8 research outputs found
Mapping transcription mechanisms from multimodal genomic data
Background
Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data.
Results
We develop a method to identify eQTLs. The method represents eQTLs as information flux between genetic variants and transcripts. We use information theory to simultaneously interrogate SNP and gene expression data, resulting in a Transcriptional Information Map (TIM) which captures the network of transcriptional information that links genetic variations, gene expression and regulatory mechanisms. These maps are able to identify both cis- and trans- regulating eQTLs. The application on a dataset of leukemia patients identifies eQTLs in the regions of the GART, PCP4, DSCAM, and RIPK4 genes that regulate ADAMTS1, a known leukemia correlate.
Conclusions
The information theory approach presented in this paper is able to infer the dependence networks between SNPs and transcripts, which in turn can identify cis- and trans-eQTLs. The application of our method to the leukemia study explains how genetic variants and gene expression are linked to leukemia.National Human Genome Research Institute (U.S.) (R01HG003354)National Institute of Allergy and Infectious Diseases (U.S.) (U19 AI067854-05)National Heart, Lung, and Blood Institute (grant T32 HL007427-28)National Institutes of Health (U.S.) (grant K99 LM009826
Influence of the interaction between nodal fibroblast and breast cancer cells on gene expression
Our aim was to evaluate the interaction between breast cancer cells and nodal fibroblasts, by means of their gene expression profile. Fibroblast primary cultures were established from negative and positive lymph nodes from breast cancer patients and a similar gene expression pattern was identified, following cell culture. Fibroblasts and breast cancer cells (MDA-MB231, MDA-MB435, and MCF7) were cultured alone or co-cultured separated by a porous membrane (which allows passage of soluble factors) for comparison. Each breast cancer lineage exerted a particular effect on fibroblasts viability and transcriptional profile. However, fibroblasts from positive and negative nodes had a parallel transcriptional behavior when co-cultured with a specific breast cancer cell line. The effects of nodal fibroblasts on breast cancer cells were also investigated. MDA MB-231 cells viability and migration were enhanced by the presence of fibroblasts and accordingly, MDA-MB435 and MCF7 cells viability followed a similar pattern. MDA-MB231 gene expression profile, as evaluated by cDNA microarray, was influenced by the fibroblasts presence, and HNMT, COMT, FN3K, and SOD2 were confirmed downregulated in MDA-MB231 co-cultured cells with fibroblasts from both negative and positive nodes, in a new series of RT-PCR assays. In summary, transcriptional changes induced in breast cancer cells by fibroblasts from positive as well as negative nodes are very much alike in a specific lineage. However, fibroblasts effects are distinct in each one of the breast cancer lineages, suggesting that the inter-relationships between stromal and malignant cells are dependent on the intrinsic subtype of the tumor
Clinical stage and histological type of the most common carcinomas diagnosed in young adults in a reference cancer hospital
Differential regulation of vitamin D receptor expression in distinct leukemic cell lines upon phorbol ester-induced growth arrest
A close correlation between vitamin D receptor (VDR) abundance and cell proliferation rate has been shown in NIH-3T3 fibroblasts, MCF-7 breast cancer and in HL-60 myeloblastic cells. We have now determined if this association occurs in other leukemic cell lines, U937 and K562, and if VDR content is related to c-myc expression, which is also linked to cell growth state. Upon phorbol myristate acetate (PMA) treatment, cells from the three lineages (HL-60, U937 and K562) differentiated and expressed specific surface antigens. All cell lines analyzed were growth inhibited by PMA and the doubling time was increased, mainly due to an increased fraction of cells in the G0/G1 phase, as determined by flow cytometry measurements of incorporated bromodeoxpuridine and cell DNA content. C-myc mRNA expression was down-regulated and closely correlated to cell growth arrest. However, VDR expression in leukemic cell lines, as determined by immunofluorescence and Northern blot assays, was not consistently changed upon inhibition of cell proliferation since VDR levels were down-regulated only in HL-60 cells. Our data suggest that VDR expression cannot be explained simply as a reflection of the leukemic cell growth state.33555956
Gene expression signatures of pediatric myelodysplastic syndromes are associated with risk of evolution into acute myeloid leukemia
Integrated differential transcriptome maps of Acute Megakaryoblastic Leukemia (AMKL) in children with or without Down Syndrome (DS)
BACKGROUND: The incidence of Acute Megakaryoblastic Leukemia (AMKL) is 500-fold higher in children with Down Syndrome (DS) compared with non-DS children, but the relevance of trisomy 21 as a specific background of AMKL in DS is still an open issue. Several Authors have determined gene expression profiles by microarray analysis in DS and/or non-DS AMKL. Due to the rarity of AMKL, these studies were typically limited to a small group of samples. METHODS: We generated integrated quantitative transcriptome maps by systematic meta-analysis from any available gene expression profile dataset related to AMKL in pediatric age. This task has been accomplished using a tool recently described by us for the generation and the analysis of quantitative transcriptome maps, TRAM (Transcriptome Mapper), which allows effective integration of data obtained from different experimenters, experimental platforms and data sources. This allowed us to explore gene expression changes involved in transition from normal megakaryocytes (MK, n=19) to DS (n=43) or non-DS (n=45) AMKL blasts, including the analysis of Transient Myeloproliferative Disorder (TMD, n=20), a pre-leukemia condition. RESULTS: We propose a biological model of the transcriptome depicting progressive changes from MK to TMD and then to DS AMKL. The data indicate the repression of genes involved in MK differentiation, in particular the cluster on chromosome 4 including PF4 (platelet factor 4) and PPBP (pro-platelet basic protein); the gene for the mitogen-activated protein kinase MAP3K10 and the thrombopoietin receptor gene MPL. Moreover, comparing both DS and non-DS AMKL with MK, we identified three potential clinical markers of progression to AMKL: TMEM241 (transmembrane protein 241) was the most over-expressed single gene, while APOC2 (apolipoprotein C-II) and ZNF587B (zinc finger protein 587B) appear to be the most discriminant markers of progression, specifically to DS AMKL. Finally, the chromosome 21 (chr21) genes resulted to be the most over-expressed in DS and non-DS AMKL, as well as in TMD, pointing out a key role of chr21 genes in differentiating AMKL from MK. CONCLUSIONS: Our study presents an integrated original model of the DS AMLK transcriptome, providing the identification of genes relevant for its pathophysiology which can potentially be new clinical markers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-014-0063-z) contains supplementary material, which is available to authorized users
Gene expression profiling in MDS and AML: potential and future avenues
Today, the classification systems for myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) already incorporate cytogenetic and molecular genetic aberrations in an attempt to better reflect disease biology. However, in many MDS/AML patients no genetic aberrations have been identified yet, and even within some cytogenetically well-defined subclasses there is considerable clinical heterogeneity. Recent advances in genomics technologies such as gene expression profiling (GEP) provide powerful tools to further characterize myeloid malignancies at the molecular level, with the goal to refine the MDS/AML classification system, incorporating as yet unknown molecular genetic and epigenetic pathomechanisms, which are likely reflected by aberrant gene expression patterns. In this study, we provide a comprehensive review on how GEP has contributed to a refined molecular taxonomy of MDS and AML with regard to diagnosis, prediction of clinical outcome, discovery of novel subclasses and identification of novel therapeutic targets and novel drugs. As many challenges remain ahead, we discuss the pitfalls of this technology and its potential including future integrative studies with other genomics technologies, which will continue to improve our understanding of malignant transformation in myeloid malignancies and thereby contribute to individualized risk-adapted treatment strategies for MDS and AML patients