Figure 2

<p>Cytotoxic effect of 5-FU on non-sorted and sorted (uPAR-positive and uPAR-negative populations) derived from SCLC cell lines. (A) 1×10⁴ cells (H211, H69AR, H1417) were placed in wells of a 48-well plate in triplicates and incubated for 72 hr in the presence of varying concentrations of 5-FU. (B) SCLC cell lines were FACS sorted after staining with anti-uPAR antibodies and were plated at the same seeding density (4×10³/well of 96-well plate) and treated with 5-FU at 0, 10, 100, 200 µg/ml for 72 hr. Cell survival was evaluated after adding Guava ViaCount reagent and counting viable and dead cells. Only viable cells were included in data analysis, and 100% viability was defined as number of viable cells cultured in absence of 5-FU. Statistical analysis (2-way ANOVA) of uPAR(+) and uPAR(−) data sets revealed significant differences among viability of uPAR(+) and uPAR(−) cells (<i>P</i> = 0.0002, 0.0027, 0.0008 for H211, H69AR, H1417 cells, respectively). The data points represent averages±SD of three independent experiments.</p

Figure 4

<p>Colony-forming activity of uPAR-positive and uPAR-negative cells derived from SCLC cell lines. (A) H1417- derived, uPAR-positive sorted cells formed multiple colonies in methylcellulose media, while uPAR-negative cells from the same sorts displayed little or no clonogenic activity. (B) Graphical representation of colony-forming ability of uPAR-positive and uPAR-negative cells at different plating densities 3000, 1000, 100 cells/6-well plate (H1417, H69AR, H211). (C) Distribution of uPAR-positive cells in the colonies derived from sorted uPAR-positive cells grown in methylcellulose media. A total of 20 cell colonies from the H1417 cell line were analyzed.</p

Figure 5

<p>Expression of CD44 and MDR1 on uPAR-positive and uPAR-negative cells. (A) FACS analysis of, H211, H69AR and H1417 SCLC cell lines double-labeled with uPAR-FITC and CD44-PE, MDR1-PE. The percentages of cells expressing CD44 and MDR1 were calculated separately for uPAR-positive and uPAR-negative cells. (B) Fluorescent microscopic analysis of double-labeled and FACS-sorted cells. Examples of uPAR-FITC/CD44-PE double-labeling (a,b,c) and uPAR-FITC/MDR1-PE double-labeling (d,e,f). (Bf-inset) H1417 cell line stained with mouse IgG isotype control-PE (red), isotype control-FITC (green) and DAPI (blue).</p

Figure 3

<p>Cytotoxic effect of cisplatin and etoposide on non-sorted cells derived from SCLC cell lines. (A) SCLC cell lines (non-sorted) treated with cisplatin, etoposide at concentrations 0, 3, 10, 100 µg/ml or their combinations (cisplatin and etoposide at final concentrations of 10 µg/ml, 100 µg/ml) for 72 hr. Cell survival was evaluated after addition of Guava ViaCount reagent and counting of both surviving and dead cells using Guava ViaCount software. Data were normalized as 100% viability of cells cultured in absence of drugs. Error bars indicate standard deviation of triplicate cultures (results of three independent experiments). (B) After treatment cisplatin and etoposide, viable adherent cells were detached by trypsin treatment and were stained with anti-uPAR-FITC antibodies and percentage of uPAR-positive cells was determined by FACS analysis. Sample with mouse IgG isotype control antibody was used to set the value of the FACS gate, which was applied to all samples stained with uPAR-FITC.</p

Long-term stability and computational analysis of migration patterns of L-<i>MYC</i> immortalized neural stem cells in the brain

<div><p>Background</p><p>Preclinical studies indicate that neural stem cells (NSCs) can limit or reverse central nervous system (CNS) damage through delivery of therapeutic agents for cell regeneration. Clinical translation of cell-based therapies raises concerns about long-term stability, differentiation and fate, and absence of tumorigenicity of these cells, as well as manufacturing time required to produce therapeutic cells in quantities sufficient for clinical use. Allogeneic NSC lines are in growing demand due to challenges inherent in using autologous stem cells, including production costs that limit availability to patients.</p><p>Methods/Principal findings</p><p>We demonstrate the long-term stability of L-<i>MYC</i> immortalized human NSCs (LM-NSC008) cells <i>in vivo</i>, including engraftment, migration, and absence of tumorigenicity in mouse brains for up to nine months. We also examined the distributions of engrafted LM-NSC008 cells within brain, and present computational techniques to analyze NSC migration characteristics in relation to intrinsic brain structures.</p><p>Conclusions/Significance</p><p>This computational analysis of NSC distributions following implantation provides proof-of-concept for the development of computational models that can be used clinically to predict NSC migration paths in patients. Previously, models of preferential migration of malignant tumor cells along white matter tracts have been used to predict their final distributions. We suggest that quantitative measures of tissue orientation and white matter tracts determined from MR images can be used in a diffusion tensor imaging tractography-like approach to describe the most likely migration routes and final distributions of NSCs administered in a clinical setting. Such a model could be very useful in choosing the optimal anatomical locations for NSC administration to patients to achieve maximum therapeutic effects.</p></div

Computational analysis of distribution of LM-NSC008 cells.

<p><b>(A)</b> Distances of LM-NSC008 cell clusters from injection sites at 3, 6, and 9 months post-injection. Distances were calculated as Euclidean distances in the 2-dimensional plane. <b>(B, C)</b> Cumulative probability distributions of distances of LM-NSC008 clusters from the injection site in WM and GM at 3, 6 and 9 months post-injection. The 9 month curve reflecting a greater distance from the injection center as compared to 3 month curve indicates the migration of NSCs away from the injection site. <b>(D)</b> Percentage of LM-NSC008 cells identified in the WM at 3, 6, and 9 months post-injection. <b>(E, F)</b> Cumulative probability distribution of distance from white matter/grey matter (WM/GM) interface. The 9 month curve being closer to the WM/GM interface as compared to the 3 month curve indicates that LM-NSC008 cells increasingly aggregated near the WM/GM interface over time.</p

Characterization of LM-NSC008 cells.

<p>Visualization of LM-NSC008 cells in naïve non-tumor bearing mouse brain 6 and 9 months post administration. <b>(A)</b> Immunohistochemistry (IHC) staining of LM-NSC008 cells (stably expressing eGFP/Ffluc) with anti-HNA antibodies (NSC injection site, white arrows indicate the LM-NSC008 cells, scale bar 100 μm). <b>(1a-1d)</b> Insets show LM-NSC008 cells co-expressing HNA and eGFP proteins (inset scale bars [1a-1f] 2 μm). <b>(B)</b> IHC staining for huNestin (green) in mouse brain sections from 6 months after administration, scale bar 20 μm; <b>(C)</b> IHC staining for Pax6 (red)/eGFP in LM-NSC008 cells, scale bar 50 μm. Inset <b>(1e</b>) shows enlarged area of neuronal cells co-expressing Pax6 and eGFP. <b>(D)</b> Bright-field image of LM-NSC008 cells stained with Stem123 and contrastained with hematoxylin, scale bar 200 μm. Inset <b>(1f)</b> enlarged LM-NSC008 cell, expressing the glial marker Stem123. Arrows (black) show LM-NSC008s (brown) in the corpus callosum. <b>(E)</b> IHC for Ki-67, showing negative staining (red) of LM-NSC008 cells expressing eGFP (injection site), scale bar 20 μm. Fluorescent-stained slides were counterstained with DAPI (blue) to visualize nuclei. <b>(F)</b> PCR analysis of genomic DNA derived from LM-NSC008 cells at every 5th passage <i>in vitro</i> (p5-p50). Controls were: L-<i>MYC</i> plasmid, DNA derived from untransduced NSC008 cells, no DNA template. (<b>G</b>) Protein expression profiles from cell lysates (G1 and G3) and CM (G2 and G4) from LM-NSC008 cells at passages 5 and 45. Protein array analysis was conducted using Cytokine Antibody Array V from RayBiotech.</p

Computational analysis of LM-NSC008 cells and tissue orientation.

<p><b>(A)</b> DiI myelin-stained cross-section defining regions of WM. <b>(B)</b> The corresponding relative tissue anisotropy (coherence) image generated by the OrientationJ plugin to FIJI with 1 pixel Gaussian kernel. A higher pixel intensity indicates higher anisotropy and vice-versa. <b>(C)</b> Orientation vectors of WM overlaid on the coherence image. The angle θ_WM is the orientation of the WM. The red dots and the yellow lines indicate the ellipses and the dominant eigenvector calculated via structure tensor analysis (see Supplementary Materials). <b>(D)</b> Stochastic simulations of 500 NSC migration paths overlaid on the coherence map evaluated using 5 pixel Gaussian kernel. Preferential migration along the corpus callosum is evident. Inset shows the paths near the seed initialization region (analogous to injection site in a biological experiment) contrasting the directional motility in the WM and GM. <b>(E)</b> Nestin-stained cross-section adjacent to the section shown in (A) of naïve mouse brain 9 months after injection of NSCs (brown). <b>(F)</b> NSC clusters were identified using color and intensity thresholds. These clusters are dilated and eroded to create a map of NSC density. <b>(G)</b> NSC density overlaid on the DiI-defined WM boundaries, excluding the injection site. The green curve through the corpus callosum shows the curve fit through one NSC coalesced region. The angle θ_NSC is the orientation angle of an NSC cluster. <b>(H)</b> Scatter plot showing the orientation of NSC clusters (θ_NSC) against the orientation of WM (θ_WM) weighted by cluster size. The slope of the line indicates the slope of the fit through the scatter plot. Note that the NSCs clusters analyzed above include clusters in both WM and GM. Separate scatter plots for NSCs in WM and GM are shown in the supplemental data.</p

Retention of FE-Pro label in HB1.F3.CD NSCs.

<p>Data is displayed as means +/− SD of Prussian blue positive iron-loaded NSCs (% of total cell number). The data were obtained from 5 random fields of each independently labeled triplicate sample at 24, 48 and 96 h post-labeling.</p

Labeling efficiency of FE-Pro.

<p>(A) Light microscopy images of Prussian blue-stained non-labeled and FE-Pro-labeled NSCs at 24, 48 and 96 hours after labeling. (B) Electron micrographs of Fe-Pro-labeled NSCs. (C) Higher magnification image of outlined area in (B). Red arrows point to internalized FE-Pro complex in membrane-bound organelles. (D–E) T2-weighted MR images of labeled (L), non-labeled (N), and an equal mixture (M) of NSCs grown in soft agar. Each phantom contained three different total numbers of NSCs (1×10⁴, 1×10⁵ and 5×10⁵) each in 500 µl of 20% DMEM and 0.8% agar. Coronal view (D) and axial view at 5×10⁵ (E. left) and 1×10⁵ (E. right) of the phantoms. Decrease in T2-w signal strength correlated with the number of labeled cells in the phantom. (F) Graph of T2-w signal intensity vs. number of labeled NSCs. Data were extracted from 5 random fields of each corresponding phantom using ImageJ and shown as mean±SE. MRI conditions: 7.0 Tesla, Gradient-Echo sequence, voxel size = 0.09 mm³, TR/TE = 5402.5/90 ms. Scale bars = 50 µm (A), 2 µm (B) and 200 nm (C).</p