Back to Search
Start Over
How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects
- Source :
- International Journal of Molecular Sciences, International Journal of Molecular Sciences, Vol 21, Iss 8415, p 8415 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI, 2020.
-
Abstract
- Breast cancer metastasis is the main cause of breast cancer mortality. Luminal breast cancer represents the majority of breast cancer cases and, despite relatively good prognosis, its heterogeneity creates problems with a proper stratification of patients and correct identification of the group with a high risk of metastatic relapse. Current prognostic tools are based on the analysis of the primary tumor and, despite their undisputed power of prediction, they might be insufficient to foresee the relapse in an accurate and precise manner, especially if the relapse occurs after a long period of dormancy, which is very common in luminal breast cancer. New approaches tend to rely on body fluid analyses, which have the advantage of being non-invasive and versatile and may be repeated and used for monitoring the disease in the long run. In this review we describe the current, newly-developed, and only-just-discovered methods which are or may become useful in the assessment of the probability of the relapse.
- Subjects :
- Oncology
medicine.medical_specialty
dormancy
Breast cancer mortality
Breast Neoplasms
Disease
Review
ER-positive
Catalysis
Metastasis
Inorganic Chemistry
lcsh:Chemistry
Breast cancer
breast cancer metastasis
Internal medicine
Long period
medicine
Humans
Physical and Theoretical Chemistry
Neoplasm Metastasis
Molecular Biology
lcsh:QH301-705.5
Spectroscopy
circulating tumor markers
business.industry
Organic Chemistry
Breast cancer metastasis
General Medicine
medicine.disease
Prognosis
Primary tumor
Computer Science Applications
hormonal crosstalk
lcsh:Biology (General)
lcsh:QD1-999
Female
Good prognosis
multigene tests
Neoplasm Recurrence, Local
business
Subjects
Details
- Language :
- English
- ISSN :
- 14220067
- Volume :
- 21
- Issue :
- 21
- Database :
- OpenAIRE
- Journal :
- International Journal of Molecular Sciences
- Accession number :
- edsair.doi.dedup.....2f8b545e736e82301806700c805906fb