Table 1.
Patient and tumour characteristics for the four canine cancer patients included in the study.
Table 2.
Optimized primer- and TaqMan probe concentrations for the genes investigated.
Table 3.
Final qPCR designs for the reference genes and the genes of interest (GOIs).
Fig 1.
Micro regional heterogeneity in distribution of 64Cu-ATSM (hypoxia) and 18F-FDG (glycolysis).
Example of calculated 18F-FDG image (left) and calculated 64Cu-ATSM image (right) from autoradiography of a tumour tissue section from tumour 4. Intensity levels in each image are individually optimized.
Fig 2.
Correlation between 64Cu-ATSM and 18F-FDG distribution in autoradiography sections.
Examples of calculated 18F-FDG images (first column) and calculated 64Cu-ATSM images (second column) from the autoradiographies from tumour 2 (A), tumour 3 (B) and tumour 4 (C). The third column shows the pixel-to-pixel plot, separating background (blue marks) and autoradiography (AR) image data (red marks) using cluster analysis. Images were downscaled a factor of 4 for this analysis. The correlation of the non-background AR image is shown in the fourth column.
Fig 3.
Correlation between 64Cu-ATSM and 18F-FDG uptake in gamma counted tumour pieces.
Spearman’s Rank correlations (ρ) and p-values for comparison of intra-tumoural spatial distribution of 64Cu-ATSM and 18 F-FDG calculated as standardized uptake value (SUV) from gamma counts of tumour pieces. a, b, c and d show data for tumour pieces from canine cancer patient 1, 2, 3 and 4, respectively. n is the number of tumour pieces included in the final analysis. Significant correlations are written in bold.
Table 4.
Maximum and minimum standardized uptake values (SUV) for 64Cu-ATSM and 18F-FDG in each tumour calculated from well counts on all biopsies.
Fig 4.
Ki-67 IHC versus 64Cu-ATSM and 18F-FDG autoradiography.
Visual example of the comparison between a Ki-67 IHC image and 64Cu-ATSM and 18F-FDG autoradiography images for tumour 2. First column: Ki-67 IHC image rescaled to the same pixel size (42 μm) as the autoradiographies (AR). A selection is chosen for illustration of correlations between Ki-67 IHC and 18F-FDG and 64Cu-ATSM AR respectively (columns 2–4).
Fig 5.
Correlation between gene expression of Ki-67 and 64Cu-ATSM and 18F-FDG uptake.
Spearman’s Rank correlations (ρ) and p-values for comparison of gene expression for Ki-67 and tumour uptake of 18F-FDG (right column) and 64Cu-ATSM (left column) calculated as standardized uptake value (SUV) from gamma counts of tumour pieces. Row A, B and C show data for tumour pieces from canine cancer patient 2, 3 and 4 respectively. n is the number of tumour pieces included in the final analysis. n.s. not significant. Significant correlations are written in bold.
Fig 6.
Correlations between hypoxic and glycolytic gene expressions and 64Cu-ATSM and 18F-FDG uptake, tumour 3.
Spearman’s Rank correlations (ρ) and p-values for comparison of gene expressions for GLUT1, GLUT3, HIF-1α and CAIX respectively and tumour uptake of 18 F-FDG (upper row) and 64Cu-ATSM (lower row) calculated as standardized uptake value (SUV) from gamma counts. n is the number of tumour pieces included in the final analysis. n.s. not significant. Significant correlations are written in bold.
Fig 7.
Correlations between the gene expressions of different genes of interest, tumour 3.
Spearman’s Rank correlations (ρ) and p-values for all possible gen-gen correlations between GLUT1, GLUT3, HIF-1α, CAIX and Ki-67. n is the number of tumour pieces included in the final analysis. n.s. not significant. Significant correlations are written in bold.