DataSheet_1_The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study.pdf

Glioblastoma multiforme (GBM) typically exhibits substantial intratumoral heterogeneity at both microscopic and radiological resolution scales. Diffusion Weighted Imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) are two functional MRI techniques that are commonly employed in clinic for the assessment of GBM tumor characteristics. This work presents initial results aiming at determining if radiomics features extracted from preoperative ADC maps and post-contrast T1 (T1C) images are associated with pathomic features arising from H&E digitized pathology images. 48 patients from the public available CPTAC-GBM database, for which both radiology and pathology images were available, were involved in the study. 91 radiomics features were extracted from ADC maps and post-contrast T1 images using PyRadiomics. 65 pathomic features were extracted from cell detection measurements from H&E images. Moreover, 91 features were extracted from cell density maps of H&E images at four different resolutions. Radiopathomic associations were evaluated by means of Spearman’s correlation (ρ) and factor analysis. p values were adjusted for multiple correlations by using a false discovery rate adjustment. Significant cross-scale associations were identified between pathomics and ADC, both considering features (n = 186, 0.45 < ρ < 0.74 in absolute value) and factors (n = 5, 0.48 < ρ < 0.54 in absolute value). Significant but fewer ρ values were found concerning the association between pathomics and radiomics features (n = 53, 0.5 < ρ < 0.65 in absolute value) and factors (n = 2, ρ = 0.63 and ρ = 0.53 in absolute value). The results of this study suggest that cross-scale associations may exist between digital pathology and ADC and T1C imaging. This can be useful not only to improve the knowledge concerning GBM intratumoral heterogeneity, but also to strengthen the role of radiomics approach and its validation in clinical practice as “virtual biopsy”, introducing new insights for omics integration toward a personalized medicine approach.</p

Side population analysis.

<p>(A) Cytometric analyses of the side population. The CD133⁺ fraction includes a small subset (0.97%), expressing the characteristic profile of a side population at FACS. (B) ABCG2 expression in SAOS2 cell line, showing an evident positivity; the grey line indicates the isotype control.</p

CD133 expression in adherent cells and floating spheres.

<p>(A) Immunohistochemical analyses on adherent cells and (B) floating spheres showing the presence of CD133 antigen (<u>arrows</u>). (Original Magnification. ×100); (C) Immunofluorescence analysis on SAOS-2 for CD133 PE, cytoskeleton is stained with phalloidin-FITC, nucleus with DAPI (Original Magnification. ×400); (D) Immunoflurescence analysis on SAOS-2 spheres for CD133 PE after 24 hours in adhesion. (Original Magnification ×200); (E) Confocal analyses on adherent cells and (F) floating spheres confirming the presence of the CD133 antigen. (Original Magnification. ×400).</p

Cytometric analyses for CD133 and OCT3/4 on sarcospheres in SAOS2, MG63 and U2OS.

<p>The blue line indicates isotype controls, red and green lines indicate the expression of CD133 at the 4^th and 6^th cell passage, respectively. In the histograms, OCT3/4 expression is analyzed at the 6^th cell passage; the green line indicates isotype controls. Sarcospheres both in CD133 and OCT3/4 are strongly positive.</p

Colony-forming efficiency of CD133⁺ cells versus CD133− population^a in SAOS2, MG63 and U2OS cell lines.

a<p>Results are the mean±standard devition of three experiments from different cases.</p>b<p>Represents the number of colonies with respect to the number of wells plated in experiments.</p>c<p>Ratio between the percentage of colonies formed by CD133+ versus CD133− cells.</p

Spheres assay.

<p>(A) Sphere clusters formed by CD133⁺ cells in semisolid medium after 24 hours (Original Magnification ×100); (B) CD133⁻ cells in semisolid medium after 7 days, do not form spheres. (Original Magnification ×100); (C) Sphere clusters formed by CD133⁺ cells after 48 hours (Original Magnification ×200); (D) Sphere clusters formed by CD133⁺ cells after a new sorting (Original Magnification ×400).</p

Cytometric analyses for CD133 on SAOS2, MG63 and U2OS cell lines.

<p>A CD133⁺ cell population can be detected in all the three cell lines.</p

Cytometric analyses for CD133, CD44, CD90, CD34 and CD29 on SAOS2, MG63 and U2OS cell lines.

<p>All three cell lines are negative for CD34 antigen but they evidence equal strong positivity for CD29, CD44 and CD90.</p

Cell cycle, proliferation and growth analyses.

<p>(A) Figure of cell cycle analyses performed on SAOS2, MG63 and U2OS cell lines. A CD133⁺ cell population is mainly observable in the G2\M phase, whereas CD133⁻ cells were predominantly in G0\G1; (B) Figure showing Ki-67 reactivity. CD133⁺ cells resulted to be Ki-67⁺, whereas CD133⁻ were mainly negative for this marker; (C) Figure showing growth curves of CD133⁺ cells with respect CD133⁻ cells in SAOS2, MG63 and U2OS cell lines. CD133⁺ cells possess a high proliferative potential in all the three cell lines.</p

CD133 intracellular expression in adherent cells.

<p>(A) Figure performed at FACS showing intracellular expression of CD133 antigen in SAOS-2, MG-63 and U2OS. (B) Figure showing at the Real time PCR the mRNA transcript expression in CD133⁺ and CD133⁻ cells. The levels are almost identical as detected by in both CD133 positive and negative cells.</p