Chapter title |
Prediction of Clinical Endpoints in Breast Cancer Using NMR Metabolic Profiles
|
---|---|
Chapter number | 9 |
Book title |
Cancer Systems Biology
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7493-1_9 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7492-4, 978-1-4939-7493-1
|
Authors |
Leslie R. Euceda, Tonje H. Haukaas, Tone F. Bathen, Guro F. Giskeødegård |
Abstract |
Metabolic profiles reflect biological conditions as a result of biochemical changes within a living system. It is therefore possible to associate metabolic signatures with clinical endpoints of diseases, such as breast cancer. Nuclear magnetic resonance (NMR) spectroscopy is one of the most common techniques used for metabolic profiling, and produces high dimensional datasets from which meaningful biological information can be extracted. Here, we present an overview of data analysis techniques used to achieve this, describing key steps in the procedure. Moreover, examples of clinical endpoints of interest are provided. Although these are specific for breast cancer, the procedures for the analysis of NMR spectra as described here are applicable to any type of cancer and to other diseases. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 11 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2 | 18% |
Librarian | 1 | 9% |
Lecturer | 1 | 9% |
Other | 1 | 9% |
Student > Bachelor | 1 | 9% |
Other | 1 | 9% |
Unknown | 4 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 36% |
Engineering | 1 | 9% |
Unknown | 6 | 55% |