High-Plex Predictive Marker Discovery for Melanoma Immunotherapy-Treated Patients Using Digital Spatial Profiling.
IF: 13.801
Cited by: 62


Protein expression in formalin-fixed, paraffin-embedded tissue is routinely measured by IHC or quantitative fluorescence (QIF) on a handful of markers on a single section. Digital spatial profiling (DSP) allows spatially informed simultaneous assessment of multiple biomarkers. Here we demonstrate the DSP technology using a 44-plex antibody cocktail to find protein expression that could potentially be used to predict response to immune therapy in melanoma.Experimental Design: The NanoString GeoMx DSP technology is compared with automated QIF (AQUA) for immune marker compartment-specific measurement and prognostic value in non-small cell lung cancer (NSCLC). Then we use this tool to search for novel predictive markers in a cohort of 60 patients with immunotherapy-treated melanoma on a tissue microarray using a 44-plex immune marker panel measured in three compartments (macrophage, leukocyte, and melanocyte) generating 132 quantitative variables. The spatially informed variable assessment by DSP validates by both regression and variable prognostication compared with QIF for stromal CD3, CD4, CD8, CD20, and PD-L1 in NSCLC. From the 132 variables, 11 and 15 immune markers were associated with prolonged progression-free survival (PFS) and overall survival (OS). Notably, we find PD-L1 expression in CD68-positive cells (macrophages) and not in tumor cells was a predictive marker for PFS, OS, and response. DSP technology shows high concordance with QIF and validates based on both regression and outcome assessment. Using the high-plex capacity, we found a series of expression patterns associated with outcome, including that the expression of PD-L1 in macrophages is associated with response.



MeSH terms

Antineoplastic Agents, Immunological
Biomarkers, Tumor
Fluorescent Antibody Technique
Lymphocytes, Tumor-Infiltrating
Molecular Diagnostic Techniques
Molecular Targeted Therapy
Proportional Hazards Models
Tissue Array Analysis
Treatment Outcome


Toki, Maria I
Merritt, Christopher R
Wong, Pok Fai
Smithy, James W
Kluger, Harriet M
Syrigos, Konstantinos N
Ong, Giang T
Warren, Sarah E
Beechem, Joseph M
Rimm, David L

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