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Functional Genomic Analysis of Breast Cancer Metastasis: Implications for Diagnosis and Therapy
- Source :
- Cancers, Vol 13, Iss 3276, p 3276 (2021), Cancers
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Simple Summary Metastasis remains the greatest cause of fatalities in breast cancer patients world-wide. The process of metastases is highly complex, and the current research efforts in this area are still rather fragmented. The revolution of genomic profiling methods to analyze samples from human and animal models dramatically improved our understanding of breast cancer metastasis. This article summarizes the recent breakthroughs in genomic analyses of breast cancer metastasis and discusses their implications for prognostic and therapeutic applications. Abstract Breast cancer (BC) is one of the most diagnosed cancers worldwide and is the second cause of cancer related death in women. The most frequent cause of BC-related deaths, like many cancers, is metastasis. However, metastasis is a complicated and poorly understood process for which there is a shortage of accurate prognostic indicators and effective treatments. With the rapid and ever-evolving development and application of genomic sequencing technologies, many novel molecules were identified that play previously unappreciated and important roles in the various stages of metastasis. In this review, we summarize current advancements in the functional genomic analysis of BC metastasis and discuss about the potential prognostic and therapeutic implications from the recent genomic findings.
- Subjects :
- 0301 basic medicine
Oncology
Cancer Research
medicine.medical_specialty
diagnosis
Economic shortage
Review
Metastasis
03 medical and health sciences
0302 clinical medicine
Breast cancer
breast cancer metastasis
Internal medicine
medicine
RC254-282
therapy
business.industry
Genomic sequencing
Cancer
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Breast cancer metastasis
medicine.disease
030104 developmental biology
genomic analysis
030220 oncology & carcinogenesis
prognosis
business
Subjects
Details
- Language :
- English
- ISSN :
- 20726694
- Volume :
- 13
- Issue :
- 3276
- Database :
- OpenAIRE
- Journal :
- Cancers
- Accession number :
- edsair.doi.dedup.....2a26735f8c7f89a7efb45f900cd66adc