Global gene expression profiling of primary tumors and lung metastases using a mouse model of spontaneous metastatic mammary carcinoma
ABSTRACT: In this study, we explored the molecular basis of site-specific metastasis of breast cancer to the lungs in a clinically relevant model based on the JygMC(A) cell line. In this dataset, we include expression data from JygMC(A) primary mammary tumors, lung metastases, normal mammary glands and normal lung parenchyma. In total, 28 samples were analyzed. We generated the following pairwise comparisons using Partek Genomic Suite 6.6 (PGS, Version 6.6, Partek Inc.): PT vs. NMG; PT vs. LM; LM vs. NL; LM vs. NMG. Genes with an FDR-adjusted p-value < 0.05 and a fold-change > 2 were selected.
Project description:Ph-negative myeloproliferative neoplasms (MPNs) are characterized by many somatic mutations which have already been shown useful in the prognostic assessment of MPN patients. Moreover, aberrant microRNA (miRNA) expression seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported. In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained gene- (GEP) and miRNA expression profiles (miEP) of CD34+ cells from 31 healthy donors and 42 PMF patients using Affymetrix technology (HG-U219 and miRNA 2.0 arrays). Differentially expressed genes (DEG) and miRNAs (DEM) were sorted out by means of Partek Genomic Suite vs 6.6. Since each miRNA can target many mRNAs while a single mRNA can be targeted by multiple miRNAs, we performed Integrative Analysis (IA) by means of Ingenuity Pathway Analysis (IPA) to untangle this combinatorial complexity. In particular, IPA points out DEM-DEG pairs among experimentally validated interactions from TarBase, miRecords and Ingenuity Expert Findings as well as predicted microRNA-mRNA interactions from TargetScan. IPA microRNA Target Filter was then employed to select only the DEM-DEG pairs showing an anti-correlated expression pattern and to build regulatory networks. Finally, 3'UTR luciferase reporter assays were performed to validate IPA predicted miRNA-mRNA interactions. This study allowed the identification of different networks possibly involved in PMF onset and progression, highlighting an aberrant cross-regulation in miRNA-targets involved in malignant hematopoiesis. Furthermore, Integrative analysis was proved a powerful tool to unravel miRNA-mRNA interactions in functional networks, shedding light on the potential contribution of miRNAs to PMF pathogenesis. Gene expression profile (GEP) and miRNA expression profile (miEP) were performed starting from the same totalRNA of CD34+ cells from 42 PMF patients and 31 healthy donors (n=16 PB CD34+, n=15 BM CD34+) (1 replicate for each sample). In particular, GEP and miEP were performed on 23 PMF patients carrying the mutation JAK2V617F and 19 wild-type samples.
Project description:MicroRNA expression profiling was performed in human BMSCs at 0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 7 days. RNA quantity and quality was assessed spectrophotometrically with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) with Agilent RNA 6000 Nano Kit for total RNA. The latest version of Affymetrix platform for miRNA expression analysis (Genechip miRNA 2.0 array) based on mirBase version 12 (http://www.mirbase.org/) was used to obtain miRNA profiles. Normalization and statistical analysis were performed with Partek Genomic Suite 6.6 software by means of ANOVA test. Fold-change (FC) and p-values were applied to generate miRNA differentially expressed lists.
Project description:HCT116 microarray done 12 hours after treatment with DMSO (control) or Nutlin Total RNA from HCT116 cells was harvested with an RNeasy kit (Qiagen) and analyzed on Affymetrix HuGene 1.0 ST arrays following the manufacturer’s instructions. Microarray data were processed using Partek Genomics Suite 6.6. Anova was used to call differentially expressed genes for which any isoform showed a fold change > |+/-1.5| with FDR <0.05. There were 362 genes called as upregulated and 367 genes as downregulated.
Project description:Goal for this study is to identified miRNA involved in metastasis development using PLC8024 and MHCC97H derived cell lines. PLC8024 derived cell lines, PLC-PT (Primary Tumor) and PLC-LM (Lung Metastasis), and MHCC97H derived cell lines, MHCC97H-PT and MHCC97H-LM were compared using the Ncode miRNA microarray platform. The experiment were repeat twice with dye-swap.
Project description:Background: Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods: We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 “ovarian cancer” cell lines has been classified into histological types using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results: Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histological type of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic “ovarian carcinoma” cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. The DNA copy number of 10 ovarian cancer cell lines was examined and changes in copy number of genes whose expression is assumed to be critical to the phenotype of ovarian clear cell carcinoma was evaluated. Copy number data was estimated from signal intensity on Affmetrix SNP 6.0 arrays. Copy number ratio values were generated in Partek Genomics Suite (v 6.6) using a Partek corporation distributed baseline file of normal (2N) genomic DNA and default parameters. Post import values were corrected for localized GC content using the inbuilt Partek feature based on methods described in Diskin et al. (Nucleic Acids Research. 2008. 36:19). The characteristic "literature reported histotype" is the reported histological subtype for each cell line from the originating laboratory or cell bank (repository). The characteristic "Predicted histology" is based on parameters described in Anglesio et al. (PLOS ONE 2013. in press), including immunohistochemical phenotype, presence of typical mutations, consistency in growth characteristics, and DNA copy number. All cell lines were grown under recomended conditions, collected near confluence (80%) and not subjected to any experimental treatments or modifications.
Project description:Prostate cancer (PCa) tends to be more aggressive and lethal in African Americans (AA) compared to European Americans (EA). To further understand the biological factors accounting for the PCa disparities observed in AA and EA patients, we performed gene profiling analysis using Affymetrix human exon 1.0 ST arrays to identify the differentially expressed genes in EA PCa vs. EA normal. 30 prostate biopsy specimens (tumor and adjacent normal tissues) were collected from 15 European American prostate cancer patients. RNA samples, purified from the collected biopy specimens, were process and applied to Affymetrix human exon ST 1.0 arrays. Array data was normalized, batch-corrected and analyzed (2-way ANOVA) using Partek Genomics Suite program.
Project description:We used microarrays to compare the gene expression profile in cultured primary neurospheres derived from the subventricular zone of adult (2 m.o.) offspring of mothers treated with PBS or methylglyoxal during pregnancy Primary neurospheres derived from 2-month-old adult CD1 mice born to mothers treated with PBS or MG twice daily from gestational day 12 until delivery were collected, and total RNA extracted. cDNA was hybridized on Affymetrix Mouse Gene 2.0 ST Array and gene expression was analyzed using Partek software. In total, 3 PBS treated and 3 MG treated mice were used.
Project description:Goal for this study is to identified miRNA involved in metastasis development using PLC8024 and MHCC97H derived cell lines. Overall design: PLC8024 derived cell lines, PLC-PT (Primary Tumor) and PLC-LM (Lung Metastasis), and MHCC97H derived cell lines, MHCC97H-PT and MHCC97H-LM were compared using the Ncode miRNA microarray platform. The experiment were repeat twice with dye-swap.
Project description:We over-expressed an epigenetic regulator in a glioblastoma (GBM) primary culture from an adult patient. These GBM cells have cancer stem cell phenotypes, as they have self-renewal properties and tumor initiation potential when transplanted in immunocompromised mice. An epigenetic regulator (ER) was over-expressed in the GBM primary culture G514NS. EGFP was expressed from the same vector backbone as a control. N = 3 biological replicates for each of EGFP- and ER-overexpressing cells. Please note that complete data output (with 74,342 data rows) from Partek analysis contains several identifiers which are not represented in the GPL17586, and therefore is linked as Series supplementary file.
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived femoral diaphysis and metaphysis transcriptome profiling (RNA-seq) to determine pathways and networks dependent on Dlx3 during bone development and homeostasis. Methods: mRNA profiles of diaphysis and metaphysis isolated from the femur of 5-week-old wild-type (WT) and Dlx3Oc-cKO (OC-cre;Dlx3f/-) conditional knockout mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level by ANOVA (ANOVA) and TopHat. qRT-PCR validation was performed using SYBR Green assay. Results: RNA-Seq data were generated with Illumina's HiSeq 2000 system. Raw sequencing data were processed with CASAVA 1.8.2 to generate fastq files. Reads of 50 bases were mapped to the mouse transcriptome and genome mm9 using TopHat 1.3.2. Gene expression values (RPKM) were calculated with Partek Genomics Suite 6.6, which was also used for the ANOVA analysis to determine significantly differentially expressed genes. Conclusions: Our study represents the first detailed analysis of Dlx3Oc-cKO diaphysis and metaphysis from femurs, with biologic triplicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Diaphysis and metaphysis mRNA profiles of metaphysis and diaphysis from femurs of 5-wk-old (WT) and Dlx3Oc-cKO male mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000.