Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.

Tytuł:: Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.
Autorzy:: Yang Y; Department of Radiology, Harvard Medical School, Harvard University, Boston, Massachusetts, USA.
Pospisil P
Iyer LK
Adelstein SJ
Kassis AI
Źródło:: PloS one [PLoS One] 2008; Vol. 3 (11), pp. e3661. Date of Electronic Publication: 2008 Nov 06.
Typ publikacji:: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
Język:: English
Imprint Name(s):: Original Publication: San Francisco, CA : Public Library of Science
MeSH Terms:: Gene Expression Profiling*
Microarray Analysis*
Biomarkers, Tumor/*blood
Neoplasm Proteins/*genetics
Neoplasms/*diagnosis
Biomarkers, Tumor/genetics ; Breast Neoplasms/blood ; Breast Neoplasms/diagnosis ; Breast Neoplasms/genetics ; Carcinoma/blood ; Carcinoma/diagnosis ; Carcinoma/genetics ; Colonic Neoplasms/blood ; Colonic Neoplasms/diagnosis ; Colonic Neoplasms/genetics ; Databases, Genetic ; Early Diagnosis ; Female ; Gene Expression Regulation, Neoplastic ; Humans ; Lung Neoplasms/blood ; Lung Neoplasms/diagnosis ; Lung Neoplasms/genetics ; Male ; Neoplasm Proteins/blood ; Neoplasms/blood ; Neoplasms/genetics ; Neoplastic Cells, Circulating ; Ovarian Neoplasms/blood ; Ovarian Neoplasms/diagnosis ; Ovarian Neoplasms/genetics ; Pancreatic Neoplasms/blood ; Pancreatic Neoplasms/diagnosis ; Pancreatic Neoplasms/genetics ; Prostatic Neoplasms/blood ; Prostatic Neoplasms/diagnosis ; Prostatic Neoplasms/genetics ; Up-Regulation
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Substance Nomenclature:: 0 (Biomarkers, Tumor)
0 (Neoplasm Proteins)
Entry Date(s):: Date Created: 20081107 Date Completed: 20081218 Latest Revision: 20181113
Update Code:: 20240104
PubMed Central ID:: PMC2575235
DOI:: 10.1371/journal.pone.0003661
PMID:: 18987750
: Czasopismo naukowe

Pełny tekst

Background: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types.
Methodology/principal Findings: In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function.
Conclusion/significance: The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the 'omics' era.

Erratum in: PLoS ONE. 2009;4(1). doi: 10.1371/annotation/9fbf88b3-5041-4a5e-b569-bc6c0e5f9c29. Pospisil, Pavel [added].

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