S-Space College of Medicine/School of Medicine (의과대학/대학원) Molecular and Clinical Oncology (분자종양의학전공) Journal Papers (저널논문_분자종양의학전공)
Clinical validity of the lung cancer biomarkers identified by bioinformatics analysis of public expression data
- Kim, Bumjin; Lee, Hyun Joo; Choi, Hye Young; Shin, Youngah; Nam, Seungyoon; Seo, Gilju; Son, Dae-Soon; Jo, Jisuk; Kim, Jaesang; Lee, Jinseon; Kim, Jhingook; Kim, Kwhanmien; Lee, Sanghyuk
- Issue Date
- American Association for Cancer Research
- Cancer Res. 2007 Aug 1;67(15):7431-8.
- Adenocarcinoma/genetics/metabolism; Adolescent; Adult; Aged; Aged, 80 and over; Antigens, Neoplasm/genetics/*metabolism; Carcinoma, Non-Small-Cell Lung/genetics/metabolism; Carcinoma, Squamous Cell/genetics/metabolism; *Computational Biology; Data Interpretation, Statistical; *Databases, Genetic; Female; *Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Lung Neoplasms/genetics/*metabolism; Male; Middle Aged; Oligonucleotide Array Sequence Analysis; Reverse Transcriptase Polymerase Chain Reaction; Tumor Cells, Cultured; Tumor Markers, Biological/genetics/*metabolism
- Identification of molecular markers often leads to important clinical applications such as early diagnosis, prognosis, and drug targeting. Lung cancer, the leading cause of cancer-related deaths, still lacks reliable molecular markers. We have combined the bioinformatics analysis of the public gene expression data and clinical validation to identify biomarker genes for non-small-cell lung cancer. The serial analysis of gene expression and the expressed sequence tag data were meta-analyzed to produce a list of the differentially expressed genes in lung cancer. Through careful inspection of the predicted genes, we selected 20 genes for experimental validation using semiquantitative reverse transcriptase-PCR. The microdissected clinical specimens used in the study consisted of three groups: lung tissues from benign diseases and the paired (cancer and pathologic normal) tissues from non-small-cell lung cancer patients. After extensive statistical analyses, seven genes (CBLC, CYP24A1, ALDH3A1, AKR1B10, S100P, PLUNC, and LOC147166) were identified as potential diagnostic markers. Quantitative real-time PCR was carried out to additionally assess the value of the seven identified genes leading to the confirmation of at least two genes (CBLC and CYP24A1) as highly probable novel biomarkers. The gene properties of the identified markers, especially their relationship to lung cancer and cell signaling pathway regulation, further suggest their potential value as drug targets as well.
- 0008-5472 (Print)
- Files in This Item: There are no files associated with this item.