Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts

Jang, Ji Young; Ko, Eun Young; Jung, Ji Soo; Kang, Kyung Nam; Kim, Yeon Soo; Kim, Chul‐Woo

doi:10.15430/jcp.2021.26.4.258

Cited by 5 publications

(7 citation statements)

References 31 publications

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“…It is identified by conserved regions in the cyclin protein and binds to a p21Kip cyclin-like method. PK and PKA phosphorylation sites are common molecular structures in signaling regulation and have a wide range of regulatory roles in cell proliferation and cell cycles [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women

Tang

Wang

et al. 2022

Applied Bionics and Biomechanics

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Objectives. Preliminary analysis of breast cancer related to unknown functional gene FAM83A through bioinformatics knowledge to inform further experimental studies. Select high expression genes for breast cancer and use bioinformatics methods to predict the biological function of FAM83A. Methods. Genes with significant differences in expression between breast tumors and normal breast tissue libraries were selected from CGAP’s SAGE Digital Gene Expression Displayer (DGED) database. An unknown functional gene, FAM83A, which is highly expressed in breast cancer, was screened. We performed an analysis of the gene structure, subcellular localization, physicochemical properties of the encoding products, functional sites, protein structure, and functional domains. Results. Through SAGE DGED, a total of 185 genes with expression differences were found. The structure and function of FAM83A have ideal predictions, and it is generally determined that this gene encodes a nuclear protein with a nucleoprotein. The active site of PLDc and the functional domain of DUF1669 can be involved in signal transduction and gene expression regulation in tumorigenesis and metastasis. Digital gene representation of the Tumor Genome Project Data Library was used to select differentially expressed genes in breast cancer tissue and breast benign tumor tissue. Conclusion. Studies show that FAM83A is a potential research target associated with tumorigenesis and metastasis. Initial tests confirmed the expression of this gene. Lay a solid foundation for further research learning. FAM83A is a highly expressed gene in breast cancer and can serve as a target for studying molecular mechanisms in breast cancer.

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Section: Discussionmentioning

confidence: 99%

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women

Tang

Wang

et al. 2022

Applied Bionics and Biomechanics

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“…In total, 16 142 articles were identified in the aforementioned databases (Table 1). However, 234 articles were retained for full reading, following the elimination of duplicates and articles whose title and abstract did not meet the eligibility criteria; of these, only 136 12…”

Section: Resultsmentioning

confidence: 99%

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Duque

Manterola

Otzen

et al. 2022

Clin Med Insights Oncol

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Background: Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid biopsy (LB) is a non-invasive diagnostic technique that allows the analysis of biomarkers in different body fluids, particularly in peripheral blood and also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal secretions, breast milk, and tears. The objective was to analyze the available evidence related to the use of biomarkers obtained by LB for the early diagnosis of BC. Methods: Articles related to the use of biomarkers for the early diagnosis of BC due to LB, published between 2010 and 2022, from the databases (WoS, EMBASE, PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied in the articles to determine their methodological quality (MQ). Descriptive statistics were used, as well as determination of weighted averages of each variable, to analyze the extracted data. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) are described. Results: In this systematic review (SR), 136 articles met the selection criteria, representing 17 709 patients with BC. However, 95.6% were case-control studies. In 96.3% of cases, LB was performed in peripheral blood samples. Most of the articles were based on microRNA (miRNA) analysis. The mean MQ score was 25/45 points. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) have been found. Conclusions: The determination of biomarkers through LB is a useful mechanism for the diagnosis of BC. The analysis of miRNA in peripheral blood is the most studied methodology. Our results indicate that LB has a high sensitivity and specificity for the diagnosis of BC, especially in early stages.

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“…Nonlinear SVM and Linear GLM Model Analyses. Our previous study confrmed that four miRNA biomarkers (miR-1246, 202, 21, and 219B) performed well in samples of women under the age of 50 and were meaningful for the early diagnosis of breast cancer in Korean women under the age of 50 [28]. Te present study reafrmed the results of previous studies, and the performance of the four miRNA biomarkers was compared with clinical information based on mammography to further confrm the possibility of their ability to support mammographic fndings.…”

Section: Modeling and Model Validation Performance Usingmentioning

confidence: 88%

Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk

Song,

Jang,

Kang

et al. 2023

The Breast Journal

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The objective of this study was to determine whether multi-microRNA analysis using a combination of four microRNA biomarkers (miR-1246, 202, 21, and 219B) could improve the diagnostic performance of mammography in determining breast cancer risk by age group (under 50 vs. over 50) and distinguish breast cancer from benign breast diseases and other cancers (thyroid, colon, stomach, lung, liver, and cervix cancers). To verify breast cancer classification performance of the four miRNA biomarkers and whether the model providing breast cancer risk score could distinguish between benign breast disease and other cancers, the model was verified using nonlinear support vector machine (SVM) and generalized linear model (GLM) and age and four miRNA qRT-PCR analysis values (dCt) were input to these models. Breast cancer risk scores for each Breast Imaging-Reporting and Data System (BI-RADS) category in multi-microRNA analysis were analyzed to examine the correlation between breast cancer risk scores and mammography categories. We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. The results of this study showed that this multi-microRNA analysis using the four miRNA biomarkers was effective in classifying breast cancer in patients under the age of 50, which is challenging to accurately diagnose. In addition, breast cancer and benign breast diseases can be classified, showing the possibility of helping with diagnosis by mammography. Verification of the performance of the four miRNA biomarkers confirmed that multi-microRNA analysis could be used as a new breast cancer screening aid to improve the accuracy of mammography. However, many factors must be considered for clinical use. Further validation with an appropriate screening population in large clinical trials is required. This trial is registered with (KNUCH 2022-04-036).

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Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts

Cited by 5 publications

References 31 publications

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk

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