Generation of a predictive melphalan resistance index by drug screen of B-cell cancer cell lines |
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Authors: | Boegsted Martin Holst Johanne M Fogd Kirsten Falgreen Steffen Sørensen Suzette Schmitz Alexander Bukh Anne Johnsen Hans E Nyegaard Mette Dybkaer Karen |
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Institution: | Department of Haematology, Aalborg Hospital Science and Innovation Center, Aarhus University Hospital, Aalborg, Denmark. martin.boegsted@rn.dk |
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Abstract: | BackgroundRecent reports indicate that in vitro drug screens combined
with gene expression profiles (GEP) of cancer cell lines may generate
informative signatures predicting the clinical outcome of chemotherapy. In
multiple myeloma (MM) a range of new drugs have been introduced and now
challenge conventional therapy including high dose melphalan. Consequently,
the generation of predictive signatures for response to melphalan may have a
clinical impact. The hypothesis is that melphalan screens and GEPs of B-cell
cancer cell lines combined with multivariate statistics may provide
predictive clinical information.Materials and MethodsMicroarray based GEPs and a melphalan growth inhibition screen of 59 cancer
cell lines were downloaded from the National Cancer Institute database.
Equivalent data were generated for 18 B-cell cancer cell lines. Linear
discriminant analyses (LDA), sparse partial least squares (SPLS) and
pairwise comparisons of cell line data were used to build resistance
signatures from both cell line panels. A melphalan resistance index was
defined and estimated for each MM patient in a publicly available clinical
data set and evaluated retrospectively by Cox proportional hazards and
Kaplan-Meier survival analysis.Principal FindingsBoth cell line panels performed well with respect to internal validation of
the SPLS approach but only the B-cell panel was able to predict a
significantly higher risk of relapse and death with increasing resistance
index in the clinical data sets. The most sensitive and resistant cell
lines, MOLP-2 and RPMI-8226 LR5, respectively, had high leverage, which
suggests their differentially expressed genes to possess important
predictive value.ConclusionThe present study presents a melphalan resistance index generated by analysis
of a B-cell panel of cancer cell lines. However, the resistance index needs
to be functionally validated and correlated to known MM biomarkers in
independent data sets in order to better understand the mechanism underlying
the preparedness to melphalan resistance. |
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