The insulin-like growth factor system and adenocarcinoma of the colon

The insulin-like growth factor (IGF) system is important in normal growth and development. However, it is also known to be involved with malignant transformation and cellular proliferation. IGF binding proteins modulate the biological activity of IGF-I, either potentiating or inhibiting its activity, as well as determining how much enters the circulation at any one time. IGF binding protein-4 (IGFBP-4), for example is believed to be inhibitory to the effects of IGF-I. This thesis shows that the colon cancer cell lines Colo 205, HT29 and WiDR proliferate in response to IGF-I, and that IGFBP-4 at high concentrations inhibits their growth. However, it was found that with lower concentrationsof IGFBP-4, proliferation in HT29 and WiDR cells increased. Nevertheless in two cell lines, IGFBP-4 partially negated the proliferative effects of IGF-I. An antibody against IGFBP-4 was used to show that endogenous IGFBP-4 plays an important role in modifying cell growth. In order to start in vivo experiments which required considerable quantities of IGFBP-4, this protein was produced in an expression system and purified using an immunoaffinity column method. The rhIGFBP-4 thus produced was shown to be functional and to inhibit colorectal cancer cell growth in vitro. A nude mouse model of colon cancer was produced and the expression of components of the IGF system in this model determined using PCR. Experiments were performed using conditioned medium from Colo 205 cells to investigate IGFBP-4 protease activity. This thesis shows that manipulation of the IGF system is a potential target for further research into treatment for adenocarcinoma of the colon

Percentage of T_FH and expression of CXCR5 and PD-1 during fingolimod treatment in MS patients.

<p>(A.) Percentage of PB follicular helper T cells (T_FH) in MS patients treated with fingolimod. Data are presented as percentage within the CD4⁺ T cell population. (B.) Expression of CXCR5 and (C.) expression of PD-1 within T_FH cell population.</p

Total number of lymphocytes, CD4⁺ T cells and CD19⁺ B cells in the PB.

<p>Total number (×10³ cells/µl blood) of lymphocytes, T cells and B cells in treatment-naive, IFN-β treated MS patients at baseline and fingolimod-treated MS patients during 12 months follow-up. Mean and standard error of the mean are presented. • lymphocytes; ▪ CD4⁺ T cells; ▴ CD19⁺ B cells.</p

Proportional B cell and T cell subtype changes in MS patients during fingolimod treatment.

<p>(A) CD19⁺ B cell subtype proportion and (B) CD4⁺ T cell subtype proportion within the PB of treatment-naive, IFN-β and fingolimod-treated MS patients. Results are presented as relative values within the CD19⁺ B cell or CD4⁺ T cell population. Subtype proportions were calculated as follows: (% subtype/100)×% CD19⁺ or CD4⁺ within the total lymphocyte population. Statistically significant differences compared to 0 m are shown in bold. For B cells: naive B cells; NCSM B cells  =  non class-switched memory B cells; CSM B cells  =  class-switched memory B cells and DN B cells  =  double negative B cells. For T cells: nTreg  =  naive Treg; mTreg  =  memory Treg; TransTreg  =  transitional Treg; nTconv  =  naive Tconv; mTconv  =  memory Tconv; TransTconv  =  transitional Tconv.</p

GO-Compartments.

<p>The 75 unique proteins (ANOVA ≤ 0.05) were categorized according to the subcellular compartment (extracellular space, plasma membrane, cytoplasm, nucleus, and unknown). Information was collected from Gene ontology by IPA. Percentages are presented.</p

Ingenuity pathway analysis networks build with focus proteins.

<p>The DLG4-KCNMA1 network (Panel A), APP-ACTB network (Panel B) and AGT-TP53 network (Panel C) are represented. These networks were obtained using the IPA-KB by linking proteins from the data-set (75 unique proteins) to the focus proteins. Nodes containing proteins identified in the dataset have a grey fill.</p

Protein expression patterns over the disease course.

<p>2D-DIGE expression profiles: ALB (spot 874), PDIA3 (spot 1149), GFAP (spot 1397), CNP (spot 1656 and 1685) and CAPG (spot 1906). The log standard abundance (the relative abundance change normalized to signals in internal standard specific for each spot) is indicated for control, onset, top and recovery samples.</p

Western blot analysis of DLG4 and KCNMA1.

<p>A quantitative fluorescent western blot was performed to analyze the presence and expression levels of KCNMA1 (Panel A) and DLG4 (Panel B). By means of peak detection, the normalized peak volumes were used for quantification. No significant difference was found in expression levels, but both proteins were detected in the samples of the 2D-DIGE experiment. All animals were included in the WB analysis; control (C), onset (O), top (T) and recovery (R).</p

Validation of the 2D-DIGE results.

<p>Immunohistochemistry was performed to demonstrate the presence of macrophages and CNP. Macrophage (ED-1) and CNP immunostaining of rat spinal cords (same animals as for 2D-DIGE) from control, and EAE rats before disease onset, top and recovery are shown in panel A. These IHC stainings were quantified (Panel B and C), and expression levels compared by Dunn's multiple comparison test (GraphPad Prism4). The error bars indicate standard deviations of measurements performed at least in triplicate. *: significant difference, p<0.01 and **: significant difference, p<0.001. In Panel D, a quantitative 1D CNP immunoblot of EAE brainstem homogenate from control and disease top is shown. An overview of the fluorescent total protein staining, anti-CNP immunostaining, the fluorescent overlay of both (red and green overlay), and finally a representation of the fluorescent signals as processed with ImageQuant TL software (GE Healthcare). The red curve corresponds with the total protein content and the green curve with the CNP fluorescence. Both a representative control animal (c) and one at the disease top (t) are presented.</p

2D-DIGE gel image.

<p>The 92 spots presented have a shift in abundance over the four experimental conditions (control, disease onset, top, and recovery) (ANOVA ≤ 0.05). Spots were picked from preparative 2D-gels and proteins identified by nano-LC-ESI-mass spectrometry. The proteins were identified with significant MASCOT and SEQUEST scores. Spots are numbered as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035544#pone.0035544.s001" target="_blank">Table S1</a>.</p