When you come across a very successful, middle-aged scientist jumping up and down shouting “This is going to be just amazing” you can only conclude that either the pressures of the life scientific have finally got to him and he’s flipped or there is something really remarkable going on. Thus my feeling this week when I noted the behaviour of Greg Hannon who now works at the Cancer Research Institute in Cambridge.
Probing further, it emerged that Hannon, who is collaborating with Xiaowei Zhuang at Harvard University in the ‘other’ Cambridge, has just been awarded a five-year grant of £20 million by the London-based charity Cancer Research UK as part of its Grand Challenge initiative – more than enough to get your jumping genes going.
But it’s the aim of the project rather than its monetary size that is truly astonishing and has almost a feel of science fiction about it. The plan is nothing less than to come up with an interactive virtual-reality map of breast cancers. That is, to reconstruct every cell that makes up a tumour, showing the different types of cell and what they are up to at any given time – meaning that the model will display the expression level of thousands of genes in each cell and the different proteins being made. Staggering.
What’s the point?
The project is driven by the fact that we have gradually come to realize that tumours are a complex mixture of cells (what’s been called the tumour microenvironment) and the signals that these cells send out and receive determine the extent of tumour growth and whether it can spread to other sites in the body (i.e. metastasize).
Where have we got to?
One approach to mapping what’s going on was laid out a couple of years ago by the converging studies of Rahul Satija and colleagues of the Broad Institute of MIT and Harvard and Kaia Achim et al. from labs in Heidelberg, Cambridge and Oxford using zebrafish embryos and worm brains, respectively.
The method has two parts:
- The tissue is dissociated into single cells and the power of sequencing is applied to obtain RNA sequences from each cell (revealing which genes are ‘switched on’ in that cell).
- The second step visualizes specific RNAs using tagged probes (fluorescently labeled RNAs that enter cells and bind to target RNAs molecules).
In essence a reference map is made by overlaying the intact tissue with a grid and matching a cell to a grid area by comparing expression of a number of ‘landmark’ genes with the fluorescence marker signal.
To do all this they devised a computational package that, using fewer than 100 landmark genes, maps hundreds of sequenced cells to their location in the tissue. In that arty way that scientists have, they named their package after Georges-Pierre Seurat, the French chappie who came up with the idea of painting in small dots of colour (though his weren’t fluorescent).
Cellular pointillism has just taken another step forward with Keren Bahar Halpern, Ido Amit and Shalev Itzkovitz at the Weizmann Institute of Science, Rehovot, Israel producing a cell-by-cell map of mouse liver, complete with RNA sequences from each cell. To be precise they mapped the hexagon-shaped units called lobules that are repeated to make up mammalian liver.
The shapes of things to come
So the next step for Hannon and his colleagues is an interactive map of a human tumour and, if you can’t wait, CLICK HERE to see their mock-up to give you some idea of what’s in store. In this synthetic video tumour cells are green, macrophages are blue and blood vessels are red.
So it’s warp factor 9 for Captain Hannon and his crew. It may be that the 3D images of tumours will look a bit the virtual graphics that the astrophysicists fob off on us whilst pretending they have some idea what a star’s doing umpti-zillion light years away. But in fact, rather than boldly going “where no man has gone before“, this cellular journey is better summed up by Marcel Proust “The real voyage of discovery consists not in seeking new landscapes, but in having new eyes” – the new eyes being the stunning combination of methods that permits 3D interrogation of individual cells.
Will this phase of the Grand Challenge produce overwhelming amounts of data? Undoubtedly. But, if we are to understand how living things work we have to front up to the complexity of nature. We then have to hope we are smart enough to resolve the crucial from the detail.
Satija, R. et al. (2015). Spatial reconstruction of single-cell gene expression data. Nature Biotechnology 33, 495–502.
Achim, K. et al. (2015). High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nature Biotechnology 33, 503–509.
Halpern, K. B. et al. (2017). Nature 542, 352–356.