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Single-Cell Analysis Zooms in on Melanoma

, by Amy E. Blum

Single breast cancer cell and microenviornment visualized by transparent tumor tomography.

Credit: National Cancer Institute

Not all tumor cells are made equal. Variation within the complex ecosystem of a tumor may explain why targeted treatments benefit some patients more than others, and new technologies now allow researchers to look closely at the role of each component of a tumor. These methods, collectively called single-cell analysis, promise to bring important new insights into precision medicine.  

A Closer Look into Tumor Relapse

In a new study published in Scienceresearchers from the Broad Institute employed a single-cell sequencing technique to analyze RNA expression in 4,645 individual cells from 19 melanoma tumors. The analysis revealed that the simultaneous expression of two different gene expression programs within the same tumor affected therapeutic resistance and relapse.

Previous studies utilizing bulk sequencing have found that melanoma tumors characterized by expression of the AXL gene are more likely to relapse after targeted therapy than tumors with an MITF expression program. By analyzing MITF versus AXL expression programs with single cell RNA sequencing, the researchers found that tumors marked by high MITF expression also contained a subset of cells characterized by AXL, forming a continuum of gene expression in each tumor.

Further, the number of single cells exhibiting the AXL expression program increased after treatment with MAPK inhibitors in melanoma patients and in cell lines. These findings strongly suggest that AXL expression may cause melanoma relapse, even in tumors that were previously characterized as MITF tumors by bulk sequencing.

Discovering the Tumor Ecosystem

The study also utilized single cell RNA sequencing to identify potential contributing factors to immunotherapeutic response. By analyzing individual T-cells in the microenvironment, which are important in fighting melanoma, the researchers identified a set of genes that distinguishes T-cells capable of mounting an effective response from those that are exhausted. This suggests that profiling individual T-cells may help predict patient responses to targeted immunotherapy.

These novel insights into individual melanoma cells not only reveal key genomic and clinical attributes of melanoma, but recommend single-cell methods as important tools for future cancer genomic research. As the field of single-cell analysis matures, these studies may discern which tumor cells are involved in mediating drug responses and aid in the development of therapies that target each component of the tumor ecosystem.

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