Tumor Biology

, Volume 37, Issue 5, pp 6349–6358 | Cite as

Diagnostic marker signature for esophageal cancer from transcriptome analysis

  • Ute Warnecke-Eberz
  • Ralf Metzger
  • Arnulf H. Hölscher
  • Uta Drebber
  • Elfriede Bollschweiler
Original Article


Esophageal cancer is often diagnosed at an advanced stage. Diagnostic markers are needed for achieving a cure in esophageal cancer detecting and treating tumor cells earlier. In patients with locally advanced squamous cell carcinoma of the esophagus (ESCC), we profiled the gene expression of ESCC compared to corresponding normal biopsies for diagnostic markers by genome microarrays. Profiling of gene expression identified 4844 genes differentially expressed, 2122 upregulated and 2722 downregulated in ESCC. Twenty-three overexpressed candidates with best scores from significance analysis have been selected for further analysis by TaqMan low-density array-technique using a validation cohort of 40 patients. The verification rate was 100 % for ESCC. Twenty-two markers were additionally overexpressed in adenocarcinoma of the esophagus (EAC). The markers significantly overexpressed already in earlier tumor stages (pT1-2) of both histological subtypes (n = 19) have been clustered in a “diagnostic signature”: PLA2G7, PRAME, MMP1, MMP3, MMP12, LIlRB2, TREM2, CHST2, IGFBP2, IGFBP7, KCNJ8, EMILIN2, CTHRC1, EMR2, WDR72, LPCAT1, COL4A2, CCL4, and SNX10. The marker signature will be translated to clinical practice to prove its diagnostic impact. This diagnostic signature may contribute to the earlier detection of tumor cells, with the aim to complement clinical techniques resulting in the development of better detection of concepts of esophageal cancer for earlier therapy and more favorite prognosis.


Esophageal cancer Diagnostic marker DNA microarrays Gene expression profiling 



Baculoviral IAP (inhibitor of apoptosis protein) Repeat-containing 5


Chemokine (C-C motif) ligand 4-like


Chemokine (C-X-C motif) ligand 6


Carbohydrate (N-acetyl-glucosamine-6-O) sulfotransferase 2


Cycle threshold


Collagen triple helix repeat containing 1


Collagen type IV, alpha2


Esophageal adenocarcinoma


Enzyme-linked immunosorbent assay


EGF-like module containing


Elastin microfibril interfacer 2


Esophageal squamous cell carcinoma


False discovery rate


Insulin-like growth factor-binding protein 2


Insulin-like growth factor-binding protein 7


Potassium inwardly-rectifying channel subfamilyJ,member 8




Insulin-like growth factor-binding protein 2


Low density array


Leucocyte immunoglobuline like receptor subfamily B, member2


Leucocyte immunoglobulin-like receptor subfamiliy A member 3


Leucocyte immunoglobuline-like receptor subfamily B, member4


Lysophatidylcholineacyltrans-ferase 1




Metalloproteinase 1


Metalloproteinase 3


Metalloproteinase 12


Phospholipase A2 group VII


Preferentially expressed antigen in melanoma


Pathologic tumor stage


Relative quantity


Reverse transcription


Real-time polymerase chain reaction


Significance analysis of microarrays


Sorting nexin 10


Tumor stage


Tumor-node-metastasis classification system of malignant tumors


Triggering receptor expressed on myeloid cells 2


WD repeat domain 72



We acknowledge Michaela Heitmann, Susanne Neiß, and Anke Wienand-Dorweiler for their excellent technical assistance.

Compliance with ethical standards

Conflicts of interest



  1. 1.
    Pennathur A, Gibson MK, Jobe BA. Oesophageal carcinoma. Lancet. 2013;381:400–12. doi: 10.1016/S0140-6736(12)60643-6.CrossRefPubMedGoogle Scholar
  2. 2.
    Bollschweiler E, Wolfgarten E, Gutschow C, Hölscher AH. Demographic variations in the rising incidence of esophageal adenocarcinoma in white males. Cancer. 2001;92:549–55.CrossRefPubMedGoogle Scholar
  3. 3.
    Thrift AP, Whiteman DC. The incidence of esophageal adenocarcinoma continues to rise: analysis of period and birth cohort effects on recent trends. Ann Oncol. 2012;23:3155–62.CrossRefPubMedGoogle Scholar
  4. 4.
    Lepage C, Drouillard A, Jouve JL, Faivre J. Epidemiology and risk factors for esophageal adenocarcinoma. Dig Liver Dis. 2013;45:625–9.CrossRefPubMedGoogle Scholar
  5. 5.
    Hölscher AH, Bollschweiler E, Schröder W, Metzger R, Gutschow C, Drebber U. Prognostic impact of upper, middle, and lower third mucosal or submucosal infiltration in early esopageal cancer. Ann Surg. 2011;254:802–7.CrossRefPubMedGoogle Scholar
  6. 6.
    Warnecke-Eberz U, Hoffmann A, Luebke T, Prenzel K, Metzger R, Heitmann M, et al. Surviving mRNA in peripheral blood is frequently detected and significantly decreased following resection of gastrointestinal cancers. J Surg Oncol. 2007;95:51–4.CrossRefPubMedGoogle Scholar
  7. 7.
    Zhang J, Zhu Z, Liu Y, Jin X, Xu Z, Yu Q, et al. Diagnostic value of multiple tumor markers for patients with esophageal carcinoma. PLoS One. 2015;10(2):e0116951. doi: 10.1371/journal.pone.0116951.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Metzger R, Heukamp L, Drebber U, Bollschweiler E, Hölscher AH, Warnecke-Eberz U. CUL2 and STK11 as novel response-predictive genes for neoadjuvant radiochemotherapy in esophageal cancer. Pharmacogenomics. 2010;11:1105–13.CrossRefPubMedGoogle Scholar
  9. 9.
    Warnecke-Eberz U, Metzger R, Bollschweiler E, Baldus SE, Müller RP, Dienes HP, et al. TaqMan low-density arrays and analysis by artificial neuronal networks predict response to neoadjuvant chemoradiation in esophageal cancer. Pharmacogenomics. 2011;11:55–64.CrossRefGoogle Scholar
  10. 10.
    Käll L, Storey JD, Noble WS. QVALITY: non-parametric estimation of q-values and posterior error probabilities. Bioinformatics. 2009;25:964–6.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Dulak AM, Stojanov P, Peng S, Lawrence MS, Fox C, Stewart C, et al. Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity. Nat Genet. 2013;45:478–86.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Gao Y-B, Chen Z-L, Li J-G, Hu X-D, Shi X-J, Sun ZM, et al. Genetic landscape of esophageal squamous cell carcinoma. Nat Genet. 2014;46:1097–102.CrossRefPubMedGoogle Scholar
  13. 13.
    Kim YW, Bae SM, Kim YW, Park DC, Lee KH, Liu HB, et al. Target-based molecular signature characteristics of cervical adenocarcinoma and squamous cell carcinoma. Int J Oncol. 2013;43:539–47.PubMedGoogle Scholar
  14. 14.
    Du Q, Yan W, Burgon VH, Hewitt SM, Wang L, Hu N, et al. Validation of esophageal squamous cell carcinoma candidate genes from high-throughput transcriptomic studies. Am J Cancer Res. 2013;3:402–10.PubMedPubMedCentralGoogle Scholar
  15. 15.
    An H, Chandra V, Piraino B, Borges L, Geczy C, McNeil HP, et al. Soluble LILRA3, a potential natural antiinflammatory protein, is increased in patients with rheumatoid arthritis and is tightly regulated by interleukin 10, tumor necrosis factor-alpha, and interferon-gamma. J Rheumatol. 2010;37:1596–606.CrossRefPubMedGoogle Scholar
  16. 16.
    El-sharkawi F, El Sabah M, Hassan Z, Khaled H. The biochemical value of urinary metalloproteinases 3 and 9 in diagnosis and prognosis of bladder cancer in Egypt. J Biomed Sci. 2014;21:72.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Fu JH, Wang LQ, Li T, Ma GJ. RNA-sequencing based identification of crucial genes for esophageal squamous cell carcinoma. J Cancer Res Ther. 2015;11:420–5.CrossRefPubMedGoogle Scholar
  18. 18.
    Su H, Hu N, Yang HH, Wang C, Takikita M, Wang Q-H, et al. Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes. Clin Cancer Res. 2011;17:2955–66.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Uraoka N, Oue N, Sakamotot N, Sentani K, Oo HZ, Naito Y, et al. NRD1, which encodes nardilysin protein, promotes esophageal cancer cell invasion through induction of MMP2 and MMP3 expression. Cancer Sci. 2014;105:134–40.CrossRefPubMedGoogle Scholar
  20. 20.
    Li X, Qu L, Zhong Y, Zhao Y, Chen H, Daru L. Association between promoters polymorphisms of matrix metalloproteinases and risk of digestive cancers: meta-analysis. J Cancer Res Clin Oncol. 2013;139:1433–47.CrossRefPubMedGoogle Scholar
  21. 21.
    Zhang J, Jin X, Fang S, Li Y, Wang R, Guo W, et al. The functional SNP in the matrix metalloproteinase-3 promoter modifies susceptibility and lymphatic metastasis in esophageal squamous cell carcinoma but not in gastric cardiac adenocarcinoma. Carcinogenesis. 2014;25:2519–24.CrossRefGoogle Scholar
  22. 22.
    Chen TY, Hwang TL, Lin CY, Lin TN, Lai HY, Tsai PW, et al. EMR2 receptor ligation modulates cytokine secretion profiles and cell survival of lipopolysaccharide-treated neutrophils. Chang Gung Med J. 2011;34:468–77.PubMedGoogle Scholar
  23. 23.
    Roman-Gomez J, Jimenez-Velasco A, Agirre X, Cast JA, Navarro G, San Jose-Eneriz E, et al. Epigenetic regulation of PRAME gene in chronic myeloid leukemia. Leuk Res. 2007;31:521–8.CrossRefGoogle Scholar
  24. 24.
    Szczepanski MJ, Whiteside TL, Szczepanski MJ, Whiteside TL. Elevated PRAME expression: what does this mean for treatment of head and neck squamous cell carcinoma? Biomark Med. 2013;7:575–8.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Sakurai E, Maesawa C, Shibazaki M, Yasuhira S, Oikawa H, Sato M, et al. Downregulation of miroRNA-211 is involved in expression of preferentially expressed antigen of melanoma in melanoma cells. Int J Oncol. 2011;39:665–72.PubMedGoogle Scholar
  26. 26.
    Saenger Y, Magidson J, Liaw B, de Moll E, Harcharik S, Fu Y, et al. Blood mRNA expression profiling predicts survival in patients treated with tremelimumab. Clin Cancer Res. 2014;12:3310–8.CrossRefGoogle Scholar
  27. 27.
    Vainio P, Lehtinen L, Mirtti T, Hilvo M, Seppänen-Laakso T, Virtanen J, et al. Phospholipase PLA2G7, associated with aggressive prostate cancer, promotes prostate cancer cell migration and invasion and is inhibited by statins. Oncotarget. 2011;2:1176–90.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Bell JL, Wächter K, Mühleck B, Pazaitis N, Köhn M, Lederer M, et al. Insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs): post-transcriptional drivers of cancer progression? Cell Mol Life Sci. 2013;70:2657–75.CrossRefPubMedGoogle Scholar
  29. 29.
    Fung KYC, Tabor B, Buckley MJ, Priebe IK, Purins L, Pompela C, et al. Blood-based protein biomarker panel for the detection of colorectal cancer. Plos One. 2015. doi: 10.1371/journal.pone.0120425.Google Scholar
  30. 30.
    Tessema M, Yingling CM, Liu Y, Tellez CS, Van Neste L, Baylin S, et al. Genome-wide unmasking of epigenetically silenced genes in lung adenocarcinoma from smokers and never smokers. Carcinogenesis. 2014;35:1248–57.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Yu C-J, Wang CL, Wang CI, Chen CD, Dan YM, Wu CC, et al. Comprehensive proteome analysis of malignant pleural effusion for lung cancer biomarker discovery by using multidimensional protein identification technology. J Proteome Res. 2011;10:4671–82.CrossRefPubMedGoogle Scholar
  32. 32.
    Marastoni S, Andreuzzi E, Paulitti A, Colladel R, Pelicani R, Todaro F, et al. EMILIN2 down-modulates the Wnt signalling pathway and suppresses breast cancer cell growth and migration. J Pathol. 2014;232:391–404.CrossRefPubMedGoogle Scholar
  33. 33.
    Mann B, Madera M, Klouckova I, Mechref Y, Dobrolecki LE, Hickey RJ, et al. A quantitative investigation of fucosylated serum glycoproteins with application to esophageal adenocarcinoma. Electrophoresis. 2010;31:1833–41.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Mares J, Szakacsova M, Soukup V, Duskova J, Horinek A, Babjuk M. Prediction of recurrence in low and intermediate risk non-muscle invasive bladder cancer by real-time quantitative PCR analysis: cDNA microarray results. Neoplasma. 2013;60:295–301.CrossRefPubMedGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2015

Authors and Affiliations

  1. 1.Laboratory for Molecular Oncology, General, Visceral and Cancer SurgeryUniversity Hospital of Cologne (CIO)CologneGermany
  2. 2.Caritasklinikum SaarbrückenSaarbrückenGermany
  3. 3.General, Visceral and Cancer SurgeryUniversity Hospital of Cologne (CIO)CologneGermany
  4. 4.Institute for PathologyUniversity Hospital of Cologne, Center for Integrated Oncology (CIO)CologneGermany

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