scholarly journals MicroRNA characteristics in epithelial ovarian cancer

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252401
Author(s):  
Kira Philipsen Prahm ◽  
Claus Kim Høgdall ◽  
Mona Aarenstrup Karlsen ◽  
Ib Jarle Christensen ◽  
Guy Wayne Novotny ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Expression Profiles ◽  
Pelvic Mass ◽  
Figo Stage ◽  
Clinicopathological Characteristics ◽  
Type I ◽  
Histologic Subtype ◽  
Mirna Expression Profiles ◽  
Using Data

The purpose of the current study was to clarify differences in microRNA expression according to clinicopathological characteristics, and to investigate if miRNA profiles could predict cytoreductive outcome in patients with FIGO stage IIIC and IV ovarian cancer. Patients enrolled in the Pelvic Mass study between 2004 and 2010, diagnosed and surgically treated for epithelial ovarian cancer, were used for investigation. MicroRNA was profiled from tumour tissue with global microRNA microarray analysis. Differences in miRNA expression profiles were analysed according to histologic subtype, FIGO stage, tumour grade, type I or II tumours and result of primary cytoreductive surgery. One microRNA, miR-130a, which was found to be associated with serous histology and advanced FIGO stage, was also validated using data from external cohorts. Another seven microRNAs (miR-34a, miR-455-3p, miR-595, miR-1301, miR-146-5p, 193a-5p, miR-939) were found to be significantly associated with the clinicopathological characteristics (p ≤ 0.001), in our data, but mere not similarly significant when tested against external cohorts. Further validation in comparable cohorts, with microRNA profiled using newest and similar methods are warranted.

scholarly journals Hypodontia phenotype in patients with epithelial ovarian cancer

2015 ◽  
Vol 49 (1) ◽  
pp. 65-70 ◽  
Author(s):  
Anita Fekonja ◽  
Andrej Cretnik ◽  
Danijel Zerdoner ◽  
Iztok Takac
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Figo Stage ◽  
Clinicopathological Characteristics ◽  
Control Group ◽  
Malignant Tumours ◽  
Cancer Group ◽  
Significant Difference ◽  
The University ◽  
And Control

Abstract Background. Ovarian cancer is usually diagnosed in an advanced stage and the present clinical and diagnostic molecular markers for early OC screening are insufficient. The aim of this study was to identify potential relationship between the hypodontia and epithelial ovarian cancer (EOC). Patients and methods. A retrospective study was conducted on 120 patients with EOC treated at the Department of Gynaecologic and Breast Oncology at the University Clinical Centre and 120 gynaecological healthy women (control group) of the same mean age. Women in both groups were reviewed for the presence of hypodontia and the patients with EOC also for clinicopathological characteristics of EOC according to hypodontia phenotype. Results. Hypodontia was diagnosed in 23 (19.2%) of patients with EOC and 8 (6.7%) controls (p = 0.004; odds ratio [OR] = 3.32; confidence interval [CI], 1.42-7.76). There was no statistically significant difference in patients with EOC with or without hypodontia regarding histological subtype (p = 0.220); they differed in regard to FIGO stage (p = 0.014; OR =3.26; CI, 1.23-8.64) and tumour differentiation grade (p = 0.042; OR = 3.1; CI, 1.01-9.53). Also, bilateral occurrence of EOC was more common than unilateral occurrence in women with hypodontia (p = 0.021; OR = 2.9; CI, 1.15-7.36). We also found statistically significant difference between the ovarian cancer group and control group in presence of other malignant tumours in subjects (p < 0.001). Conclusions. The results of the study suggest a statistical association between EOC and hypodontia phenotype. Hypodontia might serve as a risk factor for EOC detection.

scholarly journals Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 713 ◽  
Author(s):  
Kulbe ◽  
Otto ◽  
Darb-Esfahani ◽  
Lammert ◽  
Abobaker ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Biomarker Discovery ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pelvic Mass ◽  
Aurora Kinase ◽  
Malignant Tumours ◽  
Novel Biomarkers

Detection of epithelial ovarian cancer (EOC) poses a critical medical challenge. However, novel biomarkers for diagnosis remain to be discovered. Therefore, innovative approaches are of the utmost importance for patient outcome. Here, we present a concept for blood-based biomarker discovery, investigating both epithelial and specifically stromal compartments, which have been neglected in search for novel candidates. We queried gene expression profiles of EOC including microdissected epithelium and adjacent stroma from benign and malignant tumours. Genes significantly differentially expressed within either the epithelial or the stromal compartments were retrieved. The expression of genes whose products are secreted yet absent in the blood of healthy donors were validated in tissue and blood from patients with pelvic mass by NanoString analysis. Results were confirmed by the comprehensive gene expression database, CSIOVDB (Ovarian cancer database of Cancer Science Institute Singapore). The top 25% of candidate genes were explored for their biomarker potential, and twelve were able to discriminate between benign and malignant tumours on transcript levels (p < 0.05). Among them T-cell differentiation protein myelin and lymphocyte (MAL), aurora kinase A (AURKA), stroma-derived candidates versican (VCAN), and syndecan-3 (SDC), which performed significantly better than the recently reported biomarker fibroblast growth factor 18 (FGF18) to discern malignant from benign conditions. Furthermore, elevated MAL and AURKA expression levels correlated significantly with a poor prognosis. We identified promising novel candidates and found the stroma of EOC to be a suitable compartment for biomarker discovery.

scholarly journals Differential expression of collagen type I alpha 1 chain in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Fallopian Tube ◽  
Collagen Type ◽  
Expression Profiles ◽  
Collagen Type I ◽  
Type I ◽  
High Grade ◽  
Primary Tumors ◽  
Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding collagen type I alpha 1 chain, COL1A1, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. COL1A1 expression was significantly higher in high-grade serous ovarian tumors relative to normal fallopian tube. COL1A1 expression correlated with overall survival in patients with ovarian cancer. These data indicate that expression of COL1A1 is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. COL1A1 may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

scholarly journals Differential expression of collagen type I alpha 2 chain in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Fallopian Tube ◽  
Collagen Type ◽  
Expression Profiles ◽  
Collagen Type I ◽  
Type I ◽  
High Grade ◽  
Primary Tumors ◽  
Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding collagen type I alpha 2 chain, COL1A2, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. COL1A2 expression was significantly higher in high-grade serous ovarian tumors relative to normal fallopian tube. COL1A2 expression correlated with overall survival in patients with ovarian cancer. These data indicate that expression of COL1A2 is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. COL1A2 may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

scholarly journals Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Min Zhou ◽  
Shasha Hong ◽  
Bingshu Li ◽  
Cheng Liu ◽  
Ming Hu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Score ◽  
Cox Regression ◽  
Expression Profiles ◽  
Figo Stage ◽  
Prognostic Indicator ◽  
Tissue Expression ◽  
The Cancer Genome Atlas

Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

scholarly journals Differential expression of SLIT and NTRK-like family member 3 in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Family Member ◽  
Fallopian Tube ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
Progression Free Survival ◽  
High Grade ◽  
Primary Tumors ◽  
Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published and public microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding SLIT and NTRK-like family member 3, SLITRK3, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. SLITRK3 expression was significantly lower in high-grade serous ovarian tumors relative to normal fallopian tube. SLITRK3 expression correlated with progression-free survival in patients with ovarian cancer. These data indicate that expression of SLITRK3 is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. SLITRK3 may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

scholarly journals Differential expression of LSM4 homolog, U6 small nuclear RNA and mRNA degradation associated in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Fallopian Tube ◽  
Expression Profiles ◽  
Mrna Degradation ◽  
High Grade ◽  
Small Nuclear Rna ◽  
Primary Tumors ◽  
Ovarian Cancers ◽  
Nuclear Rna

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding LSM4 homolog, U6 small nuclear RNA and mRNA degradation associated, LSM4, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. LSM4 expression was significantly higher in high-grade serous ovarian tumors relative to normal fallopian tube. LSM4 expression correlated with overall survival in patients with ovarian cancer. These data indicate that expression of LSM4 is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. LSM4 may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

scholarly journals Differential expression of murine retrovirus integration site 1 homolog in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Fallopian Tube ◽  
Integration Site ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
High Grade ◽  
Primary Tumors ◽  
Ovarian Cancers ◽  
Retrovirus Integration

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published and public microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding murine retrovirus integration site 1 homolog, MRVI1, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. MRVI1 expression was significantly lower in high-grade serous ovarian tumors relative to normal fallopian tube. MRVI1 expression correlated with overall survival in patients with ovarian cancer. These data indicate that expression of MRVI1 is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. MRVI1 may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

scholarly journals Differential expression of sarcospan in human epithelial ovarian cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Fallopian Tube ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
Gene Expression Profiles ◽  
Progression Free Survival ◽  
High Grade ◽  
Primary Tumors ◽  
Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding sarcospan, SSPN, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. SSPN expression was significantly lower in high-grade serous ovarian tumors relative to normal fallopian tube. SSPN expression correlated with progression-free survival in patients with ovarian cancer. These data indicate that expression of SSPN is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. SSPN may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

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