Literature DB >> 33925125

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Ruiyang Zou1, Sau Yeen Loke2, Veronique Kiak-Mien Tan3,4,5,6, Swee Tian Quek7, Pooja Jagmohan7, Yew Chung Tang1, Preetha Madhukumar3,4,5, Benita Kiat-Tee Tan3,4,5,6,8, Wei Sean Yong3,4,5,6, Yirong Sim3,4,6, Sue Zann Lim3,4,5,6, Eunice Png9, Shu Yun Sherylyn Lee10, Mun Yew Patrick Chan10, Teng Swan Juliana Ho3,11, Boon Kheng James Khoo3,11, Su Lin Jill Wong11, Choon Hua Thng3,11, Bee Kiang Chong12, Yik Ying Teo13, Heng-Phon Too14, Mikael Hartman13,15, Ngiap Chuan Tan9,16, Ern Yu Tan10, Soo Chin Lee17, Lihan Zhou1, Ann Siew Gek Lee2,3,18.   

Abstract

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

Entities:  

Keywords:  abnormal mammograms; biomarkers; breast cancer; circulating microRNAs; qRT-PCR

Year:  2021        PMID: 33925125     DOI: 10.3390/cancers13092130

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  35 in total

1.  Biomarker identification by feature wrappers.

Authors:  M Xiong; X Fang; J Zhao
Journal:  Genome Res       Date:  2001-11       Impact factor: 9.043

Review 2.  Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review.

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Journal:  Ultrasound Med Biol       Date:  2017-10-26       Impact factor: 2.998

3.  Clinical significance of serum miR-21 in breast cancer compared with CA153 and CEA.

Authors:  Jianjian Gao; Qingyun Zhang; Jianjun Xu; Lijuan Guo; Xuefeng Li
Journal:  Chin J Cancer Res       Date:  2013-12       Impact factor: 5.087

Review 4.  Clinical relevance of circulating cell-free microRNAs in cancer.

Authors:  Heidi Schwarzenbach; Naohiro Nishida; George A Calin; Klaus Pantel
Journal:  Nat Rev Clin Oncol       Date:  2014-02-04       Impact factor: 66.675

5.  Statistics review 14: Logistic regression.

Authors:  Viv Bewick; Liz Cheek; Jonathan Ball
Journal:  Crit Care       Date:  2005-01-13       Impact factor: 9.097

6.  Identification of Specific miRNA Signature in Paired Sera and Tissue Samples of Indian Women with Triple Negative Breast Cancer.

Authors:  Seema Thakur; Rajesh K Grover; Sanjay Gupta; Ajay K Yadav; Bhudev C Das
Journal:  PLoS One       Date:  2016-07-12       Impact factor: 3.240

7.  miR-451a Inhibited Cell Proliferation and Enhanced Tamoxifen Sensitive in Breast Cancer via Macrophage Migration Inhibitory Factor.

Authors:  Zhenru Liu; Tianyu Miao; Ting Feng; Zhouhua Jiang; Mingyuan Li; Liming Zhou; Hong Li
Journal:  Biomed Res Int       Date:  2015-06-16       Impact factor: 3.246

8.  Circulating microRNA-based screening tool for breast cancer.

Authors:  Pierre Frères; Stéphane Wenric; Meriem Boukerroucha; Corinne Fasquelle; Jérôme Thiry; Nicolas Bovy; Ingrid Struman; Pierre Geurts; Joëlle Collignon; Hélène Schroeder; Frédéric Kridelka; Eric Lifrange; Véronique Jossa; Vincent Bours; Claire Josse; Guy Jerusalem
Journal:  Oncotarget       Date:  2016-02-02

9.  MicroRNA in diagnosis and therapy monitoring of early-stage triple-negative breast cancer.

Authors:  Mustafa Kahraman; Anne Röske; Thomas Laufer; Tobias Fehlmann; Christina Backes; Fabian Kern; Jochen Kohlhaas; Hannah Schrörs; Anna Saiz; Cassandra Zabler; Nicole Ludwig; Peter A Fasching; Reiner Strick; Matthias Rübner; Matthias W Beckmann; Eckart Meese; Andreas Keller; Michael G Schrauder
Journal:  Sci Rep       Date:  2018-08-02       Impact factor: 4.379

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  5 in total

1.  MicroRNAs miR-142-5p, miR-150-5p, miR-320a-3p, and miR-4433b-5p in Serum and Tissue: Potential Biomarkers in Sporadic Breast Cancer.

Authors:  Tamyres Mingorance Carvalho; Guillermo Ortiz Brasil; Tayana Schultz Jucoski; Douglas Adamoski; Rubens Silveira de Lima; Cleverton C Spautz; Karina Furlan Anselmi; Patricia Midori Murobushi Ozawa; Iglenir João Cavalli; Jaqueline Carvalho de Oliveira; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro
Journal:  Front Genet       Date:  2022-06-30       Impact factor: 4.772

2.  Meta-analysis of diagnostic cell-free circulating microRNAs for breast cancer detection.

Authors:  Emir Sehovic; Sara Urru; Giovanna Chiorino; Philipp Doebler
Journal:  BMC Cancer       Date:  2022-06-09       Impact factor: 4.638

Review 3.  Potential utility of miRNAs for liquid biopsy in breast cancer.

Authors:  Xiangrong Liu; Dimitri Papukashvili; Zhixiang Wang; Yan Liu; Xiaoxia Chen; Jianrong Li; Zhiyuan Li; Linjie Hu; Zheng Li; Nino Rcheulishvili; Xiaoqing Lu; Jinfeng Ma
Journal:  Front Oncol       Date:  2022-08-04       Impact factor: 5.738

4.  Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images.

Authors:  Mohammad Alkhaleefah; Tan-Hsu Tan; Chuan-Hsun Chang; Tzu-Chuan Wang; Shang-Chih Ma; Lena Chang; Yang-Lang Chang
Journal:  Cancers (Basel)       Date:  2022-08-20       Impact factor: 6.575

Review 5.  Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021.

Authors:  Chunyan Zhang; Caifang Sun; Yabin Zhao; Qiwen Wang; Jianlin Guo; Bingyu Ye; Guoying Yu
Journal:  Int J Mol Sci       Date:  2022-09-27       Impact factor: 6.208

  5 in total

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