The online version of this article has a Supplementary Appendix. BackgroundThe number of CD34 + cells mobilized from bone marrow to peripheral blood after administration of granulocyte colony-stimulating factor varies greatly among healthy donors. This fact might be explained, at least in part, by constitutional differences in genes involved in the interactions tethering CD34 + cells to the bone marrow. Design and MethodsWe analyzed genetic characteristics associated with CD34 + cell mobilization in 112 healthy individuals receiving granulocyte colony-stimulating factor (filgrastim; 10 μg/kg; 5 days). ResultsGenetic variants in VCAM1 and in CD44 were associated with the number of CD34 + cells in peripheral blood after granulocyte colony-stimulating factor administration (P=0.02 and P=0.04, respectively), with the quantity of CD34 + cells ¥10 6 /kg of donor (4.6 versus 6.3; P<0.001 and 7 versus 5.6; P=0.025, respectively), and with total CD34 + cells ¥10 6 (355 versus 495; P=0.002 and 522 versus 422; P=0.012, respectively) in the first apheresis. Of note, granulocyte colonystimulating factor administration was associated with complete disappearance of VCAM1 mRNA expression in peripheral blood. Moreover, genetic variants in granulocyte colony-stimulating factor receptor (CSF3R) and in CXCL12 were associated with a lower and higher number of granulocyte colony-stimulating factor-mobilized CD34 + cells/μL in peripheral blood (81 versus 106; P=0.002 and 165 versus 98; P=0.02, respectively) and a genetic variant in CXCR4 was associated with a lower quantity of CD34 + cells ¥10 6 /kg of donor and total CD34 + cells ¥10 6 (5.3 versus 6.7; P=0.02 and 399 versus 533; P=0.01, respectively). ConclusionsIn conclusion, genetic variability in molecules involved in migration and homing of CD34 + cells influences the degree of mobilization of these cells.

Mutations in mitochondrial complex II (MCII; succinate dehydrogenase, Sdh) genes cause familiar pheochromocytoma/paraganglioma tumors. Several mechanisms have been proposed to account for Sdh-mutation-induced tumorigenesis, the most accepted of which is based on the constitutive expression of the hypoxia-inducible factor 1α (Hif1α) at normal oxygen tension, a theory referred to as “pseudo-hypoxic drive”. Other molecular processes, such as oxidative stress, apoptosis, or chromatin remodeling have been also proposed to play a causative role. Nevertheless, the actual contribution of each of these mechanisms has not been definitively established. Moreover, the biological factors that determine the tissue-specificity of these tumors have not been identified. In this work, we made use of the inducible SDHD-ESR mouse, a conditional mutant in the SdhD gene, which encodes the small subunit of MCII, and that acts as a tumor suppressor gene in humans. The analysis of the Hif1α pathway in SDHD-ESR tissues and in two newly derived cell lines after complete SdhD loss -a requirement for hereditary paraganglioma type-1 tumor formation in humans- partially recapitulated the “pseudo-hypoxic” response and rendered inconsistent results. Therefore, we performed microarray analysis of adrenal medulla and kidney in order to identify other early gene expression changes elicited by SdhD deletion. Our results revealed that each mutant tissue displayed different variations in their gene expression profiles affecting to different biological processes. However, we found that the Cdkn1a gene was up-regulated in both tissues. This gene encodes the cyclin-dependent kinase inhibitor p21WAF1/Cip1, a factor implicated in cell cycle, senescence, and cancer. The two SDHD-ESR cell lines also showed accumulation of this protein. This new and unprecedented evidence for a link between SdhD dysfunction and p21WAF1/Cip1 will open new avenues for the study of the mechanisms that cause tumors in Sdh mutants. Finally, we discuss the actual role of Hif1α in tumorigenesis.

© F e r r a t a S t o r t i F o u n d a t i o ngene and miRNA expression profiles in HPC from healthy donors, and to determine whether any changes in expression signatures persist in the long-term or return to the original status. Methods SamplesCD34 + progenitor cells from peripheral blood of six healthy donors were collected before and at 5, 30 and 365 days after the mobilization with G-CSF (mobilization regimen: 10-15 mg/kg of G-CSF daily for 5 days). All donors were included in the transplant program of the Hematology Department of the University Hospital Virgen del Rocío (Seville, Spain). The local ethics committee of the same hospital provided institutional review boardapproval for this study, and informed consent was obtained from all donors in accordance with the Declaration of Helsinki. Isolation of hematopoietic progenitor cellsMononuclear cells were collected from all samples by density gradient centrifugation with Ficoll-Paque solution (Amersham Biosciences, Uppsala, Sweden). The CD34 + cells were isolated in an AutoMACS pro separator (Miltenyi Biotec, Bergisch Gladbach, Germany) by positive immunomagnetic selection using the CD34 MACS microbead Human Kit (Miltenyi Biotec, Bergisch Gladbach, Germany) and, after magnetic enrichment, CD34 + cells were sorted by flow cytometry. The purity of the isolated CD34 + cells was greater than 95% in all cases. RNA extractionTotal RNA was extracted by TRIsure (Bioline, Luckenwalde, Germany) in all samples. The quality and integrity of the RNA were verified by a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). MicroRNA and gene expressionThe expression profiles of 384 miRNA were analyzed in all samples using TaqMan Human MicroRNA v2.0 Arrays (Applied Biosystems, Foster City, CA. USA) which were analyzed on a 7900 HT Fast Real Time Polymerase Chain Reaction (PCR) System (Applied Biosystems, Foster City, CA, USA). The SDS 2.3 and RQ Manager 1.2 software (both Applied Biosystems, Foster City, CA, USA) were used for the analysis. Data were normalized using the average of the endogenous small-nucleolar RNU48 and the noncoding small nuclear U6, both included in the array.The expression profile of 45,000 genes was analyzed in the same samples using the Whole Human Genome Oligo microarray kit 4x44K (Agilent Technologies, Santa Clara, CA, USA). The microarrays were scanned in a GenePix reader (Molecular Devices, Sunnyvale, CA, USA). Samples from non-mobilized CD34 + cells were used as the reference group in both types of expression analysis.The expression of significant genes was validated by quantitative real-time PCR using Quantitec Primer Assays and the Quantitec SYBR Green Kit (both from Qiagen, Hilden, Germany) in a 7900 HT Fast Real Time PCR System (Applied Biosystems, Foster City, CA, USA). Data were normalized to the housekeeping gene ACTB and the group of samples from non-mobilized CD34 + cells was used as a control. The relative gene expression levels were calculated by the 2 -ΔΔCT method. Statistical analysisUnsupervised hierarchical clust...