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Genomic and molecular characterization of esophageal squamous cell carcinoma

Nature Genetics volume 46, pages 467–473 (2014)Cite this article

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Abstract

Esophageal squamous cell carcinoma (ESCC) is prevalent worldwide and particularly common in certain regions of Asia. Here we report the whole-exome or targeted deep sequencing of 139 paired ESCC cases, and analysis of somatic copy number variations (SCNV) of over 180 ESCCs. We identified previously uncharacterized mutated genes such as FAT1, FAT2, ZNF750 and KMT2D, in addition to those already known (TP53, PIK3CA and NOTCH1). Further SCNV evaluation, immunohistochemistry and biological analysis suggested their functional relevance in ESCC. Notably, RTK-MAPK-PI3K pathways, cell cycle and epigenetic regulation are frequently dysregulated by multiple molecular mechanisms in this cancer. Our approaches also uncovered many druggable candidates, and XPO1 was further explored as a therapeutic target because it showed both gene mutation and protein overexpression. Our integrated study unmasks a number of novel genetic lesions in ESCC and provides an important molecular foundation for understanding esophageal tumors and developing therapeutic targets.

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Figure 1: Mutation frequencies and signatures, and significantly mutated genes in 139 ESCCs.
Figure 2: Dysregulated pathways in ESCC.
Figure 3: Identification of ZNF750 as a recessive cancer gene newly implicated in ESCC.
Figure 4: Inactivation of FAT1 through multiple mechanisms.
Figure 5: Targeting XPO1 in ESCC.

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References

  1. Zhao, P., Dai, M., Chen, W. & Li, N. Cancer trends in China. Jpn. J. Clin. Oncol. 40, 281–285 (2010).

    Article  PubMed  Google Scholar 

  2. Pennathur, A., Gibson, M.K., Jobe, B.A. & Luketich, J.D. Oesophageal carcinoma. Lancet 381, 400–412 (2013).

    Article  PubMed  Google Scholar 

  3. Yang, Y.L. et al. Amplification of PRKCI, located in 3q26, is associated with lymph node metastasis in esophageal squamous cell carcinoma. Genes Chromosom. Cancer 47, 127–136 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. Bass, A.J. et al. SOX2 is an amplified lineage-survival oncogene in lung and esophageal squamous cell carcinomas. Nat. Genet. 41, 1238–1242 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Luo, M.L. et al. Amplification and overexpression of CTTN (EMS1) contribute to the metastasis of esophageal squamous cell carcinoma by promoting cell migration and anoikis resistance. Cancer Res. 66, 11690–11699 (2006).

    Article  CAS  PubMed  Google Scholar 

  6. Hu, N. et al. Genomic characterization of esophageal squamous cell carcinoma from a high-risk population in China. Cancer Res. 69, 5908–5917 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Shigaki, H. et al. PIK3CA mutation is associated with a favorable prognosis among patients with curatively resected esophageal squamous cell carcinoma. Clin. Cancer Res. 19, 2451–2459 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Agrawal, N. et al. Comparative genomic analysis of esophageal adenocarcinoma and squamous cell carcinoma. Cancer Discov. 2, 899–905 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Shi, Z.Z. et al. Genomic alterations with impact on survival in esophageal squamous cell carcinoma identified by array comparative genomic hybridization. Genes Chromosom. Cancer 50, 518–526 (2011).

    Article  CAS  PubMed  Google Scholar 

  10. Hirasaki, S. et al. BAC clones related to prognosis in patients with esophageal squamous carcinoma: an array comparative genomic hybridization study. Oncologist 12, 406–417 (2007).

    Article  CAS  PubMed  Google Scholar 

  11. Hu, N. et al. Genome wide analysis of DNA copy number neutral loss of heterozygosity (CNNLOH) and its relation to gene expression in esophageal squamous cell carcinoma. BMC Genomics 11, 576 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Beroukhim, R. et al. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lawrence, M.S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Shah, S.P. et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486, 395–399 (2012).

    Article  CAS  PubMed  Google Scholar 

  15. Burns, M.B., Temiz, N.A. & Harris, R.S. Evidence for APOBEC3B mutagenesis in multiple human cancers. Nat. Genet. 45, 977–983 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Burns, M.B. et al. APOBEC3B is an enzymatic source of mutation in breast cancer. Nature 494, 366–370 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Roberts, S.A. et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat. Genet. 45, 970–976 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Shi, Z.Z. et al. Consistent and differential genetic aberrations between esophageal dysplasia and squamous cell carcinoma detected by array comparative genomic hybridization. Clin. Cancer Res. 19, 5867–5878 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. Guagnano, V. et al. FGFR genetic alterations predict for sensitivity to NVP-BGJ398, a selective pan-FGFR inhibitor. Cancer Discov. 2, 1118–1133 (2012).

    Article  CAS  PubMed  Google Scholar 

  20. Lin, D.C., Du, X.L. & Wang, M.R. Protein alterations in ESCC and clinical implications: a review. Dis. Esophagus 22, 9–20 (2009).

    Article  PubMed  Google Scholar 

  21. Zhang, Y. et al. Reciprocal activation between PLK1 and Stat3 contributes to survival and proliferation of esophageal cancer cells. Gastroenterology 142, 521–530 (2012).

    Article  CAS  PubMed  Google Scholar 

  22. Liu, K. et al. Sox2 cooperates with inflammation-mediated Stat3 activation in the malignant transformation of foregut basal progenitor cells. Cell Stem Cell 12, 304–315 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Cohen, I. et al. ZNF750 is expressed in differentiated keratinocytes and regulates epidermal late differentiation genes. PLoS ONE 7, e42628 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Sen, G.L. et al. ZNF750 is a p63 target gene that induces KLF4 to drive terminal epidermal differentiation. Dev. Cell 22, 669–677 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yu, X. et al. Differentiation-associated genes regulated by TPA-induced c-Jun expression via a PKC/JNK pathway in KYSE450 cells. Biochem. Biophys. Res. Commun. 342, 286–292 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. Chen, H. et al. S100A14 is a novel modulator of terminal differentiation of esophageal squamous cell carcinoma. Mol. Cancer Res. 11, 1542–1553 (2013).

    Article  CAS  PubMed  Google Scholar 

  27. Morris, L.G. et al. Recurrent somatic mutation of FAT1 in multiple human cancers leads to aberrant Wnt activation. Nat. Genet. 45, 253–261 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Dikshit, B. et al. FAT1 acts as an upstream regulator of oncogenic and inflammatory pathways, via PDCD4, in glioma cells. Oncogene 32, 3798–3808 (2013).

    Article  CAS  PubMed  Google Scholar 

  29. de Bock, C.E. et al. The Fat1 cadherin is overexpressed and an independent prognostic factor for survival in paired diagnosis-relapse samples of precursor B-cell acute lymphoblastic leukemia. Leukemia 26, 918–926 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. Turner, J.G., Dawson, J. & Sullivan, D.M. Nuclear export of proteins and drug resistance in cancer. Biochem. Pharmacol. 83, 1021–1032 (2012).

    Article  CAS  PubMed  Google Scholar 

  31. Landau, D.A. et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell 152, 714–726 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Paraskeva, E. et al. CRM1-mediated recycling of snurportin 1 to the cytoplasm. J. Cell Biol. 145, 255–264 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Monecke, T. et al. Crystal structure of the nuclear export receptor CRM1 in complex with Snurportin1 and RanGTP. Science 324, 1087–1091 (2009).

    Article  CAS  PubMed  Google Scholar 

  34. Ranganathan, P. et al. Preclinical activity of a novel CRM1 inhibitor in acute myeloid leukemia. Blood 120, 1765–1773 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Etchin, J. et al. KPT-330 inhibitor of CRM1 (XPO1)-mediated nuclear export has selective anti-leukaemic activity in preclinical models of T-cell acute lymphoblastic leukaemia and acute myeloid leukaemia. Br. J. Haematol. 161, 117–127 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Etchin, J. et al. Antileukemic activity of nuclear export inhibitors that spare normal hematopoietic cells. Leukemia 27, 66–74 (2013).

    Article  CAS  PubMed  Google Scholar 

  37. Chen, L., Fischle, W., Verdin, E. & Greene, W.C. Duration of nuclear NF-kappaB action regulated by reversible acetylation. Science 293, 1653–1657 (2001).

    Article  CAS  Google Scholar 

  38. Kanezaki, R. et al. Transcription factor BACH1 is recruited to the nucleus by its novel alternative spliced isoform. J. Biol. Chem. 276, 7278–7284 (2001).

    Article  CAS  PubMed  Google Scholar 

  39. Kim, J.Y. & Casaccia, P. HDAC1 in axonal degeneration: a matter of subcellular localization. Cell Cycle 9, 3680–3684 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Lapalombella, R. et al. Selective inhibitors of nuclear export show that CRM1/XPO1 is a target in chronic lymphocytic leukemia. Blood 120, 4621–4634 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Schmidt, J. et al. Genome-wide studies in multiple myeloma identify XPO1/CRM1 as a critical target validated using the selective nuclear export inhibitor KPT-276. Leukemia 27, 2357–2365 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Walker, C.J. et al. Preclinical and clinical efficacy of XPO1/CRM1 inhibition by the karyopherin inhibitor KPT-330 in Ph+ leukemias. Blood 122, 3034–3044 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Tai, Y.T. et al. CRM1 inhibition induces tumor cell cytotoxicity and impairs osteoclastogenesis in multiple myeloma: molecular mechanisms and therapeutic implications. Leukemia 28, 155–165 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Huang, W.Y. et al. Prognostic value of CRM1 in pancreas cancer. Clin. Invest. Med. 32, E315 (2009).

    Article  PubMed  Google Scholar 

  45. Kojima, K. et al. Prognostic impact and targeting of CRM1 in acute myeloid leukemia. Blood 121, 4166–4174 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Noske, A. et al. Expression of the nuclear export protein chromosomal region maintenance/exportin 1/Xpo1 is a prognostic factor in human ovarian cancer. Cancer 112, 1733–1743 (2008).

    Article  CAS  PubMed  Google Scholar 

  47. Shen, A. et al. Expression of CRM1 in human gliomas and its significance in p27 expression and clinical prognosis. Neurosurgery 65, 153–159, discussion 159–160 (2009).

    Article  PubMed  Google Scholar 

  48. Wei, Q. et al. EGFR, HER2 and HER3 expression in esophageal primary tumours and corresponding metastases. Int. J. Oncol. 31, 493–499 (2007).

    PubMed  Google Scholar 

  49. Sato-Kuwabara, Y., Neves, J.I., Fregnani, J.H., Sallum, R.A. & Soares, F.A. Evaluation of gene amplification and protein expression of HER-2/neu in esophageal squamous cell carcinoma using fluorescence in situ hybridization (FISH) and immunohistochemistry. BMC Cancer 9, 6 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Boone, J. et al. mTOR in squamous cell carcinoma of the oesophagus: a potential target for molecular therapy? J. Clin. Pathol. 61, 909–913 (2008).

    Article  CAS  PubMed  Google Scholar 

  51. Akagi, I. et al. Overexpression of PIK3CA is associated with lymph node metastasis in esophageal squamous cell carcinoma. Int. J. Oncol. 34, 767–775 (2009).

    Article  CAS  PubMed  Google Scholar 

  52. Garnett, M.J. et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 483, 570–575 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Somaiah, N. & Simon, G.R. Molecular targeted agents and biologic therapies for lung cancer. J. Thorac. Oncol. 6, S1758–S1785 (2011).

    Article  PubMed  Google Scholar 

  54. Su, H. et al. Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes. Clin. Cancer Res. 17, 2955–2966 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Zhu, Y.H. et al. Downregulation of the novel tumor suppressor DIRAS1 predicts poor prognosis in esophageal squamous cell carcinoma. Cancer Res. 73, 2298–2309 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Lee, D.H. et al. Synergistic effect of low-dose cucurbitacin B and low-dose methotrexate for treatment of human osteosarcoma. Cancer Lett. 306, 161–170 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Sato, Y. et al. Integrated molecular analysis of clear-cell renal cell carcinoma. Nat. Genet. 45, 860–867 (2013).

    Article  CAS  PubMed  Google Scholar 

  58. Sakaguchi, H. et al. Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia. Nat. Genet. 45, 937–941 (2013).

    Article  CAS  PubMed  Google Scholar 

  59. Yoshida, K. et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature 478, 64–69 (2011).

    Article  CAS  PubMed  Google Scholar 

  60. Lin, D.C. et al. Genomic and functional characterizations of phosphodiesterase subtype 4D in human cancers. Proc. Natl. Acad. Sci. USA 110, 6109–6114 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Nannya, Y. et al. A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays. Cancer Res. 65, 6071–6079 (2005).

    Article  CAS  PubMed  Google Scholar 

  62. Yamamoto, G. et al. Highly sensitive method for genomewide detection of allelic composition in nonpaired, primary tumor specimens by use of affymetrix single-nucleotide-polymorphism genotyping microarrays. Am. J. Hum. Genet. 81, 114–126 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Eden, E., Navon, R., Steinfeld, I., Lipson, D. & Yakhini, Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10, 48 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Zhang, B., Kirov, S. & Snoddy, J. WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res. 33, W741–W748 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Wang, J., Duncan, D., Shi, Z. & Zhang, B. WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res. 41, W77–W83 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank P. Tan and Z. Zang for generously sharing related facilities. We also thank B. Koegler and S. Koegler for their generous support. This work is supported by National High-Tech R&D Program of China 2012AA02A503 and 2012AA02A209 (M.-R.W.), National Natural Science Foundation of China 81330052 (M.-R.W.), US National Institutes of Health grant R01CA026038-35 (H.P.K.), National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centers of Excellence initiative (H.P.K.), and Singapore Ministry of Health's National Medical Research Council under its Singapore Translational Research (STaR) Investigator Award to H.P.K.

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Author notes

  1. De-Chen Lin, Jia-Jie Hao, Yasunobu Nagata and Liang Xu: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Hematology/Oncology, Cedars-Sinai Medical Center, University of California Los Angeles School of Medicine, Los Angeles, California, USA

    De-Chen Lin & H Phillip Koeffler

  2. Cancer Science Institute of Singapore, National University of Singapore, Singapore

    De-Chen Lin, Liang Xu, Xuan Meng, Ana Maria Varela, Ling-Wen Ding, Manoj Garg, Li-Zhen Liu, Henry Yang & H Phillip Koeffler

  3. State Key Laboratory of Molecular Oncology, Cancer Institute (Hospital), Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China

    Jia-Jie Hao, Li Shang, Zhi-Zhou Shi, Yan-Yi Jiang, Wen-Yue Gu, Ting Gong, Yu Zhang, Xin Xu & Ming-Rong Wang

  4. Cancer Genomics Project, Graduate School of Medicine, University of Tokyo, Tokyo, Japan

    Yasunobu Nagata, Yusuke Sato, Yusuke Okuno & Seishi Ogawa

  5. Medical Research Center, Sun Yat-Sen Memorial Hospital, Guangzhou, China

    Dong Yin

  6. Karyopharm Therapeutics, Natick, Massachusetts, USA

    Ori Kalid & Sharon Shacham

  7. National University Cancer Institute, National University Hospital Singapore, Singapore

    H Phillip Koeffler

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Contributions

D.-C.L., M.-R.W. and H.P.K. designed the study and wrote the manuscript. D.-C.L., J.-J.H., Y.N., Y.S., Y.O., X.M., L.X., A.M.V., L.-W.D. and M.G. performed experiments. D.Y, J.-J.H., Z.-Z.S., L.S., Y.-Y.J., W.-Y.G., T.G., Y.Z. and X.X. coordinated sample collection and processing. O.K. and S.S. provided KPT-330 and structurally analyzed XPO1 point mutation. D.-C.L., J.-J.H., Y.N., S.O., M.-R.W. and H.P.K. analyzed and discussed the data. Y.N., H.Y., L.-Z.L., Y.S. and Y.O. performed bioinformatical analysis.

Corresponding authors

Correspondence to De-Chen Lin or Ming-Rong Wang.

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Competing interests

O.K. and S.S. are employees of Karyopharm Therapeutics Incorporated. The remaining authors declare no conflict of interest.

Integrated supplementary information

Supplementary Figure 1 Somatic mutation frequencies detected in exomes from ESCC and other human cancers.

Each dot represents an examined case (tumor-germline pair), and tumor types are ordered by their median somatic mutation frequencies (indicated by the black dash line). The number beneath X-axis indicates the number of examined cases of each cancer. Except ESCC, all of the other cancers were sequenced and published elsewhere, and their data were re-analyzed by Lawrence et al. CLL, chronic lymphocytic leukemia; MM, multiple myeloma; GBM, glioblastoma multiforme; DLBCL, diffuse large B-cell lymphoma; HNSCC, head and neck squamous cell carcinoma; EAC, esophageal adenocarcinoma; Lung AC, lung adenocarcinoma; Lung SCC, lung squamous cell carcinoma.

Source data

Supplementary Figure 2 Intratumoral clonality analysis.

Intratumoral clonality plots of four representative ESCC cases from Discovery Cohort. ESCC-D13, D15, D17 tumors were developed bi-clonaly whereas ESCC-D14 tumor showed multi-clonal structure. Variant allele frequency was calculated with copy-number neutral variants, which was further used to plot intratumoral clonal architectures.

Source data

Supplementary Figure 3 Mutation types and signatures in ESCC.

(a) The occurrence of the six types of base-substitution mutations observed in ESCC. (b) The occurrence of cytosine mutations at each group of trinucleotide, which shows biases toward mutations of TCN motifs. (c) Genes mutated in over 5% (≥ 7 cases) of the entire cohort.

Source data

Supplementary Figure 4 Down-regulation of FBXW7 protein expression in ESCC.

Representative FBXW7 IHC results of one ESCC case from Additional Cohort (Upper panel) and one ESCC case from Frequency Cohort with FBXW7 mutation. Scale bars, 200 μm.

Supplementary Figure 5 Identification of ZNF750 as a novel recessive cancer gene in ESCC.

(a) Box plot showing relative ZNF750 mRNA levels in 947 human cancer cell lines across 21 cancer types analyzed from CCLE database (see URL for the description of Box Plot). Number in the parentheses indicates the number of cell lines analyzed. (b) Summary of somatic mutations affecting ZNF750 across different tumor types including mutation data reported by The Cancer Genome Atlas (TCGA, see URL) and Catalogue Of Somatic Mutations In Cancer (COSMIC, see URL). Number in the parentheses indicates the number of cases sequenced. Concerning C-Mel/CSCC, in TCGA pathological reports, several cutaneous melanoma (C-Mel) patients with ZNF750 mutations also had cutaneous squamous cell carcinoma (CSCC). UASCC, upper aerodigestive squamous cell carcinoma; HNSCC, head and neck squamous cell carcinoma; CRC, colon and rectum adenocarcinoma; LG Glioma, lower grade glioma; AML, acute myeloid leukemia; GBM, glioblastoma multiforme; AG, autonomic ganglia carcinoma. Squamous cell carcinomas were highlighted with Orange Square. (c) Upper panel, mRNA expression of indicated terminal differentiation-related genes quantified with q-PCR in EC109 and KYSE180 cells transfected with either siRNAs against ZNF750 (siZNF750) or control siRNA (Scramble), as well as (lower panel) infected with lentivirus encoding either of ZNF750 protein (Flag-ZNF750) or GFP (GFP-control). WB results showing ZNF750 protein level in indicated samples. β-Actin was used as a loading control. Value represent mean ± s.d. N = 5. (d) Short-term cell proliferation assay of ESCC cells treated with control medium (DMSO) or TPA (100nM) for 5 days. N = 3. **, P < 0.01; *, P < 0.05.

Source data

Supplementary Figure 6 FAT gene mutations and loss of heterozygosity.

(a) Summary of somatic mutations affecting FAT1, FAT2 and FAT3 across different tumor types from COSMIC. Number in the parentheses indicates the number of cases sequenced. (b) Inactivation of both alleles of FAT1 in two ESCC cases. Upper panel, SNP-array data showing FAT1 loss of heterozygosity in both tumors (ESCC-D10 and ESCC-D20, which were from Discovery Cohort). Blue line, total gene dosage; Green and red line, alleles-specific gene dosage. The number on the left indicates log2 tumor/reference ratio. Lower panel, Sanger sequencing signals confirmed the somatic mutations of FAT1 in both cases. Arrows indicate the beginning of frameshift mutation bases in tumor DNA and the corresponding bases in germline DNA.

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Supplementary Figure 7 The growth-suppressive properties of FAT1 in ESCC cells.

KYSE150 cells stably expressing either FAT1 protein (Flag-FAT1) or GFP (GFP-control) were subjected to (a) short-term cell proliferation assay or (b) soft-agar colony formation assay. (c) WB results showing FAT1 protein level. β-Actin was used as a loading control. Value represent mean ± SD. N = 3. **, P < 0.01. *, P < 0.05.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Tables 1–13 (PDF 15766 kb)

Supplementary Table 14

Chromosome regions for targeted capture with SureSelect cRNA baits (Frequency Cohort). (XLSX 899 kb)

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Lin, DC., Hao, JJ., Nagata, Y. et al. Genomic and molecular characterization of esophageal squamous cell carcinoma. Nat Genet 46, 467–473 (2014). https://doi.org/10.1038/ng.2935

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