Genomic atlas of the human plasma proteome.

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

Interaction with both ZNRF3 and LGR4 is required for the signalling activity of R-spondin.

R-spondin proteins sensitize cells to Wnt signalling and act as potent stem cell growth factors. Various membrane proteins have been proposed as potential receptors of R-spondin, including LGR4/5, membrane E3 ubiquitin ligases ZNRF3/RNF43 and several others proteins. Here, we show that R-spondin interacts with ZNRF3/RNF43 and LGR4 through distinct motifs. Both LGR4 and ZNRF3 binding motifs are required for R-spondin-induced LGR4/ZNRF3 interaction, membrane clearance of ZNRF3 and activation of Wnt signalling. Importantly, Wnt-inhibitory activity of ZNRF3, but not of a ZNRF3 mutant with reduced affinity to R-spondin, can be strongly suppressed by R-spondin, suggesting that R-spondin primarily functions by binding and inhibiting ZNRF3. Together, our results support a dual receptor model of R-spondin action, where LGR4/5 serve as the engagement receptor whereas ZNRF3/RNF43 function as the effector receptor.

Highly multiplexed proteomic platform for biomarker discovery, diagnostics, and therapeutics.

Progression from health to disease is accompanied by complex changes in protein expression in both the circulation and affected tissues. Large-scale comparative interrogation of the human proteome can offer insights into disease biology as well as lead to the discovery of new biomarkers for diagnostics, new targets for therapeutics, and can identify patients most likely to benefit from treatment. Although genomic studies provide an increasingly sharper understanding of basic biological and pathobiological processes, they ultimately only offer a prediction of relative disease risk, whereas proteins offer an immediate assessment of "real-time" health and disease status. We have recently developed a new proteomic technology, based on modified aptamers, for biomarker discovery that is capable of simultaneously measuring more than a thousand proteins from small volumes of biological samples such as plasma, tissues, or cells. Our technology is enabled by SOMAmers (Slow Off-rate Modified Aptamers), a new class of protein binding reagents that contain chemically modified nucleotides that greatly expand the physicochemical diversity of nucleic acid-based ligands. Such modifications introduce functional groups that are absent in natural nucleic acids but are often found in protein-protein, small molecule-protein, and antibody-antigen interactions. The use of these modifications expands the range of possible targets for SELEX (Systematic Evolution of Ligands by EXponential Enrichment), results in improved binding properties, and facilitates selection of SOMAmers with slow dissociation rates. Our assay works by transforming protein concentrations in a mixture into a corresponding DNA signature, which is then quantified on current commercial DNA microarray platforms. In essence, we take advantage of the dual nature of SOMAmers as both folded binding entities with defined shapes and unique nucleic acid sequences recognizable by specific hybridization probes. Currently, our assay is capable of simultaneously measuring 1,030 proteins, extending to sub-pM detection limits, an average dynamic range of each analyte in the assay of > 3 logs, an overall dynamic range of at least 7 logs, and a throughput of one million analytes per week. Our collection includes SOMAmers that specifically recognize most of the complement cascade proteins. We have used this assay to identify potential biomarkers in a range of diseases such as malignancies, cardiovascular disorders, and inflammatory conditions. In this chapter, we describe the application of our technology to discovering large-scale protein expression changes associated with chronic kidney disease and non-small cell lung cancer. With this new proteomics technology-which is fast, economical, highly scalable, and flexible--we now have a powerful tool that enables whole-proteome proteomics, biomarker discovery, and advancing the next generation of evidence-based, "personalized" diagnostics and therapeutics.

Protein signature of lung cancer tissues.

Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan) to compare protein expression signatures of non small-cell lung cancer (NSCLC) tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.

Aptamers and the RNA world, past and present.

Aptamers and the SELEX process were discovered over two decades ago. These discoveries have spawned a productive academic and commercial industry. The collective results provide insights into biology, past and present, through an in vitro evolutionary exploration of the nature of nucleic acids and their potential roles in ancient life. Aptamers have helped usher in an RNA renaissance. Here we explore some of the evolution of the aptamer field and the insights it has provided for conceptualizing an RNA world, from its nascence to our current endeavor employing aptamers in human proteomics to discover biomarkers of health and disease.

Advances in human proteomics at high scale with the SOMAscan proteomics platform.

In 1997, while still working at NeXstar Pharmaceuticals, several of us made a proteomic bet. We thought then, and continue to think, that proteomics offers a chance to identify disease-specific biomarkers and improve healthcare. However, interrogating proteins turned out to be a much harder problem than interrogating nucleic acids. Consequently, the 'omics' revolution has been fueled largely by genomics. High-scale proteomics promises to transform medicine with personalized diagnostics, prevention, and treatment. We have now reached into the human proteome to quantify more than 1000 proteins in any human matrix - serum, plasma, CSF, BAL, and also tissue extracts - with our new SOMAmer-based proteomics platform. The surprising and pleasant news is that we have made unbiased protein biomarker discovery a routine and fast exercise. The downstream implications of the platform are substantial.

From SOMAmer-based biomarker discovery to diagnostic and clinical applications: a SOMAmer-based, streamlined multiplex proteomic assay.

Recently, we reported a SOMAmer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community.

Rapid histochemistry using slow off-rate modified aptamers with anionic competition.

Immunohistochemistry is used in both research and clinical settings to identify proteins in tissue samples. Despite the power and versatility of immunohistochemistry, limitations are imposed by the slow diffusion of antibodies through tissue and the need for secondary staining or signal amplification. Aptamers can circumvent these limitations, but their application has been hindered by nonspecific binding to cellular components, particularly in the nucleus. Here we describe unique slow off-rate modified aptamers that facilitate rapid and selective binding to target proteins in tissue. Specifically, we have developed a fluorescent aptamer that binds to the human epidermal growth factor receptor 2 (HER2) in breast carcinomas quickly and specifically, and we have shown that the slow off-rate of the aptamer from the HER2 protein contributes to its selectivity. These findings open the door to aptamer histochemistry applications in both research and clinical settings, including intraoperative diagnostics in which speed and accuracy are paramount.

Expanding the chemistry of DNA for in vitro selection.

Six new 5-position modified dUTP derivatives connected by a unique amide linkage were synthesized and tested for compatibility with the enzymatic steps of in vitro selection. Six commercially available DNA polymerases were tested for their ability to efficiently incorporate each of these dUTP derivatives during PCR. It was not possible to perform PCR under standard conditions using any of the modified dUTP derivatives studied. In contrast, primer extension reactions of random templates, as well as defined sequence templates, were successful. KOD XL and D. Vent DNA polymerases were found to be the most efficient at synthesizing full-length primer extension product, with all of the dUTP derivatives tested giving yields similar to those obtained with TTP. Several of these modified dUTPs were then used in an in vitro selection experiment comparing the use of modified dUTP derivatives with TTP for selecting aptamers to a protein target (necrosis factor receptor superfamily member 9, TNFRSF9) that had previously been found to be refractory to in vitro selection using DNA. Remarkably, selections employing modified DNA libraries resulted in the first successful isolation of DNA aptamers able to bind TNFRSF9 with high affinity.

Photoaptamer arrays applied to multiplexed proteomic analysis.

Multiplexed photoaptamer-based arrays that allow for the simultaneous measurement of multiple proteins of interest in serum samples are described. Since photoaptamers covalently bind to their target analytes before fluorescent signal detection, the arrays can be vigorously washed to remove background proteins, providing the potential for superior signal-to-noise ratios and lower limits of quantification in biological matrices. Data are presented here for a 17-plex photoaptamer array exhibiting limits of detection below 10 fM for several analytes including interleukin-16, vascular endothelial growth factor, and endostatin and able to measure proteins in 10% serum samples. The assays are simple, scalable, and reproducible. Affinity of the capture reagent is shown to be directly correlated to the limit of detection for the analyte on the array.