Project description:To date, little evidence of miRNA expression/deregulation in multiple myeloma (MM) has been reported. To characterize miRNA expression profiling of MM plasma cells (PCs) and integrate miRNA expression data with other molecular features of MM patients, global miRNA expression profiles were generated for PCs isolated from BM biopsies of 38 newly diagnosed MM, 2 plasma cell leukemia patients, and 3 healthy donors; the samples were also profiled for global gene expression, and nineteen of them underwent genome-wide DNA analysis using high-density SNP-microarrays. Differential miRNA expression patterns were mainly identified in association with the major IGH translocations: in particular, t(4;14) showed specific over-expression of let-7e, miR-125a-5p and miR-99b belonging to a cluster at 19q13.33. The occurrence of other lesions, such as 1q gain, 13q and 17p deletions, and hyperdiploidy, was less well characterized by specific miRNA signatures. Genome-wide analysis showed that some allelic imbalances led to the significantly altered expression of miRNAs located in the involved regions, such as let-7b at 22q13.31 loss and miR-142-3p at 17q22 gain. The integrative analysis based on computational target prediction, miRNA and mRNA profiling defined a network of putative functional miRNA-target regulatory relations supported by expression data. This series of microarray experiments contains the microRNA profiles of purified plasma cells (PCs) obtained from 3 normal donor (N), 38 multiple myeloma (MM) and 2 plasma cell leukemia (PCL) at diagnosis. PCs were purified from bone marrow specimens after red blood cell lysis with 0.86% ammonium chloride using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by morphology and flow cytometry and was >90% in all cases. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labeled RNA which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and hybridized on an Agilent microarray (G4470B) at 55Â°C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 9.5 software (Agilent Technologies) was used to obtain the raw microarray data. The human miRNAs included in the platform were annotated according to Sanger miRBase Release 12.0. After discarding non-human miRNAs, the data were normalized using the Aroma Light package for Bioconductor. To overcome scaling biases due to background subtraction, the data were converted to obtain positive values throughout the dataset, at a minimum value of 1. The global gene expression raw data used in this study was originally deposited as GSE13591 and renormalized for this study. The genome wide profile (DNA) analysis was originally deposited as GSE16121.

Project description:Osteosarcoma (OS) and Ewing’s sarcoma (EW) are the two most common pediatric solid tumors, after brain tumors. Multimodal treatments have significantly improved prognosis in localized disease but outcome is still poor in metastatic patients, for whom therapeutic options are often inadequate. Preclinical drug testing to identify promising treatment options that match the molecular make-up of these tumors is hampered by the lack of appropriate and molecularly well-characterized patient-derived models. To address this need, a panel of patient-derived xenografts (PDX) was established by subcutaneous implantation of fresh, surgically resected OS and EW tumors in NSG mice. Tumors were re-transplanted to next mice generations and fragments were collected for histopathological and molecular characterization. A model was considered established after observing stable histological and molecular features for at least three passages. To evaluate the similarity of the model with primary tumor, we performed a global gene expression profiling and tissue microarrays (TMA), to assess tumor specific biomarkers on tissues from OS/EW tumors and their PDXs (1st and 3rd passage). Moreover, we verified the feasibility of these models for preclinical drug testing. We implanted 61 OS and 29 EW samples: 14/38 (37%) primary OS and 9/23 (39%) OS lung metastases successfully engrafted; while among EW, 5/26 (19%) primary samples and 1/3 (33%) metastases were established. Comparison between patient samples and PDXs, highlighted that histology and genetic characteristics of PDXs were stable and maintained over passages. In particular, correlative analysis between OS and EW samples and their PDXs was extremely high (Pearson’s r range r=0.94-0.96), while patient-derived primary cultures displayed reduced correlation with human samples (r=0.90-0.93), indicating that in vitro adaptation superimpose molecular alterations that create genetic diversion from original tumors. No significant differentially expressed gene profile was observed from the comparison between EW samples and PDXs (fold change > 2, adjusted p <0.05 at paired t-test). In OS, the comparison between OS patient-derived tumors and PDX indicated differences in 397 genes, mostly belonging to immune system functional category. This is in line with the idea that human immune cells are gradually replaced by murine counterparts upon engraftment in the mouse. As proof-of concept, two EW PDX and one OS PDX have been treated with conventional and innovated drugs to test their value in terms of drug-sensitivity prediction. Overall, our study indicated that PDX models maintained the histological and genetic markers of the tumor samples and represent reliable models to test sensitivity to novel drug associations.

Project description:Primary plasma cell leukemia (pPCL) is a rare and very aggressive form of plasma cell dyscrasias. To date, no information of microRNA expression in pPCL has been reported. To investigate the role of miRNAs in pPCL, we analyzed global miRNA expression profiles of highly purified malignant plasma cells from 18 previously untreated patients included in a prospective clinical trial. MiRNA expression patterns were evaluated in the context of the molecular abnormalities of the disease and in comparison with a representative cohort of multiple myeloma (MM) patients. We identified a series of deregulated miRNAs in pPCL (42 up-regulated and 41 down-regulated) which may have a putative role in contributing to tumor progression in MM. Furthermore, we integrated miRNA and gene expression data with computational prediction of miRNA targets, finding that miRNAs differentially expressed between MM and pPCL could regulate genes with important functions in cancer. Overall, our study represents the first attempt to investigate the involvement of miRNAs in pPCL and may contribute to develop functional approaches to investigate the activity of deregulated miRNAs in aggressive forms of plasma cell dyscarsias and their possible role as novel therapeutic targets. This series of microarray experiments contains the microRNA profiles of purified plasma cells (PCs) obtained from 39 multiple myeloma (MM) and 18 primary plasma cell leukemia (pPCL) at diagnosis. PCs were purified from bone marrow specimens, after red blood cell lysis with 0.86% ammonium chloride, using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by morphology and flow cytometry and was > 90% in all cases. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labelled RNA, which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and then hybridized on an Agilent microarray (G4470B) at 55M-BM-!C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 10.7.3.1 software (Agilent Technologies) was used to obtain the microarray raw-data. The raw gTotalGeneSignal has been recalculated using the procedures described in Agilent Feature Extraction Software version 10.1 manual. Non-human probes, miRNAs flagged as M-CM-^RabsentM-CM-^S (i.e. expressed below background levels) throughout the whole dataset and miRNAs expired according to Sanger miRBase Release 15 (April 2010) were discarded, and a quantile normalization was applied on raw data using the aroma.light package for Bioconducor. The data were then converted to obtain positive values throughout the dataset, at a minimum value of 1, and log2 transformed.

Dataset Information

Ewing's sarcoma miRNA expression

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