Systems Tumor Immunology: It's Big Blue Beats Kasparov All Over Again

One innovative approach to cancer therapy involves isolating immune cells (tumor-infiltrating lymphocytes or TILs) from a tumor, and then trying to expand and activate them against tumor antigens in the lab. It can work, but in practice, not an efficient practice. TILs are a mixed bag of cells with all sorts of different personalities, some of which may or may or not be interested in attacking tumor cells. Some, recruited by the ever-devious tumor cells, can even work to supress the activity of the good guys. So sometimes you get a bunch of TILs that work, sometimes not.

A new paper describes a systems biology approach to tackling the complexity of TIL populations with the aim of predicting anti-tumor activity. They profiled the reactivity of a ton of TIL populations, and correlated this inforamtion with a battery of surface markers. They fed the info into some sort of machine learning algorithim, which came up with some pretty clear-cut boolean style predictive rules that a mere organic being (aka tumor immunologist) could never have possibly concieved of with a million years of deductive reasoning and experimental testing.

Check it out:
Rule 1) If the CD8⁺CD28^-CD152^- subpopulation constitutes less than 43% of the entire TIL population AND the CD94+constitutes less than 0.4% of the entire TIL population, then the TIL population is tumor-reactive.

Also, by manipulating the relative proportions of different TIL subpopulations, they could affect reactivity as predicted by their adding machine.

Wicked. Who knew an abacus could do immunology?

See: Predicting and controlling the reactivity of immune cell populations against cancer

University of Ottawa Researcher Blazing a Trail Through the Human Interactome

While the yeast protein interactome has been exhaustively mapped by a number of research groups using several approaches, the larger and more complex human interactome has yet to be conquered. Taking a step forward in this direction, a group led by University of Ottawa Prof and Ottawa Institute of Systems Biology director Daniel Figeys has published the interactomes of 338 proteins in NPG's Molecular Systems Biology. The set of 6486 interactions between 2371 proteins was mapped using a high-throughput immunoprecipitation/mass spectrometry approach. That's 1% of the human interactome down, 99 more to go!