Genomic Analysis of Endothelial Progenitor Cells In Multiple Myeloma Reveals Aberrant Gene Pathways Common to Tumor Cells

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3016-3016
Author(s):  
Marc J Braunstein ◽  
Sadeaqua Scott ◽  
Eric LP Smith ◽  
Danielle F Joseph ◽  
Jason Gonsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Human Genome ◽  
Progenitor Cells ◽  
Tumor Cells ◽  
Endothelial Progenitor Cells ◽  
Copy Number ◽  
Gene Expression Level ◽  
Expression Level ◽  
Gains And Losses

Abstract Abstract 3016 Background: Multiple myeloma (MM) is an incurable disease characterized by genetically transformed clonal plasma cells that develop a proliferative advantage within the supportive bone marrow (BM) microenvironment. Recent findings from our and other laboratories have shown genetically unstable endothelial progenitor cells (EPCs) to be a key component of the MM microenvironment, integral to tumor neovascularization. However, the contribution and characterization of genomic alterations in the tumor microenvironment in the progression of MM has not been established. Using array-comparative genomic hybridization (aCGH), the present study examined genome-wide copy number alterations (CNAs) within the EPC genome and compared them to tumor cells and control endothelial cells (ECs). Published human copy number variations (CNVs) were excluded from the analyses. Methods: Informed consent was obtained from all subjects. EPCs (>98% vWF/CD133/KDR+/CD38–) from BM aspirates of 16 untreated MM patients were outgrown on laminin-coated flasks. Controls included EPCs from healthy subjects and human umbilical vein ECs (HUVECs). For microarray analysis, genomic DNA from paired EPCs and tumor cells from MM patients enriched for CD38+ cells, as well as control cells, were hybridized to Agilent 244A Human Genome CGH Microarrays with differentially labeled control peripheral blood mononuclear cells, and feature intensities and ratios were extracted in Agilent CGH Analytics Software. The aberration detection method-1 algorithm was used to assess intervals in which the average log2 ratio of the MM cells and EPCs to control cells and ECs exceeded 0.3 (at least 1.23 fold-change). Human Genome Structural Variation Project (humanparalogy.gs.washington.edu) and the Database of Genomic Variants (projects.tcag.ca/variation) served as control CNVs. Affymetrix U133 plus 2.0 GeneChips confirmed gene expression using GeneSpring software (Agilent), and group comparisons were made by ANOVA. Results: Extensive chromosomal CNAs were found in MM EPCs; gains and losses were found to approximately the same extent in matched tumor cells. Germline CNVs accounted for less than 10% of MM EPC CNAs. The greatest number of CNA gains in EPCs were found on chr 7q, followed by 2p and 22q; the most recurrent sequences with CNA gains were on chr 7. The greatest CNAs losses in MM EPCs were found equivalently on chr 1q, 11q, and 15q. Consistent with their clonal expression in MM, immunoglobulin genes were found to be dysregulated in MM EPCs (e.g., 14q32 gains), which were confirmed at the gene expression level (e.g., over-expression of IGHG1 mRNA compared to control ECs). When comparing CNAs in MM EPCs to those in corresponding tumor cells, 15 of 16 patients (94%) shared identical CNAs at 2 or more loci, with greater than 48% similarity in CNAs between EPCs and tumor cells. Control EPCs and HUVECs did not show significant baseline alterations compared to control normal lymphocyte DNA, whereas identical CNAs were found in MM EPCs and tumor cells throughout their genomes. The most recurrent CNAs in both EPCs and tumors were found on chr 1 and 14, which are known to be highly dysregulated in MM. The clinical relevance of our aCGH data is suggested by the finding that more CNA gains and losses were found both in EPCs and in tumor cells from MM patients with treatment-resistant, progressive MM than in patients in remission (P<.01). The consequences of CNAs at the gene expression level in EPCs showed the highest level of dysregulation among the extracellular matrix genes. Discussion: aCGH results presented here are an extension of our previous findings of clonality within EPCs, including allelic X-chromosome inactivation and idiotypic IgH rearrangement, and further elucidate the genomic alterations responsible for increased angiogenesis in MM. The finding that MM-specific CNAs within EPCs correlate with resistant disease and poor survival may enhance existing criteria for prediction of aggressive MM, and also improve individualization of anti-myeloma strategies. Conclusions: Our results strongly indicate that EPCs are an integral part of the neoplastic process in MM. Their altered genomic profile compared to control ECs indicates pathogenic functions critical for MM evolution. The high degree of commonly dysregulated genes among EPCs and MM cells permits prioritization of candidate MM-endothelial biomarkers not yet defined in this disease. Disclosures: No relevant conflicts of interest to declare.

Clonotypic Bone Marrow-Derived Endothelial Progenitor Cells in Multiple Myeloma.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3497-3497
Author(s):  
Marc J. Braunstein ◽  
Daniel R. Carrasco ◽  
David Kahn ◽  
Kumar Sukhdeo ◽  
Alexei Protopopov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Bone Marrow ◽  
High Resolution ◽  
Gene Expression Profiling ◽  
Progenitor Cells ◽  
Tumor Cells ◽  
Endothelial Progenitor Cells ◽  
Expression Profiling ◽  
Gains And Losses

Abstract In multiple myeloma (MM), bone marrow-derived endothelial progenitor cells (EPCs) contribute to tumor neoangiogenesis and their levels covary with tumor mass and prognosis. Recent X-chromosome inactivation studies in female patients showed that, similar to tumor cells, EPCs are clonally restricted in MM. Genomic profiling of MM using high-resolution array comparative genomic hybridization (aCGH) has been previously utilized to mine the genome and find clinical correlates in MM patients. In this study, clonotypic aspects of bone marrow-derived EPCs and MM cells were investigated using aCGH and expression profiling analysis. Confluent EPCs were outgrown from bone marrow aspirates by adherence to laminin. EPCs were >98% vWF/CD133/KDR+ and <1% CD38+. The laminin-nonadherent bone marrow fraction enriched for tumor cells was >50% CD38+. For aCGH and for gene expression profiling, genomic DNA and total RNA from EPCs and MM cells were hybridized to human oligonucleotide arrays (Agilent Technologies) and human cDNA microarrays (Affymetrix), respectively. High resolution aCGH with segmentation analysis showed that EPCs and MM cells in one of ten cases share identical patterns of chromosomal gains and losses, while another 5 cases shared multiple focal copy number alterations (CNAs) including gains and losses. The genomes of EPCs and MM cells additionally displayed exclusive CNAs, but these were far fewer in EPCs than in MM cells. In 3 patients, EPCs harbored a common 0.6Mb deletion at 1q21 not shared by MM cells. Pertinent genes in this region that could affect proliferation and tumor suppression include N2N, NBPF10, and TXNIP. Validation studies of aCGH findings by other methods are ongoing. Gene expression profiling showed decreased expression of 1q21 region genes (e.g., calgranulin C and lamin A/C). A genome-wide comparison of patients’ MM cells and EPCs, which is focused on their shared genetic characteristics, will be presented.

Genome-Wide Profiling of Endothelial Progenitor Cells in Multiple Myeloma: Overlaps with Myeloma Tumor Cells and Common Cancer Gene-Pathways.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 394-394
Author(s):  
Marc J. Braunstein ◽  
Daniel R. Carrasco ◽  
Fabien Campagne ◽  
Piali Mukherjee ◽  
Kumar Sukhdeo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Bone Marrow ◽  
Progenitor Cells ◽  
Tumor Cells ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Biomarkers ◽  
Genome Wide

Abstract Background: In multiple myeloma (MM), bone-marrow-derived endothelial progenitor cells (EPCs) contribute to tumor neoangiogenesis, and their levels covary with tumor mass and prognosis. Recent X-chromosome inactivation studies showed that EPCs are clonally restricted in MM. In addition, high-resolution array comparative genomic hybridization (aCGH) found that the genomes of EPCs and MM cells display similar chromosomal gains and losses in the same patient. In this study, we performed an integrative analysis of EPCs and tumor cells by genome-wide expression profiling, and applied a bioinformatics approach that leverages gene expression data from cancer datasets to mine MM gene pathways common to multiple tumor tissues and likely involved in MM pathogenesis. Methods: Confluent EPCs (&gt;98% vWF/CD133/KDR+ and CD38−) were outgrown from 22 untreated MM patients’ bone marrow aspirates by adherence to laminin. The fractions enriched for tumor cells were &gt;50% CD38+. For gene expression profiling, total RNA from EPCs, MM cells, and control HUVECs were hybridized to cDNA microarrays, and comparisons were made by analysis of variance. Results: Two sets of EPC gene profiles were of particular interest. The first contained genes that differ significantly between EPCs and HUVEC, but not between EPCs and tumor (Profile 1). We hypothesize that this profile is a consequence of the clonal identity previously reported between EPCs and tumor, and that a subset of these genes is largely responsible for MM progression. The second set of important EPC genes are differentially regulated compared both to HUVECs and to tumor cells (Profile 2). These genes may represent the profile of EPCs that are clonally diverse from tumor cells but nevertheless display common gene expression patterns with other cancers. Profile 2 genes may also represent genes that confer a predisposition to clonal transformation of EPCs. When genes in Profile 1 and Profile 2 were overlapped with published lists of cancer biomarkers, significant similarities (P&lt;.05) were apparent. The largest overlaps were observed with the HM200 gene list, a list composed of 200 genes most consistently differentially expressed in human/mouse cancers (Campagne and Skrabanek, BMC Bioinformatics 2006). More than 80% of genes in either EPC profile have not been previously characterized in MM, but have been identified as cancer biomarkers in other cancer studies. These genes will be presented and discussed in the context of MM. Current studies are aimed at integrating Profile 1 and Profile 2 genes in each patient with chromosomal copy number abnormalities (CNAs) found in EPCs, and also with clinical stage and disease severity, in order to elucidate the pathogenic information that the profiles hold. Conclusions: The genomes of EPCs display ranges of overlap with tumor cells in MM, evidenced by gene expression profiles with varying similarity to those found in MM tumor cells. More importantly, MM EPC gene expression profiles, in contrast to normal endothelial cells, contain cancer biomarker genes in tumors not yet associated with MM. Results strongly support the concept that EPCs are an integral part of the neoplastic process in MM.

Candidate glioblastoma development gene identification using concordance between copy number abnormalities and gene expression level changes

2007 ◽  
Vol 46 (10) ◽  
pp. 875-894 ◽  
Author(s):  
Ken C. Lo ◽  
Michael R. Rossi ◽  
Jeffrey LaDuca ◽  
David G. Hicks ◽  
Yaron Turpaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Gene Expression Level ◽  
Expression Level ◽  
Gene Identification

scholarly journals Identification of genes with correlated patterns of variations in DNA copy number and gene expression level in gastric cancer

Genomics ◽  
2007 ◽  
Vol 89 (4) ◽  
pp. 451-459 ◽  
Author(s):  
Sanghwa Yang ◽  
Hei-Cheul Jeung ◽  
Ha Jin Jeong ◽  
Yeon Ho Choi ◽  
Ji Eun Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Copy Number ◽  
Gene Expression Level ◽  
Expression Level ◽  
Dna Copy Number ◽  
Correlated Patterns

Characterization of Hemangioblastic Traits within Endothelial Progenitor Cells of Multiple Myeloma Patients

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2984-2984
Author(s):  
Sadeaqua S Scott ◽  
Marc J Braunstein ◽  
Christopher Lange ◽  
Christopher Roman ◽  
Eric LP Smith ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Multiple Myeloma ◽  
Flow Cytometry ◽  
Progenitor Cells ◽  
Tumor Cells ◽  
Endothelial Progenitor Cells ◽  
Conflicts Of Interest ◽  
Cell Phenotype ◽  
Endothelial Progenitor ◽  
Cell Cycle Status

Abstract Abstract 2984 Background: Multiple myeloma (MM), a neoplasm of committed B-lymphocytes within the bone marrow (BM), is the second most common hematologic malignancy in the U.S. Despite prolonged median survival with anti-myeloma strategies aimed at the tumor and its BM microenvironment, MM remains invariably fatal. Endothelial progenitor cells (EPCs) are CD133+/KDR+ cells that originate in the BM and play a key role in supporting tumor growth and MM progression. Using X-chromosome inactivation and RT-PCR analyses, we previously found EPCs from MM patients to be clonally restricted and to display clonotypic IG heavy-chain gene rearrangements identical to the same patients' tumor cells (Braunstein et al., 2006). Based on the shared genetic identity that we and others have demonstrated between tumor cells and EPCs in MM patients, the present study explored the hypothesis that, similar to hemangioblasts, which are CD133-expressing precursors to adult hematopoietic and endothelial cells, EPCs may be a source of vascular and MM progenitor cells. Since hemangioblasts are known to exist predominately in the quiescent phases of the cell cycle, in this study we also examined the cell cycle status of CD133-expressing BM cells from MM patients in order to gain insight into their hemangioblastic traits. Methods: BM aspirates were acquired from MM patients under IRB approval. EPCs (>98% vWF/CD133/KDR+ and CD38-) from BM aspirates of MM patients were outgrown on laminin-coated flasks as previously described. The spleen colony assay was used to determine the stem cell capacity within BM-derived EPCs by i.v. injection into NOD/SCID mice. The spleens and BM of mice were harvested 2–4 weeks later. Cells were analyzed by immunofluorescence (IF) and flow cytometry. Hoechst 33342 (Hst) and Pyronin Y (PY) were used to measure the cell cycle status of CD133+ cells using FACS analysis. Results: Two to four weeks following i.v. injection of MM EPCs, human cell surface marker expression detected by flow cytometry within mouse BM and spleen cells shifted from CD133+/CD45-lo, a progenitor cell phenotype, to CD133−/CD45-hi, a more differentiated phenotype, suggesting the ability of MM EPCs to differentiate in vivo. Cell cycle analysis of the CD133+ population in BM cells of MM patients showed that these cells were predominantly non-cycling. On average, 60.5% of CD133+ cells were found to be in the G0/G1 phase of the cell cycle, as indicated by low levels of IF staining with Hst and PY. Conclusions: CD133+ cells are strong candidates as precursors to MM tumor and vascular progenitor cells. As quiescent cells are non-dividing, they often escape cytotoxic effects of chemotherapy, resulting in relapse, and therefore, identification of these cells is critical. Ongoing studies include the engraftment of CD133+ cells in the subcutaneous NOD/SCID gamma xenotransplant model and their growth in response to anti-myeloma strategies; results of these studies will be discussed. Disclosures: No relevant conflicts of interest to declare.

Genome-Wide Profiling of Endothelial Progenitor Cells in Multiple Myeloma: Disease-Relevant Pathways and Overlaps with Common Cancer Biomarkers

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 626-626 ◽  
Author(s):  
Marc J. Braunstein ◽  
Fabien Campagne ◽  
Piali Mukherjee ◽  
Daniel Ruben Carrasco ◽  
Kumar Sukhdeo ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Progenitor Cells ◽  
Tumor Cells ◽  
Endothelial Progenitor Cells ◽  
Cancer Biomarkers ◽  
Differentially Expressed ◽  
Genomic Profile ◽  
Endothelial Progenitor ◽  
Neoplastic Process ◽  
And Control

Abstract Background: The current study is based on recent findings from our and other laboratories demonstrating endothelial progenitor cells (EPCs) in multiple myeloma (MM) to be a key component of the tumor microenvironment, integral to the neoplastic process. EPCs contribute to tumor neoangiogenesis, and their levels covary with MM progression. Furthermore, MM EPCs are genetically unstable, as evidenced by restricted X-chromosome inactivation patterns; by immunoglobulin rearrangements identical to those harbored by tumor cells; and by a range of shared chromosomal gains or losses with tumor cells, shown by array comparative genomic hybridization (aCGH). The present study further characterized the EPC genomic profile in MM by comparison of EPC gene expression with that of tumor cells and control ECs using a bioinformatics approach that integrated cancer gene databases to prioritize key molecular MM biomarkers. Methods: EPCs (&gt; 98% vWF/CD133/KDR+/CD38–) from bone marrow aspirates of 22 untreated MM patients were outgrown on laminin-coated flasks. The fractions enriched for tumor cells were &gt; 50% CD38+. For expression profiling, total RNA from EPCs, MM cells, and control ECs (EPCs and HUVECs) was hybridized to Affymetrix U133 Plus 2.0 arrays, and comparisons were made by ANOVA with corrections for multiple comparisons to achieve a false discovery rate &lt; 5%. Functional enrichment of gene ontology (GO) categories was performed using DAVID (NIAID) and Ingenuity Systems software. Results: A total of 334 genes were differentially expressed in MM EPCs versus control ECs (&gt; 1.5-fold difference and P &lt;. 05). Of these, 81% were over-expressed in MM EPC. Functional annotation clustering of all 334 genes into GO categories by DAVID focused similar annotations together into 16 significant clusters (P &lt; .01). This analysis revealed top biological clusters to be differentiation and development (P = 8×10−8, 159 genes); extracellular matrix adhesion (P = 2×109, 110 genes); bone formation (P = 4×10−5, 33 genes); and angiogenesis (P = 8×10−5, 35 genes). From these clusters, an expression profile was obtained consisting of the strongest 21 differentially expressed genes (versus control ECs; P &lt; 1×10−5) characterized by highest expression of 4 genes associated with metastasis and tumor growth: COL1A1, LUM, CYP1B1, and GREM1. RT-PCR validation studies of these genes are ongoing. Moreover, there was a 34% greater overlap of MM EPC and tumor profiles versus control ECs and tumor profiles (P &lt; .001). In comparing the 334-gene set to the tumor cell profile, 2 important EPC gene sets emerged. The first set included 158 MM EPC genes differing significantly from control ECs, but similar to tumor (Profile 1). We hypothesize that this profile is a consequence of the clonal identity previously reported between MM EPCs and tumor, and that these genes contribute to MM progression. The second profile included 39 EPC genes that differed significantly both from control ECs and tumor cells (Profile 2). This gene profile may confer a predisposition to clonal transformation of EPCs. When genes in both profiles were compared with published databases of cancer biomarkers (Campagne et al., BMC Bioinformatics 2006), significant overlaps (P &lt; .05) were found. The largest similarities were observed with the HM200 gene list which comprises 200 genes most consistently differentially expressed in human/mouse cancers, and containing potentially key genes previously undescribed in MM, including FZD7, TWIST1, and CARD8. Current studies are aimed at integrating genes in EPC Profiles 1 and 2 with chromosomal copy number abnormalities found in EPCs, and with MM progression and survival. Conclusions: Our results strongly indicate that EPCs are an integral part of the neoplastic process in MM. Their altered genomic profile compared to control ECs indicates pathogenic functions critical for MM evolution, including angiogenesis, adhesion, bone turnover, and cell differentiation. The high degree of commonly expressed EPC genes compared with MM and other tumors permits prioritization of candidate MM-endothelial biomarkers not yet defined in this disease.

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