Gene Expression Profiles in a Porcine Model of Infarction: Differential Expression After Intracoronary Injection of Heterologous Bone Marrow Mesenchymal Cells

Within the bone marrow microenvironment, mesenchymal stromal cells (MSCs) are an essential precursor to bone marrow adipocytes and osteoblasts. The balance between this progenitor pool and mature cells (adipocytes and osteoblasts) is often skewed by disease and aging. In multiple myeloma (MM), a cancer of the plasma cell that predominantly grows within the bone marrow, as well as other cancers, MSCs, preadipocytes, and adipocytes have been shown to directly support tumor cell survival and proliferation. Increasing evidence supports the idea that MM-associated MSCs are distinct from healthy MSCs, and their gene expression profiles may be predictive of myeloma patient outcomes. Here we directly investigate how MM cells affect the differentiation capacity and gene expression profiles of preadipocytes and bone marrow MSCs. Our studies reveal that MM.1S cells cause a marked decrease in lipid accumulation in differentiating 3T3-L1 cells. Also, MM.1S cells or MM.1S-conditioned media altered gene expression profiles of both 3T3-L1 and mouse bone marrow MSCs. 3T3-L1 cells exposed to MM.1S cells before adipogenic differentiation displayed gene expression changes leading to significantly altered pathways involved in steroid biosynthesis, the cell cycle, and metabolism (oxidative phosphorylation and glycolysis) after adipogenesis. MM.1S cells induced a marked increase in 3T3-L1 expression of MM-supportive genes including Il-6 and Cxcl12 (SDF1), which was confirmed in mouse MSCs by qRT-PCR, suggesting a forward-feedback mechanism. In vitro experiments revealed that indirect MM exposure prior to differentiation drives a senescent-like phenotype in differentiating MSCs, and this trend was confirmed in MM-associated MSCs compared to MSCs from normal donors. In direct co-culture, human mesenchymal stem cells (hMSCs) exposed to MM.1S, RPMI-8226, and OPM-2 prior to and during differentiation, exhibited different levels of lipid accumulation as well as secreted cytokines. Combined, our results suggest that MM cells can inhibit adipogenic differentiation while stimulating expression of the senescence associated secretory phenotype (SASP) and other pro-myeloma molecules. This study provides insight into a novel way in which MM cells manipulate their microenvironment by altering the expression of supportive cytokines and skewing the cellular diversity of the marrow.

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RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

International Journal of Molecular Sciences ◽

10.3390/ijms20236098 ◽

2019 ◽

Vol 20 (23) ◽

pp. 6098 ◽

Cited By ~ 1

Author(s):

Amarinder Singh Thind ◽

Kumar Parijat Tripathi ◽

Mario Rosario Guarracino

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Web Application ◽

Cellular Response ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Experimental Conditions ◽

Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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Effect of cell source and osteoblast differentiation on gene expression profiles of mesenchymal stem cells derived from bone marrow or adipose tissue

Journal of Cellular Biochemistry ◽

10.1002/jcb.28463 ◽

2019 ◽

Vol 120 (7) ◽

pp. 11842-11852 ◽

Cited By ~ 5

Author(s):

Simone Ortiz Moura Fideles ◽

Adriana Cassia Ortiz ◽

Amanda Freire Assis ◽

Max Jordan Duarte ◽

Fabiola Singaretti Oliveira ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Bone Marrow ◽

Mesenchymal Stem Cells ◽

Adipose Tissue ◽

Osteoblast Differentiation ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cell Source

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Maturation-associated gene expression profiles during normal human bone marrow erythropoiesis

Cell Death Discovery ◽

10.1038/s41420-019-0151-0 ◽

2019 ◽

Vol 5 (1) ◽

Cited By ~ 4

Author(s):

Fabiana V. Mello ◽

Marcelo G. P. Land ◽

Elaine. S. Costa ◽

Cristina Teodósio ◽

María-Luz Sanchez ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Human Bone ◽

Human Bone Marrow ◽

Normal Human ◽

Normal Human Bone Marrow

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Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles

Journal of Translational Medicine ◽

10.1186/s12967-018-1589-1 ◽

2018 ◽

Vol 16 (1) ◽

Cited By ~ 4

Author(s):

Angelina Boccarelli ◽

Flavia Esposito ◽

Mauro Coluccia ◽

Maria Antonia Frassanito ◽

Angelo Vacca ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Matrix Factorization ◽

Nonnegative Matrix Factorization ◽

Expression Profiles ◽

Nonnegative Matrix ◽

Gene Expression Profiles ◽

Automatic Extraction ◽

Factorization Approach ◽

Bone Marrow Fibroblasts

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Interaction of Stem Cells and Their Niche: Behavior and Gene Expression Profiles of CD34+/CD38− Cells upon Co-Cultivation with AFT024.

Blood ◽

10.1182/blood.v104.11.1281.1281 ◽

2004 ◽

Vol 104 (11) ◽

pp. 1281-1281

Author(s):

Wolfgang Wagner ◽

Rainer Saffrich ◽

Ute Wirkner ◽

Volker Eckstein ◽

Jonathon Blake ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Bone Marrow ◽

Differential Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Nuclear Antigen ◽

Cd34 Cells ◽

Differential Gene ◽

The Impact

Abstract Cell-cell contact between stem cells and cellular determinants of the microenvironment plays an essential role in the regulation of self-renewal and differentiation. The stromal cell line derived from murine fetal liver (AFT024) has been shown to support maintenance of primitive human hematopoietic progenitor cells (HPC) in vitro. We have studied the interaction between HPC (defined as CD34+/CD38− umbilical cord blood cells) and AFT024 and the impact of co-cultivation on the behavior and gene expression of HPC. By time lapse microscopy the mobility and behavior of CD34+/CD38− cells were monitored. Approximately 30% of the CD34+/CD38− cells adhered to the cellular niche through an uropod. CD44 and CD34 were co-localized at the site of contact. Gene expression profiles of CD34+/CD38− cells were then compared upon co-cultivation either with or without AFT024. After cultivation for 16h, 20h, 48h or 72h the HPC were separated form the feeder layer cells by a second FAC-Sort. Differential gene expression was analyzed using our Human Genome cDNA Microarray of over 51,145 ESTs. Among the genes with the highest up-regulation in contact with AFT024 were several genes involved in cell adhesion, proliferation and DNA-modification including tubulin genes, ezrin, complement component 1 q subcomponent 1 (C1QR1), proto-oncogene proteins c-fos and v-fos, proliferating cell nuclear antigen (PCNA), HLA-DR, gamma-glutamyl hydrolase (GGH), minichromosome maintenance deficient 6 (MCM6), uracil-DNA glycolase (UNG) and DNA-methyltransferase 1 (DNMT1). In contrast, genes that were down-regulated after contact with AFT024 included collagenase type iv (MMP2), elastin (ELN) and hemoglobin genes. Differential expression of six genes was confirmed by RT-PCR. Other authors have reported on the differential gene expression profiles of CD34+ cells derived from the bone marrow versus those from G-CSF mobilized blood. As CD34+ cells from the bone marrow might represent cells exposed to the natural HPC niche we have then compared our findings with these experiments. In these comparisons we identified several overlapping genes that are involved in regulation of cell cycle and DNA repair including PCNA, DNMT1, MCM6, MCM2, CDC28 protein kinase regulatory subunit 1B (CKS1B), Topoisomerase II (TOP2a), DNA Ligase 1 (LIG1) and DNA mismatch repair protein MLH1. All these genes were up-regulated among CD34+/CD38− cells upon co-culture with AFT024, as well as among CD34+ cells derived from the bone marrow versus those from peripheral blood. Our studies support the hypothesis that intimate contact and adhesive interaction of HPC with their niche profoundly influenced their proliferative potential and their differentiation program.

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Gene Expression Profiling of Murine HOXB4-Transduced HSCs Shows Multiple Counter-Regulatory Signals That May Control HSC Pool Size

Blood ◽

10.1182/blood.v118.21.2361.2361 ◽

2011 ◽

Vol 118 (21) ◽

pp. 2361-2361

Author(s):

Hui Yu ◽

Sheng Zhou ◽

Geoffrey A. Neale ◽

Brian P. Sorrentino

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Bone Marrow Cells ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Expression Array ◽

Self Renewal ◽

Time Points ◽

Time Point

Abstract Abstract 2361 HOXB4 is a homeobox transcription factor that can induce hematopoietic stem cell (HSC) expansion both in vivo and in vitro. An interesting feature of HOXB4-induced HSC expansion is that HSC numbers do not exceed normal levels in vivo due to an unexplained physiological capping mechanism. To gain further insight into HOXB4 regulatory signals, we transplanted mice with bone marrow cells that had been transduced with a MSCV-HOXB4-ires-YFP vector and analyzed gene expression profiles in HSC-enriched populations 20 weeks after transplant, a time point at which HSC numbers have expanded to normal levels but no longer increasing beyond physiologic levels. We used Affymetrix arrays to analyze gene expression profiles in bone marrow cells sorted for a Lin−Sca-1+c-Kit+ (LSK), YFP+ phenotype. Using ANOVA, we identified1985 probe sets with >2 fold difference in expression (FDR<, 0.1) relative to a control vector-transduced LSK cells. A cohort of genes was identified that were known positive regulators of HSC self-renewal and proliferation. Hemgn, which we identified in a previous screen as a positive regulator of expansion and a direct transcriptional target of HOXB4, was 3.5 fold up-regulated in HOXB4 transduced LSKs. Other genes known to be important for HSCs survival, self-renewal and differentiation were upregulated to significant levels including N-myc, Meis1, Hoxa9, Hoxa10 and GATA2. Microarray data for selected genes was validated by quantitative real-time PCR on HOXB4 transduced CD34low LSK cells, a highly purified HSC population, obtained from another set of transplanted mice at the 20 week time point. In contrast, other gene expression changes were noted that would potentially limit or decrease stem cell numbers. PRDM16, a set domain transcription factor critical for HSC maintenance and associated with clonal hematopoietic expansions when inadvertently activated as a result of retroviral insertion, was dramatically down-regulated on the expression array and 7.6 fold decreased in the real time PCR assay of CD34low LSK cells. TFG-beta signaling is a well defined inhibitor HSC proliferation and utilize Smad proteins as downstream effectors. Expression of Smad1 and Smad7 were significantly upregulated on the LSK expression array and 8.1 and 3.5 fold up-regulated by qPCR in CD34low LSK cells. Another potential counter-regulatory signal was down regulation of Bcl3 mRNA, a potential anti-apoptotic effector in HSCs. We hypothesize that the HOXB4 expansion program involves activation of genes that lead to increased HSC numbers with later activation of counter-regulatory signals that limit expansion to physiologic numbers of HSCs in vivo. We are now examining how this program changes at various time points after transplantation and hypothesize the capping limits are set at relatively later time points during reconstitution. We also are studying the functional effects of these gene expression changes, and in particular, whether enforced expression of HOXB4 and PRMD16 will result in uncontrolled HSC proliferation and/or leukemia. Disclosures: No relevant conflicts of interest to declare.

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