Human mesenchymal stem cells (hMSCs) have the capacity to differentiate along several pathways to form bone, cartilage, tendon, muscle, and adipose tissues. The adult hMSCs reside in vivo in the bone marrow in niches where oxygen concentration is far below the ambient air, which is the most commonly encountered laboratory condition. The study reported here was designed to determine whether oxygen has a role in the differentiation of hMSCs into adipocytes. Indeed, when exposed to atmosphere containing only 1% of oxygen, the formation of adipocytelike phenotype with cytoplasmic lipid inclusions was observed. The effect of hypoxia on the expression of adipocyte-specific genes was determined by real-time reverse transcription polymerase chain reaction. Interestingly, neither of the two central regulators of adipogenesis-the transcription factors peroxisome proliferatoractivated receptor γ2 (PPAR-γ2) and ADD1/SREBP1c-was induced. Furthermore, hypoxia did not have any effect on the transcription of early (lipoprotein lipase) or late (aP2) marker genes. By the same token, neither of the mature adipocyte-specific genes-leptin and adipophilinwas found responsive to the treatment. High level of induction, however, was observed with the PPAR-γ-induced angiopoietin-related gene, PGAR. The lack of an adipocyte-specific transcription pattern thus indicates that despite accumulation of the lipid, true adipogenic differentiation did not take place. In conclusion, hypoxia appears to exert a potent lipogenic effect independent of PPAR-γ2 maturation pathway.

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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