Abstract
Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants. Multi-omic profiling of candidate protein, lipid, and metabolite biomarkers is confounded by timing and fasting status of sample collection, participant demographics and treatment exposures of the study population. Contamination by hemoglobin, whether caused by hemolysis during sample preparation or underlying red cell fragility, contributes 0–10 g/L of extraneous protein to plasma, serum, and Buffy coat samples and may interfere with biomarker detection and validation. We analyzed 617 plasma, 701 serum, and 657 buffy coat samples from a 7-year longitudinal multi-omic biomarker discovery program evaluating 400+ participants with or at risk for pancreatic cancer, known as Project Survival. Hemolysis was undetectable in 93.1% of plasma and 95.0% of serum samples, whereas only 37.1% of buffy coat samples were free of contamination by hemoglobin. Regression analysis of multi-omic data demonstrated a statistically significant correlation between hemoglobin concentration and the resulting pattern of analyte detection and concentration. Although hemolysis had the greatest impact on identification and quantitation of the proteome, distinct differentials in metabolomics and lipidomics were also observed and correlated with severity. We conclude that quality control is vital to accurate detection of informative molecular differentials using OMIC technologies and that caution must be exercised to minimize the impact of hemolysis as a factor driving false discovery in large cancer biomarker studies.
Highlights
Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants
To evaluate the impact of hemolysis on biomarker discovery utilizing a multi-omics platform, we compared proteins, lipids, and metabolites identified across plasma, serum, and buffy coat samples acquired from 420 non-diseased and pancreatic cancer patients
Adaptive omic technologies such as proteomics, lipidomics, and metabolomics demonstrate tremendous promise associating the patient phenotypic with causal biology but are significantly impacted by red blood cell contamination in plasma, serum, or buffy coat
Summary
Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants. Contamination by hemoglobin, whether caused by hemolysis during sample preparation or underlying red cell fragility, contributes 0–10 g/L of extraneous protein to plasma, serum, and Buffy coat samples and may interfere with biomarker detection and validation. Hemolysis has the potential to drastically alter the observed proteome of buffy coat samples due to contamination of hemoglobin and other high-abundance proteins seen in RBC. Guidelines governing omics analysis of clinical samples have been developed over the past decade as the use of such platforms has been broadly adopted in R&D and clinical trial assessments[4,5] This includes standardized sample preparation approaches and techniques, quality controls, and the recommended size of cohorts required to ensure statistical significance of potential findings. One potentially impactful occurrence that should be included is the effect of hemolysis, which can directly contribute to both aforementioned challenges
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