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Advances in decoding breast cancer brain metastasis

Overview of attention for article published in Cancer and Metastasis Reviews, November 2016
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Title
Advances in decoding breast cancer brain metastasis
Published in
Cancer and Metastasis Reviews, November 2016
DOI 10.1007/s10555-016-9638-9
Pubmed ID
Authors

Chenyu Zhang, Dihua Yu

Abstract

The past decade has witnessed impressive advances in cancer treatment ushered in by targeted and immunotherapies. However, with significantly prolonged survival, upon recurrence, more patients become inflicted by brain metastasis, which is mostly refractory to all currently available therapeutic regimens. Historically, brain metastasis is an understudied area in cancer research, partly due to the dearth of appropriate experimental models that closely simulate the special biological features of metastasis in the unique brain environment and to the sophistication of techniques required to perform in-depth studies of the extremely complex and challenging brain metastasis. Yet, with increasing clinical demand for more effective treatment options, brain metastasis research has rapidly advanced in recent years. The present review spotlights the recent major progresses in basic and translational studies of brain metastasis with focuses on new animal models, novel imaging technologies, omics "big data" resources, and some new and exciting biological insights on brain metastasis.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Student > Master 4 12%
Student > Bachelor 4 12%
Student > Doctoral Student 3 9%
Researcher 3 9%
Other 7 21%
Unknown 7 21%
Readers by discipline Count As %
Medicine and Dentistry 6 18%
Neuroscience 5 15%
Biochemistry, Genetics and Molecular Biology 4 12%
Agricultural and Biological Sciences 3 9%
Nursing and Health Professions 3 9%
Other 5 15%
Unknown 8 24%