Good science is predictive.
When trying to predict how a disease might progress, modern science loves to use genetics. Normal gene X = patient does better, mutated gene X = patient does worse.
Genotype can predict disease phenotype. But is it the best way?
Cancer is often considered a genetic disease. Mainly by those who can't stop sequencing everything.
But while cancer is caused by mutated genes, it's cellular phenotypes that ultimately kill a patient. For example, consider a mutant kinase gene. The mutant gene itself is not pathological (cancer mutations are everywhere). However, the new cellular signaling network produced by the mutant gene can wreak havoc. Deregulated signalling might cause the cell to grow, to move, to avoid the immune system. To spread into the liver and kill a patient. Cellular phenotypes functionally distinguish healthy tissue from tumours.
But how linear is the route from genotype to phenotype in cancer? We know cancer is genetically heterogenous. What we don’t know is whether this genetic chaos produces equally, less, or more chaotic cellular phenotypes. Genotype-to-phenotype linearity limits the accuracy of extrapolating from genetic data — and we don't understand it.
So rather than using genetics to predict cancer progression, why not use cellular phenotypes themselves? Why not use cell signaling? Cellular phenotypes are, after all, what defines the disease phenotype.
A precocious new paper from Fey et al., in Science Signaling does just that. The authors demonstrate JNK pathway flux can be used to predict neuroblastoma survival. Prognosis based not on up-regulation of a biomarker, or the presence of a mutated gene — but how the cell actually processes signals. How signals flow through the cancer cell. They show how a dynamic cell signaling phenotype can predict the larger disease phenotype. Not a gene in sight.
It's an awesome proof-of-principle. But the question of linearity still remains: which is better to predict disease phenotype? Genetics or cellular phenotypes?
With more eloquent studies of cellular phenotypes — maybe paid for by dropping some dreary sequencing projects — and we might get an answer.