The problem of prioritization

Dan Kobolt just threw up a great post talking about sifting through the hundreds of mutations that we’re finding in each genome to find those that actually, y’know, mean something.

we are facing two significant challenges. First, identifying the subset of variants have functional significance – separating the wheat from the chaff, if you will. Second, understanding how these functional variants contribute to a phenotype. This is soon to be the frontier in genetics and genomics.

I couldn’t agree more, and since my comment on his post got to be a little longer than I intended, I decided to reproduce it (edited slightly) over here.

I’ve been tackling similar ideas as part of my thesis work. Specifically, we’ve been developing tools that go beyond simple recurrence and look at mutational patterns that can give insight into the significance and functional role of mutations.

The easiest one to think about is mutual exclusivity. If I have part of an oncogenic pathway with two genes (A and B), then we expect that mutations in either one may be enough to disrupt the system, and there will be no selective pressure for mutation in the other. So if we assay a panel of tumors and see that half the tumors have a mutation in gene A, and the other half have a mutation in gene B, with no overlap, it’s quite likely that the mutations play similar functional roles. By detecting these patterns, we can create testable hypotheses about how genes interact, even if they’re not represented in functional databases.

It’s also important to remember that pathways can be disrupted in multiple ways. Exome sequencing to find point mutations may not be enough, as we know that copy-number alterations may lead to altered expression levels, or aberrant methylation may cause dysregulation. A integrative approach is going to be key as we move forward.

So my point is, yeah, there are absolutely people working on improving this process and doing a better job of prioritizing these mutations for in vivo validation. It’s an exciting place to be working right now, as it’s a major bottleneck preventing us from translating ubiquitous sequencing into personalized medicine. I’m glad to be working here in the thick of it.