Project description:A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9-10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

| S-EPMC6192980 | biostudies-literature

Plasma small extracellular vesicles microRNAs profile in advanced ovarian cancer

Project description:No residual disease after debulking Surgery (R0 resection) is the most critical independent prognostic factor for advanced ovarian cancer (AOC). Therefore, it is of paramount importance to preoperative estimate the likelihood of R0 resection for choosing the best therapeutic strategy. Our study aimed to develop a non-invasive and reliable detection method for AOC patients with a high risk of residual disease. An integrated plasma small extracellular vesicles (sEVs) microRNA profiling was generated by RNA sequencing in AOC patients with no residual disease patients (R0) and residual disease(non-R0). We identified and validated a logistic model based on plasma sEVs miRNAs to predict residual disease in AOC patients.

2023-04-01 | GSE166310 | GEO

Plasma small extracellular vesicles microRNAs profile in advanced ovarian cancer

Project description:No residual disease after debulking Surgery (R0 resection) is the most critical independent prognostic factor for advanced ovarian cancer (AOC). Therefore, it is of paramount importance to preoperatively estimate the likelihood of R0 resection for choosing the best therapeutic strategy. Our study aimed to develop a non-invasive and reliable detection method for AOC patients with a high risk of residual disease. An integrated plasma small extracellular vesicles (sEVs) microRNA profiling was generated by RNA sequencing in AOC patients with no residual disease patients (R0) and residual disease (non-R0). We identified and validated a logistic model based on plasma sEVs miRNAs to predict residual disease in AOC patients.

2024-01-02 | GSE223126 | GEO

Ovarian Cancer MicroRNA

Project description:Comparison of various ovarian tumors and ovarian cell lines. Keywords: Various ovarian tumors and cell lines. Samples from ovarian tumors and ovarian cell lines were examined for their microRNA expression patterns.

2008-06-29 | E-GEOD-10150 | biostudies-arrayexpress

microRNA screening in human pancreatic adenocarcinoma

Project description:microRNA screening in human pancreatic adenocarcinoma

| PRJNA300855 | ENA

microRNA profiling of recurrent high grade ovarian carcinoma compared to primary ovarian cancer and normal ovary

Project description:To determine microRNA expression in chemoresistant ovarian cancer, we have employed whole microRNA microarray expression profiling as a discovery platform to identify genes with the potential to distinguish recurrent ovarian cancer. 8 recurrent ovarian cancer tissue and 8 primary ovarian cancer tissue and 4 normal ovarian tissue was used to identify miRNA profiling.

2017-06-01 | GSE83693 | GEO

Circulating microRNA screening of high-risk individuals enrolled in COSMOS lung cancer screening trial.

Project description:Lung cancer is the leading cause of cancer death worldwide. Low-dose computed tomography screening (LDCT) was recently shown to anticipate the time of diagnosis, thus reducing lung cancer mortality. We identifed a serum microRNA signature (the miR-Test) that could identify the optimal target population for LDCT screening. Here, we performed a large-scale validation study of the miR-Test in high-risk individuals enrolled in the Continuous Observation of Smoking Subjects (COSMOS) lung cancer screening program. RT-qPCR of circulating microRNA purified from serum samples. Trizol-LS and miRNEASY Mini kit (Qiagen) were used for miRNA purification. Custom TaqManÂ® Low Density Array microRNA Custom Panel (Life Technologies) was used to screen serum circulating microRNA.

2016-02-29 | E-GEOD-76462 | biostudies-arrayexpress

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