Whole-Body Profiling of Cancer Metastasis with Single-Cell Resolution
Author(s) -
Shimpei I. Kubota,
Kei Takahashi,
Jun Nishida,
Yasuyuki Morishita,
Shogo Ehata,
Kazuki Tainaka,
Kohei Miyazono,
Hiroki R. Ueda
Publication year - 2017
Publication title -
cell reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.264
H-Index - 154
eISSN - 2639-1856
pISSN - 2211-1247
DOI - 10.1016/j.celrep.2017.06.010
Subject(s) - profiling (computer programming) , metastasis , cancer , computational biology , biology , cancer research , medicine , computer science , operating system
Stochastic and proliferative events initiated from a single cell can disrupt homeostatic balance and lead to fatal disease processes such as cancer metastasis. To overcome metastasis, it is necessary to detect and quantify sparsely distributed metastatic cells throughout the body at early stages. Here, we demonstrate that clear, unobstructed brain/body imaging cocktails and computational analysis (CUBIC)-based cancer (CUBIC-cancer) analysis with a refractive index (RI)-optimized protocol enables comprehensive cancer cell profiling of the whole body and organs. We applied CUBIC-cancer analysis to 13 mouse models using nine cancer cell lines and spatiotemporal quantification of metastatic cancer progression at single-cell resolution. CUBIC-cancer analysis suggests that the epithelial-mesenchymal transition promotes not only extravasation but also cell survival at metastatic sites. CUBIC-cancer analysis is also applicable to pharmacotherapeutic profiling of anti-tumor drugs. CUBIC-cancer analysis is compatible with in vivo bioluminescence imaging and 2D histology. We suggest that a scalable analytical pipeline with these three modalities may contribute to addressing currently incurable metastatic diseases.
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