Presentation Abstract

Abstract Number: 3730
Presentation Title: A quick and cost effective 12-cell line panel assay to predict drug activity in human tumor xenograft models
Presentation Time: Tuesday, Apr 08, 2014, 8:00 AM -12:00 PM
Location: Hall A-E, Poster Section 32
Poster Board Number: 4
Author Block: Michael J. Roberts1, Tommie A. Gamble1, Richard D. May1, Murray Stackhouse1, Kristy L. Berry1, Andrew D. Penman1, Robert J. Rooney2, Yulia Maxuitenko1, Michael S. Koratich1. 1Southern Research Institute, Birmingham, AL; 2Genome Explorations Incorporated, Memphis, TN
Abstract Body:
The procedure to identify and develop an anti-cancer drug
first involves testing drug candidates in cell lines followed by human tumor xenograft
models, usually selected based upon the histotype of the cell lines in which
the drug showed optimal activity. Many drugs fail at this stage, as activity in
cell lines does not often correlate with activity in xenograft models. This is
not surprising, as we have previously shown that gene expression in xenograft
models does not necessarily correlate with the cell line from which it was
derived. In an attempt to improve the success rate of drugs tested in xenograft
models, we have developed a fast and cost effective 12-panel human tumor cell
line assay that represents the genetic diversity of all our xenograft models
and several different cancer histotypes.
Affymetrix genomic analysis was performed on 100 human tumor
xenograft and cell line models. The genomic profiles obtained underwent
Unsupervised Hierarchical Cluster Analysis to group models with similar genetic
profiles. This analysis resulted in 12 distinct clusters; a representative cell
line was chosen from each cluster. Stocks of each representative cell line were
frozen and tested to ensure exponential growth immediately upon thawing,
resulting in no waiting time for drug testing. It follows that if a candidate
drug shows activity in one or more of these representative cell lines, other
cell lines and/or xenograft models in the same cluster can also be tested. As
the cell lines and xenograft models within the same cluster will have a similar
genetic profile, the chances of success should thus be increased.
To test the effectiveness of this approach, we used our database
to further develop an internal compound. SRI-20900 had been tested previously in
the CCRF-CEM and CAKI-1 xenograft models. The compound showed no activity in
CCRF-CEM cells, but excellent activity in CAKI-1 cells. These models were in
completely different clusters. So, based on these data, we tested the compound
in the SKOV-3 and IGROV-1 xenograft models, as these clustered closely to the
CAKI-1 model. The compound showed excellent activity in both SKOV-3 and IGROV-1
models.
Although these data provide proof of principle, further work
needs to be done by testing targeted compounds in the 12-cell line panel, followed
by testing in xenograft models within the same cluster as the cell lines that
show optimal activity. In addition, it would follow that a xenograft model within
the same cluster as an inactive cell line should also be tested. We hope to
start these studies early in 2014.