S' Dan Li

1
S. Dan Li

• Current position Senior Research Scientist,
  Informatics, Eli Lilly and Company
• Education
• Ph.D. (1999) Cell Molecular Biology, University
  of Texas Southwestern Medical Center at Dallas
  Gene regulation in B lymphocyte differentiation.
• M.S. (2001) Computer Science, University of Texas
  at Dallas
• M.S. (2008, expected) Applied Statistics, Purdue
  University
• Professional experience
• 2001-2002 Postdoctoral Scientist, Tularik Inc.
  South San Francisco
• 2002-present Research Scientist, Sr. Research
  Scientist, Eli Lilly and Company
• Main research interests comparative functional
  genomics cancer informatics

2
Comparative analysis of gene expression between
the SAGE and microarray platforms

• Goal To test the data comparability between SAGE
  and microarray technologies, through examining
  the expression pattern of genes under normal
  physiological states across multiple tissues
• Results
• Significant discrepancies between the two
  platforms only 30-40 genes exhibited positive
  correlations
• The discrepancies are not caused by heterogeneity
  of tissue sources, microarray probe designs, mRNA
  abundance, or gene function
• The discrepancies can be at least partially
  explained by
• Errors in SAGE tag annotation
• Splice variants
• SAGE tags and array probesets represent different
  regions of the same genes
• Reference Li S., Li Y. H., Wei T., Su E. W.,
  Duffin K., and Liao B. (2006). Too much data, but
  little inter-changeability A lesson learned from
  mining public data on tissue specificity of gene
  expression. Biology Direct 1, 33

3
Evaluation of Model Experimental Systems- Cancer
cell lines vs. primary tumors

• Q1 If the cell lines represent the tumor tissues
  that they are originally derived from?
• Correlation analysis suggests that 51 of NCI60
  cell lines represent their presumed tumor origin.
• Q2 What cancer subtypes or tumor stages do the
  cell lines represent?
• Classification based on supervised learning.
  Examples 6 NSCLC lines represent stage 2/3
  tumors.

Stage III/IV
Stage II
Stage I
A549
NCI-H460, EKVX, HOP-92, NCI-H226, HOP-62
4
Evaluation of Model Experimental Systems- Cancer
cell lines vs. primary tumors

• Q3 What pathways are activated in primary
  cancers and cell lines?
• Derive gene expression signature representing the
  activated pathways and predict pathway activity
  in primary tumors and cell lines. Example Ras
  pathway is activated in 70 of lung
  adenocarcinomas and 4 NSCLC cell lines.
• Reference Wang H., Huang S., Shou J., Su E. W.,
  Onyia J. E., Liao B., and Li S. (2006).
  Comparative analysis and integrative
  classification of NCI60 cell lines and primary
  tumors using gene expression profiling data. BMC
  Genomics 7, 166.

Ras
Active
Control
Inactive