Dataset Information

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

ABSTRACT: Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

SUBMITTER: Juan L

PROVIDER: S-EPMC4152751 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Juan Li L Tong Hong-li HL Zhang Pengjun P Guo Guanghong G Wang Zi Z Wen Xinyu X Dong Zhennan Z Tian Ya-ping YP

Scientific reports 20140903

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo ...[more]

PMID: 25182173

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Project description:Cervical cancer is one of the most common causes of cancer-associated mortality in females worldwide. Serum biomarkers are important tools for diagnosis, disease staging, monitoring treatment and detecting recurrence in different types of cancer. However, only a small number of established biomarkers have been used for clinical diagnosis of cervical cancer. Therefore, the identification of minimally invasive, sensitive and highly specific biomarkers for detection of cervical cancer may improve outcomes. In the present pilot study, changes in disease-relevant proteins in 31 patients with cervical cancer were compared with 16 healthy controls. The Human 14 Multiple Affinity Removal system was used to deplete the 14 most abundant serum proteins to decrease sample complexity and to enrich proteins that exhibited decreased levels of abundance in the serum samples. Immunoaffinity-depleted serum samples were analyzed by in-gel digestion, followed by liquid chromatography mass spectrometry analysis and data processing. Automated quantitative western blot assays and receiver operating characteristic (ROC) curves were used to evaluate the differential protein expression levels between the two groups. Capillary electrophoresis-based western blot analysis was performed to quantitatively determine serum levels of the candidate biomarkers. Significantly increased levels of α-1-antitrypsin (A1AT) and pyrroline-5-carboxylate reductase 2 (PYCR2) were detected, whereas the levels of transthyretin (TTR), apolipoprotein A-I (ApoA-I), vitamin D binding protein (VDBP) and multimerin-1 (MMRN1) were significantly decreased in patients with cervical cancer compared with the healthy controls. ROC curve analysis indicated that the sensitivity and specificity was improved through the combination of the 6 candidate biomarkers. In summary, the results demonstrated that 6 candidate biomarkers (A1AT, PYCR2, TTR, ApoA-I, VDBP and MMRN1) exhibited significantly different expression between serum samples from healthy controls and patients with cervical cancer. These proteins may represent potential biomarkers for distinguishing patients with cervical cancer from healthy controls and for differentiation of patient subgroups.

Dataset Information

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Publications

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Similar Datasets

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