Outcome prediction in adult core binding factor (CBF) acute myeloid leukemia (AML) with gene expression profiling: A Cancer and Leukemia Group B (CALGB) study

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 7011-7011 ◽  
Author(s):  
P. Paschka ◽  
M. D. Radmacher ◽  
G. Marcucci ◽  
A. S. Ruppert ◽  
T. Vukosavljevic ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Outcome Prediction ◽  
Prediction Algorithm ◽  
Expression Of Genes ◽  
Binding Factor ◽  
Diagnostic Samples ◽  
Group B ◽  
Biological Entities

7011 Background: In CBF AML with t(8;21)(q22;q22) or inv(16)(p13q22)/t(16;16)(p13;q22) [abbreviated inv(16)], KIT mutations (mutKIT) and, in inv(16), trisomy 22 predict outcome and may guide the development of novel risk-adapted therapies. However, prognosis of patients (pts) lacking the aforementioned markers is less clear. Therefore, we profiled gene expression in t(8;21) (n=22) or sole inv(16) (n=25) pts who lacked mutKIT to identify signatures predictive of outcome. All pts were treated on CALGB trials incorporating consolidation therapy with multiple courses of higher dose cytarabine. Methods: Gene expression profiling was performed using Affymetrix U133 plus 2.0 arrays on diagnostic samples. As differences in gene expression distinguished all t(8;21) pts from all inv(16) pts, indicating two different biological entities, we pursued outcome prediction separately for each cytogenetic group. Gene expression-based outcome predictors for event-free survival (EFS) were constructed using a cross-validated prediction algorithm. Results: Among t(8;21) pts, EFS for predicted good (n=13) and poor (n=9) outcome groups differed strikingly (P=0.005; estimated 3-year EFS rates: 69% v 11%). Prediction was correct for 77% of pts. Among sole inv(16) pts, EFS for predicted good (n=18) and poor (n=7) outcome groups also differed (P=0.08; 3-year EFS rates: 78% v 29%). Prediction was correct for 76% of pts. FLT3 mutations appeared not to account for differences in EFS between the predicted groups; only the predicted outcome groups were associated with EFS (all baseline clinical characteristics at P>0.10). Pts with predicted poor outcome had higher expression of genes with leukemogenic potential such as WT1 [t(8;21) and inv(16)], CCNA1 [t(8;21)] and the oncogene MYCN [inv(16)]. Conclusions: Gene expression profiling improves outcome prediction in CBF AML pts lacking the known prognostic markers. Future studies should explore the clinical usefulness of targeting products of over- expressed genes, such as WT1 encoding a potential target for immunotherapy in AML. No significant financial relationships to disclose.

Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients

Blood ◽  
2010 ◽  
Vol 116 (14) ◽  
pp. 2543-2553 ◽  
Author(s):  
Annemiek Broyl ◽  
Dirk Hose ◽  
Henk Lokhorst ◽  
Yvonne de Knegt ◽  
Justine Peeters ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Plasma Cells ◽  
Medical Science ◽  
Protein Tyrosine Phosphatases ◽  
Molecular Classification ◽  
Newly Diagnosed ◽  
Expression Of Genes

Abstract To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6 corresponded to clusters described in the University of Arkansas for Medical Science (UAMS) classification, CD-1 (n = 13, 4.1%), CD-2 (n = 34, 1.6%), MF (n = 32, 1.0%), MS (n = 33, 1.3%), proliferation-associated genes (n = 15, 4.7%), and hyperdiploid (n = 77, 24.1%). Moreover, the UAMS low percentage of bone disease cluster was identified as a subcluster of the MF cluster (n = 15, 4.7%). One subgroup (n = 39, 12.2%) showed a myeloid signature. Three novel subgroups were defined, including a subgroup of 37 patients (11.6%) characterized by high expression of genes involved in the nuclear factor kappa light-chain-enhancer of activated B cells pathway, which include TNFAIP3 and CD40. Another subgroup of 22 patients (6.9%) was characterized by distinct overexpression of cancer testis antigens without overexpression of proliferation genes. The third novel cluster of 9 patients (2.8%) showed up-regulation of protein tyrosine phosphatases PRL-3 and PTPRZ1 as well as SOCS3. To conclude, in addition to 7 clusters described in the UAMS classification, we identified 3 novel subsets of multiple myeloma that may represent unique diagnostic entities.

scholarly journals Gene expression profiling reveals insights into infant immunological and febrile responses to group B meningococcal vaccine

2020 ◽  
Vol 16 (11) ◽  
Author(s):  
Daniel O’Connor ◽  
Marta Valente Pinto ◽  
Dylan Sheerin ◽  
Adriana Tomic ◽  
Ruth E Drury ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Meningococcal Vaccine ◽  
Group B

scholarly journals Genomic dissection of the cytokine-controlled STAT5 signaling network in liver

2008 ◽  
Vol 34 (2) ◽  
pp. 135-143 ◽  
Author(s):  
Atsushi Hosui ◽  
Lothar Hennighausen
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Target Genes ◽  
Global Gene Expression ◽  
Specific Expression ◽  
Partial Explanation ◽  
Downstream Target ◽  
Expression Of Genes ◽  
Global Gene Expression Profiling

Growth hormone (GH) controls the physiology and pathophysiology of the liver, and its signals are conducted by two members of the family of signal transducers and activators of transcription, STAT5A and STAT5B. Mice in which the Stat5a/b locus has been inactivated specifically in hepatocytes display GH resistance, the sex-specific expression of genes associated with liver metabolism and the cytochrome P-450 system is lost, and they develop hepatosteatosis. Several groups have shown by global gene expression profiling that a cadre of STAT5A/B target genes identify genetic cascades induced by GH and other cytokines. Evidence is accumulating that in the absence of STAT5A/B GH aberrantly activates STAT1 and STAT3 and their downstream target genes and thereby offers a partial explanation of some of the physiological alterations observed in Stat5a/b-null mice and human patients. We hypothesize that phenotypic changes observed in the absence of STAT5A/B are due to two distinct molecular consequences: first, the failure of STAT5A/B target genes to be activated by GH and second, the rerouting of GH signaling to other members of the STAT family. Rerouting of GH signaling to STAT1 and STAT3 might partially compensate for the loss of STAT5A/B, but it certainly activates biological programs distinct from STAT5A/B. Here we discuss the extent to which studies on global gene expression profiling have fostered a better understanding of the biology behind cytokine-STAT5A/B networks in hepatocytes. We also explore whether this wealth of information on gene activity can be used to further understand the roles of cytokines in liver disease.

scholarly journals Gene expression profiling of mantle cell lymphoma cells reveals aberrant expression of genes from the PI3K-AKT, WNT and TGFbeta signalling pathways

2005 ◽  
Vol 130 (4) ◽  
pp. 516-526 ◽  
Author(s):  
Edgar Gil Rizzatti ◽  
Roberto Passetto Falcao ◽  
Rodrigo Alexandre Panepucci ◽  
Rodrigo Proto-Siqueira ◽  
Wilma Terezinha Anselmo-Lima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mantle Cell Lymphoma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
Signalling Pathways ◽  
Lymphoma Cells ◽  
Aberrant Expression ◽  
Expression Of Genes ◽  
Mantle Cell

Gene expression profiling in lung fibroblasts reveals new players in alveolarization

2007 ◽  
Vol 32 (1) ◽  
pp. 128-141 ◽  
Author(s):  
Olivier Boucherat ◽  
Marie-Laure Franco-Montoya ◽  
Christelle Thibault ◽  
Roberto Incitti ◽  
Bernadette Chailley-Heu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Retinoic Acid Receptor ◽  
Lung Fibroblasts ◽  
Fetal Life ◽  
Isolated Cells ◽  
Signal Molecule ◽  
Expression Of Genes ◽  
Extracellular Matrix Components

Little is known about the molecular basis of lung alveolarization. We used a microarray profiling strategy to identify novel genes that may regulate the secondary septation process. Rat lung fibroblasts were extemporaneously isolated on postnatal days 2, 7, and 21, i.e., before, during, and after septation, respectively. Total RNA was extracted, and cRNAs were hybridized to Affymetrix rat genome 230 2.0 microarrays. Expression levels of a selection of genes were confirmed by real-time PCR. In addition to genes already known to be upregulated during alveolarization including drebrin, midkine, Fgfr3, and Fgfr4, the study allowed us to identify two remarkable groups of genes with opposite profiles, i.e., gathering genes either transiently up- or downregulated on day 7. The former group includes the transcription factors retinoic acid receptor ( RXR)-γ and homeobox ( Hox) a2, a4, and a5 and genes involved in Wnt signaling ( Wnt5a, Fzd1, and Ndp); the latter group includes the extracellular matrix components Comp and Opn and the signal molecule Slfn4. Profiling in whole lung from fetal life to adulthood confirmed that changes were specific for alveolarization. Two treatments that arrest septation, hyperoxia and dexamethasone, inhibited the expression of genes that are upregulated during alveolarization and conversely enhanced that of genes weakly expressed during alveolarization and upregulated thereafter. The possible roles of these genes in secondary septation are discussed. Gene expression profiling analysis on freshly isolated cells represents a powerful approach to provide new information about differential regulation of genes during alveolarization and pathways potentially involved in the pathogenesis of bronchopulmonary dysplasia.

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