Timothy H. W. Chan, Calum MacAulay, Wan Lam, Stephen Lam, Kim Lonergan, Steven Jones, Marco Marra, Raymond T. Ng

1. Pool together cancer and normal libraries • Null Hypothesis: • Alternative Hypothesis Simulated Normal Pool (same size as normal samples) Simulated Cancer Pool (same size as cancer samples) Mean Sum of Squares N Observed Simulated Standard Deviation PLOT Score those >=99% confidence Permutation (Z) Score Using the Permutation Test to Analyze Lung Cancer SAGE Libraries Timothy H. W. Chan, Calum MacAulay, Wan Lam, Stephen Lam, Kim Lonergan, Steven Jones, Marco Marra, Raymond T. Ng Department of Computer Science, University of British Columbia The British Columbia Cancer Research Centre BACKGROUND RESULTS Permutation Test • Previously analyzed publicly available Breast and Brain SAGE libraries using the permutation test (Ng. et al, Frontiers of Cardiovascular Science 2003) and had some success (60% of top ranked genes for breast SAGE data were verified to be related to the neoplastic process). • BC Cancer Research Centre has produced various Lung Cancer SAGE libraries including 5 CIS (carcinoma in situ), 6 Invasive and 17 Normal libraries. • It would be interesting to use the permutation test to contrast and compare the various stages of lung cancer and search for small transcriptional changes (pathway regulators, check points, switches). • 1981 out 32,871 TAGS considered at 99% confidence failed the permutation test for Normal vs Invasive Lung Cancer. • 1887 TAGS out of 40,476 TAGS considered at 99% confidence failed the permutation test for Normal vs CIS Lung Cancer • 119 TAGS out of 20,077 TAGS considered failed the permutation test for CIS vs Invasive Lung Cancer Verification Results OBJECTIVES • To use the permutation test on normal and different stages of lung cancer (CIS and Invasive) SAGE libraries to discover candidate cancer-related genes. • To contrast and compare these two stages of lung cancer. • To demonstrate the advantages and power the permutation test holds over the T-test. METHODOLGY Data Pre-Processing • Quality of these genes is mostly dependent on criteria A and B. Following closely are criteria C and D as they are important genes in the neoplastic process • Hypotheticals or genes who have no known function did not meet any of the criteria. • * Indicates that there exists a duplicate (more than one TAG match to the same gene). 99% confidence - Output 1. Gene-to-Tag Assignment • Some tags map to more than one gene. To deal with this, the expression level of the tag is assigned to each gene the tag maps to. For instance, if tag A maps to genes 1, 2, and 3, all the genes will be assigned the tag count of tag A. Intersections of Top Ranked Genes Between the Inv. vs Norm. and CIS vs Norm. Results • The null hypothesis states that there is no difference between the mean of the normal and the cancer sample. If this were the case, it would make no difference if we “mix up the labels” of the libraries. • The alternative hypothesis states that it does make a difference and the mean of the normal and cancer sample are different. 2. Normalizing the Libraries • The low intersections suggest that CIS and Invasive stages of cancer are different. • To reduce comparison errors, the tag frequencies are normalized by scaling each library up to 300,000. Scoring and Ranking Genes Power of The Permutation Test • Higher permutation scores correspond to either greater differences between the two samples or greater differential consistencies between the two samples. • For each tissue and significant genes, rank the genes by sorting the permutation scores in descending order. CONCLUSION • With the permutation test, the number of samples required for the test to be acceptable is relatively low compared to other statistical tests (ie. T-test, chi-square). • The permutation test is great at picking out genes that are related to the neoplastic process. • It is also much better at picking out these genes than the T-test. • The permutation test between Invasive and CIS show that there are 119 Tags that are differentially expressed which suggests that the two stages of cancer have different genes turned on or off. In addition, the intersections between the top ranked genes between Normal vs Invasive And Normal vs CIS are quite low (top 200 only 25% of the Tags intersect) which also suggest differences between the 2 stages. Literature Verification • An investigation is conducted on the top ranked genes for cancer-relation using the currently available literatures on PubMed. Verification Criteria: FUTURE DIRECTIONS • Continue to use the permutation test to analyze other SAGE libraries. • The permutation also has the power to detect small transcriptional changes as long as the gene across all the libraries have a consistent Tag count. Further analysis of these low TAG count significant genes (with high permutation scores) is required as they could be vital pathway regulators, checkpoints or switches that may have led to the onset of lung cancer. • Validate genes further by experimentation. • Use validated genes for early cancer detection or derive new treatments from data.