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| Status |
Public on Oct 19, 2023 |
| Title |
Double ratio of microRNA signatures as promising diagnosis biomarkers for mucinous borderline and malignant ovarian tumors |
| Platform organism |
synthetic construct |
| Sample organism |
Homo sapiens |
| Experiment type |
Non-coding RNA profiling by array
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| Summary |
Epithelial ovarian cancer (EOC) are a heterogeneous collection of malignancies, each with their own developmental origins, clinical behavior and molecular profile. With less than 5% of EOC cases, mucinous ovarian carcinoma is a rare form with a poor prognosis with a 5-year survival of 11% for advanced stages (III/IV). Clinically, due to the large size and heterogeneity of mu-cinous tumors, Malignant forms are difficult to distinguish from Borderline (15%) and benign (80%) forms with a better prognosis. Improving their diagnosis is therefore a challenge with regard to the risk of under-treating a malignant form or of unnecessarily undertaking radical surgical excision. The involvement of microRNAs (miRNAs) in cancer and their potential as biomarkers of diagnosis are becoming increasingly recognized. In this study, miRNA expres-sion profiling generates using FFPE patient samples followed by qRT-PCR validation allows to identify 10 down-regulated and 5 up-regulated miRNAs between Malignant and Borderline tumors. To overcome issues linked to data normalization and to improve the accuracy of the results, a ratio analysis combining up-regulated and down-regulated miRNAs was used. Alt-hough 21/50 miRNA expression ratio were significantly different between Malignant and Bor-derline tumor samples, any ratio could perfectly discriminate the two groups. However, a combination of 14 miRNAs expression ratio (double ratio) showed high discriminatory poten-tial, with 100% of accuracy in distinguishing Malignant and Borderline ovarian tumors, and suggests that miRNAs may hold significant clinical potential as a diagnostic tool.
Epithelial ovarian cancer (EOC) are a heterogeneous collection of malignancies, each with their own developmental origins, clinical behavior and molecular profile. With less than 5% of EOC cases, mucinous ovarian carcinoma is a rare form with a poor prognosis with a 5-year survival of 11% for advanced stages (III/IV). Clinically, due to the large size and heterogeneity of mu-cinous tumors, Malignant forms are difficult to distinguish from Borderline (15%) and benign (80%) forms with a better prognosis. Improving their diagnosis is therefore a challenge with regard to the risk of under-treating a malignant form or of unnecessarily undertaking radical surgical excision. The involvement of microRNAs (miRNAs) in cancer and their potential as biomarkers of diagnosis are becoming increasingly recognized. In this study, miRNA expres-sion profiling generates using FFPE patient samples followed by qRT-PCR validation allows to identify 10 down-regulated and 5 up-regulated miRNAs between Malignant and Borderline tumors. To overcome issues linked to data normalization and to improve the accuracy of the results, a ratio analysis combining up-regulated and down-regulated miRNAs was used. Alt-hough 21/50 miRNA expression ratio were significantly different between Malignant and Bor-derline tumor samples, any ratio could perfectly discriminate the two groups. However, a combination of 14 miRNAs expression ratio (double ratio) showed high discriminatory poten-tial, with 100% of accuracy in distinguishing Malignant and Borderline ovarian tumors, and suggests that miRNAs may hold significant clinical potential as a diagnostic tool.
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| Overall design |
microRNA analysis mucinous borderline and malignant ovarian tumors
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| Contributor(s) |
Denoyelle C, Meryet-Figuiere M |
| Citation(s) |
37958997 |
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| Submission date |
Oct 18, 2023 |
| Last update date |
Jan 19, 2024 |
| Contact name |
frédéric leprêtre |
| E-mail(s) |
frederic.lepretre@univ-lille.fr
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| Organization name |
Lille University
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| Department |
CHU of Lille, CBP
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| Lab |
plateforme de génomique fonctionnelle et structurale
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| Street address |
Boulevard du Pr Leclercq
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| City |
lille |
| ZIP/Postal code |
59037 |
| Country |
France |
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| Platforms (1) |
| GPL19117 |
[miRNA-4] Affymetrix Multispecies miRNA-4 Array |
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| Samples (6)
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| Relations |
| BioProject |
PRJNA1029619 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE245725_RAW.tar |
4.4 Mb |
(http)(custom) |
TAR (of CEL) |
| Raw data provided as supplementary file |
| Processed data not provided for this record |
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