BEHAV3D Tumor Profiler pipeline.

Schematic representation of the workflow showing data preparation, input and outputs in each of the three modules. The programmatic processing is represented with a yellow background a, Time-lapse image processing and preparation, based on segmentation and tracking of tumor and labelled TME cells. Upload to Google Drive is optional but recommended to work in the Google Colab framework. b, Heterogeneity Module provides distinct behavioral clusters for DMG cells, and relates them to dynamic features and provides a back-projection of the tracked cells. c, d, Optional modules, additional to the Heterogeneity module. c, Large-scale phenotyping module combines TME large-scale information with DMG behavioral profiling to further depict population frequencies in distinct TME regions. d, Small-scale phenotyping module combines TME small-scale information with DMG behavioral profiling to depict how the cellular environment can influence tumor cell behavior.

Behavioral profiling of DMG cells with BEHAV3D-TP heterogeneity module.

a, Representative intravitally imaged position showing DMG cells tracked relative to tumor Edge (left panel). Tracks were classified according to DMG behavior (right, color coded by cluster). Representative of n = 18 independent positions. b, UMAP plot showing seven color-coded DMG cell behavioral clusters identified by BEHAV3D-TP. Each datapoint represents one T cell track. c, Representative intravitally imaged positions and enlarged sections for showcasing distinct DMG behavioral clusters Invading (yellow), Retreating (green), Erratic (dark purple) and Static (light purple) through the time series. n = 18 independent experiments. Scale bars 10µm. d, Heatmap depicting relative values of DMG cell features indicated for each cluster, named according to their most distinct characteristics. Arbitrary units in respect to maximal and minimal values for each feature. Bubble size according to significance levels, all features represented have a significance level of P < 0.001 (***): mean_displ2, mean squared displacement; speed; delta displacement; displacement length; persistence; invasion. P-valuves represent the significance of differences across clusters tested through ANOVA for each feature. e, f, UMAP representation of DMG cells’ velocity relative to the tumor edge(µm) (e) and speed (µm/h) (f). Each datapoint represents one T cell track and is colored following a color gradient. For each feature colors represent the mean DMG track values.

Mapping distinct DMG behavioral patterns to distinct TME regions.

a, Overview of the large-scale TME region phenotyping workflow. After IVM imaging session, the tissue is fixed and stained and then analyzed using mLSR-3D. CytoMAP Spatial Analysis Toolbox is used to identify distinct large-scale regions, that are subsequently matched to IVM imaging dataset. b, Representative fixed multispectral image of a mLSR3D imaged DMG tumor and zoomed-in images of TME large-scale regions: Void (blue outline), TAMM/vascularized (red outline) and TAMM/Oligo (yellow outline). DMG nuclei (blue), CD31 (pink), Olig2 (purple), and Iba1 (yellow) are represented on the imaged. Scale bars, 100 µm (overview), 30 µm (zoomed-in regions). c, 3D multispectral image DMG cell rendering color-coded per large TME region: Void (blue), TAMM/Oligo (yellow) and TAMM/vascularized (red) (left). Regions were mapped on intravital imaging data (right). d, DMG single-cell behavioral cluster frequencies among the TME large-scale regions identified with CytoMAP. Slow retreating, P < 0.05; Static, P < 0.05; Invading, P < 0.05. P-values represent the significance of differences across TME regions tested through ANOVA for each behavioral cluster.

The BEHAV3D-TP small-scale phenotyping correlates DMG behavioral profiles with microenvironmental composition at a single-cell resolution.

a, Overview of the small-scale TME phenotyping module. During IVM imaging, information about spatial distribution of SR101+ (purple), CD20r+ (purple) and CD31+ (red) cells is collected and processed by the BEHAV3D-TP small-scale phenotyping module. Single DMG cell spatial TME features like distance to its neighbors, number of cells in a radius or minimal distance to a cell type were measured. b, Heatmap depicting DMG cell small-scale niches’ features across distinct DMG behavioral clusters. Arbitrary units in respect to maximal and minimal values for each feature. Bubble size according to significance levels, from smallest (P < 0.05 (**)) to medium (P < 0.01 (**)) to biggest (P < 0.001 (***)): dist_10_cell, Distance to nearest 10 cells, P < 0.01 (**); n_SR101, number of SR101 cells, P < 0.05 (*); min_SR101, minimal distance to a SR101 cell, P < 0.05 (*); n_CD20r, number of CD20r cells, P < 0.05 (*); min_Cd20r, minimal distance to a CD20r cell, P < 0.01 (**); min_BV_dist, minimal distance to a Blood vessel, P < 0.001 (***). P-values represent the significance of differences across clusters tested through ANOVA for each feature. c, e, Boxplot depicting the Minimal distance to a CD20r+ TAMM (µm) (c) and the Minimal distance to a blood vessel (µm) (e) across DMG behavioral clusters. c, Invading versus Erratic, P < 0.01 (**); Invading versus Slow, P < 0.05 (*). e, Static versus Erratic, P < 0.01 (**); Static versus Retreating, P < 0.001 (***); Static versus Invading, P < 0.001 (***); Slow versus Retreating, P < 0.1 (·); Slow invading versus Retreating, P < 0.1 (·); Slow versus Invading, P < 0.1 (·); Slow invading versus Invading, P < 0.1 (·). d, Fixed multispectral image showing the movement of DMG cells (grey) relative to CD20r+ TAMM (blue) and the Tumor core. The trajectories show a path from the initial (blue) to the final position (red). Scale bar, 10 µm. f, Time lapse multispectral images (left to right) showing the DMG cells (blue) displacement along CD31 blood vessel (purple) away from the tumor edge. Scale bars, 30 µm.