Complementary proteomic platforms: when adding the SomaScan® Assay to mass spectrometry research makes sense
Complementary proteomic platforms: when adding the SomaScan® Assay to mass spectrometry research makes sense
Identifying disease biomarkers, both in terms of pathogenic pathways and therapeutic targets, is increasingly
important for realizing the potential of personalized medicine.1,2 This involves profiling thousands of proteins within complex biologic samples.3,4 So far, mass spectrometry has been the workhorse of profiling proteins in such samples.3 However, mass spectrometry faces many challenges in studying novel proteins that may be in low abundance and that can vary widely from sample to sample.3,5
Pairing the SomaScan Assay with mass spectrometry can help overcome these barriers by measuring thousands of proteins in small volumes of biological samples with low limits of detection, a broad dynamic range, and high reproducibility.3,6-9
How the SomaScan Assay works
The SomaScan Assay is based on SOMAmer® (Slow Off-Rate Modified Aptamer) reagents, which are aptamers that are custom engineered to have enhanced shape complementarity to their targets, as well as slow off-rates for longer target binding. A universal polyanionic competitor further enhances specificity to the target protein.1,6,10
The current menu offers 7,000 unique proteins that can be measured simultaneously in a small volume of sample, with effective detection of low and highly abundant proteins over a 10-log dynamic range (fmol – μmol).6,8,9 High-throughput profiling of the full menu or a customized subset can be performed with excellent reproducibility and industry-leading coefficients of variation around 5%.8,9,11,12
Many researchers are already using the SomaScan Assay to elevate their mass spectrometry research in a
variety of ways.
Pairing the SomaScan Assay and mass spectrometry
Stem cells13 | |
---|---|
Challenge | Mass spectrometry has dynamic range limitations (difficulty detecting low expressed proteins), which poses a challenge in human embryonic and mesenchymal stem cells, where many of the targeted proteins are found in low abundance. |
Solution | Researchers compared the SomaScan Assay with mass spectrometry (MS) and RNA sequencing (RNAseq) in analyzing proteins from human embryonic and mesenchymal stem cells. |
Key findings |
|
Clinical trial for COVID-1914 | |
---|---|
Challenge | Since COVID-19 is a complex and heterogeneous condition involving multiple metabolic processes, investigating variations in the pathophysiological state of the infection can be difficult. |
Solution | Researchers used the SomaScan Assay and mass spectrometry to help identify the role of molecular mechanisms in different pathophysiological processes in COVID-19 among 73 hospitalized patients with COVID-19 and 32 negative controls. |
Key findings |
|
Cancer risk15 | |
---|---|
Challenge | The mechanism by which aspirin reduces colorectal cancer risk has not yet been fully elucidated. |
Solution |
|
Key findings |
|
These studies show just a few of the exciting discoveries that can be made when the SomaScan Assay is added
to other proteomic technologies.
References
- Kim B, Araujo R, Howard M, Magni R, Liotta LA, Luchini A. Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers. Exp Rev Proteomics. 2018;15(4):353-366. doi:10.1080/14789450.2018.1450631.
- Fiblin MR, Mehta A, Schneider AM, et al. Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions. Cell Rep Med. 2021;2(5):100287. doi:10.1016/j.xcrm.2021.100287.
- Petrera A, von Toerne C, Behler J, et al. Multiplatform approach for plasma proteomics: complementarity of Olink proximity extension assay technology to mass spectrometry-based protein profiling. J Proteome Res. 2021;20(1):751-762. doi:10.1021/acs.jproteome.0c00641.
- Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genomics. 2015;8:33. doi:10.1186/s12920-015-0108-y.
- Nakayasu ES, Gritsenko M, Piehowski PD, et al. Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation. Nat Protoc. 2021;16(8):3737-3760. doi:10.1038/s41596-021-00566-6.
- Gold L, Ayers D, Bertino J, et al. Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One. 2010;5(12):e15004. doi:10.1371/journal.pone.0015004.
- Ngo D, Sinha S, Shen D, et al. Aptamer-based proteomic profiling reveals novel candidate biomarkers and pathways in cardiovascular disease. Circulation. 2016;134(4):270-285. doi:10.1161/CIRCULATIONAHA.116.021803.
- Palstrøm NB, Matthiesen R, Rasmussen LM, Beck HC. Recent developments in clinical plasma proteomics—applied to cardiovascular research. Biomedicines. 2022;10(1):162. doi:10.3390/ biomedicines10010162.
- Jiang W, Jones JC, Shankavaram U, Sproull M, Camphausen K, Krauze AV. Analytical considerations of large-scale aptamer-based datasets for translational applications. Cancers (Basel). 2022;14(9):2227. doi:10.3390/cancers14092227.
- Lollo B, Steele F, Gold L. Beyond antibodies: new affinity reagents to unlock the proteome. Proteomics. 2014;14(6):638-644. doi:10.1002/pmic.201300187.
- Masvekar R, Wu T, Kosa P, Barbour C, Fossati V, Bielekova B. Cerebrospinal fluid biomarkers link toxic astrogliosis and microglial activation to multiple sclerosis severity. Mult Scler Relat Disord. 2019;28:34-43. doi:10.1016/j.msard.2018.11.032.
- Raffield LM, Dang H, Pratte KA, et al; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium. Comparison of proteomic assessment methods in multiple cohort studies. Proteomics. 2020;20(12):e1900278. doi:10.1002/pmic.201900278.
- Billing AM, Ben Hamidane H, Bhagwat AM, et al. Complementarity of SOMAscan to LC-MS/MS and RNA-seq for quantitative profiling of human embryonic and mesenchymal stem cells. J Proteomics. 2017;150:86-97. doi:10.1016/j.jprot.2016.08.023.
- Galbraith MD, Kinning KT, Sullivan KD, et al. Seroconversion stages COVID19 into distinct pathophysiological states. eLife. 2021;10:e65508. doi:10.7554/eLife.65508.
- Nounu A, Greenhough A, Heesom KJ, et al. A combined proteomics and Mendelian randomization approach to investigate the effects of aspirin-targeted proteins on colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2021;30(3):564-575. doi:10.1158/1055-9965.EPI-20-1176.
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