1. Tumor target vs. tissue of tumor origin: Cluster analysis of genomic profile of 42 human tumor
in vitro and in vivo models
Abstract #2778
Michael J. Roberts1, Michael S. Koratich1, Murray Stackhouse1, Richard D. May1, Andrew D. Penman1, Tommie A. Gamble1, Kristy L. Berry1, Joseph Murphy1, Robert J. Rooney2, Yulia Maxuitenko1
1Southern Research Institute, Birmingham, AL; 2Genome Explorations Inc., Memphis, TN
2000 Ninth Avenue South ● Birmingham, AL 35205 ● www.SouthernResearch.org ● 1 (800) 967-6774 (USA) ● 1 (205) 581-2000
Do the Human Tumor Xenograft Models Show a Similar
Genetic Profile to the Cell Lines From Which They Were
Derived?
Traditionally, drug development has relied upon testing cancer drug candidates in cell
lines. Active drugs are then tested in human tumor xenograft models, usually selected
based upon the cell lines in which the drug showed activity. The majority of drugs fail at
this stage as they do not show activity in the xenograft models chosen. We performed
Affymetrix genomic analysis on 42 human tumor xenograft models and the original cell
lines from which they were established. The genomic profiles obtained underwent
Unsupervised Hierarchical Cluster Analysis to ascertain which cell lines and xenograft
models had similar genomic profiles and which did not. The analysis showed that only 24
of 42 human tumor xenograft models clustered side-by-side with the cell line from which
they were established. All 6 human leukemia/lymphoma xenograft models clustered very
well with the cell lines from which they were established, and they clustered perfectly
according to histological class. Five out of six human colon tumor xenograft models
clustered well with the cell lines from which they were established and according to
histotype. Of the 18 xenograft/cell line pairs that did not cluster side-by-side, 10 pairs
remained in the same general cluster, whereas the partners of 8 other pairs were
dispersed across different major clusters. Ovarian, breast, melanoma, and pancreatic
human tumor xenograft models did not cluster according to histotype. Our data may
explain why some drugs that show in vitro activity in some cell lines are not active in
other cell lines of the same histological type, and also why some drugs that show activity
in vitro then fail in xenograft models. In our laboratory, the PANC-1 cell line is very often
chosen as a model of pancreatic cancer. A drug showing activity in the PANC-1 cell line
would next be tested in other in vitro models of pancreatic cancer (e.g., MIA PaCa-2,
CFPAC-1, and BxPC-3). However, none of these other pancreatic models have a similar
genetic profile to PANC-1. Based upon our data, the cell line showing most similarity to
the PANC-1 cell line is the breast cancer cell line MDA-MB-231. It is our suggestion that a
drug showing activity in the PANC-1 cell line should be tested in other cell lines showing
similar genetic profiles, not in cell lines based on histotype. Another example from our
analysis is the LOX-IMV1 melanoma cell line. Not only does this cell line not cluster with
its corresponding LOX-IMV1 xenograft model, it clusters most closely with the NCI/ADR-
RES ovarian cell line. In summary, the genomic profiles of approximately 57% of the
tumor xenograft models analyzed closely associate with the cell line from which they
were established. Some of the tumor xenograft models show very little similarity to the
cell lines from which they were established. Additionally, many of the models (both
xenografts and cell lines), do not cluster according to their tissue of origin.
Over 40% of the human tumor xenograft models displayed markedly different gene
expression profiles relative to the cell line from which they were derived clearly
illustrating that the in vitro models poorly represent the in vivo models
Only the leukemia/lymphoma and colon human tumor xenograft models clustered
according to phenotype strongly suggesting that limiting targeted therapies to particular
phenotpyes is incorrect
Do Human Tumor Xenograft Models of the Same Phenotype
Show a Similar Genetic Profile?
Results
Conclusions
Results
Leukemia/Lymphoma, Melanoma, Colon, Renal, and Glioblastoma cell lines generally
cluster very well with few exceptions
Breast, Ovarian, Uterine, Prostate, Pancreatic and Lung cell lines show genetic disparity.
The leukemia/Lymphoma human tumor xenograft models clustered very well with the
cell lines from which they were derived
The colon human tumor xenograft models clustered very well with the cell lines from
which they were derived (with one exception)
Only 24 of 42 human tumor xenograft models clustered side by side with the cell line
from which they were derived
Of the 18 xenograft/cell line pairs that did not cluster side by side, 10 pairs remained in
the same general cluster, whereas the partners of 8 other pairs were dispersed across
different major clusters
The leukemia/Lymphoma human tumor xenograft models clustered perfectly according
to histological class
4 out of 6 colon human tumor xenograft models clustered closely according to
hi8stotype, with the 5th (HCT-116) falling in the same major cluster and the 6th (SW620)
exhibiting significant divergence
Ovarian, Breast, Melanoma, and Pancreatic human tumor xenograft models all exhibited
significant divergence and did not cluster according to phenotype
Southern will search our genetic database for models that express your target of interest
Following in vitro screening of your compound, Southern will suggest other in vitro
and/or in vivo models with a similar genetic profile
Following in vivo screening, Southern will suggest other in vivo models with a similar
genetic profile, often expanding the potential of your drug to be utilized in other
histotypes
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