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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
SH2D1A/SAP Reflects Immune Activation in Melanoma and Is a Superior Predictive Biomarker of Immune Checkpoint
Federico Fusco1, Johannes Weigel1, Marius Schliemann2
1Institute of Pathology, School of Medicine and Health, German Cancer Consortium, Technical University of Munich, Munich, Germany.
Abstract:
Immune checkpoint inhibitors (ICIs) have markedly improved outcomes in malignant melanoma, yet accessible, tissue-based predictive biomarkers of response remain limited. PD-L1 expression, which remains widely used, offers some prognostic value but performs poorly at low expression levels. We performed liquid chromatography-mass spectrometry proteomic profiling on 185 melanoma samples, including 52 pretreatment samples from ICI responders and nonresponders. Differential expression and pathway analyses identified a 73-protein immune activation signature correlating with ICI response. Within this immune context, SH2D1A (SAP), a regulator of T- and natural killer-cell cytotoxicity, emerged as a top candidate biomarker. Internal immunohistochemical validation confirmed its strong predictive accuracy (area under the receiver operating characteristic curve: 0.93; sensitivity: 88%; specificity: 91%) in distinguishing responders from nonresponders, outperforming PD-L1, CD3, and CD8. Notably, SH2D1A retained its predictive power in PD-L1-low tumors (combined positive score < 10), suggesting clinical use in which the current markers fall short. Independent validation in an external tissue microarray cohort revealed attenuated predictive performance, likely reflecting the impact of intratumoral heterogeneity, as further suggested by whole-slide validation. Nevertheless, SH2D1A remained significantly enriched in tumors that responded to ICIs and was associated with improved survival outcomes, outperforming CD3, CD8, and PD-L1. In conclusion, these results suggest that SH2D1A provides information beyond established immune infiltration- and exhaustion-related markers, supporting further investigation of its potential role in biomarker-guided prediction of ICI response in melanoma.

