Hye Young Choi

PURPOSE: One of the main challenges of lung cancer research is identifying patients at high risk for recurrence after surgical resection. Simple, accurate, and reproducible methods of evaluating individual risks of recurrence are needed. EXPERIMENTAL DESIGN: Based on a combined analysis of time-to-recurrence data, censoring information, and microarray data from a set of 138 patients, we selected statistically significant genes thought to be predictive of disease recurrence. The number of genes was further reduced by eliminating those whose expression levels were not reproducible by real-time quantitative PCR. Within these variables, a recurrence prediction model was constructed using Cox proportional hazard regression and validated via two independent cohorts (n = 56 and n = 59). RESULTS: After performing a log-rank test of the microarray data and successively selecting genes based on real-time quantitative PCR analysis, the most significant 18 genes had P values of <0.05. After subsequent stepwise variable selection based on gene expression information and clinical variables, the recurrence prediction model consisted of six genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, and IFI44). Two pathologic variables, pStage and cellular differentiation, were developed. Validation by two independent cohorts confirmed that the proposed model is significantly accurate (P = 0.0314 and 0.0305, respectively). The predicted median recurrence-free survival times for each patient correlated well with the actual data. CONCLUSIONS: We have developed an accurate, technically simple, and reproducible method for predicting individual recurrence risks. This model would potentially be useful in developing customized strategies for managing lung cancer.

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.

Objective To evaluate the effects of zolpidem on functional recovery in a rat model of acute ischemic stroke. Methods Following ischemic stroke procedures, 42 rats (six in each group) were randomly assigned to receive zolpidem (0.1, 0.25, 0.5, 1.0, 2.0 or 4.0 mg/kg) or normal saline administer intraperitoneally once daily for two weeks. Motor behavioural index (MBI) scores, radial 8-arm maze (RAM) test times and brain MRI scans were obtained 24 hours (Day 1) and two weeks (Day 14) post-procedure. Immunohistochemistry was performed on Day 14. Results By comparison with the normal saline group, the 0.5 and 1.0 mg/kg zolpidem groups showed statistically significant improvements in MBI scores and increased numbers of brain-derived neurotrophic factor (BDNF) stained cells over the two week dosing period. By contrast, the 4.0 mg/kg zolpidem group had statistically significantly impaired MBI scores compared with the control group. No differences among groups were found in RAM times or infarction volumes. Conclusions This study in a rat model showed that 0.5-1.0 mg/kg of zolpidem had beneficial effects on behavioural recovery by enhancing neural plasticity without causing any memory impairment in acute ischemic stroke.