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Predicting treatment resistance and relapse through circulating DNA
Emma Beddowes
, Stephen J. Sammut
, Meiling Gao
,
Carlos Caldas
*
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
peer-review
20
Scopus citations
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Dive into the research topics of 'Predicting treatment resistance and relapse through circulating DNA'. Together they form a unique fingerprint.
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Keyphrases
Clinical Relapse
100%
Circulating DNA
100%
Treatment Resistance
100%
Treatment Response
75%
Genetic Modification
25%
Further Development
25%
Deep Sequencing
25%
Early Breast Cancer
25%
High Response Rate
25%
Early Detection
25%
Disease Relapse
25%
Technological Progress
25%
Copy number Variation
25%
Tumor-specific
25%
New mutation
25%
PI3K Inhibitor
25%
Liquid Biopsy
25%
Resistance to Treatment
25%
Screening Tool
25%
Patient Tumor
25%
Metastatic Breast Cancer
25%
Whole Exome
25%
Prognosis Prediction
25%
Non-invasive Screening
25%
PIK3CA mutation
25%
Patients with Breast Cancer
25%
Endocrine Therapy
25%
Micrometastatic Disease
25%
Early Breast Cancer Detection
25%
Digital PCR (dPCR)
25%
Chromosomal Copy number
25%
Personalized Genomics
25%
Predicting Disease
25%
Whole Genome Approach
25%
ESR1 mutation
25%
Exosomal miRNA
25%
Hypermethylated DNA
25%
Medicine and Dentistry
Breast Cancer
100%
Treatment Response
100%
Diseases
66%
Genetics
66%
microRNA
33%
Hormone Therapy
33%
Cancer Diagnosis
33%
Specific Tumor
33%
Liquid Biopsy
33%
Exome
33%
Metastatic Breast Cancer
33%
Tumor
33%