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Microfluidics and spectroscopic imaging for personalized medicine in ovarian cancer
| Content Provider | Semantic Scholar |
|---|---|
| Author | Astolfi, Mélina St-Georges-Robillard, Amélie Leblond, Frederic Mès-Masson, Anne-Marie Gervais, Thomas |
| Copyright Year | 2016 |
| Abstract | With certain cancers, such as ovarian cancers, a significant number of patients are non-responsive to the standard chemotherapy treatment. These patients, therefore, experience the negative side effects of chemotherapy without clinical benefits. With the everincreasing number of available anti-cancer drug alternatives to chemotherapy, there is tremendous pressure on clinicians to make the right treatment choice. The biomarker approach—a statistical method that associates drug-response rates with specific patient characteristics—is effective for predicting which patients will respond best to a given treatment. However, only very specific cancer subtypes have associated biomarkers (i.e., the BRCA mutation for breast cancer). There is a crucial need, therefore, for a complementary predictive method that is applicable to virtually all types of cancers. Clusters of cells, known as spheroids, are the most popular 3D tissue model in cancer research. These samples, which have standard diameters of around 400 m, are relatively easy to culture and they represent patient tumors better than traditional 2D cell cultures.1 The spheroids are often formed and cultured in miniaturized fluidic systems—or microfluidic chips—in which biological assays are performed. However, spheroids have been of little use in personalized therapy because they are formed using generic cell lines that do not reproduce the specificities of a patient’s tumor. A promising alternative would be to directly test therapies on small amounts of cancer tissue from patients, but this approach has had limited success in the past because of challenges associated with culturing patient tissue outside the human body and with developing detection methods to measure drug response in 3D tissue. Figure 1. Personalized approach for the selection of an optimal anticancer treatment. Small amounts of tissue from a patient are sectioned into spheroid-sized samples. These individual samples are then introduced into a microsystem, in which different treatment options can be tested and their effects measured using various detection systems. Inset shows a top-view image of a sample trapped inside a well. The sample is labeled with fluorescent probes marking cells that are viable (green) and dead (red), and is imaged using confocal fluorescence microscopy. The results of the test may help medical specialists choose the most effective treatment for each patient. |
| File Format | PDF HTM / HTML |
| DOI | 10.1117/2.1201602.006352 |
| Alternate Webpage(s) | http://www.spie.org/documents/Newsroom/Imported/006352/006352_10.pdf |
| Alternate Webpage(s) | https://doi.org/10.1117/2.1201602.006352 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
