Sequencing studies using large oncogene panels in advanced cancers find an actionable DNA mutation in 5–35% of cases, depending on associated tumor histology 3, 4. Biomarker-driven personalized cancer treatment has been shown to improve response rates and extend progression-free survival 2. Precision oncology holds the promise of improving outcomes in cancer patients by tailoring effective therapies to an individual’s tumor while minimizing toxic side effects from ineffective drugs 1. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.
Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. We find that QPI EC 50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay.
Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment.
Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time.
0 kommentar(er)
