Literature DB >> 29282678

Biomarker Studies in Early Detection and Prognosis of Breast Cancer.

Gang Li1, Jing Hu1, Guohong Hu2,3.   

Abstract

Breast cancer is characterized with enormous heterogeneity, which represents the major hurdle for accurate diagnosis and curative therapy. It is generally believed that genome unstability and molecular evolvability underlie the robustness of cancer cells in hostile microenvironment and their resilience to therapeutic intervention. Conventional histopathological classification of breast cancer falls short of providing sufficient prognostic and predictive power, and thus biomarkers indicative of tumor intrinsic features at molecular levels have been actively pursued in biomedical researches. Currently, a number of molecular biomarkers are being used in standard clinical practice, including the hormone receptors for breast cancer subtyping and several genes involved in genome maintenance for prediction of breast cancer susceptibility. In addition, a number of biomarkers of single genes or multigene signatures have been approved for clinical use for breast cancer prognosis. A growing body of molecular biomarkers are being studied and tested to facilitate disease diagnosis and management, especially for breast cancer early detection, accurate prediction of metastatic behaviors, and selection of therapy. However, most of them are still at the preclinical stages. Finally, biomarkers of noninvasive protocols, such as serological molecules, have advantages in detection convenience over other biomarker types and therefore are of particular interest in translational and clinical development to improve diagnosis, prognosis, and treatment.

Entities:  

Keywords:  Breast cancer; Early detection; Gang prognosis; Genetic susceptibility; Molecular biomarkers; Molecular subtyping; Serological biomarkers

Mesh:

Substances:

Year:  2017        PMID: 29282678     DOI: 10.1007/978-981-10-6020-5_2

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  20 in total

1.  Cysteine conjugate beta-lyase 2 (CCBL2) expression as a prognostic marker of survival in breast cancer patients.

Authors:  Xiangyu Meng; Ling Wang; Miao He; Zhaoying Yang; Yan Jiao; Yubo Hu; Keren Wang
Journal:  PLoS One       Date:  2022-06-30       Impact factor: 3.752

2.  Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers.

Authors:  Yiduo Liu; Linxin Teng; Shiyi Fu; Guiyang Wang; Zhengjun Li; Chao Ding; Haodi Wang; Lei Bi
Journal:  BMC Cancer       Date:  2021-05-31       Impact factor: 4.430

3.  Prognostic role of microRNAs in breast cancer: A systematic review.

Authors:  Eleni Zografos; Flora Zagouri; Despoina Kalapanida; Roubini Zakopoulou; Anastasios Kyriazoglou; Kleoniki Apostolidou; Maria Gazouli; Meletios-Athanasios Dimopoulos
Journal:  Oncotarget       Date:  2019-12-24

Review 4.  Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer.

Authors:  Hsing-Ju Wu; Pei-Yi Chu
Journal:  Int J Mol Sci       Date:  2021-01-10       Impact factor: 5.923

5.  Lipocalin-1 Expression as a Prognosticator Marker of Survival in Breast Cancer Patients.

Authors:  Xueyan Zhang; Yingnan Cui; Miao He; Yan Jiao; Zhaoying Yang
Journal:  Breast Care (Basel)       Date:  2019-10-08       Impact factor: 2.860

6.  Tumor elastography and its association with cell-free tumor DNA in the plasma of breast tumor patients: a pilot study.

Authors:  Yi Hao; Wei Yang; Wenyi Zheng; Xiaona Chen; Hui Wang; Liang Zhao; Jinfeng Xu; Xia Guo
Journal:  Quant Imaging Med Surg       Date:  2021-08

7.  Identification of LEA, a podocalyxin-like glycoprotein, as a predictor for the progression of colorectal cancer.

Authors:  Dezheng Yuan; Hang Chen; Shuo Wang; Furong Liu; Yajie Cheng; Jin Fang
Journal:  Cancer Med       Date:  2018-09-12       Impact factor: 4.452

8.  Identification of Long Noncoding RNAs as Predictors of Survival in Triple-Negative Breast Cancer Based on Network Analysis.

Authors:  Xiao-Xiao Li; Li-Juan Wang; Jie Hou; Hong-Yang Liu; Rui Wang; Chao Wang; Wen-Hai Xie
Journal:  Biomed Res Int       Date:  2020-03-03       Impact factor: 3.411

9.  MicroRNA-623 inhibits tumor progression and is a predictor of poor prognosis of breast cancer.

Authors:  Chunfeng Wang; Juan Wang; Jing Zhang; Yongxiang Li; Qinghui Sun; Feng Guo; Xiupeng An
Journal:  Oncol Lett       Date:  2020-10-29       Impact factor: 2.967

10.  Long non-coding RNA-based signatures to improve prognostic prediction of breast cancer.

Authors:  Yi Zhang; Yuzhi Wang; Gang Tian; Tianhua Jiang
Journal:  Medicine (Baltimore)       Date:  2020-10-02       Impact factor: 1.817

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