Blood based gene expression signature for diagnosis of epithelial ovarian cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE31682 | GEO | 2011/09/02
SECONDARY ACCESSION(S): PRJNA145643
REPOSITORIES: GEO
Similar Datasets
Project description:Objective: The immune system is a key player in fighting cancer. Thus, we seeked 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 48 EOC patients and 20 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 which were finally used in 343 samples (90 healthy, 6 cystadenoma, 8 low malignant potential tumor, and 239 EOC patients). Using new 65 controls and 224 EOC patients the abundances of six plasma proteins 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%. Conclusion: The combination of expression based and plasma protein based biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer. The expression of a blood cell fraction from 20 healthy controls and 48 patients with epithelial ovarian cancer was compared.
2011-09-01 | E-GEOD-31682 | biostudies-arrayexpress
Project description:Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC. We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validationsets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients. Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis. We designed a multi-stage, retrospective, nested case-control study to determine whether serum miRNA profiles can be used to predict EOC development. All samples were grouped into screening, training, and validation sets. A total of 560 plasma samples (360 cases and 200 controls) were obtained from Tianjin Medical University Cancer Institute and Hospital (TCIH) and Cancer Center of Nanjing Medical University. The cases and controls were well matched for age. The International Federation of Gynaecology and Obstetrics (FIGO) staging system was used to stage cases. All patients and controls were genetically unrelated, ethnic Han Chinese women who were permanent residents of the urban area of Tianjin and Nanjing. Controls with cardiovascular, respiratory, digestive, urinary, reproductive, and endocrine diseases were excluded. The study protocols were approved by the Tianjin and Nanjing Center review committees. In screening set, to detect generalizable miRNA signatures, we pooled serum samples of 10 early-stage cases (stage I), 10 late-stage cases (stage IIIc-IV), and 10 healthy controls, respectively, and analyzed these three pool samples using a TaqMan low-density array (TLDA set 2.0, Applied Biosystems) chip screening in the discovery stage. In training set, the miRNAs identified in the screening set were validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on individual plasma samples of 76 EOC patients and 30 normal controls. In validation set, the validation set comprised a two-phase process. Promising associations from the screening and training set were evaluated in the validation phase I set, comprising 134 cases and 70 controls from Tianjin Center. The validation phase II set included samples of 77 EOC cases and 50 normal controls were from Tianjin Center and 73 EOC cases and 50 normal controls were from Nanjing Center.
2013-08-30 | E-GEOD-50472 | biostudies-arrayexpress
Project description:Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC. We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validationsets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients. Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis.
2013-08-30 | GSE50472 | GEO
Project description:Epithelial ovarian cancer (EOC) is the type of ovarian cancer having the highest mortality rate. Because of the asymptomatic characteristic and a few diagnostic tests, it is mostly diagnosed at advanced stages. Therefore, this study aims to gain the predictive and/or early diagnostic novel circulating miRNAs for EOC. Firstly, microarray analysis of miRNA expression level is performed on plasma samples from pathologically confirmed EOC patients and matching healthy individuals; EOC tissue samples and benign ovarian neoplastic tissues. 31 significantly dysregulated miRNAs in serum and 3 miRNAs in tissue were identified by microarray. The results were validated using RT-qPCR. KEGG database was used for the target gene and pathway analysis. Three miRNA from EOC serum (hsa-miR-1909-5p, hsa-miR-885-5p, hsa-let-7d-3p) and one microRNA from tissue samples (hsa-miR-200c-3p) were validated as significant enough to distinguish EOC patients from healthy individuals. KEGG pathway enrichment analysis showed 7 significant pathways, which are prion diseases, proteoglycans in cancer, oxytocin signaling pathway, hippo signaling pathway, adrenergic signaling in cardiomyocytes, oocyte meiosis, and thyroid hormone signaling pathway, in which our validated miRNAs have a role. It supports our hypothesis that several miRNAs, in our case validated 4 miRNAs, can have the potential to be a biomarker of EOC diagnosis and treatment.
2023-02-24 | GSE216150 | GEO
Project description:Background
There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery.
Methods
We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues.
Results
We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues.
Conclusions
Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.
2024-03-01 | MSV000094219 | MassIVE
Project description:Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detection and management of this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. The immunoreactivity was compared between 45 BLBC cases and 45 controls against 10,000 human proteins that printed on microscopic slides
2015-04-22 | E-GEOD-68115 | biostudies-arrayexpress
Project description:Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detection and management of this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. The immunoreactivity was compared between 45 BLBC cases and 45 controls against 10,000 human proteins that printed on microscopic slides
2015-04-22 | E-GEOD-68114 | biostudies-arrayexpress
Project description:Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detection and management of this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. The immunoreactivity was compared between 45 BLBC cases and 45 controls against 10,000 human proteins that printed on microscopic slides
2015-04-22 | E-GEOD-68117 | biostudies-arrayexpress
Project description:Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detection and management of this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. The immunoreactivity was compared between 45 BLBC cases and 45 controls against 10,000 human proteins that printed on microscopic slides
2015-04-22 | E-GEOD-68116 | biostudies-arrayexpress
Project description:Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detection and management of this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. The immunoreactivity was compared between 45 BLBC cases and 45 controls against 10,000 human proteins that printed on microscopic slides
2015-04-22 | E-GEOD-68118 | biostudies-arrayexpress