Imaging Circulating Tumor Cells in Freely Moving Awake Small Animals Using a Miniaturized Intravital Microscope

<div><p>Metastasis, the cause for 90% of cancer mortality, is a complex and poorly understood process involving the invasion of circulating tumor cells (CTCs) into blood vessels. These cells have potential prognostic value as biomarkers for early metastatic risk. But their rarity and the lack of specificity and sensitivity in measuring them render their interrogation by current techniques very challenging. How and when these cells are circulating in the blood, on their way to potentially give rise to metastasis, is a question that remains largely unanswered. In order to provide an insight into this "black box" using non-invasive imaging, we developed a novel miniature intravital microscopy (mIVM) strategy capable of real-time long-term monitoring of CTCs in awake small animals. We established an experimental 4T1-GL mouse model of metastatic breast cancer, in which tumor cells express both fluorescent and bioluminescent reporter genes to enable both single cell and whole body tumor imaging. Using mIVM, we monitored blood vessels of different diameters in awake mice in an experimental model of metastasis. Using an in-house software algorithm we developed, we demonstrated <i>in vivo</i> CTC enumeration and computation of CTC trajectory and speed. These data represent the first reported use we know of for a miniature mountable intravital microscopy setup for <i>in vivo</i> imaging of CTCs in awake animals.</p></div

<i>In vivo</i> CTCs imaging using miniature mountable intravital microscopy (mIVM) method.

<p>(<b>A</b>, <b>B</b>, <b>C</b>) <i>In vivo</i> imaging of CTCs using the mIVM after systemic injection of FITC-dextran for vessel labeling followed by injection of 1×10⁶ 4T1-GL labeled with CFSE. (<b>A</b>) Raw image from the miniature microscope. (<b>B</b>) Image processed by our MATLAB algorithm for detection of CTCs and vessel edges. (<b>C</b>) Computing of CTCs trajectories within the blood vessel. (<b>D</b>) Quantification of the speeds of CTCs over time as imaged in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086759#pone.0086759.s003" target="_blank">Movie S1</a>, and (<b>E</b>) corresponding average speeds per CTC, plotted as box and whiskers where the box extends from the 25th to 75th percentiles and the whiskers extend from the minimum to the maximum speed values measured. (<b>F</b>) For the slowest CTC – CTC2 on (<b>D</b>, <b>E</b>) – details of the speed of the cell over time (red curve) and the corresponding location of the cell relative to the vessel edge (blue curve).</p

Imaging of circulating tumor cells in an awake, freely behaving animal using the mIVM.

<p>(<b>A</b>) Photograph of the animal preparation: Following tail-vein injection of FITC-dextran for vessel labeling and subsequent injection of 1×10⁶ 4T1-GL labeled with CFSE, the animal was taken off the anesthesia and allowed to freely behave in its cage while CTCs were imaged in real-time. (<b>B</b>) mIVM image of the field of view containing two blood vessel, Vessel 1 of 300 µm diameter and Vessel 2 of 150 µm diameter. (<b>C</b>, <b>D</b>) Quantification of number of CTCs events during 2h-long awake imaging, using a MATLAB image processing algorithm, in Vessel 1 (<b>C</b>) and Vessel 2 (<b>D</b>). (<b>E</b>, <b>F</b>) Computing of CTC dynamics: average CTC frequency (Hz) as computed over non-overlapping 1 min windows for Vessel 1 (<b>E</b>) and Vessel 2 (<b>F</b>) and (<b>G</b>) Second-order smoothing (10 neighbor algorithm) of the data presented in (<b>E</b>, <b>F</b>)<b>.</b></p

Experimental mouse metastatic breast cancer model.

<p>(<b>A</b>) Schematic of lentiviral construct comprising a fusion reporter gene (Luciferase-2 and enhanced GFP) under the control of the ubiquitin promoter, used to establish the imageable metastatic mammary carcinoma cell line 4T1-GL. (<b>B</b>) FACs analysis of GFP fluorescence, comparing the stable cell line 4T1-GL at passage 2 and passage 12 (resp. P2 and P12) to wild-type 4T1 cells (4T1-WT). (<b>C</b>) Metastatic tumor growth in the lungs as monitored non-invasively by Bioluminescence (BLI) imaging, following a systemic injection of 1×10⁶ 4T1-GL cells via the tail vein (n = 7). (<b>D</b>) Biodistribution of metastatic cells, 12 days after systemic injection (n = 7) in the following organs: Lungs, Liver, Heart, Kidneys Spleen, Bone marrow, and corresponding quantification of BLI signal per organ (n = 7). (<b>E</b>) CTCs in 100 µL blood samples of mice (n = 7) at various times from day 0 (immediately after injection) to 12 days after injection and corresponding signal quantification. Positive BLI signals correspond to <20 CTCs/100 uL of blood.</p

Miniature mountable intravital microscopy system design for <i>in vivo</i> CTCs imaging in awake animals.

<p>(<b>A</b>) Computer-assisted design of an integrated microscope, shown in cross-section. Blue and green arrows mark illumination and emission pathways, respectively. (<b>B</b>) Image of an assembled integrated microscope. Insets, filter cube holding dichroic mirror and excitation and emission filters (bottom left), PCB holding the CMOS camera chip (top right) and PCB holding the LED illumination source (bottom right). The wire bundles for LED and CMOS boards are visible. Scale bars, 5 mm (<b>A</b>,<b>B</b>). (<b>C</b>) Schematic of electronics for real-time image acquisition and control. The LED and CMOS sensor each have their own PCB. These boards are connected to a custom, external PCB via nine fine wires (two to the LED and seven to the camera) encased in a single polyvinyl chloride sheath. The external PCB interfaces with a computer via a USB (universal serial bus) adaptor board. PD, flash programming device; OSC, quartz crystal oscillator; I²C, two-wire interintegrated circuit serial communication interface; and FPGA, field-programmable gate array. (<b>D</b>) Schematic of the miniature mountable intravital microscopy system and corresponding images. The miniature microscope is attached to a dorsal skinfold window chamber via a lightweight holder. (<b>E</b>) mIVM imaging of cells in suspension in a glass-bottom 96-well plate. 4T1-GL cells; 4T1-GL cells that have been transiently transfected with the Luc2-eGFP DNA to enhance their fluorescence (4T1-GL-tt); 4T1-GL cells that have been labeled with the bright green fluorescent CFSE dye (4T1-GL-CFSE). (<b>F</b>) Quantification of the cell to background green fluorescence for the three cell types described in (E) for n = 3 field of view, average ±standard deviation. <b>Fig. 2</b> (<b>A</b>)<b>,</b> (<b>B</b>)<b>,</b> (<b>C</b>) reprinted by permission from Macmillan Publishers Ltd: Nature Methods (Ghosh, K. K. <i>et al.</i> Miniaturized integration of a fluorescence microscope. <i>Nat Meth </i><b>8,</b> 871–878 (2011)), copyright 2011.</p

Excised pig colon backgrounds, mean, and first two principal components.

<p>Excised pig colon backgrounds, mean, and first two principal components.</p

Excised pig colon results.

<p>Excised pig colon results.</p

Simulation results.

<p>(a) Example of fitted spectra, (b) corresponding residuals, (c) histograms of Durbin-Watson statistics produced by each method, (d) estimated concentrations, and (e-f) mean and standard deviation of fractional errors generated by the LS-3P, HLA and HLP algorithms.</p

Acquired signals, mean signal, and the first two principal components of the S440 nanoparticle (left) and the paraffin background (right).

<p>Acquired signals, mean signal, and the first two principal components of the S440 nanoparticle (left) and the paraffin background (right).</p

Bioluminescence imaging of primary tumor and metastases in the 4T1-GL orthotopic mammary tumor model.

<p>(<b>A</b>) Primary tumor growth in the mammary fat pad (m.f.p) as monitored using BLI, following implantation of 2×10⁷ 4T1-GL cells in the fourth left mammary fat pad (image scales in p/s/cm²/sr, n = 7 mice). (<b>B</b>) Corresponding quantification of BLI signal in the m.f.p area, shown as mean ± SEM and fit of the mean values to a Gompertzian tumor growth equation (dashed line, R² = 0.86). (<b>C</b>) Metastases in the upper body (lung area) as monitored using BLI in the same animals (image scales in p/s/cm²/sr). (<b>D</b>) Corresponding quantification of the signal in the lung area, shown as mean ± SEM. (<b>E</b>) Metastases in excised organs on day 23, as monitored using BLI in the same animals: a. tumor (scale: 2×10⁸–3×10⁹ p/s/cm²/sr), b. lungs (scale: 2×10⁸–3×10⁹ p/s/cm²/sr), c. liver (scale: 2×10⁵–7×10⁶ p/s/cm²/sr), d. brain (scale: 1×10⁴–1×10⁵ p/s/cm²/sr), e. heart (scale: 1×10⁷–6×10⁷ p/s/cm²/sr), f. kidneys (scale: 2×10⁵–7×10⁶ p/s/cm²/sr), g. spleen (scale: 2×10⁵–7×10⁶ p/s/cm²/sr), h. bone (scale: 2×10⁵–7×10⁶ p/s/cm²/sr). (<b>F</b>) Corresponding quantification of BLI signal in these organs, shown as mean ± SD.</p