A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer--a study of the OVCAD consortium
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A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer--a study of the OVCAD consortium. / Pils, Dietmar; Tong, Dan; Hager, Gudrun; Obermayr, Eva; Aust, Stefanie; Heinze, Georg; Kohl, Maria; Schuster, Eva; Wolf, Andrea; Sehouli, Jalid; Braicu, Ioana; Vergote, Ignace; Van Gorp, Toon; Mahner, Sven; Concin, Nicole; Speiser, Paul; Zeillinger, Robert.
In: BMC CANCER, Vol. 13, 01.01.2013, p. 178.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer--a study of the OVCAD consortium
AU - Pils, Dietmar
AU - Tong, Dan
AU - Hager, Gudrun
AU - Obermayr, Eva
AU - Aust, Stefanie
AU - Heinze, Georg
AU - Kohl, Maria
AU - Schuster, Eva
AU - Wolf, Andrea
AU - Sehouli, Jalid
AU - Braicu, Ioana
AU - Vergote, Ignace
AU - Van Gorp, Toon
AU - Mahner, Sven
AU - Concin, Nicole
AU - Speiser, Paul
AU - Zeillinger, Robert
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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.
AB - 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.
KW - Adult
KW - Aged
KW - Aged, 80 and over
KW - Analysis of Variance
KW - Area Under Curve
KW - Blood Proteins
KW - CA-125 Antigen
KW - Case-Control Studies
KW - Cystadenoma
KW - Female
KW - Gene Expression Profiling
KW - Humans
KW - Insulin-Like Growth Factor II
KW - Intramolecular Oxidoreductases
KW - Leptin
KW - Macrophage Migration-Inhibitory Factors
KW - Membrane Proteins
KW - Middle Aged
KW - Neoplasms, Glandular and Epithelial
KW - Oligonucleotide Array Sequence Analysis
KW - Osteopontin
KW - Ovarian Neoplasms
KW - Prolactin
KW - ROC Curve
KW - Retrospective Studies
KW - Tumor Markers, Biological
KW - Young Adult
U2 - 10.1186/1471-2407-13-178
DO - 10.1186/1471-2407-13-178
M3 - SCORING: Journal article
C2 - 23551967
VL - 13
SP - 178
JO - BMC CANCER
JF - BMC CANCER
SN - 1471-2407
ER -
