Researchers are blending tools from developmental biology with technologies such as cell sorting and CRISPR to gain fresh insight into cancer
What Anna Obenauf needed was a time machine. In 2016, Obenauf, then at Memorial Sloan Kettering Cancer Center in New York City, read a case report about a person with melanoma who, in 2011, had been given a drug that blocks a cancer-promoting form of the protein BRAF. Before treatment, the person’s torso was covered with tumours. Within weeks, the growths had disappeared. But six months later, they were back — and were resistant to the drug. The person died.
Now, researchers are expanding the tumour-barcoding toolkit to avoid destroying barcoded cells. New techniques instead enable the cells to be isolated and injected into animal models to understand drug resistance, or to be identified in tumours and then modifiedto see how the tumour microenvironment changes.
For Obenauf, there was another key consideration. Existing barcodes could help her to trace cellular lineages, but not to isolate them. So, she built her own system. In a studypublished last year, Obenauf and her colleagues created a library of some 130 million barcodes, each of which was connected to a fluorescent protein, and used them to tag a melanoma cell line so that each cell contained a unique barcode.
Using a strategy called CaTCH , the team targeted the barcodes using CRISPR–Cas9 gene editing. The researchers used a short piece of RNA to guide a modified Cas protein towards the barcode, inducing expression of a fluorescent protein gene alongside it. The resulting fluorescence provided a handle that Obenauf’s team could use to isolate those particular barcoded cells using flow cytometry.
To bridge that gap, Grüner and her colleagues generated distinctly labelled copies of a pancreatic cancer cell line and grew them in 96-well plates. Each well was treated with one of 712 compounds, and to differentiate the various groups, the team used a six-base barcode coupled to a fluorescent protein — enough to resolve 4,096 treatments . “You can’t make [the barcode] too much shorter, because if single-base mutations arise, you can’t distinguish them in a sequencer,” Grüner says.
The scientists started with a set of six peptides and chose a combination of three peptides per barcode to create a library — an approach they call six-choose-three. To detect the barcodes, the team uses a technique called multiplexed ion beam imaging . Each peptide has a corresponding antibody attached to a unique heavy-metal atom, which produces a distinct MIBI signal.
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