A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer - a study of the OVCAD consortium

BMC Cancer

Robert Zeillinger⁴  Paul Speiser²  Nicole Concin⁶  Sven Mahner⁸  Toon Van Gorp³  Ignace Vergote⁷  Ioana Braicu⁵  Jalid Sehouli⁵  Andrea Wolf²  Eva Schuster²  Maria Kohl¹  Georg Heinze¹  Stefanie Aust²  Eva Obermayr²  Gudrun Hager²  Dan Tong²  Dietmar Pils⁴ 

[1]Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, European Union, Vienna, Austria

[2]Department of Obstetrics and Gynecology, Molecular Oncology Group, Medical University of Vienna, European Union, Vienna, Austria

[3]Division of Gynaecological Oncology, Department of Obstetrics and Gynaecology, MUMC+, GROW – School for Oncology and Developmental Biology, European Union, Maastricht, The Netherlands

[4]Ludwig Boltzmann Cluster “Translational Oncology”, General Hospital Vienna, European Union, Waehringer Guertel 18-20, Room-No.: 5.Q9.27, Vienna, A-1090, Austria

[5]Department of Gynecology, Campus Virchow Klinikum, Charite Medical University, European Union, Berlin, Germany

[6]Department of Gynecology and Obstetrics, Innsbruck Medical University, European Union, Innsbruck, Austria

[7]Department of Obstetrics and Gynecology, Division of Gynecological Oncology, University Hospitals Leuven, Katholieke Universiteit Leuven, European Union, Leuven, Belgium

[8]Department of Gynecology and Gynecologic Oncology, University Medical Center Hamburg-Eppendorf, European Union, Hamburg, Germany

关键词: Ovarian cancer;    Diagnosis;    Plasma protein;    Transcriptomics;    Biomarker;    Peripheral blood leukocytes;   

Others  :  1079812
DOI  :  10.1186/1471-2407-13-178

 received in 2012-07-25, accepted in 2013-03-18,  发布年份 2013

【 摘 要 】

Background

The immune system is a key player in fighting cancer. Thus, we sought to identify a molecular ‘immune response signature’ indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC.

Methods

Comparing the expression of 32,000 genes in a leukocytes fraction from 44 EOC patients and 19 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes (AP2A1, B4GALT1, C1orf63, CCR2, CFP, DIS3, NEAT1, NOXA1, OSM, PAPOLG, PRIC285, ZNF419, and BC037918) which were finally used in 343 samples (90 healthy, six cystadenoma, eight low malignant potential tumor, 19 FIGO I/II, and 220 FIGO III/IV EOC patients). Using new 65 controls and 224 EOC patients (thereof 14 FIGO I/II) the abundances of six plasma proteins (MIF, prolactin, CA125, leptin, osteopondin, and IGF2) was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC.

Results

Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%.

Conclusions

The combination of gene expression and plasma protein based blood derived biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer.

【 授权许可】

   
2013 Pils et al.; licensee BioMed Central Ltd.

【 图 表 】

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