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Biomark Res. 2017 Oct 17;5:30. doi: 10.1186/s40364-017-0110-y. eCollection 2017.

Assessing biological and technological variability in protein levels measured in pre-diagnostic plasma samples of women with breast cancer.

Author information

1
Department of Biomedical Informatics, Stanford University School of Medicine, Stanford, CA 93405 USA.
2
Department of Radiology, Canary Center at Stanford for Cancer Early Detection, Stanford University School of Medicine, Palo Alto, CA 94304 USA.
3
Department of Genetics, Stanford University School of Medicine, Stanford, CA 93405 USA.
4
Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305 USA.
5
Cancer Prevention Institute of California, Fremont, CA 94538 USA.
#
Contributed equally

Abstract

BACKGROUND:

Quantitative proteomics allows for the discovery and functional investigation of blood-based pre-diagnostic biomarkers for early cancer detection. However, a major limitation of proteomic investigations in biomarker studies remains the biological and technical variability in the analysis of complex clinical samples. Moreover, unlike 'omics analogues such as genomics and transcriptomics, proteomics has yet to achieve reproducibility and long-term stability on a unified technological platform. Few studies have thoroughly investigated protein variability in pre-diagnostic samples of cancer patients across multiple platforms.

METHODS:

We obtained ten blood plasma "case" samples collected up to 2 years prior to breast cancer diagnosis. Each case sample was paired with a matched control plasma from a full biological sister without breast cancer. We measured protein levels using both mass-spectrometry and antibody-based technologies to: (1) assess the technical considerations in different protein assays when analyzing limited clinical samples, and (2) evaluate the statistical power of potential diagnostic analytes.

RESULTS:

Although we found inherent technical variation in the three assays used, we detected protein dependent biological signal from the limited samples. The three assay types yielded 32 proteins with statistically significantly (p < 1E-01) altered expression levels between cases and controls, with no proteins retaining statistical significance after false discovery correction.

CONCLUSIONS:

Technical, practical, and study design considerations are essential to maximize information obtained in limited pre-diagnostic samples of cancer patients. This study provides a framework that estimates biological effect sizes critical for consideration in designing studies for pre-diagnostic blood-based biomarker detection.

KEYWORDS:

Blood plasma; Breast cancer; Immunoassay; Mass spectrometry; Protein

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