| Title |
Tumor characterization by ultrasound-release of multiple protein and microRNA biomarkers, preclinical and clinical evidence
|
|---|---|
| Published in |
PLOS ONE, March 2018
|
| DOI | 10.1371/journal.pone.0194268 |
| Pubmed ID | |
| Authors |
Aloma L. D’Souza, John R. Chevillet, Pejman Ghanouni, Xinrui Yan, Muneesh Tewari, Sanjiv S. Gambhir |
| Abstract |
We have previously shown that low frequency ultrasound can release biomarkers from cells into the murine circulation enabling an amplification and localization of the released biomarker that could be used as a blood-based method to detect cancer earlier and monitor therapy. In this study, we further demonstrate that this technique could be used for characterization of tumors and/or identification of cellular masses of unknown origin due to the release of multiple protein and nucleic acid biomarkers in cells in culture, mice and patients. We sonicated colon (LS174T) and prostate (LNCaP) cancer cell lines in culture at a low frequency of 1 MHz and show that there were several-fold changes in multiple protein and microRNA (miRNA) abundance with treatment at various intensities and time. This release was dependent on the duration and intensity of the sonication for both cell lines. Significant increased release in biomarkers was also observed following tumor sonication in living mice bearing subcutaneous LS174T cell line xenografts (for proteins and nucleic acids) and in an experimental LS174T liver tumor model (for proteins only). Finally, we demonstrated this methodology of multiple biomarker release in patients undergoing ablation of uterine fibroids using MR guided high intensity focused ultrasound. Two protein biomarkers significantly increased in the plasma after the ultrasound treatment in 21 samples tested. This proof that ultrasound-amplification method works in soft tissue tumor models together with biomarker multiplexing, could allow for an effective non-invasive method for identification, characterization and localization of incidental lesions, cancer and other disease. Pre-treatment quantification of the biomarkers, allows for individualization of quantitative comparisons. This individualization of normal marker levels in this method allows for specificity of the biomarker-increase to each patient, tumor or organ being studied. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 18% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Bachelor | 4 | 10% |
| Student > Master | 4 | 10% |
| Other | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 9 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 18% |
| Medicine and Dentistry | 7 | 18% |
| Neuroscience | 3 | 8% |
| Engineering | 3 | 8% |
| Agricultural and Biological Sciences | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 11 | 28% |
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 21 March 2018.
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#17,934,709
of 23,028,364 outputs
Outputs from PLOS ONE
#148,926
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#242,258
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Outputs of similar age from PLOS ONE
#2,724
of 3,667 outputs
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