Comparison of oligonucleotide-microarray and serial analysis of gene expression (SAGE) in transcript profiling analysis of megakaryocytes derived from CD34+ cells

Kim, Hyung Lae

doi:10.1038/emm.2003.60

Cited by 54 publications

(28 citation statements)

References 16 publications

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“…Our observations of moderate or low correlations among the two data types agree with previous studies that compared SAGE data to microarray data for other organisms [19][20][21]. By focusing on genes that are most reliably detected in both microarray and MPSS analyses, we are likely to improve the correlations that we have reported here.…”

Section: Conclusion and Prospectssupporting

confidence: 81%

A comparison of global gene expression measurement technologies in Arabidopsis thaliana

Coughlan

Agrawal

2004

Comp Funct Genom

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Microarrays and tag-based transcriptional profiling technologies represent diverse but complementary data types. We are currently conducting a comparison of highdensity in situ synthesized microarrays and massively-parallel signature sequencing (MPSS) data in the model plant, Arabidopsis thaliana. The MPSS data (available at http://mpss.udel.edu/at) and the microarray data have been compiled using the same RNA source material. In this review, we outline the experimental strategy that we are using, and present preliminary data and interpretations from the transcriptional profiles of Arabidopsis leaves and roots. The preliminary data indicate that the log ratio differences of transcripts between leaves and roots measured by microarray data are in better agreement with the MPSS data than the absolute intensities measured for individual microarrays hybridized to only one of the cRNA populations. The correlation was substantially improved by focusing on a subset of genes excluding those with very low expression levels; this selection may have removed noisy data. Future reports will incorporate more than 10 tissues that have been sampled by MPSS.

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Section: Conclusion and Prospectssupporting

confidence: 81%

A comparison of global gene expression measurement technologies in Arabidopsis thaliana

Coughlan

Agrawal

2004

Comp Funct Genom

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“…This finding is not surprising given studies that have demonstrated that a modest agreement between SAGE-and DNA microarray-based profiling data exists and that the correlation improves for genes with higher expression levels. 40,41 It is noteworthy that Dennis et al 6 found an accuracy of 83% when a panel of IHC markers, two of which were identical to our markers, was used. However, there are two major distinctions between that study and our study, beyond the fact that different technologies (IHC vs. qRT-PCR) were used.…”

Section: Discussionmentioning

confidence: 66%

A Quantitative Reverse Transcriptase-Polymerase Chain Reaction Assay to Identify Metastatic Carcinoma Tissue of Origin

Talantov

Baden

Jatkoe

et al. 2006

The Journal of Molecular Diagnostics

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Identifying the primary site in patients with metastatic carcinoma of unknown primary origin can enable more specific therapeutic regimens and may prolong survival. Twenty-three putative tissue-specific markers for lung, colon, pancreatic, breast, prostate, and ovarian carcinomas were nominated by querying a gene expression profile database and by performing a literature search. Ten of these marker candidates were then selected based on validation by reverse transcriptase-polymerase chain reaction (RT-PCR) on 205 formalin-fixed, paraffin-embedded metastatic carcinoma specimens originating from these six and from other cancer types. Next, we optimized the RNA isolation and quantitative RT-PCR methods for these 10 markers and applied the quantitative RT-PCR assay to a set of 260 metastatic tumors. We then built a gene-based algorithm that predicted the tissue of origin of metastatic carcinomas with an overall leaveone-out cross-validation accuracy of 78%. Lastly, our assay demonstrated an accuracy of 76% when tested on an independent set of 48 metastatic samples, 37 of which were either a known primary or initially presented as carcinoma of unknown primary but were subsequently resolved.

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“…In this cohort, most of the identified genes have previously been shown to be expressed in cells of the megakaryocyte lineage. [62][63][64] These include glycoproteins IIb/IIIa (GP1BB and ITGA2B), GATA1, and MRPS12. In addition, we identified a number of novel genes not previously associated with this leukemia subtype.…”

Section: Discussionmentioning

confidence: 99%

Gene expression profiling of pediatric acute myelogenous leukemia

Ross

Mahfouz

Onciu

et al. 2004

Blood

398

416

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Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17) [ PML-RAR␣], t(8;21)[AML1-ETO], inv 16 [CBF␤-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation. IntroductionAcute myeloid leukemia (AML) is a relatively rare malignancy in the pediatric population, comprising only 15% to 20% of the acute leukemias diagnosed in this age group. 1 Nevertheless, it remains a challenging disease with an inferior treatment outcome compared with pediatric acute lymphoblastic leukemia (ALL). Despite the introduction of new drugs, the aggressive use of allogeneic and autologous bone marrow transplantation, and improvements in supportive care, overall cure rates of AML in most contemporary treatment protocols remain below 60%. [2][3][4][5] Further improvements in cure rates are likely to come from a better understanding of both the molecular abnormalities responsible for the formation and growth of the leukemic cells, and the mechanisms underlying drug resistance.Increasingly, contemporary treatment protocols are incorporating methods for both accurate diagnosis and subsequent risk stratification. To achieve this requires not only distinguishing myeloblasts from lymphoblasts, but also assessing the extent of lineage commitment and differentiation, as well as the presence of specific molecular lesions or chromosomal abnormalities. Efforts over the last several decades have revealed AML to be a heterogeneous disease, with marked differences in cure rates between various genetic subtypes. [6][7][8][9] Acute promyelocytic leukemia was the first clear example of a clinically distinct AML subtype, being characterized by FAB-M3 morphology and expression of the t(15;17)-encoded promyelocytic leukemia-retinoic acid receptor alpha (PML-RAR␣) fusion protein. [10][11][12][13][14] ...

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Comparison of oligonucleotide-microarray and serial analysis of gene expression (SAGE) in transcript profiling analysis of megakaryocytes derived from CD34+ cells

Cited by 54 publications

References 16 publications

A comparison of global gene expression measurement technologies in Arabidopsis thaliana

A comparison of global gene expression measurement technologies in Arabidopsis thaliana

A Quantitative Reverse Transcriptase-Polymerase Chain Reaction Assay to Identify Metastatic Carcinoma Tissue of Origin

Gene expression profiling of pediatric acute myelogenous leukemia

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