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PMID: 16540643 Published · ppublish English Journal Article

Common cancer biomarkers.

Cancer research ·Vol. 66 ·No. 6 ·2006-03-15 ·Pages 2953-61

Basil CF, Zhao Y, Zavaglia K, Jin P, Panelli MC, Voiculescu S, Mandruzzato S, Lee HM, Seliger B, Freedman RS, Taylor PR, Hu N, Zanovello P, Marincola FM, Wang E

Abstract

There is an increasing interest in complementing conventional histopathologic evaluation with molecular tools that could increase the sensitivity and specificity of cancer staging for diagnostic and prognostic purposes. This study strove to identify cancer-specific markers for the molecular detection of a broad range of cancer types. We used 373 archival samples inclusive of normal tissues of various lineages and benign or malignant tumors (predominantly colon, melanoma, ovarian, and esophageal cancers). All samples were processed identically and cohybridized with an identical reference RNA source to a custom-made cDNA array platform. The database was split into training (n = 201) and comparable prediction (n = 172) sets. Leave-one-out cross-validation and gene pairing analysis identified putative cancer biomarkers overexpressed by malignant lesions independent of tissue of derivation. In particular, seven gene pairs were identified with high predictive power (87%) in segregating malignant from benign lesions. Receiver operator characteristic curves based on the same genes could segregate malignant from benign tissues with 94% accuracy. The relevance of this study rests on the identification of a restricted number of biomarkers ubiquitously expressed by cancers of distinct histology. This has not been done before. These biomarkers could be used broadly to increase the sensitivity and accuracy of cancer staging and early detection of locoregional or systemic recurrence. Their selective expression by cancerous compared with paired normal tissues suggests an association with the oncogenic process resulting in stable expression during disease progression when the presently used differentiation markers are unreliable.

MeSH Terms
Biomarkers, Tumor/biosynthesis,genetics Cluster Analysis Gene Expression Regulation, Neoplastic Humans Neoplasms/genetics,metabolism Oligonucleotide Array Sequence Analysis Predictive Value of Tests Sensitivity and Specificity Up-Regulation
Chemicals
Biomarkers, Tumor
Authors & Affiliations
15 authors, click to expand affiliations / ORCID
Basil Christopher F
Department of Transfusion Medicine, Warren G. Magnuson Clinical Center, National Cancer Institute, NIH, Bethesda, Maryland 20892-1184, USA.
Zhao Yingdong
Zavaglia Katia
Jin Ping
Panelli Monica C
Voiculescu Sonia
Mandruzzato Susanna
Lee Hueling M
Seliger Barbara
Freedman Ralph S
Taylor Phil R
Hu Nan
Zanovello Paola
Marincola Francesco M
Wang Ena
Article Info
Journal
Cancer research
Abbr.
Cancer Res
ISSN
0008-5472
Published
2006-03-15
Pages
2953-61
Language
English
Region
United States
NLM ID
2984705R
Subset
IM
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