Fig. 2: Automated analysis of TILs and morphometric features correlate with outcomes and biology in skin melanoma.

A Schematic of weakly supervised annotation pipeline to train Convolutional Neural Network (CNN) models for automated tumor delineation, coupled with Tumor Infiltrating Lymphocyte (TIL) inferencing and morphometric analysis. B Sample Hematoxylin & Eosin (H&E)-stained Whole Slide Image (WSI) case input (top) and Class Activation Map output (bottom) of a representative case from The Cancer Genome Atlas Skin Cutaneous Melanoma (TCGA-SKCM) cohort; custom region of interest (melanoma) shown in brown; adipose and fibroconnective tissue shown in red and yellow, respectively. Scale bars = 2 mm. C Representative output of HoverNet/PanNuke for nuclear segmentation and classification; nuclei from neoplastic cells delineated in red, TILs in yellow. Tile length = 129 µm. D Sample distribution of TIL counts in 200 tiles classified as tumor and computed sample-level TIL score (mean and standard deviation shown in red) from 200 target tiles extracted from this representative case. E Scatter plot of case-level correlation between PHARAOH-based TIL quantification and RNA-based Lymphocyte infiltration signature score across TCGA-SKCM cohort. (R² and p-value generated by simple linear fit model). F Kaplan–Meier survival curves for TCGA-SKCM cohort split into “high” (yellow) and “low” (blue) PHARAOH-TIL scores based on the overall cohort’s median value. p-value derived from 2-sided log rank test. Shaded bands show 95% confidence intervals of the variance in survival estimates (standard deviation). G Top ranked morphometric features whose values were found to predict divergent values in the Mitotic spindle program (p < 0.05, 2-sided ANOVA). H Sample case images with low, intermediate and high activations for the feature “AreaOccupied_NucleiObjects”, showing an expected increase in nuclear density. Tiles = 256 × 256 pixels. I Volcano plot highlighting significant differences in Single Sample Gene Sets Enrichment (ssGSEA) between subgroups of cases with high and low values of the morphometric feature “AreaOccupied_NucleiObjects”. Legend is shown above plot (p-value generated by 2-sided ANOVA, no FDR). J Morphometric model of interpretable features that predict melanoma with elevated mitotic spindle activity. All relevant source data for this figure are provided as Supplementary Data files. Panels (A, J) created with Biorender.com. Diamandis, P. (2025) https://BioRender.com/c69l485.