Cargando…

Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction

OBJECTIVE: To correlate the genome-wide methylation signature of microRNA genes with dysregulated expression of selected candidate microRNA in tissue and serum samples of epithelial ovarian cancer (EOC) and control using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and eva...

Descripción completa

Detalles Bibliográficos
Autores principales: Kumar, Vivek, Gupta, Sameer, Varma, Kachnar, Chaurasia, Amrita, Sachan, Manisha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology; Japan Society of Gynecologic Oncology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250857/
https://www.ncbi.nlm.nih.gov/pubmed/35557032
http://dx.doi.org/10.3802/jgo.2022.33.e49
_version_ 1784739895415144448
author Kumar, Vivek
Gupta, Sameer
Varma, Kachnar
Chaurasia, Amrita
Sachan, Manisha
author_facet Kumar, Vivek
Gupta, Sameer
Varma, Kachnar
Chaurasia, Amrita
Sachan, Manisha
author_sort Kumar, Vivek
collection PubMed
description OBJECTIVE: To correlate the genome-wide methylation signature of microRNA genes with dysregulated expression of selected candidate microRNA in tissue and serum samples of epithelial ovarian cancer (EOC) and control using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and evaluation of EOC predictive value of candidate microRNA at an early stage. METHODS: We performed Methylated DNA Immunoprecipitation coupled with NGS (MeDIP-NGS) sequencing of 6 EOC and 2 normal tissue samples of the ovary. Expression of selected microRNA from tissue (EOC=85, normal=30) and serum (EOC=50, normal=15) samples was evaluated using qRT-PCR. We conducted bioinformatics analysis to identify the candidate miRNA’s potential target and functional role. RESULTS: MeDIP-NGS sequencing revealed hypermethylation of several microRNAs gene promoters. Three candidate microRNAs were selected (microRNA-34a, let-7f, and microRNA-31) from MeDIP-NGS data analysis based on log2FC and P-value. The relative expression level of microRNA-34a, let-7f, and microRNA-31 was found to be significantly reduced in early-stage EOC tissues and serum samples (p<0.0001). The receiver operating characteristic analysis of microRNA-34a, let-7f and miR-31 showed improved diagnostic value with area under curve(AUC) of 92.0 (p<0.0001), 87.9 (p<0.0001), and 85.6 (p<0.0001) and AUC of 82.7 (p<0.0001), 82.0 (p<0.0001), and 81.0 (p<0.0001) in stage III-IV and stage I-II EOC serum samples respectively. The integrated diagnostic performance of microRNA panel (microRNA-34a+let-7f+microRNA-31) in late-stage and early-stage serum samples was 95.5 and 96.9 respectively. CONCLUSION: Our data correlated hypermethylation-associated downregulation of microRNA in EOC. In addition, a combined microRNA panel from serum could predict the risk of EOC with greater AUC, sensitivity, and specificity.
format Online
Article
Text
id pubmed-9250857
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology; Japan Society of Gynecologic Oncology
record_format MEDLINE/PubMed
spelling pubmed-92508572022-07-06 Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction Kumar, Vivek Gupta, Sameer Varma, Kachnar Chaurasia, Amrita Sachan, Manisha J Gynecol Oncol Original Article OBJECTIVE: To correlate the genome-wide methylation signature of microRNA genes with dysregulated expression of selected candidate microRNA in tissue and serum samples of epithelial ovarian cancer (EOC) and control using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and evaluation of EOC predictive value of candidate microRNA at an early stage. METHODS: We performed Methylated DNA Immunoprecipitation coupled with NGS (MeDIP-NGS) sequencing of 6 EOC and 2 normal tissue samples of the ovary. Expression of selected microRNA from tissue (EOC=85, normal=30) and serum (EOC=50, normal=15) samples was evaluated using qRT-PCR. We conducted bioinformatics analysis to identify the candidate miRNA’s potential target and functional role. RESULTS: MeDIP-NGS sequencing revealed hypermethylation of several microRNAs gene promoters. Three candidate microRNAs were selected (microRNA-34a, let-7f, and microRNA-31) from MeDIP-NGS data analysis based on log2FC and P-value. The relative expression level of microRNA-34a, let-7f, and microRNA-31 was found to be significantly reduced in early-stage EOC tissues and serum samples (p<0.0001). The receiver operating characteristic analysis of microRNA-34a, let-7f and miR-31 showed improved diagnostic value with area under curve(AUC) of 92.0 (p<0.0001), 87.9 (p<0.0001), and 85.6 (p<0.0001) and AUC of 82.7 (p<0.0001), 82.0 (p<0.0001), and 81.0 (p<0.0001) in stage III-IV and stage I-II EOC serum samples respectively. The integrated diagnostic performance of microRNA panel (microRNA-34a+let-7f+microRNA-31) in late-stage and early-stage serum samples was 95.5 and 96.9 respectively. CONCLUSION: Our data correlated hypermethylation-associated downregulation of microRNA in EOC. In addition, a combined microRNA panel from serum could predict the risk of EOC with greater AUC, sensitivity, and specificity. Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology; Japan Society of Gynecologic Oncology 2022-03-23 /pmc/articles/PMC9250857/ /pubmed/35557032 http://dx.doi.org/10.3802/jgo.2022.33.e49 Text en Copyright © 2022. Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology, and Japan Society of Gynecologic Oncology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kumar, Vivek
Gupta, Sameer
Varma, Kachnar
Chaurasia, Amrita
Sachan, Manisha
Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title_full Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title_fullStr Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title_full_unstemmed Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title_short Diagnostic performance of microRNA-34a, let-7f and microRNA-31 in epithelial ovarian cancer prediction
title_sort diagnostic performance of microrna-34a, let-7f and microrna-31 in epithelial ovarian cancer prediction
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250857/
https://www.ncbi.nlm.nih.gov/pubmed/35557032
http://dx.doi.org/10.3802/jgo.2022.33.e49
work_keys_str_mv AT kumarvivek diagnosticperformanceofmicrorna34alet7fandmicrorna31inepithelialovariancancerprediction
AT guptasameer diagnosticperformanceofmicrorna34alet7fandmicrorna31inepithelialovariancancerprediction
AT varmakachnar diagnosticperformanceofmicrorna34alet7fandmicrorna31inepithelialovariancancerprediction
AT chaurasiaamrita diagnosticperformanceofmicrorna34alet7fandmicrorna31inepithelialovariancancerprediction
AT sachanmanisha diagnosticperformanceofmicrorna34alet7fandmicrorna31inepithelialovariancancerprediction