Literature DB >> 21745686

Quantum dots-based molecular classification of breast cancer by quantitative spectroanalysis of hormone receptors and HER2.

Chuang Chen1, Sheng-Rong Sun, Yi-Ping Gong, Chu-Bo Qi, Chun-Wei Peng, Xue-Qin Yang, Shao-Ping Liu, Jun Peng, Shan Zhu, Ming-Bai Hu, Dai-Wen Pang, Yan Li.   

Abstract

The emerging molecular breast cancer (BC) classification based on key molecules, including hormone receptors (HRs), and human epidermal growth factor receptor 2 (HER2) has been playing an important part of clinical practice guideline. The current molecular classification mainly based on their fingerprints, however, could not provide enough essential information for treatment decision making. The molecular information on both patterns and quantities could be more helpful to heterogeneities understanding for BC personalized medicine. Here we conduct quantitative determination of HRs and HER2 by quantum dots (QDs)-based quantitative spectral analysis, which had excellent consistence with traditional method. Moreover, we establish a new molecular classification system of BC by integrating the quantitative information of HER2 and HRs, which could better reveal BC heterogeneity and identify 5 molecular subtypes with different 5-year prognosis. Furthermore, the emerging 5 molecular subtypes based on simple quantitative molecules information could be as informative as multi-genes analysis in routine practice, and might help formulate a more personalized comprehensive therapy strategy and prognosis prediction.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21745686     DOI: 10.1016/j.biomaterials.2011.06.029

Source DB:  PubMed          Journal:  Biomaterials        ISSN: 0142-9612            Impact factor:   12.479


  20 in total

Review 1.  Prospects of nano-material in breast cancer management.

Authors:  A K Singh; A Pandey; M Tewari; R Kumar; A Sharma; H P Pandey; H S Shukla
Journal:  Pathol Oncol Res       Date:  2013-02-23       Impact factor: 3.201

Review 2.  Quantum Dot-Based Simultaneous Multicolor Imaging.

Authors:  Wenxia Wang; Zhen Liu; Xiaoli Lan
Journal:  Mol Imaging Biol       Date:  2020-08       Impact factor: 3.488

3.  Quantum dot-based in situ simultaneous molecular imaging and quantitative analysis of EGFR and collagen IV and identification of their prognostic value in triple-negative breast cancer.

Authors:  Hong-Mei Zheng; Chuang Chen; Xin-Hong Wu; Jian Chen; Si Sun; Jin-Zhong Sun; Ming-Wei Wang; Sheng-Rong Sun
Journal:  Tumour Biol       Date:  2015-09-19

Review 4.  Quantum dots-based tissue and in vivo imaging in breast cancer researches: current status and future perspectives.

Authors:  Lin-Wei Wang; Chun-Wei Peng; Chuang Chen; Yan Li
Journal:  Breast Cancer Res Treat       Date:  2015-04-02       Impact factor: 4.872

5.  Caveolin-1 expression level in cancer associated fibroblasts predicts outcome in gastric cancer.

Authors:  Xianda Zhao; Yuyu He; Jun Gao; Lifang Fan; Zonghuan Li; Guifang Yang; Honglei Chen
Journal:  PLoS One       Date:  2013-03-19       Impact factor: 3.240

6.  Quantum dots for cancer research: current status, remaining issues, and future perspectives.

Authors:  Min Fang; Chun-Wei Peng; Dai-Wen Pang; Yan Li
Journal:  Cancer Biol Med       Date:  2012-09       Impact factor: 4.248

7.  Near-infrared quantum dots for HER2 localization and imaging of cancer cells.

Authors:  Sarwat B Rizvi; Sepideh Rouhi; Shohei Taniguchi; Shi Yu Yang; Mark Green; Mo Keshtgar; Alexander M Seifalian
Journal:  Int J Nanomedicine       Date:  2014-03-11

8.  Quantum dot-based immunofluorescent imaging of Ki67 and identification of prognostic value in HER2-positive (non-luminal) breast cancer.

Authors:  Jin-Zhong Sun; Chuang Chen; Guan Jiang; Wei-Qun Tian; Yan Li; Sheng-Rong Sun
Journal:  Int J Nanomedicine       Date:  2014-03-11

9.  Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications.

Authors:  Chuang Chen; Jing-Ping Yuan; Wen Wei; Yi Tu; Feng Yao; Xue-Qin Yang; Jin-Zhong Sun; Sheng-Rong Sun; Yan Li
Journal:  Int J Nanomedicine       Date:  2014-02-21

10.  Computer-based image studies on tumor nests mathematical features of breast cancer and their clinical prognostic value.

Authors:  Lin-Wei Wang; Ai-Ping Qu; Jing-Ping Yuan; Chuang Chen; Sheng-Rong Sun; Ming-Bai Hu; Juan Liu; Yan Li
Journal:  PLoS One       Date:  2013-12-12       Impact factor: 3.240

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