High-plex protein profiling for cancer research: Maximize target selection and validation
The SomaScan® Assay profiles thousands of proteins in a 55-μL blood sample and efficiently detects low-abundance proteins in complex biological samples.
The pioneering SomaScan® Assay empowers discovery
Achieve high-plex protein analysis to reveal more biological insights and accelerate your cancer research. Identify proteins and protein networks related to the origin, proliferation and metastasis of solid tumor and blood-based cancers. Drive early discovery and validation for translational science and pre-clinical research.
The SomaScan Assay is the premier high-plex, high-throughput assay for protein profiling
Profiles thousands of different proteins from only 55 μL of plasma/serum
|Obtain the most biological insights into proteins and protein networks – simultaneously
Compatible for use with blood and other complex biological fluids and tissue
|Eliminate complex sample preparation inherent in mass spectrometry
|10-log dynamic range from femtomolar to micromolar
|Achieve sensitive detection of low-abundance proteins
~5% median coefficient of variation (CV)
|Maintain intra- and inter-assay reproducibility across samples/projects
Added value features
Learn more about the SomaScan Platform
SomaScan 11K Assay v5.0 Tech Note
The SomaScan® Platform is a powerful tool with applications in scientific research and health and wellness. This technical note provides background on the platform itself, as well as performance metrics for the SomaScan 11K Assay v5.0.
SomaScan Assay v4.1 Tech Note
The SomaScan® Platform is a powerful tool with applications in scientific research and health and wellness. This technical note provides background on the platform itself, as well as performance metrics for the SomaScan® Assay v4.1.
Pre-analytical variation assessment for more reliable results
In biomarker discovery, it is critical to assess any pre-analytical variation in order to avoid artificial bias in the intended measurements. Pre-analytical variation may arise from both avoidable and unavoidable factors, resulting in misleading data and incorrect conclusions.
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Dive deeper into how proteomics is advancing cancer research
WebinarProteomic risk scores can help identify high-risk patients and monitor short- and long-term effects of treatmentIn this 1-hour discussion, you will learn how large-scale proteomics can be leveraged for multiple applications in the field of oncology. The focus will be on 2 new avenues of oncology research. The first is using proteomic risk scores to monitor the cardiotoxic effects of anthracycline treatment and identify patients who may benefit from cardioprotective therapy. The other is developing blood-based protein tests for stratifying lung cancer susceptibility. From biomarker discovery to medicine application and the potential to inform and impact patients’ standard of care—there is a lot to learn and look forward to in oncology research using proteomics.
PosterAptamer-based analysis of plasma proteome of growing tumorsWith proteins, the presence of a tumor is more often accompanied with changes in the levels of endogenous, unmutated proteins in circulation. In this context, knowing which proteins represent the earliest markers or tumor presence would be enormously useful.
BLOGProteomic profiling for discovery of biomarkers and mechanistic insights into acute myeloid leukemia (AML)Acute myeloid leukemia (AML) is a cancer of the blood and bone marrow that is characterized by the abnormal proliferation of immature myeloid cells. It is the most common type of leukemia among the adult population that accounts for about 80% of all cases1. AML is a complex, genetically heterogeneous disease, which presents challenges for treatment. Although most patients respond to standard intensive chemotherapy, approximately two-thirds of the patients relapse within 18 months to 5 years of the initial treatment2. The bone marrow microenvironment is thought to play a significant role in mediating the persistence of malignant leukemic stem cells. However, the exact nature of bone marrow–leukemic cell interactions is not well understood.
White paperCirculating protein biomarkers are a promising avenue for predicting patient response to cancer immunotherapiesCancer Immunotherapy relies on activating or enhancing the antitumor immune response and has taken a central position in cancer treatment modalities. While offering a generally safer and more efficacious alternative to standard chemotherapy and radiotherapy, not all patients respond to immunotherapy, and combination immunotherapies increase cost of treatment and heighten the risk for toxicity-related adverse events. An understanding of the molecular factors that contribute to clinical outcomes could enable improved selection of subject cohorts; therefore, identifying predictive biomarkers of immunotherapy response has become a growing focus of immuno-oncology research.
The study of proteins is the missing ‘-omic’ in the study of cancer. Having proteomic measurements in our data gives us the strongest case for the integration of genetics, behavior and environment in improving the prediction of disease.”
Professor of Cancer Epidemiology and Prevention,
Imperial College London
In current -omics era, discovery and validation of protein biomarkers are essential for both research and clinical practice having huge impact on early cancer detection, diagnosis improvement, recurrence prevention, therapeutic response monitoring and increased survival outcome. Developing cancer risk-identifier biomarkers that aid both early detection and targeted therapy constitutes an essential aim of the oncology field.”
Learn more about SomaLogic products
The proteomics revolution is now, and SomaLogic is here to partner with you in your discoveries.
Focus your protein profiling with curated panels – designed with a selection of protein targets for drug discovery and development
See how SomaSignal® Tests for pre-analytical variation can help and how for a limited time you can receive sample tests for free!
- Ghadermarzi S, et al. Sequence-derived markers of drug targets and potentially druggable human proteins. Front Genet ID (2019 ). doi:10.3389/fgene.2019.01075