| Title |
Anthracycline induced cardiotoxicity: biomarkers and “Omics” technology in the era of patient specific care
|
|---|---|
| Published in |
Clinical and Translational Medicine, May 2017
|
| DOI | 10.1186/s40169-017-0148-3 |
| Pubmed ID | |
| Authors |
Shayan Moazeni, Martin Cadeiras, Eric H. Yang, Mario C. Deng, Kim-Lien Nguyen |
| Abstract |
Anthracyclines are highly effective against a variety of malignancies. However, their dose-dependent cardiotoxic effects can potentially limit their use. In the past decade, serum biomarkers have been used to diagnose, monitor, predict, and prognosticate disease. Biomarkers such as cardiac troponin and natriuretic peptides have some predictive value, but still lack reliability in this patient population. Novel biomarkers such as galectin-3, soluble ST-2 proteins, myeloperoxidase, and fibrocytes are being explored as potential biomarkers to reliably predict the onset of cardiotoxicity. Leveraging multiomics technology to map highly sensitive biomarkers in an integrated approach through pattern deconvolution may better define those at highest risk of developing cardiotoxicity and further the goal of precision medicine. In this work, we aim to provide a brief overview of traditional serum biomarkers, summarize current investigations on novel circulating biomarkers, and discuss a systems-based approach to anthracycline-induced cardiotoxicity through "omics" technology. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 70 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 21% |
| Student > Ph. D. Student | 7 | 10% |
| Other | 6 | 9% |
| Student > Master | 6 | 9% |
| Student > Bachelor | 5 | 7% |
| Other | 15 | 21% |
| Unknown | 16 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 36% |
| Biochemistry, Genetics and Molecular Biology | 10 | 14% |
| Agricultural and Biological Sciences | 5 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Nursing and Health Professions | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 21 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 May 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Clinical and Translational Medicine
#851
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Outputs of similar age
#284,807
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Outputs of similar age from Clinical and Translational Medicine
#7
of 7 outputs
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