Telltale number

Not all cancer cells are created equal. Only a relatively rare subset of tumor cells typically drive malignancies and seed metastases. To truly snuff out a cancer, then, drugs must target such stem-like cells. In a January paper in Science, Ludwig Stanford investigators led by Aaron Newman reported an elegant way to identify stem cells in healthy tissues and their counterparts in tumors. They first confirmed that the number of genes expressed by a cell reliably correlates with the developmental state of that cell: the more genes expressed, the less differentiated and more stem-like that cell is likely to be. They then applied that insight and single-cell profiling of RNA—which carries information encoded by DNA during gene expression—to create an algorithm named CytoTRACE that’s based on the number of genes expressed by a cell and the number of RNA copies per gene. Aaron and his colleagues applied CytoTRACE to triple negative breast cancer, which is notoriously difficult to treat. In homing in on stem-like cells in such tumors, CytoTRACE identified several known markers of triple-negative breast cancer and at least one novel marker that seems to be a prime target for future drug development.

This article appeared in the August 2020 issue of Ludwig Link. Click here to download a PDF (2 MB).


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