Literature DB >> 32384044

Experimental Breast Cancer Models: Preclinical Imaging Perspective.

Ulku Korkmaz1, Funda Ustun1.   

Abstract

BACKGROUND: Breast cancer is the leading cause of cancer in women. 13% of breast cancer patients are at a distant stage and mortality is due to metastases rather than primary disease. The unique genetic structure and natural process of breast cancer make it a very suitable area for targeted therapies. Experimental tumor models are validated methods to examine the pathogenesis of cancer, the onset of the neoplastic process and progression.
OBJECTIVE: This study aims to review the current literature on experimental breast cancer models and to bring a new perspective to the use of these models in teranostic preclinical studies in terms of the imaging.
METHODS: Search for relevant literature from academic databases using keywords (Breast cancer, theranostic, preclinical imaging, tumor models, animal study, and tailored therapy) was conducted. The full text of the articles was reached and reviewed. Current scientific data has been reevaluated and compiled according to subtitles. RESULTS AND
CONCLUSION: The development of animal models for breast cancer research has been done in the last century. Imaging methods used in breast cancer are used for tumor localization, quantification of tumor mass, imaging of genes and proteins, evaluation of tumor microenvironment, evaluation of tumor cell proliferation and metabolism and treatment response evaluation. Since human breast cancer is a heterogeneous group of diseases in terms of genetics and phenotype; it is not possible for a single model to adequately address all aspects of breast cancer biology. Considering that each model has advantages and disadvantages, the most suitable model should be chosen to verify the thesis of the study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  Breast cancer; animal study; preclinical imaging; tailored therapy; theranostic; tumor models

Year:  2021        PMID: 32384044     DOI: 10.2174/1874471013666200508080250

Source DB:  PubMed          Journal:  Curr Radiopharm        ISSN: 1874-4710


  2 in total

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Authors:  Marian N Aziz; Arzoo Patel; Amany Iskander; Avisankar Chini; Delphine Gout; Subhrangsu S Mandal; Carl J Lovely
Journal:  Molecules       Date:  2022-01-27       Impact factor: 4.411

2.  lncRNA ACTA2-AS1 predicts malignancy and poor prognosis of triple-negative breast cancer and regulates tumor progression via modulating miR-532-5p.

Authors:  Yi Peng; Xiaoxi Huang; Hongmei Wang
Journal:  BMC Mol Cell Biol       Date:  2022-07-27
  2 in total

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