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Turning Blood into Gold: The Wellness Chip

Larry Gold’s SomaLogic detects thousands of protein biomarkers with unprecedented sensitivity and specificity. 

By Kevin Davies 

August 2, 2011 | BOULDER, CO—Fourteen years after conceiving a tool to discover and measure protein biomarkers, Larry Gold and his colleagues at SomaLogic are poised to see their first diagnostic—a lung cancer blood test licensed to Quest Diagnostics—reach the marketplace, perhaps before the end of the year. This would be the first of a potentially extensive list of diagnostic assays under development for various cancers, cardiovascular disease, neurological disorders and neglected diseases. Eventually, they could be brought together into a single, simple blood test: the Wellness Chip. 

“We understand that longitudinal ‘omics is the ball game,” says Gold, the company’s chairman and CEO. “Whether it’s proteomics or lipidomics or transcriptomics, snapshots at time T are interesting but a series of snapshots at many times T are better for managing health.” 

Gold says his friends tease him, wondering how such a terrific hypothesis-driven scientist—he sold his former company NeXstar to Gilead in 1999 for about $550 million—is content to be data-gathering ‘omics guy?  

Gold smiles and tells them: “I have a hypothesis: if we can measure more things than you, better than you, we will learn more than you know. That’s it! That’s what all ‘omics is about. That’s why I don’t dump on genomics. But I don’t think DNA sequencing or biopsies of numerous tissues are the best measurements to detect diseases in a way that is immediate and actionable.” 

Gold says SomaLogic aims to become “a longitudinal proteomic biomarker monitoring company.”  

Blood Simple 

What could be easier than monitoring an individual’s health over time via a blood test? In a few situations, screening blood biomarkers can be as simple as measuring a single protein, such as in pregnancy (HCG) or prostate cancer (PSA). But what if the early—and treatable—presence of cancer or heart disease could be gleaned in a similar blood test, measuring a critical subset or “signature” of circulating proteins unequivocally associated with the disease? The task begins by whittling down the total number of secreted proteins in blood—the number is around 3,400, or one seventh of the human proteome—to the subset that represents a validated diagnostic.  

Using proprietary reagents called SOMAmers, custom nucleic acids that target a specific protein, SomaLogic’s current technology can simultaneously detect and quantify 1,100 human proteins (see “The Strength of SOMAmers”). “We’re a quarter of the way there,” says Gold, noting that the total number of blood proteins (including intracellular proteins released after cell death) is probably closer to 4,000. “1,100 is already an awful lot. Nobody else can do more than 20-30 at a time. For the moment, we have an opportunity to learn a lot of medicine and biology quickly. Every time we’ve added proteins to the chip, the performance gets better.” 

The “Wellness Chip” (the term is trademarked) refers to measuring all 1,100 proteins in one assay, providing information on all diseases on the same chip. Of those 1,100 proteins, Gold says one third have already turned out to be markers in various diseases or indications.  

He shows me a wall chart in which all of the current biomarkers are laid out horizontally like a bar code, with diseases grouped vertically. The key markers are color coded for each indication. Interestingly, part of the blue oncology group overlaps with the red cardiovascular disease markers, which Gold says might be indicative of inflammatory pathways. The green markers at the bottom are what Gold calls “the horse****”—pre-analytic variation largely due to sample acquisition and handling differences. 

Big Business  

Gold has assembled an experienced executive team to explore the full range of diagnostic and research applications for the SOMAmer platform. Among his key colleagues are two ex-Pfizer executives—Steve Williams (chief medical officer) and Nicholas Saccomano (chief technology officer). (Ed. Note: Saccomano was on the cover of Bio•IT World in April 2005 while Pfizer’s senior VP global research technology.)  

Mark Messenbaugh, SomaLogic’s director of corporate strategy, joined the firm three years ago, having previously worked as a lawyer and on Al Gore’s 2000 presidential election campaign. “My guy lost. I wrote a lot of those losing briefs,” he admits. While working in the non-profit world, Messenbaugh went to hear Gold speak at a local business meeting, and was instantly hooked by Gold’s vision for the future of health care. “I was smitten!” he admits. Messenbaugh followed Gold to the elevators and asked for a job, which he eventually took just as the SOMAmer technology was maturing.  

The deal with Quest Diagnostics, worth $15 million at the time, was signed in 2005. “We’ve raised a lot of money here without any revenues,” says Gold. (The first SOMAmer on the market is actually part of a “hot-start” PCR kit sold by New England Biolabs.) Now Messenbaugh and colleagues are laying out the longer-term vision. “How do we move toward the Wellness Chip?” 

Pharma customers clearly like the technology, using SOMAmers to study basic disease biology, drug effects, target discovery and selection. “We recognized that the tool is more powerful than we as a small company can ever make use of completely,” says Messenbaugh. “Pharmas can create value out of this, but how do we enable that without standing in our own way?” 

In one study with Bristol-Myers Squibb, Gold says analysis of blood samples before and after administration with an anti-angiogenesis drug candidate revealed some delayed responses. “We saw a pattern of what was coming within a month to help understand the mechanism of action,” he says. 

SomaLogic has struck deals with Japan’s Otsuka to use SOMAmers for target validation in animal models, and NEC to deliver data analysis tools and, ultimately, health information via cloud-computing services, among others. “Discovery is quite easy here,” says Messenbaugh. “We can do broad-based discovery on virtually any clinical question. So far, the successes are outnumbering failures—by a lot.” 

Messenbaugh and Gold recognize the need to stay disciplined. “This tool will be great for basic science and understanding biology,” says Messenbaugh, “but our core function is driving diagnostic tests into the market. We have to ask: Is the clinical indication of value? If not, we have to think about our resources.”  

They see a broader impact of SOMAmers for the advancement of medicine. “Could some gene be overexpressed and thus be a good target for drug development? I think there’s enormous hope for neglected diseases,” says Gold.  

“Wouldn’t it be nice if we could do proteomics on people with single-gene mutations and find something that helps understand the biology or helps with ideas about therapeutics?” SomaLogic has programs looking at ALS and Duchenne muscular dystrophy, but as Gold says, “We have to be careful not to be drawn away from our end-goal of powerful, simple, and fast diagnostics.” 

Information Model 

The release of the lung cancer test is in Quest’s hands. Says Messenbaugh: “It’s an LDT [lab-developed test].They’ll do it at the pace they consider right.” The test will enable early detection of lung cancer, providing an indication whether nodules are cancerous. Another test for pancreatic cancer has also been licensed to Quest. An ongoing challenge is to standardize the methods for blood sample collection and analysis to eliminate variability as much as possible (see “Rule of Four”). 

“One would hope that as you add more markers, you get more perfect, but there’s an asymptotic plateau,” says Gold. Having studied some 12,000 blood samples to date, SomaLogic scientists have concluded there’s a lot of redundancy in biology—many markers simply shift up and down in tandem with others. To better understand the underlying biology, Gold is learning about KEGG, GO and other pathway tools. 

Ultimately, Gold sees his business model as “an information model,” especially if one uses the term “longitudinal ‘omics.” He says: “You do your annual test, get your 1,100, 2,000, or 3,000 data points. The computer sends you a note, ‘Nice job, see you next year. We didn’t see anything.’ Or ‘Go see Dr. Finklestein, because you need your [whatever] examined.’  

“Medicine will change over the next decade: people who get sick will be able to enter the medical system more effectively than they do today, because they’ll have early, even pre-symptomatic access to real information. Nobody’s got time to think the way you do about your own health.”  

The Strength of SOMAmers

Larry Gold and Craig Tuerk invented aptamers, short oligonucleotides that can bind proteins, at the University of Colorado in 1989. The first aptamer drug, produced by Gilead after acquiring Gold’s company NeXstar in 1999, was called Macugen for the treatment of age-related macular degeneration. (The drug was successful, although Gold concedes that Genentech’s Lucentis, which targets the same receptor, is also a very good drug.)  

Shortly after Gilead bought NeXstar for about $550 million in July 1999, Gold was furloughed. But he had already started researching new uses for aptamer reagents. Gilead allowed Gold to buy back the diagnostic rights to the technology, which formed the basis for SomaLogic.  

SomaLogic developed a new class of aptamer reagents, which they call SOMAmers (the term stands for “Slow Off-rate Modified Aptamers”). SOMAmers are made of DNA-containing modified nucleotides with unique chemical and kinetic properties. Each SOMAmer contains a unique stretch of about 40 modified nucleotides, with a total library size of about 1015 different species. With so much variation to choose from, and a development process designed to select against non-specific binding, a single SOMAmer can combine the specificity of two antibodies. Gold explains: 

“Why do people do ELISA assays with two antibodies instead of one? The reason is one antibody can grab a protein, but the binding affinity (Kd) is such that the antibody will also bind to other [more abundant] proteins with lower affinity. There are 12 logs difference in protein concentrations in blood, and 4 logs difference in affinity. A monoclonal antibody’s (mAb) specificity is usually based on Kd—you might end up measuring albumin or ferritin [two prevalent proteins], which you don’t want. If you use two mAbs, you get to multiply the specificities.”  

SomaLogic has finally been able to reproduce the specificity of two antibodies in a single SOMAmer reagent, in a way that allows for multiplexing literally thousands of SOMAmers on a single array. Gold admits solving that problem was hard, but “all the biomarkers are likely to be down in the weeds, at very low concentrations,” he says. “When things weren’t working, we had to change. The previous aptamer technology wasn’t good enough. We didn’t lose heart. We kept funding coming, and it worked.” 

SOMAmers can be generated in weeks to virtually any given target. After selecting the SOMAmer to detect a specific protein, protein levels can be measured by combining samples with all the specific SOMAmers. After the free SOMAmers are discarded, the bound SOMAmers are released, producing fluorescently tagged SOMAmers ready for high-throughput detection using microarray technologies (Agilent is used the most at SomaLogic), which in turn gives a readout of the identities and concentrations of the proteins in the original sample. K.D. 

Rule of Four  

Larry Gold views SomaLogic as a longitudinal proteomic biomarker monitoring company. “You have to partner with someone interested in IT,” he says. “You’re not going to sit around with 20,000 protein measurements and expect the person to compare this year’s data to last year. It’s about handling the informatics around vectors as an aid to health and disease management.” 

“Our bioinformatics guys have developed their own tool set necessary to do blood-based proteomics. We’re committed to developing a bio-IT tool set for our end-users as well. It’s all going to be about decision support,” explains Mark Messenbaugh, SomaLogic’s head of corporate strategy. “It’s not just the array any more. It’s the dataset and the filter for the dataset. We’ve got to take that framework into the health care world.” 

“Google thinks you can get there with a set of non-physical measurements. We think the key physical measurement is proteomics,” says Gold. “The algorithm part is actually not the thing that limits the enterprise. That’s figuring out how to make the measurements. We were ready to do algorithm development 6-7 years ago. We just didn’t have the data.” 

The SomaLogic informatics team is a small unit of four staff led by Dom Zichi. “A key strength is that we’re familiar with the measurement devices. We know the pitfalls. It’s an evolving technology,” says Zichi. 

Ultimately it comes down to understanding the protein differences between cases and controls—what is real and what is an artifact resulting from how the samples were collected, handled, and stored, as well as what might be attributable to a co-morbidity and not the disease in question. Zichi’s team builds the classifiers to distinguish the two groups using various machine-learning algorithms–Bayesian classifier, random forests, clustering and multi-dimensional scaling, or PCA (principal component analysis). “There’s no one right way,” he says. In most cases, a subset of 10-15 markers “should be sufficient for most things we’re looking at.” 

An ongoing challenge is understanding the relationship between protein levels and the manner in which the blood samples are collected. Major variations can hinge on the type of tube, needle gauge, and speed of sample collection. The rate of blood flow impacts the shear on the platelets, which in turn can result in a tenfold difference in some proteins.  

“We hope this work will define a protocol for collection, a foolproof way to collect a sample. We’re still developing a best practice for sample collection,” Zichi says. “For example, PCA is helping to get a handle on which analytes move in tandem with abuses of the blood sample (cell lysis). We’re starting to understand certain signatures.” 

“The Holy Grail is to recover what the analyte levels were prior to the abuse,” says Gold. “You don’t want to [discard] the valid markers [hidden in the sample handling variability]. You’ve got to figure it out.” K.D. 

This article also appeared in the 2011 July-August issue of Bio-IT World. 

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