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Open AccessJournal ArticleDOI

Phases of Biomarker Development for Early Detection of Cancer

TLDR
The purpose of this commentary is to define a formal structure to guide the process of biomarker development and to provide a checklist of issues that should be addressed at each phase of development before proceeding to the next.
Abstract
Recent developments in such areas of research as geneexpression microarrays, proteomics, and immunology offer new approaches to cancer screening (1). The surge in research to develop cancer-screening biomarkers prompted the establishment of the Early Detection Research Network (EDRN) by the National Cancer Institute (2). The purpose of the EDRN is to coordinate research among biomarker-development laboratories, biomarker-validation laboratories, clinical repositories, and population-screening programs. By coordination of research efforts, the hope is to facilitate collaboration and to promote efficiency and rigor in research. With the goals of the EDRN in mind, the purpose of this commentary is to define a formal structure to guide the process of biomarker development. We categorize the development into five phases that a biomarker needs to pass through to produce a useful population-screening tool. The phases of research are generally ordered according to the strength of evidence that each provides in favor of the biomarker, from weakest to strongest. In addition, the results of earlier phases are generally necessary to design later phases. Therapeutic drug development has had such a structure in place for some time (3). The clinical phases of testing a new cancer drug are as follows: phase 1, determinations of toxicity, pharmacokinetics, and optimal dose levels; phase 2, determinations of biologic efficacy; and phase 3, definitive controlled trials of effects on clinical endpoints. For each phase, guidelines exist for subject selection, outcome measures, relevant comparisons for evaluating study results, and so forth. Although deviations are common, the basic structure facilitates coherent, thorough, and efficient development of new therapies. A phased approach has also been proposed for prevention trials (4,5). In a similar vein, we hope that our proposed guidelines or some related construct will facilitate the development of biomarker-based screening tools for early detection of cancer. Although deviations from these guidelines may be necessary in specific applications, our proposal will, at the minimum, provide a checklist of issues that should be addressed at each phase of development before proceeding to the next.

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Citations
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Biomarkers in cancer staging, prognosis and treatment selection.

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The power and the promise of DNA methylation markers

TL;DR: The past few years have seen an explosion of interest in the epigenetics of cancer as a consequence of both the exciting coalescence of the chromatin and DNA methylation fields, and the realization thatDNA methylation changes are involved in human malignancies.
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Biomarkers of cardiovascular disease: molecular basis and practical considerations.

TL;DR: This review provides an overview of the molecular basis of biomarker discovery and selection and the practical considerations that are a prerequisite to their clinical use.
References
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Journal ArticleDOI

Comparison of discrimination methods for the classification of tumors using gene expression data

TL;DR: Different discrimination methods for the classification of tumors based on gene expression data include nearest-neighbor classifiers, linear discriminant analysis, and classification trees, which are applied to datasets from three recently published cancer gene expression studies.
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Human neoplasms elicit multiple specific immune responses in the autologous host.

TL;DR: The unexpected frequency of human tumor antigens indicates that human neoplasms elicit multiple specific immune responses in the autologous host and provides diagnostic and therapeutic approaches to human cancer.
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Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry.

TL;DR: The overall history and recent advances in surface enhanced laser desorption/ionization‐time of flight‐mass spectrometry (SELDI‐TOF‐MS) technology is reviewed and its application to functional genomics and biomarker discovery is discussed and exemplified by elucidating a biomarker candidate for prostatic carcinoma.
Journal ArticleDOI

Analyzing a portion of the ROC curve.

TL;DR: The area under the ROC curve is a common index summarizing the information contained in the curve when comparing two ROC curves, though, problems arise when interest does not lie in the entire range of false-positive rates.
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