Thursday, September 28, 2017
Is it finally time to revisit biomarker discovery in plasma proteomics?!?
There are facilities I've been to where people worry about saying "biomarker discovery" out loud. Where the impressions from the fleets of FT-ICRs still remain indented in the floors...and 6 cars fill lots that could hold 600....
We underestimated the problem. We underestimated the matrix. We didn't have enough speed, our separations were too primitive, and -- especially this -- we didn't have the dynamic range. I'm saying this all in past tense...cause this is the real question....
...and this great new open review tries to tackle this question head on!
The review starts off with some very good perspective. We all know the dynamic range of proteins in plasma is 10 or 11 orders, right? But, honestly, what does that mean in relation to disease states and current biomarkers? This is addressed very well here.
Okay -- another cool thing in the paper is the literature analysis, the rise of published proteomics studies that just keeps going versus the plasma proteomics biomarkers studies that went way up and then went way down. I think you could directly correlate that graph with the parking lot(s) I mentioned earlier!
I mentioned above that we didn't have the dynamic range. This is only partly true. It is more accurate to say -- we didn't have the dynamic range per unit time. I have a good friend who does incredibly deep analysis of samples. She gets coverage of her samples on par with anything we see in the literature today on today's newest instruments -- and she's been doing it for years with little change in her instruments and methods. However...she may spend 1-2 months of analysis on a single sample. Multiple protein extraction and digestion techniques, 2D-offline fractionation, that sort of thing. We've always been able to do that stuff...eventually....but now we have dynamic range / unit time!
This is where this review goes from reviewing the history of plasma biomarker proteomics -- to providing the blueprints we might use and changes we'll need to initiate if it turns out we're finally there. I especially like the grouping of the strategies into 2 clear groups, triangular and rectangular and I plan to add them to my terminology list.
Are we there yet? Maybe? At the very least, we're a whole lot closer than we've ever been, but there's definitely some work ahead still.
Loosely linked side note/foot note: I just learned recently about Eroom's law. It's a play on Moore's law (that we'll double computer power every 2 years or whatever). Eroom's Law is the opposite. It states that each new drug discovery will cost more and will take longer than the last one. This was based on observations from the pharmaceutical industry and there are lots of thoughts on the causes. One leading theory is the tendency for companies to expand and continuously add non-scientific staff like management, administrators and HR to "support" the scientific development. I've also seen it thrown out there that as a company expands it becomes commonplace to bring in outside thinkers from other industries and this may contribute.
It turns out that the fictional(?) parking lot I mentioned above had 30 spaces for the scientists and 569 spaces for the managers, administrators, marketing and human resources people and, of course, 1 for the hot shot executive bringing in all the freshest ideas from AOL...maybe our technological limitations weren't 100% of the problem...