Bias, Randomization, and Ovarian Proteomic Data: A Reply to “Producers and Consumers”

Author:

Baggerly Keith A.1,Coombes Kevin R.1,Morris Jeffrey S.1

Affiliation:

1. Department of Biostatistics, U.T. M.D. Anderson Cancer Center, Houston, Texas, USA

Abstract

Proteomic patterns derived from mass spectrometry have recently been put forth as potential biomarkers for the early diagnosis of cancer. This approach has generated much excitement, particularly as initial results reported on SELDI profiling of serum suggested that near perfect sensitivity and specificity could be achieved in diagnosing ovarian cancer. However, more recent reports have suggested that much of the observed structure could be due to the presence of experimental bias. A rebuttal to the findings of bias, subtitled “Producers and Consumers”, lists several objections. In this paper, we attempt to address these objections. While we continue to find evidence of experimental bias, we emphasize that the problems found are associated with experimental design and processing, and can be avoided in future studies.

Publisher

SAGE Publications

Subject

Cancer Research,Oncology

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1. A Rapid and Affordable Screening Tool for Early-Stage Ovarian Cancer Detection Based on MALDI-ToF MS of Blood Serum;Applied Sciences;2022-03-16

2. Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studies;Statistical Applications in Genetics and Molecular Biology;2019-05-11

3. Proteomics;Principles and Applications of Molecular Diagnostics;2018

4. Proteomics;Principles and Applications of Clinical Mass Spectrometry;2018

5. Statistical contributions to bioinformatics: Design, modelling, structure learning and integration;Statistical Modelling;2017-06-15

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