Analytical Validation of Serum Proteomic Profiling for Diagnosis of Prostate Cancer: Sources of Sample Bias

McLerran, Dale; Grizzle, William E.; Feng, Ziding; Bigbee, William L.; Bañez, Lionel L.; Cazares, Lisa H.; Chan, Daniel W.; Diaz, José I.; Izbicka, Elzbieta; Kagan, Jacob; Malehorn, David E.; Malik, Gunjan; Oelschlager, Denise K.; Partin, Alan W.; Randolph, Timothy W.; Rosenzweig, Nicole; Srivastava, Shiv; Srivastava, Sudhir; Thompson, Ian M.; Thornquist, Mark; Troyer, Dean A.; Yasui, Yutaka; Zhang, Zhen; Zhu, Liu; Semmes, O. John

doi:10.1373/clinchem.2007.091470

Cited by 114 publications

(112 citation statements)

References 28 publications

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“…Whereas earlier studies have reported that MSbased serum profiling could be used to accurately distinguish cancer from healthy or benign cases (35,36 ), the observed differences in MS profiles were due to artifacts of sample processing and selection (37,38 ). Standard operating procedures for sample collection and handling (39 ) must be implemented.…”

Section: Discussionmentioning

confidence: 99%

Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer

et al. 2010

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Background: The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls. Methods: We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set. Results: Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set. Conclusions: For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.

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Section: Discussionmentioning

confidence: 99%

Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer

et al. 2010

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“…13 Variables that may impact analytic outcomes include: 1) the type of blood collection tube and additive, 2) sample processing protocols, times and temperatures, 3) hemolysis, 4) transport conditions, 5) storage parameters (temperatures and freeze-thaw cycles). [14][15][16] These types of differences between samples have a significant impact on the stability of analytes causing deterioration in data quality. The challenge to harmonization of SOPs is to move forward with SOPs developed from the current state of the science and based on empirical evidence and not on ritual.…”

Section: Standardization and Best Practices Guidelinesmentioning

confidence: 99%

Enhancing translational research in paediatric rheumatology through standardization

et al. 2016

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“…They wrote, "Our analysis uncovered possible sources of storage time variability that arose from different collection protocols," and they concluded, "These are critical issues often overlooked in the biomarker discovery process that are likely to be the single greatest reason most biomarker discoveries fail to be validated." 17 This kind of attention to detail and candid reporting is to be encouraged. Although these types of problems are common in observational research, investigators may not routinely search for or report them.…”

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confidence: 99%

Sources of Bias in Specimens for Research About Molecular Markers for Cancer

Ransohoff

Gourlay

2010

JCO

182

129

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Claims about the diagnostic or prognostic accuracy of markers often prove disappointing when "discrimination" found between cancers versus normals is due to bias, a systematic difference between compared groups. This article describes a framework to help simplify and organize current problems in marker research by focusing on the role of specimens as a source of bias in observational research and using that focus to address problems and improve reliability. The central idea is that the "fundamental comparison" in research about markers (ie, the comparison done to assess whether a marker discriminates) involves two distinct processes that are "connected" by specimens. If subject selection (first process) creates baseline inequality between groups being compared, then laboratory analysis of specimens (second process) may erroneously find positive results. Although both processes are important, subject selection more fundamentally influences the quality of marker research, because it can hardwire bias into all comparisons in a way that cannot be corrected by any refinement in laboratory analysis. An appreciation of the separateness of these two processes-and placing investigators with appropriate expertise in charge of each-may increase the reliability of research about cancer biomarkers.

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Analytical Validation of Serum Proteomic Profiling for Diagnosis of Prostate Cancer: Sources of Sample Bias

Cited by 114 publications

References 28 publications

Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer

Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer

Enhancing translational research in paediatric rheumatology through standardization

Sources of Bias in Specimens for Research About Molecular Markers for Cancer

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