the 'DNA constructs and mutagenesis' section in the Online Methods "BamHI" should have been "EcoRV" and the penultimate sentence should have been deleted. These errors have been corrected for the print, PDF and HTML versions of this article.

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Author information

Affiliations

  1. Department of Thoracic Surgery, Cancer Institute and Hospital Chinese Academy of Medical Sciences, Beijing, China.

    • Yi-Bo Gao,
    • Zhao-Li Chen,
    • Jia-Gen Li,
    • Xue-Da Hu,
    • Xue-Jiao Shi,
    • Zeng-Miao Sun,
    • Fan Zhang,
    • Zi-Yuan Liu,
    • Yu-Da Zhao,
    • Jian Sun,
    • Cheng-Cheng Zhou,
    • Ran Yao,
    • Su-Ya Wang,
    • Nan Sun,
    • Bai-Hua Zhang,
    • Jing-Si Dong,
    • Yue Yu,
    • Mei Luo,
    • Fang Zhou,
    • Feng-Wei Tan,
    • Bin Qiu,
    • Ning Li,
    • Kang Shao,
    • Qi Xue,
    • Shu-Geng Gao &
    • Jie He
  2. Department of Clinical Medicine, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.

    • Zi-Ran Zhao,
    • Zi-Tong Li &
    • Pan Wang
  3. Department of Pathology, Cancer Institute and Hospital Chinese Academy of Medical Sciences, Beijing, China.

    • Xiao-Li Feng &
    • Su-Sheng Shi
  4. Department of Thoracic Surgery, Peking University Cancer Hospital, Beijing, China.

    • Li-Jian Zhang
  5. Department of Thoracic Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China.

    • Lan-Jun Zhang

Contributions

J.H. devised and supervised this project. J.H. and Y.-B.G. designed the study and wrote the manuscript. J.H., F.-W.T., B.Q., N.L., K.S., Li-Jian Zhang, Lan-Jun Zhang, Q.X. and S.-G.G. contributed clinical samples and information. X.-L.F. and S.-S.S. performed pathological review. Y.-B.G., Z.-L.C., J.-G.L., Y.-D.Z., J.S., C.-C.Z., R.Y., S.-Y.W., P.W., N.S., B.-H.Z., J.-S.D., Y.Y., M.L. and F. Zhou processed the samples and performed the experiments. Y.-B.G. and Y.-D.Z. performed EP300 HAT domain sequencing. Y.-B.G. and X.-D.H. performed bioinformatic and statistical analyses. F. Zhang, Z.-R.Z., Z.-T.L., Y.-D.Z. and S.-Y.W. validated genetic variations. X.-J.S., Z.-M.S. and Z.-Y.L. performed cellular biology experiments. Y.-B.G., Z.-L.C., J.-G.L., X.-D.H., X.-J.S. and J.H. analyzed and discussed the data.

Competing financial interests

The authors declare no competing financial interests.

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Supplementary information

Supplementary Figures

  1. Supplementary Figure 1: Distribution of somatic mutations detected by exome sequencing in the ESCC patient cohort. (150 KB)

    The average, median and range of mutation numbers in each category are shown.

  2. Supplementary Figure 2: Landscape of somatic copy number alterations detected by exome sequencing in the ESCC patient cohort. (233 KB)

    Chromosomes are arranged circularly end to end, with the cytobands frequently affected marked in the outer rim. The inner space displays copy number data inferred from whole-exome sequencing, with red dots indicating copy number gains and blue dots indicating copy number losses. Amplifications are arranged as inward radiations in proportion to the fold change.

  3. Supplementary Figure 3: Substitution composition of smokers and non-smokers in the ESCC exome. (167 KB)

    (a) Comparison of the average substitution rates at non-CpG dinucleotides and at CpG dinucleotides between smokers and non-smokers. Most of the excessive substitution of C>T over C>A/G occurred at CpG dinucleotides. (b) Comparison of the average rates of all possible single-base substitutions between ESCC smokers (n = 77) and non-smokers (n = 36). Error bars indicate s.e.m. No significant difference was found between smokers and non-smokers.

  4. Supplementary Figure 4: Distribution of non-silent mutations or SCNAs of known cancer genes. (206 KB)

    (a) Mapping of cancer signaling pathways in ESCC, indicated by the number of mutations per capita and by the fraction of tumors carrying at least one mutation in the corresponding pathway. (b) Fraction of tumors carrying mutations in known oncogenes and tumor suppressor genes (TSGs). Pathway definition and gene classification are as shown in Supplementary Table 14.

  5. Supplementary Figure 5: Recurrently mutated COSMIC Cancer Census genes in ESCC cell lines. (240 KB)
  6. Supplementary Figure 6: Somatic alterations of RB1, NOTCH1, CCND1 and MIR548K correlate with clinical features. (305 KB)

    (a) Mutation spectrum of RB1 (n = 10). (b) RB1 mutation was associated with younger age of onset of ESCC (P = 0.010, Student’s t test, two-tailed). (c) Mutation spectrum of NOTCH1 (n = 16). (d) NOTCH1 mutation was associated with older age of onset of ESCC (P = 0.001, Student’s t test, two-tailed). Amplifications of (e) CCND1 and (f) MIR548K were associated with poor overall survival (P = 0.006 and P = 0.022, log-rank test).

  7. Supplementary Figure 7: Western blot confirmation of p300 knockdown efficiency in KYSE-150 and KYSE-450 cells. (117 KB)
  8. Supplementary Figure 8: Representative fields of immunohistochemistry results. (641 KB)

    The proteins of interest are designated in rows. Immunoreactivity scores are listed above. p-YAP1, phosphorylated YAP1.

  9. Supplementary Figure 9: Somatic alterations in the PI3K-Ras and Notch pathways in ESCC. (158 KB)

    Genes are shown along with the percentage of samples with alterations, including somatic mutations (blue), homozygous deletions (green) and amplifications (red).

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    Supplementary Figures 1–9

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    Supplementary Tables 1–21

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