title: Discovery of prognostic biomarkers for predicting lung cancer metastasis using microarray and survival data.
abstract: BACKGROUND
  Few studies have investigated prognostic biomarkers of distant metastases of lung cancer. One of the central difficulties in identifying biomarkers from microarray data is the availability of only a small number of samples, which results overtraining. Recently obtained evidence reveals that epithelial-mesenchymal transition (EMT) of tumor cells causes metastasis, which is detrimental to patients' survival.
  
  
  RESULTS
  This work proposes a novel optimization approach to discovering EMT-related prognostic biomarkers to predict the distant metastasis of lung cancer using both microarray and survival data. This weighted objective function maximizes both the accuracy of prediction of distant metastasis and the area between the disease-free survival curves of the non-distant and distant metastases. Seventy-eight patients with lung cancer and a follow-up time of 120 months are used to identify a set of gene markers and an independent cohort of 26 patients is used to evaluate the identified biomarkers. The medical records of the 78 patients show a significant difference between the disease-free survival times of the 37 non-distant- and the 41 distant-metastasis patients. The experimental results thus obtained are as follows. 1) The use of disease-free survival curves can compensate for the shortcoming of insufficient samples and greatly increase the test accuracy by 11.10%; and 2) the support vector machine with a set of 17 transcripts, such as CCL16 and CDKN2AIP, can yield a leave-one-out cross-validation accuracy of 93.59%, a test accuracy of 76.92%, a large disease-free survival area of 74.81%, and a mean survival prediction error of 3.99 months. The identified putative biomarkers are examined using related studies and signaling pathways to reveal the potential effectiveness of the biomarkers in prospective confirmatory studies.
  
  
  CONCLUSIONS
  The proposed new optimization approach to identifying prognostic biomarkers by combining multiple sources of data (microarray and survival) can facilitate the accurate selection of biomarkers that are most relevant to the disease while solving the problem of insufficient samples.
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. hlhuang@mail.nctu.edu.tw.|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan. hlhuang@mail.nctu.edu.tw.
authors.forename: Hui-Ling
authors.initials: HL
authors.lastname: Huang
authors.affiliation: Division of Thoracic Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan. wuyc@vghtpe.gov.tw.
authors.forename: Yu-Chung
authors.initials: YC
authors.lastname: Wu
authors.affiliation: Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan. sulijen@ncu.edu.tw.
authors.forename: Li-Jen
authors.initials: LJ
authors.lastname: Su
authors.affiliation: Institute of Molecular Medicine and Bioengineering, National Chiao Tung University, Hsinchu, Taiwan. woodstock_ivy@hotmail.com.
authors.forename: Yun-Ju
authors.initials: YJ
authors.lastname: Huang
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. phaznexus@hotmail.com.
authors.forename: Phasit
authors.initials: P
authors.lastname: Charoenkwan
authors.affiliation: Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan. wenurea@yahoo.com.tw.
authors.forename: Wen-Liang
authors.initials: WL
authors.lastname: Chen
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. huachinlee@g2.nctu.edu.tw.|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan. huachinlee@g2.nctu.edu.tw.
authors.forename: Hua-Chin
authors.initials: HC
authors.lastname: Lee
authors.affiliation: Department of Computer Science, Tunghai University, Taichung, Taiwan. cchu@thu.edu.tw.
authors.forename: William Cheng-Chung
authors.initials: WC
authors.lastname: Chu
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. syho@mail.nctu.edu.tw.|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan. syho@mail.nctu.edu.tw.
authors.forename: Shinn-Ying
authors.initials: SY
authors.lastname: Ho
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics / Q000401:mortality / Q000556:secondary*; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D018287:Carcinoma, Large Cell / Q000235:genetics / Q000401:mortality / Q000556:secondary*; D002294:Carcinoma, Squamous Cell / Q000235:genetics / Q000401:mortality / Q000556:secondary*; D058750:Epithelial-Mesenchymal Transition; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics / Q000401:mortality / Q000473:pathology*; D008297:Male; D046228:Microarray Analysis; D009367:Neoplasm Staging; D011379:Prognosis; D011446:Prospective Studies; D015398:Signal Transduction; D015996:Survival Rate
chemical_list: D014408:Biomarkers, Tumor