Associations between spatial distribution of immune cell subsets and clinical outcomes in patients with advanced melanoma treated with immune checkpoint inhibitors: results from the PUMA challenge
Schuiveling, M.; Liu, H.; Eek, D.; Hanusov, M.; van Duin, I.; ter Maat, L. S.; van der Weerd, J. C.; van den Berkmortel, F. W. P. J.; Blank, C. U.; Breimer, G. E.; Burgers, F. H.; Boers-Sonderen, M.; van den Eertwegh, A. J. M.; de Groot, J. W.; Haanen, J. B. A. G.; Hospers, G. A. P.; Kapiteijn, E.; Piersma, D.; Simkens, L. H. J.; Westgeest, H. M.; Schrader, A. M. R.; van Diest, P. J.; Lv, J.; Zhu, Y.; Tenorio, C. G. C.; Chohan, B. S.; Eastwood, M.; Raza, S. E. A.; Torbati, N.; Meshcheryakova, A.; Mechtcheriakova, D.; Mahbod, A.; Adams, D.; Galdran, A.; Pluim, J. P. W.; Blokx, W. A. M.; Suijker
Show abstract
Patients with advanced melanoma are treated with immune checkpoint inhibitors (ICIs), yet less than 50% of patients achieve a durable response while all patients are exposed to the risk of severe side effects. Tumor-infiltrating lymphocytes (TILs) in pathology images are associated with ICI outcomes, but manual assessment is subjective. In addition, the predictive value of other immune cell subsets, including plasma cells, neutrophils, histiocytes, and melanophages, remains unclear. We organized the Panoptic segmentation of nUclei and tissue in advanced MelanomA (PUMA) challenge to evaluate whether the spatial localization of TILs and other immune cell subsets on melanoma H&E slides collected before start of treatment was associated with treatment outcomes. Algorithm performance was evaluated on a hidden test set, after which top-ranked algorithms were applied to pre-treatment metastatic whole-slide images from a large, multicenter cohort of patients with advanced melanoma treated with first-line ICIs (n=1102). Automatically quantified tissue features and immune cell subsets were then associated with clinical outcomes. Top-performing algorithms improved detection of immune cell subsets, although accuracy for rare classes remained limited. Across challenge participants, TIL density showed the most consistent association with treatment response and survival. Associations for stromal TILs were weaker, while plasma cells, histiocytes, melanophages, neutrophils, necrosis and blood vessels did not show independent associations with outcomes. Overall, the results from the PUMA challenge improved the state of the art of immune cell detection in melanoma histopathology and show that intra-tumoral lymphocytes are the immune cell subset most consistently associated with treatment response and survival. HighlightsO_LIWe organized the first melanoma-specific tissue and nuclei segmentation competition C_LIO_LIWinning algorithms were applied to 1102 whole-slide images for biomarker analysis C_LIO_LIIntra-tumoral TILs were associated with response to immune checkpoint inhibitors C_LIO_LIOther immune cell subsets showed no independent association with treatment outcomes C_LIO_LITissue segmentation on WSIs was limited by low heterogeneity in training data. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/26347935v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@13838e4org.highwire.dtl.DTLVardef@1f34a6org.highwire.dtl.DTLVardef@b9a65borg.highwire.dtl.DTLVardef@58d300_HPS_FORMAT_FIGEXP M_FIG C_FIG
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