Literature DB >> 22385199

Tapping the potential of quantum dots for personalized oncology: current status and future perspectives.

Chuang Chen1, Jun Peng, Sheng-Rong Sun, Chun-Wei Peng, Yan Li, Dai-Wen Pang.   

Abstract

Cancer is one of the most serious health threats worldwide. Personalized oncology holds potential for future cancer care in clinical practice, where each patient could be delivered individualized medicine on the basis of key biological features of an individual tumor. One of the most urgent problems is to develop novel approaches that incorporate the increasing molecular information into the understanding of cancer biological behaviors for personalized oncology. Quantum dots are a heterogeneous class of engineered fluorescent nanoparticles with unique optical and chemical properties, which make them promising platforms for biomedical applications. With the unique optical properties, the utilization of quantum dot-based nanotechnology has been expanded into a wide variety of attractive biomedical applications for cancer diagnosis, monitoring, pathogenesis, treatment, molecular pathology and heterogeneity in combination with cancer biomarkers. Here, we focus on the clinical application of quantum dot-based nanotechnology in personalized oncology, covering topics on individualized cancer diagnosis and treatment by in vitro and in vivo molecular imaging technologies, and in-depth understanding of the biological behaviors of tumors from a nanotechnology perspective. In addition, the major challenges in translating quantum dot-based nanotechnology into clinical application and promising future directions in personalized oncology are also discussed.

Entities:  

Mesh:

Year:  2012        PMID: 22385199     DOI: 10.2217/nnm.12.9

Source DB:  PubMed          Journal:  Nanomedicine (Lond)        ISSN: 1743-5889            Impact factor:   5.307


  20 in total

Review 1.  Quantum dots for quantitative imaging: from single molecules to tissue.

Authors:  Tania Q Vu; Wai Yan Lam; Ellen W Hatch; Diane S Lidke
Journal:  Cell Tissue Res       Date:  2015-01-27       Impact factor: 5.249

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.  Inorganic nanoparticles in diagnosis and treatment of breast cancer.

Authors:  Cristina Núñez; Sergio Vázquez Estévez; María Del Pilar Chantada
Journal:  J Biol Inorg Chem       Date:  2018-02-16       Impact factor: 3.358

5.  Synthesis of CdTe quantum dot-conjugated CC49 and their application for in vitro imaging of gastric adenocarcinoma cells.

Authors:  Yun-Peng Zhang; Peng Sun; Xu-Rui Zhang; Wu-Li Yang; Cheng-Shuai Si
Journal:  Nanoscale Res Lett       Date:  2013-06-22       Impact factor: 4.703

Review 6.  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

7.  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

8.  Quantum dots-based immunofluorescent imaging of stromal fibroblasts Caveolin-1 and light chain 3B expression and identification of their clinical significance in human gastric cancer.

Authors:  Yuyu He; Xianda Zhao; Jun Gao; Lifang Fan; Guifang Yang; William Chi-Shing Cho; Honglei Chen
Journal:  Int J Mol Sci       Date:  2012-10-24       Impact factor: 5.923

9.  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

10.  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
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