Genome-wide expression profiling reveals novel biomarkers in epithelial ovarian cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE212991 | GEO | 2022/09/13
REPOSITORIES: GEO
Similar Datasets
Project description:This study showed that MeDIP-seq could be used for methylation profiling in an efficient manner and identified a number of potential hub genes and pathways important in the ovarian cancer carcinogenesis that may deepen our understanding of the molecular mechanisms involved inthe development of ovarian cancer.
2023-12-31 | GSE244405 | GEO
Project description:Epithelial ovarian cancer (EOC) is a high-risk cancer presenting with heterogeneous tumors. The high incidence of EOC metastasis from primary tumors to nearby tissues and organs is a major driver of EOC lethality. We used cellular models of spheroid formation and re-adherence to investigate cellular signaling dynamics in each step toward EOC metastasis. In our system, adherent cells model primary tumors, spheroids formation represents the initiation of metastatic spread, while re-adherent spheroid cells represent secondary tumors. Proteomic and phosphoproteomic analyses show that spheroid cells are hypoxic and show markers for cell cycle arrest. Aurora kinase B (AURKB) abundance and downstream substrate phosphorylation are significantly reduced in spheroids and re-adherent cells, explaining their cell cycle arrest phenotype. The proteome of re-adherent cells is most similar to spheroids, yet greater changes in the phosphoproteome show that spheroid cells stimulate Rho-associated kinase 1 (ROCK1) mediated signaling, which controls cytoskeletal organization. In spheroids, we found significant phosphorylation of ROCK1 substrates that were reduced in both adherent and re-adherent cells. Application of the ROCK1-specific inhibitor Y-27632 to spheroids increased the rate of re-adherence and spheroid density. The data suggest ROCK1 inhibition increases EOC metastatic potential. We identified novel pathways controlled by AURKB and ROCK1 as major drivers of metastatic behavior in EOC cells. Our data show that phosphoproteomic reprogramming precedes proteomic changes that characterize spheroid re-adherence in EOC metastasis.
2024-01-26 | PXD043220 | Pride
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:Altered phosphatidylcholine (PC) metabolism in epithelial ovarian cancer (EOC) can provide choline-based imaging approaches as powerful tools to improve diagnosis and identify new therapeutic targets. Biochemical, protein and mRNA expression analyses demonstrated that the increase in the major choline-containing metabolite phosphocholine (PCho) in EOC compared with normal and non-tumoral immortalized counterparts (EONT) mainly rely upon: 1) ChoK activation, consistent with higher protein content and increased ChoK? mRNA expression levels; 2) PC-plc activation, consistent with higher, previously reported, protein expression. More limited and variable sources of PCho could derive, in some EOC cells, from activation of Phospholipase D or GPC-pd. Phospholipase A2 activity and isoforms’ expression levels were lower or unchanged in EOC compared with EONT cells. Increased ChoK? mRNA, as well as ChoK and PC-plc protein expression, were also detected in surgical specimens isolated from EOC patients. Overall, we demonstrated that the elevated PCho pool detected in EOC cells primarily resulted from the upregulation/activation of ChoK and PC-plc involved in the biosynthetic and in a degradative pathway of the PC-cycle, respectively. 20 EOC frozen surgical specimens, 8 EOC cell lines and Ovarian Surface Epithelial (OSE) cells (4 different preparations, 3 of them pooled in one sample).
2009-12-07 | E-GEOD-19352 | biostudies-arrayexpress
Project description:Altered phosphatidylcholine (PC) metabolism in epithelial ovarian cancer (EOC) can provide choline-based imaging approaches as powerful tools to improve diagnosis and identify new therapeutic targets. Biochemical, protein and mRNA expression analyses demonstrated that the increase in the major choline-containing metabolite phosphocholine (PCho) in EOC compared with normal and non-tumoral immortalized counterparts (EONT) mainly rely upon: 1) ChoK activation, consistent with higher protein content and increased ChoKalpha mRNA expression levels; 2) PC-plc activation, consistent with higher, previously reported, protein expression. More limited and variable sources of PCho could derive, in some EOC cells, from activation of Phospholipase D or GPC-pd. Phospholipase A2 activity and isoforms’ expression levels were lower or unchanged in EOC compared with EONT cells. Increased ChoKalpha mRNA, as well as ChoK and PC-plc protein expression, were also detected in surgical specimens isolated from EOC patients. Overall, we demonstrated that the elevated PCho pool detected in EOC cells primarily resulted from the upregulation/activation of ChoK and PC-plc involved in the biosynthetic and in a degradative pathway of the PC-cycle, respectively.
2009-12-08 | GSE19352 | GEO
Project description:Epithelial ovarian cancer (EOC) has the highest mortality among gynecological carcinomas. The lack of specific markers for prognostic determination of EOC progression hinders the search for novel effective therapies. The aim of the present study was (i) to explore differences in expressions of ATP-binding cassette and solute carrier transporter genes, genes associated with drug metabolism and cell cycle regulation between control ovarian tissues, primary epithelial ovarian carcinomas (EOC) and intraperitoneal EOC metastases; (ii) to investigate associations of gene expression level with prognosis of patients with intraperitoneal metastases.
2017-09-01 | GSE102180 | GEO
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:Epithelial ovarian cancer (EOC) represents the gynecologic cancer with the highest mortality rate. Despite a high initial response to chemotherapy, the majority of patients with advanced EOC relapses and subsequently develops chemoresistance that results in treatment failure and death of the patient. AIM: we have generated an isogenic model of PT-resistance in a panel of 3 EOC cell lines. microRNA profiling was used to identify new molecular pathway that regulate chemoresistance.
2017-07-24 | GSE93794 | GEO
Project description:Epithelial ovarian cancer (EOC) represents the gynecologic cancer with the highest mortality rate. Despite a high initial response to chemotherapy, the majority of patients with advanced EOC relapses and subsequently develops chemoresistance that results in treatment failure and death of the patient. AIM: we have generated an isogenic model of PT-resistance in a panel of 3 EOC cell lines. Gene Expression Profile (GEP) was used to identify new molecular pathawy that regulate chemoresistance.
2017-07-24 | GSE93793 | GEO
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.
2011-09-02 | GSE31682 | GEO