MicroRNA expression profiles in bone marrow fractions from gastric cancer patients
ABSTRACT: Both disseminated tumor cells and noncancerous host cells contributed to cancer progression cooperatively in bone marrow. Bone marrow samples were obtained from 4 gastric cancer patients, and were separated into 3 fractions (CD45 positive, CD45 negative/EpCAM positive, and CD14 positive fractions) by the automagnetic-activated cell separation (AutoMACS) system using CD45, EpCAM, and CD14 microbeads (Miltenyi Biotec, Germany). microRNA expression profiles in each fractions were evaluated in order to identify candidate prognostic markers for gastric cancer patients. In 4 patients with gastric cancer, bone marrow samples (40 mL) were obtained from iliac bones. Nucleated cells were collected by gradient centrifugation using Ficoll-Paque PREMIUM (GE Healthcare Life Science, USA) and Leucosep (Greiner Bio-One, Germany) according to the manufacturer’s instructions. Next, we separated bone marrow cells into 3 fractions using MACS: CD45 positive (CD45+), CD45 negative/EpCAM positive (CD45-/EpCAM+), and CD14 positive (CD14+). microRNA expression levels of whole bone marrow cells and each fractions were measured by the miRCURY™ LNA array microarray (6th gen-hsa, mmu & rno#208402, Exiqon, Vedbaek, Denmark). The miRCURY™ LNA array microarray slides were scanned using the Agilent G2505C Microarray Scanner System (Agilent Technologies, Inc., USA) and the data analysis was carried out using the Feature Extraction 10.7.3.1 (Agilent Technologies, Inc., USA).
Project description:To further development of our gene expression approach to biodosimetry, we have employed microRNA microarray expression profiling to identify genes with the potential to distinguish liver metastasis related microRNA. Colorectal cancer patients were administered anesthesia and 20 mL BM was taken from the right and left anterior iliac crests before surgery. Mononucleated cells were collected using a standard Ficoll-Hypaque gradient technique. To enrich for EpCAM+ cells, CD14+ cells were removed from the whole bone marrow using auto MACSTM pro (Milteny Biotec, Bergisch Gladbach, Germany) with anti-CD14 immunomagnetic beads (clone; TÜK4, Milteny Biotec). Next, CD45+ cells were removed by treatment with anti-CD45 immunomagnetic beads (clone; 5B1; Milteny Biotec). The residual CD14−CD45− cells were then incubated with FcR blocking reagent (Milteny Biotec), followed by incubation with anti-EpCAM immunomagnetic beads (clone; HEA-125, Milteny Biotec), and the CD14−CD45−EpCAM+ cells were taken up. Total RNA of these cells we analyzed the microRNA levels of CD14−CD45−EpCAM+ cells obtained from non-metastasis patients (n = 12) and liver metastasis patients (n = 7). Ten-microRNA consensus signature was identified that distinguished between CD14−CD45−EpCAM+ cells from liver metastasis patients and CD14−CD45−EpCAM+ cells from non-liver metastasis patients. MicroRNA expression of CD14-CD45-EpCAM+ cells in human bone marrow was measured. RNA of these cells we analyzed the microRNA levels of CD14−CD45−EpCAM+ cells obtained from non-metastasis patients (n = 12) and liver metastasis patients (n = 7).
Project description:To identify the role of miRNAs in patient bone marrow (BM) and explore the function of these molecules during HCC progression, we employed microarray-based profiling to analyze miRNA expression in the BM of patients with HCC. MicroRNA expression in the BW of HCC patients was measured by using microarray-based profiling. BM cells were separated into 3fraction by cell surface markers as follows: CD45+(macrophage), CD14-/CD45+(lymphocyte) and CD14-/CD45-/EpCAM+(epithelial cell).
Project description:This article describes a mass spectrometry data set generated from osteogenic differentiated bone marrow stromal cells (BMSCs) and adipose tissue derived stromal cells (ASCs) of a 24-year old healthy donor spiked with iRT peptides. Cells have been identified via FACS-Analysis positive for CD90 and CD105 and negative for CD14, CD34, CD45 and CD11b and tri-lineage differentiation. Obtaining a sufficient amount of high-quality tissue is the key limiting factor for establishing a region-specific spectral library. Hence, combining existing spectral libraries for data-independent acquisition analysis (DIA) can overcome this major limitation. Moreover, these data can be used to map region-specific proteins and to model region-specific pathways. Both can improve our understanding of the functioning in greater depth. In addition, these data can also be used to determine the optimal settings for measuring proteins and peptides of interest. To create the specific spectral library, the tissue was first homogenized and then fractionated via different types of SDS gel electrophoresis, resulting in 11 fractions. These fractions were analysed by nanoHPLC-ESI-MS/MS, resulting in 24 data files.
Project description:Human mucosa was collected from two different individuals undergoing colectomy. After treatment with EDTA, colonic crypts were isolated and further dis-aggregated using Dispase. Next, cells were stained using antibodies directed against the extracellular domain of EpCAM, PTK7, CD11, CD31, and CD45. Cells were analyzed and sorted via flow cytometry (BD Aria). After excluding non-epithelial cells (Epcam. CD11, CD31, and CD45 negative), the EpCAM positive fraction was divided into fractions expressing either high, medium, low, or negative levels of PTK7. Sorted cells were transferred to Trizol for RNA extraction and RNA was purified using the Qiagen RNA Mini Kit. Colonic crypts were isolated from normal human mucosa derived from individuals undergoing colectomy. Single cell fractions from these crypts were sorted and isolated RNA processed and hybridized to Affymetrix PrimeView Arrays
Project description:Adipose tissue from 6 non-obese patients was collagenase treated and adipocytes separated from the stromal vascular fraction(SVF). SVF was then FACS sorted for the following fractions CD45-/CD34+/CD31+ (endothelial), CD45-/CD34+/CD31- (progenitor), CD45+/CD14+ (monocyte/macrophage), CD45+/CD14-(Leukocyte). RNA was isolated from adipocyte, SVF, progenitor, macrophage/monocyte and leukocyte fractions and analyzed on the Affymetrix Human Transcriptome 2.0 array. We also sorted SVF from an additional 13 (10 non-obese, 9 obese) patients and sent progenitor RNA for Affymetrix Human Transcriptome 2.0 array analysis. Overall design: Adipose tissue from 6 non-obese patients was collagenase treated and adipocytes separated from the stromal vascular fraction(SVF). SVF was then FACS sorted for the following fractions CD45-/CD34+/CD31+ (endothelial), CD45-/CD34+/CD31- (progenitor), CD45+/CD14+ (monocyte/macrophage), CD45+/CD14-(Leukocyte). RNA was isolated from adipocyte, SVF, progenitor, macrophage/monocyte and leukocyte fractions and analyzed on the Affymetrix Human Transcriptome 2.0 array. We also sorted SVF from an additional 13 (10 non-obese, 9 obese) patients and sent progenitor RNA for Affymetrix Human Transcriptome 2.0 array analysis.
Project description:Transcriptome of specific cell types residing in human subcutaneous adipose tissue Overall design: White adipose tissue (WAT) from 3 lean and 3 overweight-obese patients was collagenase treated and adipocytes were separated from the stromal vascular fraction (SVF). SVF was then FACS sorted for the following fractions CD45-/CD34+/CD31- (progenitor), CD45+/CD14+/CD206+ (total macrophages), CD45+/CD14+/CD206+/CD11c+ (M1 macrophages), CD45+/CD14+/CD206+/CD11c- (M2 macrophages), CD45+/CD3+ (total T cells), CD45+/CD3+/CD4+/CD8- (Th T-cells), CD45+/CD3+/CD4-/CD8+ (Tc T-cells). RNA was isolated from all these fractions as well as from adipocytes and analyzed on the Affymetrix Human ClariomTMD microarray.
Project description:Bone is the most frequent site of metastasis in prostate cancer (PCa) and patients with bone metastases are deemed incurable. Targeting prostate cancer cells that disseminated to the bone marrow (BM) prior to surgery and before metastatic outgrowth may therefore prevent lethal metastasis. This prompted us to directly analyse the transcriptome of disseminated cancer cells (DCC) isolated from non-metastatic (UICC stage M0) prostate cancer patients. We screened 105 BM samples of M0-stage prostate cancer patients and 18 BM samples of patients without malignancy for the presence of EpCAM+ single cells. In total we isolated 270 cells from both groups by micromanipulation and globally amplified their mRNA. We used targeted transcriptional profiling to unambiguously identify DCCs for subsequent in-depth analysis. Transcriptomes of all cells were examined for the expression of EPCAM, KRT8, KRT18, KRT19, KRT14, KRT6a, KRT5, KLK3 (PSA), MAGEA2, MAGEA4, PTPRC (CD45), CD33, CD34, CD19, GYPC, SCL4A1 (band 3), and HBA2. Using these transcripts we found it impossible to reliably identify true DCCs. We then applied combined genome and transcriptome analysis of single cells and found that EpCAM+ cells from controls expressed transcripts thought to be epithelial-specific, while true DCCs may express haematopoietic transcripts. These results point to an unexpected plasticity of epithelial cancer cells in bone marrow and question common transcriptional criteria to identify DCCs. Array-CGH was used to analyze EpCAM-positive single cells isolated from bone marrow of M0-stage prostate cancer patients, and individuals without cancer. The purpose was to demonstrate that cells with genomic aberrations are true tumour cells.
Project description:Different human mTEC subsets (MUC1, CEACAM5 and SGLT1) were purified by sequential enzymatic digestion (collagenase/dispase, trypsin) followed by enrichment using magnetic beads (CD45 beads, Miltenyi Biotech) and FACS sorting. Cells of the surface phenotype CD45-, CDR2-, EpCAM+ were further subdivided into MUC1+/MUC1-, CEACAM5+/CEACAM5- and SGLT1+/SGLT1- fractions. RNA was isolated using μMACS™ SuperAmp™ protocol (Miltenyi Biotec) and hybridized to Illumina Whole-Genome Expression Beadchips. Gene expression of Antigen-positive and Antigen-negative mTEC subsets was compared. Total RNA was isolated from ex-vivo isolated human mTEC subsets using μMACS™ SuperAmp™ protocol (Miltenyi Biotec)