Nuclear HKII-P-p53 (Ser15) Interaction is a Prognostic Biomarker for Chemoresponsiveness and Glycolytic Regulation in Epithelial Ovarian Cancer.
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SUBMITTER: Han CY
PROVIDER: S-EPMC8306240 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundResistance to chemotherapy continues to be a challenge when treating epithelial ovarian cancer (EOC), contributing to low patient survival rates. While CA125, the conventional EOC biomarker, has been useful in monitoring patients' response to therapy, there are no biomarkers used to predict treatment response prior to chemotherapy. Previous work in vitro showed that plasma gelsolin (pGSN) is highly expressed in chemoresistant EOC cell lines, where it is secreted in small extracellular vesicles (sEVs). Whether sEVs from tumour cells are secreted into the circulation of EOC patients and could be used to predict patient chemoresponsiveness is yet to be determined. This study aims to identify if sEV-pGSN in the circulation could be a predictive biomarker for chemoresistance in EOC.MethodsSandwich ELISA was used to measure pGSN concentrations from plasma samples of 96 EOC patients (primarily high grade serous EOC). sEVs were isolated using ExoQuick ULTRA and characterized using western blot, nanoparticle tracking analysis, and electron microscopy after which pGSN was measured from the sEVs. Patients were stratified as platinum sensitive or resistant groups based on first progression free interval (PFI) of 6 or 12 months.ResultsTotal circulating pGSN was significantly decreased and sEV-pGSN increased in patients with a PFI ≤ 12 months (chemoresistant) compared to those with a PFI > 12 months (chemosensitive). The ratio of total pGSN to sEV-pGSN further differentiated these groups and was a strong predictive marker for chemoresistance (sensitivity: 73.91%, specificity: 72.46%). Predetermined CA125 was not different between chemosensitive and chemoresistant groups and was not predictive of chemoresponsiveness prior to treatment. When CA125 was combined with the ratio of total pGSN/sEV-pGSN, it was a significant predictor of chemoresponsiveness, but the test performance was not as robust as the total pGSN/sEV-pGSN alone.ConclusionsTotal pGSN/sEV-pGSN was the best predictor of chemoresponsiveness prior to treatment, outperforming the individual biomarkers (CA125, total pGSN, and sEV-pGSN). This multianalyte predictor of chemoresponsiveness could help to inform physicians' treatment and follow up plan at the time of EOC diagnosis, thus improving patients' outcomes.
| S-EPMC9841140 | biostudies-literature
Project description:PurposeTo analyze the role of six human epididymis protein 4 (HE4)-related mitochondrial ribosomal proteins (MRPs) in ovarian cancer and selected MRPL15, which is most closely related to the tumorigenesis and prognosis of ovarian cancer, for further analyses.MethodsUsing STRING database and MCODE plugin in Cytoscape, six MRPs were identified among genes that are upregulated in response to HE4 overexpression in epithelial ovarian cancer cells. The Cancer Genome Atlas (TCGA) ovarian cancer, GTEX, Oncomine, and TISIDB were used to analyze the expression of the six MRPs. The prognostic impact and genetic variation of these six MRPs in ovarian cancer were evaluated using Kaplan-Meier Plotter and cBioPortal, respectively. MRPL15 was selected for immunohistochemistry and GEO verification. TCGA ovarian cancer data, gene set enrichment analysis, and Enrichr were used to explore the mechanism of MRPL15 in ovarian cancer. Finally, the relationship between MRPL15 expression and immune subtype, tumor-infiltrating lymphocytes, and immune regulatory factors was analyzed using TCGA ovarian cancer data and TISIDB.ResultsSix MRPs (MRPL10, MRPL15, MRPL36, MRPL39, MRPS16, and MRPS31) related to HE4 in ovarian cancer were selected. MRPL15 was highly expressed and amplified in ovarian cancer and was related to the poor prognosis of patients. Mechanism analysis indicated that MRPL15 plays a role in ovarian cancer through pathways such as the cell cycle, DNA repair, and mTOR 1 signaling. High expression of MRPL15 in ovarian cancer may be associated with its amplification and hypomethylation. Additionally, MRPL15 showed the lowest expression in C3 ovarian cancer and was correlated with proliferation of CD8+ T cells and dendritic cells as well as TGFβR1 and IDO1 expression.ConclusionMRPL15 may be a prognostic indicator and therapeutic target for ovarian cancer. Because of its close correlation with HE4, this study provides insights into the mechanism of HE4 in ovarian cancer.
| S-EPMC8178508 | biostudies-literature
Project description:Background:p53 is a tumor suppressor and key regulator of glycolysis in cancer cells, however highly mutated in tumors. In ovarian cancer, studies concerning p53 mutations focus on the DNA binding domain since the majority of hotspot mutations affects this region. Yet, mutations in other regions such as the proline rich domain may also affect the protein's expression and activity. The aim of this study is to investigate the effect of various positions of mutations in TP53 gene on glycolysis, apoptosis and transcription of p53 target genes. Methods:Mutations frequency and their effect on p53 expression were assessed by PCR-SSCP, sequencing and immunohistochemistry on 30 ovarian cancer biopsies. Six tumors were cultured, as well as SK-OV-3, OVCAR-3 and Igrov-1. SK-OV-3 cells were transfected with 2 TP53 mutants. p53 transcriptional activity was assayed by qPCR, apoptosis by flow cytometry and glycolysis by glucose and lactate measurements, with quantification of glycolytic enzymes expression. Results:Our results showed a high frequency of the P72R mutant, associated with p53 overexpression in the ovarian biopsies. However, P72R mutant cells showed similar apoptosis and glycolysis as WT cells. DNA binding domain mutations decreased the transcriptional activity of the protein and increased glucose consumption and lactate production. Conclusion:Despite the overexpression of the P72R mutated protein in the biopsies, it showed a similar apoptotic activity and glucose regulation ability as WT p53. Knowing that p53 expression status is used for chemotherapeutic approaches and prognosis in ovarian cancer, the results obtained highlight the importance of locating TP53 mutations.
| S-EPMC5791177 | biostudies-literature
Project description:Protein biomarkers of early stages of disease are critical for managing the disease and improving outcomes. Unfortunately, discovery of protein biomarkers is hampered by the limited availability of assays for sensitive and reproducible quantification of proteins in complex biological matrices such as blood plasma. In the recent years, Selected Reaction Monitoring (SRM) has emerged as a robust mass spectrometric method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing protein biomarkers for epithelial ovarian cancer, and illustrate the extent to which SRM platform, combined with sound experimental design and statistical analysis, results in robust detection of predictive analytes. First, the biomarker development was guided by a discovery-driven proteomic effort to detect potential N-glycoprotein biomarker candidates in tissue of a genetically stable ovarian cancer mouse model. Next, 65 candidate markers were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive 5-protein signatures for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
2019-07-02 | MSV000084048 | MassIVE
Project description:BACKGROUND:Primary systemic treatment for ovarian cancer is surgery, followed by platinum based chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers of platinum resistance. METHODS:A database of ovarian cancer transcriptomic datasets including treatment and response information was set up by mining the GEO and TCGA repositories. Receiver operator characteristics (ROC) analysis was performed in R for each gene and these were then ranked using their achieved area under the curve (AUC) values. The most significant candidates were selected and in vitro functionally evaluated in four epithelial ovarian cancer cell lines (SKOV-3-, CAOV-3, ES-2 and OVCAR-3), using gene silencing combined with drug treatment in viability and apoptosis assays. We collected 94 tumor samples and the strongest candidate was validated by IHC and qRT-PCR in these. RESULTS:All together 1,452 eligible patients were identified. Based on the ROC analysis the eight most significant genes were JRK, CNOT8, RTF1, CCT3, NFAT2CIP, MEK1, FUBP1 and CSDE1. Silencing of MEK1, CSDE1, CNOT8 and RTF1, and pharmacological inhibition of MEK1 caused significant sensitization in the cell lines. Of the eight genes, JRK (p?=?3.2E-05), MEK1 (p?=?0.0078), FUBP1 (p?=?0.014) and CNOT8 (p?=?0.00022) also correlated to progression free survival. The correlation between the best biomarker candidate MEK1 and survival was validated in two independent cohorts by qRT-PCR (n?=?34, HR?=?5.8, p?=?0.003) and IHC (n?=?59, HR?=?4.3, p?=?0.033). CONCLUSION:We identified MEK1 as a promising prognostic biomarker candidate correlated to response to platinum based chemotherapy in ovarian cancer.
| S-EPMC4247127 | biostudies-literature
Project description:Background: Drug resistance is a major obstacle to successful chemotherapy for epithelial ovarian cancer (EOC). We found a subset of miRNAs associated with the response to first-line platinum-based chemotherapy in EOC by microarray, and miR-206 was one of the most significant miRNAs. The purposes of this study were to evaluate the prognostic and platinum-resistance predictive value of miR-206 in EOC patients and to investigate the functional roles of miR-206 in regulating the platinum resistance of EOC and the underlying mechanism.Methods: MiRNA expression profiling in EOC specimens was performed using a TaqMan miRNA array. miR-206 expression was confirmed by quantitative real-time PCR (qRT-PCR) analysis. Overexpression of miR-206 in EOC cell lines was achieved by the stable transfection of a recombinant plasmid. In vitro assays of cisplatin cytotoxicity, cell cycle distribution, apoptosis, transwell invasion and cell scratching were employed. Connexin 43 (Cx43) expression was detected by Western blotting. Murine xenograft models were used to determine the effects of miR-206 on platinum resistance in vivo.Results: miR-206 expression was increased in primary platinum-resistant EOC. High miR-206 expression was related to poor prognosis in EOC patients who received platinum-based chemotherapy and predicted chemoresistance to platinum treatment. Overexpression of miR-206 in cisplatin-sensitive EOC cell lines significantly increased cell viability, migration and invasion in the presence of cisplatin and decreased cisplatin-induced apoptosis. Cx43, a target gene of miR-206, was negatively regulated by miR-206 in EOC cell lines and significantly related to better prognosis in patients who received platinum-based chemotherapy (KmPlot). miR-206 had high expression and Cx43 had low expression in platinum-sensitive EOC cell lines compared with resistant ones. In vivo murine xenograft models showed that miR-206 profoundly promoted the chemoresistance of EOC to cisplatin treatment.Conclusion: miR-206 was highly expressed in primary platinum-resistant EOCs and functionally promoted platinum resistance in part by downregulating Cx43 expression, thereby providing a useful biomarker for prognostic and platinum-resistance prediction.
| S-EPMC7641844 | biostudies-literature
Project description:PurposeThe dysregulation of arrestin domain containing 3 (ARRDC3) has an important effect on oncogenesis and tumor progression in many cancers, including renal cell carcinoma and breast cancer. However, the role of ARRDC3 in ovarian cancer (OC) has not been reported.MethodsThe present study explored the diagnostic and prognostic roles of ARRDC3 in ovarian cancer using GEPIA, ONCOMINE, GEO, and Kaplan-Meier Plotter databases for training and validation. Then, we conducted a stratified analysis for clinicopathological factors using Kaplan-Meier Plotter and GEPIA databases. To further explore the mechanisms, we also used the MIST database to visualize the protein-protein interaction network of ARRDC3 associated with OC. The gene-gene interaction network was visualized by GeneMANIA plugin in Cytoscape 3.8.0 software, and the associated co-expression genes of ARRDC3 were analyzed by the cBioPortal database. The 100 top co-expression genes chosen for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used by the DAVID website.ResultsA significant difference in ARRDC3 mRNA expression was found between OC and normal ovary tissues. ARRDC3 could potentially be implicated in the diagnosis of OC. A high ARRDC3 mRNA expression level was associated with poor overall survival and progression-free survival. However, no significance was reported in respect to post progression survival. Except for histology, which had no prognostic value for PPS in stratified analysis, stratified analysis of other factors had prognostic value for OS, PFS, and PPS. Interestingly, we found a positive correlation between ARRDC3 expression and CD8+ T cells, macrophages, neutrophils, and dendritic cells, indicating that ARRDC3 might be associated with immune infiltration of these immune cells. Co-expression genes enrichment analysis found that they were involved in the Renin-angiotensin system pathway.ConclusionDifferentially expressed ARRDC3 might be a potential prognostic and diagnostic marker in Ovarian Cancer.
| S-EPMC7997607 | biostudies-literature
Project description:ObjectiveThe aim of the present study was to construct and test a liquid-liquid phase separation (LLPS)-related gene signature as a prognostic tool for epithelial ovarian cancer (EOC).Materials and methodsThe data set GSE26712 was used to screen the differentially expressed LLPS-related genes. Functional enrichment analysis was performed to reveal the potential biological functions. GSE17260 and GSE32062 were combined as the discovery to construct an LLPS-related gene signature through a three-step analysis (univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox analyses). The EOC data set from The Cancer Genome Atlas as the test set was used to test the LLPS-related gene signature.ResultsThe differentially expressed LLPS-related genes involved in several cancer-related pathways, such as MAPK signaling pathway, cell cycle, and DNA replication. Eleven genes were selected to construct the LLPS-related gene signature risk index as prognostic biomarker for EOC. The risk index could successfully divide patients with EOC into high- and low-risk groups. The patients in high-risk group had significantly shorter overall survival than those with in low-risk group. The LLPS-related gene signature was validated in the test set and may be an independent prognostic factor compared to routine clinical features.ConclusionWe constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.
| S-EPMC8217755 | biostudies-literature
Project description:BACKGROUND: Tumour necrosis factor-?-induced protein 8 (TNFAIP8) has been recently documented in various malignancies, but its role in epithelial ovarian cancer (EOC) remains unknown. METHODS: Tumour necrosis factor-?-induced protein 8 expression was determined by real-time reverse transcription PCR and western blot analysis. Tumour tissues, consisting of serous, mucinous, endometrioid and clear cell histotypes, from 202 EOC patients (International Federation of Gynecologists and Obstetricians I-IV) who underwent primary cytoreduction were collected. Then, we examined the immunohistochemical expression of TNFAIP8 and evaluated its clinical significances. RESULTS: Tumour necrosis factor-?-induced protein 8 overexpression was significantly associated with high histologic grade (P=0.005), large residual tumour size (P=0.014), recurrence (P=0.024) and response to chemotherapy (P<0.001). Multivariate analysis showed that TNFAIP8 overexpression was independently correlated with the presence of lymph node (odds ratio (OR): 4.129; 95% confidence interval (CI): 1.491-11.435; P=0.006) and intraperitoneal metastasis (OR: 2.209; 95% CI: 1.174-4.156; P=0.014). Moreover, results revealed that the status of TNFAIP8 expression was an independently prognostic factor for both cancer-specific survival (hazard ratio (HR): 1.852; 95% CI: 1.322-2.594; P<0.001) and disease-free survival (HR: 1.724; 95% CI: 1.235-2.407; P=0.001) in patients with EOC. CONCLUSION: The present data provide evidence that TNFAIP8 predicts EOC metastasis and poor survival, highlighting its potential function as a therapeutic target for EOCs.
| S-EPMC3777007 | biostudies-other
Project description:BackgroundAmplified centrosomes in cancers are recently garnering a lot of attention as an emerging hub of diagnostic, prognostic and therapeutic targets. Ovarian adenocarcinomas commonly harbor supernumerary centrosomes that drive chromosomal instability. A centrosome clustering molecule, KIFC1, is indispensable for the viability of extra centrosome-bearing cancer cells, and may underlie progression of ovarian cancers.MethodsCentrosome amplification in low- and high- grade serous ovarian adenocarcinomas was quantitated employing confocal imaging. KIFC1 expression was analyzed in ovarian tumors using publically-available databases. Associated grade, stage and clinical information from these databases were plotted for KIFC1 gene expression values. Furthermore, interactions and functional annotation of KIFC1 and its highly correlated genes were studied using DAVID and STRING 9.1.ResultsClinical specimens of ovarian cancers display robust centrosome amplification and deploy centrosome clustering to execute an error-prone mitosis to enable karyotypic heterogeneity that fosters tumor progression and aggressiveness. Our in silico analyses showed KIFC1 overexpression in human ovarian tumors (n = 1090) and its upregulation associated with tumor aggressiveness utilizing publically-available gene expression databases. KIFC1 expression correlated with advanced tumor grade and stage. Dichotomization of KIFC1 levels revealed a significantly lower overall survival time for patients in high KIFC1 group. Intriguingly, in a matched-cohort of primary (n = 7) and metastatic (n = 7) ovarian samples, no significant differences in KIFC1 expression were detectable, suggesting that high KIFC1 expression may serve as a marker of metastases onset. Nonetheless, KIFC1 levels in both primary and matched metastatic sites were significantly higher compared to normal tissue . Ingenuity based network prediction algorithms combined with pre-established protein interaction networks uncovered several novel cell-cycle related partner genes on the basis of interconnectivity, illuminating the centrosome clustering independent agenda of KIFC1 in ovarian tumor progression.ConclusionsOvarian cancers display amplified centrosomes, a feature of aggressive tumors. To cope up with the abnormal centrosomal load, ovarian cancer cells upregulate genes like KIFC1 that are known to induce centrosome clustering. Our data underscore KIFC1 as a putative biomarker that predicts worse prognosis, poor overall survival and may serve as a potential marker of onset of metastatic dissemination in ovarian cancer patients.
| S-EPMC4098650 | biostudies-literature