Dataset Information

A novel serum miRNA-pair classifier for diagnosis of sarcoma.

ABSTRACT: Soft tissue sarcomas (STS) is a set of rare malignant tumor originated from mesoderm. For the prognosis of sarcoma, early diagnosis is important, however, currently no mature and non-invasive method for diagnosis exists. MicroRNAs (miRNAs) are a class of noncoding RNAs and their expression varies greatly, especially during tumor activity. The purpose of this study was to construct a predictive model for the diagnosis of sarcomas based on the relative expression level of miRNA in serum. miRNA array expression data of 677 samples including 402 malignant sarcoma samples and 275 healthy samples was used to construct the prediction model. Based on 6 gene pairs, random generalized linear model (RGLM) was constructed, with an accuracy of 100% in the internal test dataset and of 74.3% in the merged external dataset in prediction whether a serum sample was obtained from a sarcoma patient, with a specificity of 100% in the internal test dataset and 90.5% in the external dataset. In conclusion, our serum miRNA-pair classifier has the potential to be used for the screening of sarcoma with high accuracy and specificity.

SUBMITTER: Jin Z

PROVIDER: S-EPMC7365454 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A novel serum miRNA-pair classifier for diagnosis of sarcoma.

Jin Zheng Z Liu Shanshan S Zhu Pei P Tang Mengyan M Wang Yuanxin Y Tian Yuan Y Li Dong D Zhu Xun X Yan Dongmei D Zhu Zhenhua Z

PloS one 20200716 7

Soft tissue sarcomas (STS) is a set of rare malignant tumor originated from mesoderm. For the prognosis of sarcoma, early diagnosis is important, however, currently no mature and non-invasive method for diagnosis exists. MicroRNAs (miRNAs) are a class of noncoding RNAs and their expression varies greatly, especially during tumor activity. The purpose of this study was to construct a predictive model for the diagnosis of sarcomas based on the relative expression level of miRNA in serum. miRNA arr ...[more]

PMID: 32673360

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Project description:Background: Exosomes are extracellular microvesicles that are released by most cells and widely distributed in various body fluids. Malignant cells secrete large amounts of exosomes containing various molecular constituents reflecting the originating tumor. We investigated the difference in microRNA (miRNA) expression in serum exosomes from the patients with benign, borderline and malignant ovarian masses to assess the diagnostic relevance of serum exosomal miRNAs as biomarkers for preoperative diagnosis of ovarian carcinoma. Methods: A total of 68 cases of ovarian masses were enrolled, comprising benign ovarian cysts (benign; n=10), borderline ovarian tumors (BOT, n=10), high-grade serous ovarian carcinomas (HGSOC, n=39) and non-HGSOCs (n=9). Exosomal RNA was extracted from the serum, and expression levels of seven miRNAs (miRNA-21, -93, -141, -145, -200a, -200b and -200c), which were reportedly dysregulated in serous ovarian cancer in previous studies, were quantified by real-time PCR, and compared between the four groups. Results: MiR-93, -145, and -200c, showed significantly higher expression in serum exosomes of the cancer group (HGSOC and non-HGSOC) than of the non-cancer group (benign and BOT; all p<0.05). The remaining three miRs (miR-141, -200a, and -200b) were expressed at extremely low levels, and not appropriate as serological biomarkers. To test discrimination of cancer from non-cancer, the area under the receiver operating characteristic curves determined for cancer antigen 125 (CA125), miR-145, miR-200c, miR-21, and miR-93 were 0.801 (p<0.001), 0.910 (p<0.001), 0.802 (p<0.001), 0.585 (p=0.303), and 0.755 (p=0.002), respectively. MiR-145 showed superior sensitivity (91.6%), and miR-200c showed superior specificity (90.0%), compared with CA125. Conclusion: Expression of exosomal miR-93, miR-145 and miR-200c was significantly elevated in the serum of ovarian cancer patients. Serum exosomal miR-145 in particular appeared to be the most promising biomarker for preoperative diagnosis of ovarian cancer.

Dataset Information

A novel serum miRNA-pair classifier for diagnosis of sarcoma.

Publications

A novel serum miRNA-pair classifier for diagnosis of sarcoma.

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