4.3 Article

In Vivo Autofluorescence Imaging of Tumor Heterogeneity in Response to Treatment

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NEOPLASIA
卷 17, 期 12, 页码 862-870

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.neo.2015.11.006

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  1. NIH [R01 CA185747]
  2. DoD [W81XWH-13-1-0194]
  3. Mary Kay Foundation [067-14]
  4. NSF Graduate Research Fellowship [DGE-0909667]
  5. NIH/NCI [R25 CA136440-04, R00 CA143231-03]
  6. Vanderbilt-Ingram Cancer Center (VICC) [P30 CA68485]
  7. VICC Ambassadors

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Subpopulations of cells that escape anti-cancer treatment can cause relapse in cancer patients. Therefore, measurements of cellular-level tumor heterogeneity could enable improved anti-cancer treatment regimens. Cancer exhibits altered cellular metabolism, which affects the autofluorescence of metabolic cofactors NAD(P)H and FAD. The optical redox ratio (fluorescence intensity of NAD(P)H divided by FAD) reflects global cellular metabolism. The fluorescence lifetime (amount of time a fluorophore is in the excited state) is sensitive to microenvironment, particularly protein-binding. High-resolution imaging of the optical redox ratio and fluorescence lifetimes of NAD(P)H and FAD (optical metabolic imaging) enables single-cell analyses. In this study, mice with FaDu tumors were treated with the antibody therapy cetuximab or the chemotherapy cisplatin and imaged in vivo two days after treatment. Results indicate that fluorescence lifetimes of NAD(P)H and FAD are sensitive to early response (two days post-treatment, P < .05), compared with decreases in tumor size (nine days post-treatment, P < .05). Frequency histogram analysis of individual optical metabolic imaging parameters identifies subpopulations of cells, and a new heterogeneity index enables quantitative comparisons of cellular heterogeneity across treatment groups for individual variables. Additionally, a dimensionality reduction technique (viSNE) enables holistic visualization of multivariate optical measures of cellular heterogeneity. These analyses indicate increased heterogeneity in the cetuximab and cisplatin treatment groups compared with the control group. Overall, the combination of optical metabolic imaging and cellular-level analyses provide novel, quantitative insights into tumor heterogeneity.

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