| Title |
Methodological requirements for valid tissue-based biomarker studies that can be used in clinical practice
|
|---|---|
| Published in |
Virchows Archiv, February 2014
|
| DOI | 10.1007/s00428-013-1531-0 |
| Pubmed ID | |
| Authors |
Lawrence D. True |
| Abstract |
Paralleling the growth of ever more cost efficient methods to sequence the whole genome in minute fragments of tissue has been the identification of increasingly numerous molecular abnormalities in cancers--mutations, amplifications, insertions and deletions of genes, and patterns of differential gene expression, i.e., overexpression of growth factors and underexpression of tumor suppressor genes. These abnormalities can be translated into assays to be used in clinical decision making. In general terms, the result of such an assay is subject to a large number of variables regarding the characteristics of the available sample, particularities of the used assay, and the interpretation of the results. This review discusses the effects of these variables on assays of tissue-based biomarkers, classified by macromolecule--DNA, RNA (including micro RNA, messenger RNA, long noncoding RNA, protein, and phosphoprotein). Since the majority of clinically applicable biomarkers are immunohistochemically detectable proteins this review focuses on protein biomarkers. However, the principles outlined are mostly applicable to any other analyte. A variety of preanalytical variables impacts on the results obtained, including analyte stability (which is different for different analytes, i.e., DNA, RNA, or protein), period of warm and of cold ischemia, fixation time, tissue processing, sample storage time, and storage conditions. In addition, assay variables play an important role, including reagent specificity (notably but not uniquely an issue concerning antibodies used in immunohistochemistry), technical components of the assay, quantitation, and assay interpretation. Finally, appropriateness of an assay for clinical application is an important issue. Reference is made to publicly available guidelines to improve on biomarker development in general and requirements for clinical use in particular. Strategic goals are formulated in order to improve on the quality of biomarker reporting, including issues of analyte quality, experimental detail, assay efficiency and precision, and assay appropriateness. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 2% |
| Spain | 1 | 2% |
| Denmark | 1 | 2% |
| Unknown | 45 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 29% |
| Student > Ph. D. Student | 9 | 19% |
| Other | 6 | 13% |
| Student > Master | 6 | 13% |
| Student > Bachelor | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 5 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 38% |
| Agricultural and Biological Sciences | 9 | 19% |
| Biochemistry, Genetics and Molecular Biology | 7 | 15% |
| Engineering | 4 | 8% |
| Psychology | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 7 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 February 2014.
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#18,363,356
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Outputs from Virchows Archiv
#1,529
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#229,649
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Outputs of similar age from Virchows Archiv
#27
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