Dataset Information

Performance of an ancillary test for cervical cancer that measures miRNAs and cytokines in serum and cervical mucus.

ABSTRACT: Currently, human papillomavirus tests and cytology are used to screen for cervical cancer. However, more accurate ancillary screening tests are needed. MicroRNAs (miRNAs) and cytokines are promising biomarkers that are aberrantly expressed in cervical cancer. Therefore, the potential of developing new screening markers based on the levels of miRNAs and cytokines in serum and local mucus samples from the same patients with cervical neoplasia was investigated. miRNA screening was performed by microarray and measurement using real-time reverse-transcriptase PCR. Cytokine were measured using multiplex bead assay, and changes in expressions were analyzed based on disease severity. As lesions progressed, miR-20b-5p, -155-5p, -144-3p, -451a, and -126-3p expression levels were increased in mucus, and miR-16-5p, -223-3p, and -451a expression levels were decreased in serum. Regarding cytokines, IL-6, IL-8, monocyte chemoattractant protein-1, Eotaxin, interferon-γ, and RANTES were increased, whereas granulocyte-colony-stimulating factor (G-CSF) was significantly decreased in mucus. miRNAs and cytokines in serum did not have high diagnostic accuracy. However, a combination of miR-20b-5p, -451a, -126-3p, Eotaxin, as well as G-CSF in mucus samples, had high diagnostic accuracy with an area under the receiver operating characteristic curve of 0.989 (0.979-0.999). Our results suggest that using mucus for this ancillary test is more beneficial than serum.

SUBMITTER: Fujii T

PROVIDER: S-EPMC11309926 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Performance of an ancillary test for cervical cancer that measures miRNAs and cytokines in serum and cervical mucus.

Fujii Takuma T Nishio Eiji E Tsukamoto Tetsuya T Kukimoto Iwao I Iwata Aya A

Cancer science 20240515 8

Currently, human papillomavirus tests and cytology are used to screen for cervical cancer. However, more accurate ancillary screening tests are needed. MicroRNAs (miRNAs) and cytokines are promising biomarkers that are aberrantly expressed in cervical cancer. Therefore, the potential of developing new screening markers based on the levels of miRNAs and cytokines in serum and local mucus samples from the same patients with cervical neoplasia was investigated. miRNA screening was performed by micr ...[more]

PMID: 38749770

Similar Datasets

Project description:Tumor-promoting cytokines are a cause of tumor progression; therefore, identifying key regulatory microRNAs (miRNAs) for controlling their production is important. The aim of this study is to identify promising miRNAs associated with tumor-promoting cytokines in non-small cell lung cancer (NSCLC). We identified circulating miRNAs from 16 published miRNA profiles. The selected miRNAs were validated in the serum of 32 NSCLC patients and compared with 33 patients with other lung diseases and 23 healthy persons using quantitative real-time PCR. The cytokine concentration was investigated using the enzyme-linked immunoassay in the same sample set, with clinical validation of the miRNAs. The correlation between miRNA expression and cytokine concentration was evaluated by Spearman's rank correlation. For consistent direction, one up-regulated miRNA (miR-145) was found in four studies, and seven miRNAs were reported in three studies. One miRNA (miR-20a) and four miRNAs (miR-25-3p, miR-223, let-7f, and miR-20b) were reported in six and five studies. However, their expression was inconsistent. In the clinical validation, serum miR-145 was significantly down-regulated, whereas serum miR-20a was significantly up-regulated in NSCLC, compared with controls. Regarding serum cytokine, all cytokines [vascular endothelial growth factor (VEGF), interleukin-6 (IL-6), and transforming growth factor β (TGF-β)], except tumor necrosis factor-α (TNF-α), had a higher level in NSCLC patients than controls. In addition, we found a moderate correlation between the TGF-β concentration and miR-20a (r = -0.537, p = 0.002) and miR-223 (r = 0.428, p = 0.015) and a weak correlation between the VEGF concentration with miR-20a (r = 0.376, p = 0.037) and miR-223 (r = -0.355, p = 0.046). MiR-145 and miR-20a are potential biomarkers for NSCLC. In addition, the regulation of tumor-promoting cytokine, through miR-20a and miR-223, might be a new therapeutic approach for lung cancer.

Project description:Advanced ovarian cancer is one of the most lethal gynecological tumor, mainly due to late diagnoses and acquired drug resistance. MicroRNAs (miRNAs) are small-non coding RNA acting as tumor suppressor/oncogenes differentially expressed in normal and epithelial ovarian cancer and has been recognized as a new class of tumor early detection biomarkers as they are released in blood fluids since tumor initiation process. Here, we evaluated by droplet digital PCR (ddPCR) circulating miRNAs in serum samples from healthy (N = 105) and untreated ovarian cancer patients (stages I to IV) (N = 72), grouped into a discovery/training and clinical validation set with the goal to identify the best classifier allowing the discrimination between earlier ovarian tumors from health controls women. The selection of 45 candidate miRNAs to be evaluated in the discovery set was based on miRNAs represented in ovarian cancer explorative commercial panels. We found six miRNAs showing increased levels in the blood of early or late-stage ovarian cancer groups compared to healthy controls. The serum levels of miR-320b and miR-141-3p were considered independent markers of malignancy in a multivariate logistic regression analysis. These markers were used to train diagnostic classifiers comprising miRNAs (miR-320b and miR-141-3p) and miRNAs combined with well-established ovarian cancer protein markers (miR-320b, miR-141-3p, CA-125 and HE4). The miRNA-based classifier was able to accurately discriminate early-stage ovarian cancer patients from health-controls in an independent sample set (Sensitivity = 80.0%, Specificity = 70.3%, AUC = 0.789). In addition, the integration of the serum proteins in the model markedly improved the performance (Sensitivity = 88.9%, Specificity = 100%, AUC = 1.000). A cross-study validation was carried out using four data series obtained from Gene Expression Omnibus (GEO), corroborating the performance of the miRNA-based classifier (AUCs ranging from 0.637 to 0.979). The clinical utility of the miRNA model should be validated in a prospective cohort in order to investigate their feasibility as an ovarian cancer early detection tool.

Project description:BackgroundEndometriosis is a chronic gynecological inflammatory disease characterized by the presence of functional endometrial glands and stroma outside of the uterine cavity. It affects 7-10% of women of reproductive age and up to 50% of women with infertility. The current gold standard for the diagnosis combines laparoscopic evaluation and biopsy of the visualized lesions. However, laparoscopy requires general anesthesia and developed surgical skills and it has a high procedural cost. In addition, it is associated with the risk, although rare, of potential intraoperative or postoperative complications. To date, several noninvasive biomarkers have been proposed; however, no definite diagnostic biomarker is yet available. The aim of this study was to characterize the CM proteome in patients with endometriosis using high resolution mass spectrometry-based proteomics, implemented by bioinformatic tools for quantitative analysis, in order to investigate the pathophysiological mechanisms of endometriosis.MethodsCervical mucus samples were collected from patients affected by endometriosis and fertile controls. An aliquot of the soluble acidic fraction of each cervical mucus sample, corresponding to 0.5 mg of total protein, was left to digest with sequencing grade modified porcine trypsin. The peptides were analyzed by LC-MS/MS on a high resolution Orbitrap Elite mass spectrometer and data were evaluated using bioinformatic tools.ResultsWe aimed at the first total profiling of the cervical mucus proteome in endometriosis. From the list of identified proteins, we detected a number of differentially expressed proteins, including some functionally significant proteins. Six proteins were quantitatively increased in endometriosis, almost all being involved in the inflammatory pattern. Nine proteins were quantitatively reduced in endometriosis, including some proteins related with local innate immunity (CRISP-3 and Pglyrp1) and protection against oxidative stress (HSPB1). Fifteen proteins were not detected in endometriosis samples including certain proteins involved in antimicrobial activity (SLURP1 and KLK13) and related to seminal plasma liquefaction and male fertility (KLK13).ConclusionsThis is the first application of high resolution mass spectrometry-based proteomics aimed in detecting an array of proteins in CM to be proposed for the noninvasive diagnosis of endometriosis. This chronic disease presents in CM an inflammatory protein pattern.

Dataset Information

Performance of an ancillary test for cervical cancer that measures miRNAs and cytokines in serum and cervical mucus.

Publications

Performance of an ancillary test for cervical cancer that measures miRNAs and cytokines in serum and cervical mucus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets