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Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers
المؤلفون المشاركون
Schreiner, Wolfgang
Cibena, Michael
Kenn, Michael
Singer, Christian F.
Kölbl, Heinz
Tong, D.
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-27، 27ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-06
دولة النشر
مصر
عدد الصفحات
27
التخصصات الرئيسية
الملخص EN
Precision medicine for breast cancer relies on biomarkers to select therapies.
However, the reliability of biomarkers drawn from gene expression arrays has been questioned and calls for reassessment, in particular for large datasets.
We revisit widely used data-normalization procedures and evaluate differences in outcome in order to pinpoint the most reliable reprocessing methods biomarkers can be based upon.
We generated a database of 3753 breast cancer patients out of 38 studies by downloading and curating patient samples from NCBI-GEO.
As gene-expression biomarkers, we select the assessment of receptor status and breast cancer subtype classification.
Each normalization procedure is applied separately, and biomarkers are then evaluated for each patient.
Differences between normalization pipelines are quantified as percentages of patients having outcomes different for each pipeline.
Some normalization procedures lead to quite consistent biomarkers, differing only in 1-2% of patients.
Other normalization procedures—some of them have been used in many clinical studies—end up with distrusting discrepancies (10% and more).
A good deal of doubt regarding the reliability of microarrays may root in the haphazard application of inadequate preprocessing pipelines.
Several modes of batch corrections are evaluated regarding a possible improvement of receptor prediction from gene expression versus the golden standard of immunohistochemistry.
Finally, we nominate those normalization methods yielding consistent and trustable results.
Adequate bioinformatics data preprocessing is key and crucial for any subsequent statistics to arrive at trustable results.
We conclude with a suggestion for future bioinformatics development to further increase the reliability of cancer biomarkers.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kenn, Michael& Tong, D.& Singer, Christian F.& Cibena, Michael& Kölbl, Heinz& Schreiner, Wolfgang. 2020. Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers. BioMed Research International،Vol. 2020, no. 2020, pp.1-27.
https://search.emarefa.net/detail/BIM-1131602
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kenn, Michael…[et al.]. Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers. BioMed Research International No. 2020 (2020), pp.1-27.
https://search.emarefa.net/detail/BIM-1131602
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kenn, Michael& Tong, D.& Singer, Christian F.& Cibena, Michael& Kölbl, Heinz& Schreiner, Wolfgang. Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-27.
https://search.emarefa.net/detail/BIM-1131602
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1131602
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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