Most signaling responses map between distinct pathways.

SORGER/ELSEVIER

Cells often weigh conflicting signals. They do so in part, say Kevin Janes, Peter Sorger (MIT, Cambridge, MA), and colleagues, by generating extracellular signaling circuits that allow for group consensus.

The MIT group measured 19 signaling markers over 13 time points after cells were stimulated with different combinations of proapoptotic TNF and mitogenic insulin and EGF. The data were plotted and regressed in 19-dimensional space. “You take this space and try to reduce the number of dimensions while retaining important information,” says Sorger. The resulting two-dimensional graph showed that a few markers were solely related to signaling by one pathway, but most were clustered somewhere in between.

This crosstalk resulted in alternating pro- and antiapoptotic signals. First, TNF receptor activation induces shedding of TGFα, which turns on the EGF receptor. The two active receptors (TNFR and EGFR) combine to stimulate secretion of IL-1α; later the TNFR acts alone to promote secretion of an antagonist of the IL-1α receptor.

“Much to our astonishment, a large part of the crosstalk was extracellular,” says Sorger. “And it is so time variant. You can pulse for 10 minutes, then 36 hours later it is still changing.” Exactly why the cell flip-flops through pro- and antiapoptotic pathways is not clear, but based on the pathways being extracellular, “we presume that this is involved in a kind of communal decision making,” says Sorger.

“Computation was necessary to discover connections that you can't get from simple inspection,” says Sorger. These are pathways that have been well-studied by more traditional means, so “it might have been that we just rediscovered the obvious.” But, he suggests, “what [the signaling community has] now is a bewildering set of molecular data without any clear understanding of pathways.” Self-consistent datasets and computation help make sense of large amounts of information. Now the group is investigating why the same signals affect different tissues and cancer cells in different ways.

Reference:

Janes, K.A., et al.
2006
.
Cell.
124
:
1225
–1239.