Novel Spatial Gene-Signature Approach May Help to Predict Immunotherapy Outcomes in Patients With Melanoma

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Researchers have demonstrated that spatial gene signatures may enhance the prediction of immunotherapy outcomes in patients with melanoma, according to a recent study published by Aung et al in Clinical Cancer Research. The current gene signatures used to predict immunotherapy outcomes may lack accuracy as a result of their inability to account for the spatial distribution of cells within tumors and their surrounding microenvironment.

Study Methods and Results

In the recent study, the researchers used Digital Spatial Profiling of Whole Transcriptome Atlas technology to collect gene-expression data from three distinct cellular compartments—CD68-positive macrophages, CD45-positive leukocytes, and S100B-positive tumor cells—across 55 melanoma specimens treated with immune checkpoint inhibitors. They then developed a computational pipeline to derive compartment-specific gene signatures and evaluate whether the integration of spatial information could enhance patient stratification.

The researchers found that their novel method performed well in predicting how patients would respond to immune checkpoint inhibitors. Among the three compartment-specific signatures, the tumor signature was the most accurate in an independent validation group of 45 patients. This signature included eight genes—five of which indicated a positive response to treatment and three of which indicated resistance to treatment. Further, the S100B tumor spatial signature outperformed previously published gene signatures that did not consider spatial information.


The findings indicated that spatially defined signatures, which use detailed information about the tumor and its microenvironment, may provide more accurate predictions of treatment outcomes. By focusing on the spatial aspects of gene expression within tumor tissue samples, the researchers provided oncologists with a refined method to predict how patients may respond to immune checkpoint inhibitors.

“[T]he translational implications of our analysis pipeline could extend beyond melanoma, potentially optimizing immunotherapeutic approaches in other cancer types,” concluded the study authors.

The researchers hope to conduct prospective clinical assessments of these spatially defined melanoma compartment signatures to validate their utility in clinical practice.

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The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.