Transcriptosome Profiling of B-CLL Identifies WNT-3A and ROR-1 as an Autocrine Mechanism in Cell Survival.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2116-2116
Author(s):  
James Choi ◽  
B. Simons ◽  
Chris Riley ◽  
T. Klinkhammer ◽  
Laurence Cooke ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tyrosine Kinase ◽  
B Cell ◽  
Real Time ◽  
Mononuclear Cells ◽  
Lymphocytic Leukemia ◽  
Western World ◽  
Specific Gene ◽  
Rt Pcr ◽  
Normal Peripheral Blood

Abstract Background: B-cell chronic lymphocytic leukemia (B-CLL) is the most common leukemia afflicting the Western world. B-CLL accounts for 25% of all newly diagnosed leukemias. Despite many new therapeutic advances, B-CLL is still not a curable malignancy. The hallmark feature is the presence of an elevated number of circulating clonal leukemic B cells that typically express CD 5, CD 19, CD 23, and low levels of surface immunoglobulins. Methods: Mononuclear cells from 5 patients were analyzed utilizing the HG-U133A 2.0 Affymetrix array (~18,400 transcripts, 22,000 probe sets) after isolating and purifying total RNA (Qiagen, RNAeasy). The control RNA samples were isolated from normal peripheral blood (PB) B-cell (AllCell, CA). Immunohistochemistry (IHC) confirmed tumor lineage and quantitative real time RT-PCR was performed on selected genes to validate the microarray study. The GEP data was processed and analyzed utilizing Affymetrix MAS 5.0 and GeneSpring 5.0 software. Our data was analyzed in the light of published GEP of B-cell CLL. Fifteen B-CLL patients (retrospectively) were evaluated by RT-PCR for ROR-1 and WNT-3A with gene specific probes. As a potential therapy, thalidomide was evaluated on B-CLL cells grown in cell culture for 24 hours. GEP of the thalidomide treated B-CLL from the initial 5 patients was performed to look for gene expression changes that could drive the B-CLL toward apoptosis. A homology model of ROR-1 tyrosine kinase was built, ATP docked and in silico databases screened for potential lead molecules. Results: Data are represented as “robust” increases or decreases of relative gene expression common in the 5 patients. However, ROR-1 and WNT-3A were consistently over-expressed together in these 5 patients. The average increase was 25-fold for ROR-1 and 7-fold by WNT-3A when compared to normal B-cell RNA. Of the 15 patients we evaluated for ROR-1 and WNT-3A with gene specific probes, the increase in gene expression correlated well with our initial gene expression profiling study. Thalidomide specific gene changes included several molecules involved in apoptosis. Of these gene changes, Bcl-G, p35, and Cdk-5 were up-regulated several fold. Data will be presented on the influence of the stage of disease on ROR-1 and WNT-3A expression. Conclusions: GEP of B-CLL in combination with quantitative real time RT-PCR has identified several novel therapeutic targets for therapy based on a comparison to normal (B-cell) RNA. GEP has identified ROR-1 as a key component in an autocrine pathway that helps B-CLL elude apoptosis. The identification of this novel tyrosine kinase-like protein has led to the development of a molecular target for future therapeutic applications. Several lead compounds have been identified and are being evaluated as potential therapeutics in B-CLL.

B-Cell Prolymphocytic Leukemia (B-PLL) and Chronic Lymphocytic Leukemia (CLL) Express Distinct Genomic Profiles.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 4372-4372
Author(s):  
Ilaria Del Giudice ◽  
Nnenna Osuji ◽  
Tim Dexter ◽  
Estella Matutes ◽  
Vasantha Brito-Babapulle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Clinical Features ◽  
Mononuclear Cells ◽  
Expression Profiles ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Specific Gene ◽  
Prolymphocytic Leukemia

Abstract B-cell prolymphocytic leukemia (B-PLL) is a rare disease, originally described in the early seventies and now recognized as a specific entity by the WHO classification. Diagnosis is based on clinical features and lymphocyte morphology (>55% circulating prolymphocytes), as no specific immunophenotypic or cytogenetic marker is available. According to WHO, cases of chronic lymphocytic leukemia (CLL) with increased prolymphocytes (CLL/PL) (>10% and <55%) should not be considered as B-PLL, because they have different genetic features. However, the existence of B-PLL as a separate entity from CLL has been questioned. We investigated the gene expression profiles of B-PLL and CLL to identify key genetic differences potentially useful for the diagnosis or involved in their different natural history. We retrospectively selected cryopreserved samples from 10 de-novo B-PLL and 10 untreated CLL. Diagnosis was well-defined by clinical features, lymphocyte morphology and immunophenotype. Matutes immunophenotypic score was 4–5 in all CLL; 3 cases showed CLL/PL morphology. B-PLL scored 0–3, with 3 CD5+ cases. Diagnosis of B-PLL was corroborated by excluding a leukemic form of MCL; t(11;14) assessed by fluorescent in situ hybridization (FISH) was absent in all but one case which, originally diagnosed as B-PLL, was reclassified as leukemic MCL. Five B-PLL and 2 CLL showed del(p53) by FISH. Total RNA was extracted from frozen blood mononuclear cells containing ≥95% purity of malignant cells, determined by flow cytometry. cDNA synthesis followed by biotin-labelled cRNA synthesis was carried out as per Affymetrix protocols. Microarray experiments were performed by MRC geneservice (UK HGMP Resource Centre), using the Affymetrix Human U133PLUS2 GeneChip array (54K probes). Hierarchical clustering was performed on samples using a filtered set of 9878 genes with >4 different algorithms. Prediction analysis for microarray (PAM) and significance analysis of microarray data (SAM) were used to evaluate class performance, and to partition genes using a priori defined labels of morphology, immunophenotype and cytogenetics. Unsupervised analysis reproducibly partitioned samples into two homogeneous distinct groups, corresponding to the diagnoses of B-PLL and CLL. SAM analysis identified 3957 differentially expressed transcripts (false discovery rates <1%), >77% of which showed an over 2-fold difference in expression between the groups. PAM analysis refined a sub-group of 46 genes which most efficiently differentiated the two diseases. Differentially expressed genes included those encoding surface antigens, oncogenes, transcription factors, adhesion molecules or involved in cell cycle/cell proliferation, lipidic metabolism and catalytic protein activity. Comparison of CD5 positive (13) versus CD5 negative (7) cases and cases with (7) or without (13) del(p53) showed no reliable class prediction. Our study formally demonstrates that B-PLL and CLL are two distinct diseases, each showing a specific gene expression. B-PLL has a homogeneous genomic profile irrespective of its heterogeneity in laboratory features. Validation of a model based on the expression of few genes predictive of diagnosis is on going. Further analysis of these data may also identify specific genes involved in B-PLL pathogenesis and drug resistance.

410. Gene expression analysis in endometriotic lesions using laser capture microdissection

2008 ◽  
Vol 20 (9) ◽  
pp. 90
Author(s):  
L. Fu ◽  
J. E. Girling ◽  
P. A. W. Rogers
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
Laser Capture Microdissection ◽  
Stromal Cells ◽  
Expression Profiles ◽  
Specific Gene ◽  
Rt Pcr ◽  
Normal Endometrium ◽  
Rna Quality ◽  
Laser Capture

Previous studies examining gene expression profiles in normal endometrium and endometriotic lesions have used RNA extracted from whole tissue samples. Results from these studies can be difficult to interpret as they reflect expression averaged across several different cell types that may be functionally quite different. The aim of this study was to establish laser capture microdissection (LCM) as a technique to examine gene expression in stromal and epithelial cells from normal and ectopic endometrium. We hypothesised that genes associated with inflammation would be elevated in cells from endometriotic lesions. Full thickness uterine samples were collected during abdominal hysterectomy from normal cycling premenopausal women. Endometriotic lesions were collected during abdominal laparoscopy. Samples were either frozen in OCT or stored in RNAlater for 12 h before freezing. Tissues were immunostained with an antibody against CD10 to identify ectopic endometrial stromal cells before LCM. Endometrial epithelial and stromal cells were collected using the PALM MicroLaser System. RNA quality was accessed using Experion. TGFβ1, MMP1, αSMA, SMAD2 and NFκB mRNA was analysed using real-time RT–PCR. Of the endometriotic samples stored in OCT (n = 58), only 14% (n = 8) had visible endometrial glands. Of these, only 37% (n = 3) had RNA of an acceptable quality for further analysis. However, RNA quality and quantity were dramatically improved in 3 of 5 samples collected in RNAlater. In preliminary studies, expression of TGFβ1 and αSMA mRNA was elevated in endometriotic lesions in comparison to the normal endometrium, whereas NFκB expression did not change. We have shown that RNAlater solution is useful to preserve RNA quality for small clinical endometriotic samples and that immuno-guided LCM-generated homogenous cell populations coupled with real-time RT–PCR can provide valuable insights into cell and disease-specific gene expression in endometriotic lesions.

Gene Expression Profiling of Peripheral T-Cell Lymphoma (PTCL, NOS) and Comparison to Diffuse Large B-Cell Lymphoma (DLBCL).

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2277-2277
Author(s):  
Daruka Mahadevan ◽  
Catherine Spier ◽  
Kimiko Della Croce ◽  
Susan Miller ◽  
Benjamin George ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
T Cell ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Real Time ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
Rt Pcr

Abstract Background: WHO classifies NHL into B (~85%) and T (~15%) cell subtypes. Of the T-cell NHL, peripheral T-cell NHL (PTCL, NOS) comprises ~6–10% with an inferior response and survival to chemotherapy compared to DLBCL. Gene Expression Profiling (GEP) of DLBCL has provided molecular signatures that define 3 subclasses with distinct survival rates. The current study analyzed transcript profiling in PTCL (NOS) and compared and contrasted it to GEP of DLBCL. Methods : Snap frozen samples of 5 patients with PTCL (NOS) and 4 patients with DLBCL were analyzed utilizing the HG-U133A 2.0 Affymetrix array (~18,400 transcripts, 22,000 probe sets) after isolating and purifying total RNA (Qiagen, RNAeasy). The control RNA samples were isolated from normal peripheral blood (PB) B-cell (AllCell, CA), normal PB T-cell (AllCell, CA) and normal lymph node (LN). Immunohisto-chemistry (IHC) confirmed tumor lineage and quantitative real time RT-PCR was performed on selected genes to validate the microarray study. The GEP data were processed and analyzed utilizing Affymetrix MAS 5.0 and GeneSpring 5.0 software. Our data were analyzed in the light of the published GEP of DLBCL (lymphochip and affymtrix) and the validated 10 prognostic genes (by IHC and real time RT-PCR). Results : Data are represented as “robust” increases or decreases of relative gene expression common to all 5 PTCL or 4 DLBCL patients respectively. The table shows the 5 most over-expressed genes in PTCL or DLBCL compared to normal T-cell (NT), B-cell (NB) and lymph node (LN). PTCL vs NT PTCL vs LN DLVCL vs NB DLBCL vs LN COL1A1 CHI3L1 CCL18 CCL18 CCL18 CCL18 VNN1 IGJ CXCL13 CCL5 UBD VNN1 IGFBP7 SH2D1A LYZ CD52 RARRES1 NKG7 CCL5 MAP4K1 Of the top 20 increases, 3 genes were common to PTCL and DLBCL when compared to normal T and B cells, while 11 were common when compared to normal LN. Comparison of genes common to normal B-cell and LN Vs DLBCL or PTCL and normal T-cell and LN Vs PTCL or DLBCL identified sets of genes that are commonly and differentially expressed in PTCL and/or DLBCL. The 4 DLBCL patients analyzed express 3 of 10 prognostic genes compared to normal B-cells and 7 of 10 prognostic genes compared to normal LN and fall into the non-germinal center subtype. Quantitative real time RT-PCR on 10 functionally distinct common over-expressed genes in the 5 PTCL (NOS) patients (Lumican, CCL18, CD14, CD54, CD106, CD163, α-PDGFR, HCK, ABCA1 and Tumor endothelial marker 6) validated the microarray data. Conclusions: GEP of PTCL (NOS) and DLBCL in combination with quantitative real time RT-PCR and IHC have identified a ‘molecular signature’ for PTCL and DLBCL based on a comparison to normal (B-cell, T-cell and LN) tissue. The categorization of the GEP based on the six hallmarks of cancer identifies a ‘tumor profile signature’ for PTCL and DLBCL and a number of novel targets for therapeutic intervention.

scholarly journals SYK Inhibition Disrupts the Cross-Talk Between B-Cell Activation Factor (BAFF) and B-Cell Receptor (BCR) and Thereby Antagonizes Mcl-1 in Chronic Lymphocytic Leukemia (CLL) B-Cells

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 303-303
Author(s):  
Cody Paiva ◽  
Taylor Rowland ◽  
Olga Danilova ◽  
Bhargava Sreekantham ◽  
Stephen E Spurgeon ◽  
...  
Keyword(s):  
B Cells ◽  
Tyrosine Kinase ◽  
B Cell ◽  
Cell Survival ◽  
Research Funding ◽  
Mononuclear Cells ◽  
Lymphocytic Leukemia ◽  
Mutational Status ◽  
Pathway Gene ◽  
Bcr Signaling

Abstract Although small molecule inhibitors of BCR-associated kinases (BCRi) revolutionized therapy in CLL, they provide incomplete responses. Soluble mediators emanating from the tumor microenvironment perpetrate CLL cell survival and may account for resistance to BCRi. Tumor necrosis factor receptor superfamily ligands BAFF and APRIL induce NFκB, which in turn upregulates pro-survival Bcl-2 family proteins and thereby drives anti-apoptotic responses.The exact roles of the individual NFκB pathways, as well as the implications of targeting BCR in context of BAFF signaling in CLL remain understudied. We explored the mechanistic underpinnings of CLL cell survival in response to BAFF signaling, uncovering the functional significance of the BCR-associated kinases and Bcl-2 family proteins in this setting. Peripheral blood mononuclear cells were isolated from patients with CLL. We established a novel BAFF-expressing stromal co-culture model and referenced it to control, CD40L-expressing stroma and soluble BAFF. We employed inhibitors of Bruton tyrosine kinase (BTK, ibrutinib), phosphoinositide-3 kinase (PI3K, idelalisib) and spleen tyrosine kinase (SYK, entospletinib) and measured CLL cell apoptosis, migration, NFκB activity, protein and mRNA expression by flow cytometry, immunoblotting, ELISA, RT-PCR and immunocytochemistry. CLL cells co-cultured with BAFF-expressing stroma were resistant to spontaneous apoptosis (12.3±3.2% after 24 h, vs 34.8±6.2% off stroma) and chemotherapy agents (bendamustine, fludarabine). Gene expression profiling exposed the NFκB pathway gene targets as the most significantly upregulated upon BAFF stimulation (p<0.0001). We and others have shown that CD40L-expressing stroma induces canonical and non-canonical NFκB in CLL. By contrast, while BAFF led to strong activation of the non-canonical NFκB with processing of p100 (to p52) by 4 h and a 5-fold increase in p52 DNA-binding activity by 24 h, canonical NFκB (RelA) activation was less pronounced. BAFF predominantly induced Mcl-1, compared to CD40L which strongly upregulated Bcl-X. BCR is a major driver of canonical NFκB signaling in CLL. Thus, we studied whether BAFF co-opted BCR signaling in CLL. BAFF induced rapid (15 min) phosphorylation of the proximal BCR kinases SYKand LYN, sustained for up to 4 h, as well as ERK, in CLL cells. AKT activation occurred late (>2 h), suggesting that BAFF induced AKT independent of BCR. BAFF-mediated BCR activation did not correlate with IGHV mutational status. Like IgM, BAFF induced CLL cell chemotaxis. SYK inhibition effectively antagonized survival and chemotaxis of BAFF-stimulated CLL cells. By contrast, targeting BTK or PI3K was less effective. All BCRi's fully blocked canonical NFκB activation in BAFF-stimulated CLL cells (suggesting its dependence on BCR signaling), but none inhibited the non-canonical pathway. We found that entospletinib, but not other BCRi's, decreased Mcl-1 expression in CLL cells co-cultured with BAFF-expressing stroma. Unlike in IgM-stimulated cells, entospletinib did not promote Mcl-1 protein degradation. By contrast,, targeting SYK in BAFF-stimulated cells abrogated BAFF-mediated upregulation of pSTAT3, a transcription factor which regulates Mcl-1. This was accompanied by a decrease in Mcl-1 transcript, an effect mimicked by ruxolitinib, a JAK/STAT inhibitor. BAFF receptor signals via the TRAF3/NIK/IKK1 axis to induce non-canonical NFκB activation in neoplastic B-cells. We supposed that NIK (NFκB-inducing kinase) or IKK1 could be directly responsible for SYK activation by BAFF. Indeed, genetic knockdown of NIK resulted in decreased SYK activation, whereas IP experiments demonstrated that NIK directly complexed with SYK in BAFF-stimulated neoplastic B-cells, confirming NIK role in activation of BCR signaling. Thus, BAFF-mediated induction of BCR-associated kinases and Mcl-1 contributes to CLL cell survival. SYK inhibition is a promising therapeutic strategy uniquely poised to antagonize crosstalk between BAFF and BCR, thereby disrupting the pro-survival microenvironment signaling in CLL. Disclosures Spurgeon: Gilead Sciences: Research Funding; Bristol Myers Squibb: Research Funding; Acerta Pharma: Research Funding; Genentech: Research Funding; Janssen: Research Funding. Danilov:Prime Oncology: Honoraria; Dava Oncology: Honoraria; ImmunoGen: Consultancy; GIlead Sciences: Research Funding; Takeda: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Consultancy.

Transcriptosome and Serum Cytokine Profiling of B-CLL Identifies Oncogenic Pathways in Pathogenesis and Survival.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 4953-4953
Author(s):  
James Choi ◽  
Harinder Garewal ◽  
Christopher Riley ◽  
Laurence Cooke ◽  
Thomas Klinkhammer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Real Time ◽  
Signaling Pathway ◽  
Cytokine Profile ◽  
Lymphocytic Leukemia ◽  
Rt Pcr ◽  
Serum Cytokine ◽  
Oncogenic Signaling ◽  
Oncogenic Signaling Pathways

Abstract Background: B-cell chronic lymphocytic leukemia (B-CLL) the most common leukemia in the Western world accounts for 25% of all newly diagnosed leukemias. Despite new therapeutic advances, B-CLL is currently not curable. Potential oncogenic signaling pathways in B-CLL require elucidation. We identified ROR-1 receptor tyrosine kinase (RTK) in the WNT/Planar Cell Polarity non-canonical pathway as a possible mechanism of oncogenesis by gene expression profiling (GEP). Methods: Mononuclear cells from 8 low stage CLL patients were obtained through an IRB approved protocol and analyzed utilizing the HG-U133A 2.0 Affymetrix array (~18,400 transcripts, 22,000 probe sets) after isolating and purifying total RNA (Qiagen, RNAeasy). The control RNA samples were isolated from 8 normal volunteer peripheral blood (PB) B-cells (AllCell, CA) and a normal reactive lymph node. Tumor lineage was confirmed by immunohistochemistry (IHC). Quantitative real time RT-PCR was performed on 20 selected genes to validate the microarray GEP. Twenty one B-CLL patients (includes the 8 patients from the GEP) were evaluated by RT-PCR for several key components of oncogenic signaling pathways based on the GEP with gene specific probes. A serum cytokine profile (120 cytokines) on 12 CLL patients (8 for which GEP is available and 4 additional patients) and 4 normal volunteers were performed for identification of a signature for diagnostic and prognostic value. Results: Data are represented as “robust” increases or decreases of relative gene expression common to 8 patients. ROR-2, a close member of ROR-1, has been shown to bind Wnt-5A via the cysteine rich domain (CRD) and to activate the JNK signaling pathway. Our findings identify over-expression of members of the non-canonical WNT/PCP- ROR-1- signaling pathway genes that were validated by RT-PCR. A serum cytokine profile of 12 patients provides a signature that may be useful in CLL diagnosis and prognosis. Conclusions: GEP identified WNT/PCP-ROR-1 as key components of an autocrine pathway that helps B-CLL avoid apoptosis. Several serum cytokines are elevated and require validation as potential diagnostic and prognostic markers. GEP of B-CLL in combination with quantitative real time RT-PCR has identified several novel targets for therapy. The identification of ROR-1 RTK has led to the development of a molecular target for future therapeutic application. Several lead compounds have been identified and are being evaluated as potential therapies in B-CLL.

Biological and Clinical Relevance of Surrogate Markers of IgVH Mutational Status in B-Cell Chronic Lymphocytic Leukemia.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1062-1062
Author(s):  
Fortunato Morabito ◽  
Marta Lionetti ◽  
Giovanna Cutrona ◽  
Katia Todoerti ◽  
Serena Matis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Candidate Genes ◽  
Lymphocytic Leukemia ◽  
Surrogate Markers ◽  
Rt Pcr ◽  
Mutation Status ◽  
Expression Levels ◽  
Cell Chronic Lymphocytic Leukemia

Abstract B-cell chronic lymphocytic leukemia (B-CLL) is a heterogeneous disease; some patients have a rapidly progressing disease and others exhibit an indolent course and survive for many years without treatment. Mutation status of IgVH genes utilized by CLL cells represents a very reliable predictor of clinical outcome in B-CLL, but its analysis is expensive and beyond the capacities of most diagnostic laboratories. To identify surrogate markers we performed a gene expression profiling analysis of CD19+ purified cells from 80 B-CLL untreated patients in Binet stage A, by means of Affymetrix GeneChip® HGU133A arrays. The comparison of 46 IgVH-unmutated versus 34 mutated samples using the Prediction Analysis of Microarrays software identified 78 differentially expressed probes, specific for 59 well-characterized genes. Specifically, 43 genes had a higher and 16 genes a lower average expression in the IgVH unmutated group. These genes are involved in cellular functions, including cell cycle regulation (SEPT7, SEPT10, CDK2AP1), cell proliferation (SLAMF1, LDOC1), apoptosis (CD63, IFT57, P2RX1, RNF130, TNFRSF1B), cell adhesion (CNTNAP2, C1orf38, PCDH9), immune response (ZAP70, IFI44), signal transduction (AKAP13, RASGRP1, USP6NL, TGFBR3, AKAP12), lipid metabolism and fatty-acid degradation (FADS3, LPL, LASS6), cell-cell signalling (FCRL2), phospholipid biosynthetic process (AYTL2), regulation of circadian rhythm (EGR3, CRY1, OPN3), DNA-dependent regulation of transcription (MYBL1, NR4A2, NRIP1, ZBTB20), muscle development (VAMP5, SRI, DMD). The expression signature identified in the proprietary database was then validated by means of a meta-analysis of a publicly available gene expression dataset of 100 B-CLL (Haslinger et al., 2005), showing classification accuracy measures leading to a global classification rate of 82.93% of the test set and thus suggesting the strength of the identified expression signature. The expression levels of 11 genes (LPL, ZBTB20, ZAP70, CRY1, COBLL1, SEPT10, LDOC1, TNFRSF1B, DMD, SRI, NRIP1) were confirmed by means of quantitative real-time PCR (Q-RT-PCR) in a subset of 40 CLL patients. The prognostic impact for Time To Treatment (TTT) of the 59 candidate genes of our classifier model was investigated in 77 patients. Forty-nine (36.4%) of these received treatment after a median follow up of 4 years. As expected, patients with unmutated IgVH genes had a risk of therapy requirement that was about 3 times higher (HR: 3.1,95% C.I. 1.6–5.8, p&lt;0.0001) than those with mutated IgVH. Based on microarray expression levels, 43/59 genes significantly predicted TTT with a HR ranging from 1.5 (LPL gene) to 4.2 (SRI gene) (value for ZAP-70 = HR: 1.9, 95% C.I. 1.0–3.4, p=0.039). The same analysis performed in the panel of the 11 genes validated by Q-RT-PCR revealed 4 candidate genes which significantly predicted TTT. Specifically, Cox univariate analysis confirmed ZAP-70 as a predictor of disease outcome and underscored the prognostic role of the LPL, TNFRSF1B and CRY1 genes. The predictive power of the novel putative surrogate markers for the IgVH mutation status is now being further validated at protein expression level.

scholarly journals RNA-Based Drug Screening Using Automated RNA Purification and Real-time RT-PCR1

2004 ◽  
Vol 9 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Susanne Ullmann ◽  
Thorsten Hage ◽  
Regina Draheim ◽  
Ute Egerland ◽  
Uwe OelmÜller ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Real Time ◽  
Drug Screening ◽  
Mononuclear Cells ◽  
Assay System ◽  
Automated System ◽  
Chronic Obstructive ◽  
Rt Pcr ◽  
Rna Purification

A new system has been developed for RNA-based drug screening, and the feasibility of this approach has been demonstrated by the identification of new immunomodulating compounds. Peripheral blood mononuclear cells were chosen as the cellular assay system. Cells were either stimulated by TPA/ionomycin to produce T cell cytokines as asthma targets or stimulated by lipopolysaccharide to produce proinflammatory cytokines as targets for chronic obstructive pulmonary disease (COPD). The authors developed a new fully automated system for RNA purification from cells grown in 96-well plates. Gene expression was determined in 384-well plates using real-time quantitative one-tube RT-PCR. Small interdonor variation could be demonstrated. The assay system was validated with known immunosuppressants cyclosporine and dexamethasone. Screening of 800 compounds resulted in 9.5% compounds inhibiting the induction of at least 1 T cell derived cytokine and 6.8% compounds inhibiting at least 1 cytokine relevant for COPD. All these compounds were retested by analyzing remaining RNA from the 1st round of screening. The reproducibility of hits was between 56% and 74% for different cytokines. One compound selectively inhibited TNF, which was confirmed by IC50 determination. Analyzing its effect on cells from different donors revealed little interdonor variation. In conclusion, the authors established fully automated RNA isolation and precise gene expression profiling using real-time RT-PCR for drug screening. ( Journal of Biomolecular Screening 2004:95-102)

B-Cell Chronic Lymphocytic Leukemia Cells Exposed to the Non-Genotoxic p53 Activator Nutlin-3 Are Characterized by a Specific Gene Expression Signature.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4374-4374
Author(s):  
Michele Dal-Bo ◽  
Paola Secchiero ◽  
Massimo Degan ◽  
Riccardo Bomben ◽  
Dania Benedetti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Differentially Expressed Genes ◽  
Chemotherapeutic Agents ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Specific Gene ◽  
P53 Mutations ◽  
Cell Chronic Lymphocytic Leukemia

Abstract Abstract 4374 Introduction p53 plays a key role in determining the clinical features of B cell chronic lymphocytic leukemia (CLL). Disruption of p53 by point mutations, deletion at 17p13, or both, occurs in a fraction of cases at diagnosis and predicts poor survival and chemorefractoriness. In cells with functional p53, p53 activity is inhibited through interaction with MDM2. In fact, p53 can be activated upon exposure of cells to inhibitors of p53/MDM2 interaction, like Nutlins. Exposure of CLL cells to Nutlin-3 is effective in raising the levels of p53 protein with subsequent induction of cell cycle arrest and/or apoptosis, independently of the most relevant prognostic markers. The aim of the present study was to analyze the gene expression profile (GEP) induced by Nutlin-3 exposure in primary CLL cells from p53wt and p53del/mut cases. Patients and methods purified cells from 24 PB CLL samples, all characterized for IGHV mutational status, CD38 and ZAP-70 and p53 mutations (16 p53wt CLL, 8 p53del/mut CLL of which 6 with del17p13 and p53 mutations, 1 with del17p13 alone, and 1 with p53 mutations alone), were exposed to 10 mM Nutlin-3 for 24 hours. GEP was performed using a dual labelling strategy; the differential expression of the below reported genes were validated by quantitative real-time PCR. Results i) signature of Nutlin-3 exposure in p53wt CLL: 144 differentially expressed genes (143 up-regulated, 1 down-regulated) were correlated with response to Nutlin-3. Among the over-expressed genes, several genes were related to apoptosis (e.g. BAX, BBC3, E124, IKIP, FAS, LRDD, FLJ11259, TRIAP1, GADD45, TP53INP1, ISG20L1, ZMAT3, TNFRS10C, TNFRSF10B/TRAIL-R2), while other genes (e.g. MDM2, CDKN1A, PCNA) were up-regulated by Nutlin-3 as a part of a negative feed-back mechanism. Of note, this signature was not shared by 3/16 p53wt cases (identified as “non-responder” p53wt CLL) and 7/8 p53del/mut cases (identified as “non-responder” p53del/mut CLL); consistently, cells from these cases were also significantly resistant to the in-vitro cytotoxic effects of Nutlin-3; ii) signature of Nutlin-3 “non-responder” p53wt CLL: by comparing the constitutive GEP of 13 “responder” versus 3 “non-responder” p53wt CLL, we obtained 278 differentially expressed genes, 149 up-regulated and 129 down-regulated in “non-responder” p53wt CLL. Among up-regulated genes, we focused on MDM4/MDMX, a gene whose product was known to have an inhibitor activity of p53-dependent transcription and to form Nutlin-3 resistant complexes with p53. Among down-regulated genes, validations were made for BIRC4BP, whose product is known to act as an antagonist of the anti-apoptotic protein XIAP; iii) signature of Nutlin-3 “non-responder” p53del/mut CLL: by comparing the constitutive GEP of 13 “responder” versus 7 “non-responder” p53del/mut cases, we obtained 72 differentially expressed genes, 26 up-regulated and 46 down-regulated (31/46 located at the 17p segment) in “non-responder” p53del/mut CLL. Validations were made for several genes whose products display pro-apoptotic activities (e.g. PSMB6, RPL26 and ZBTB4, located at 17p segment, and GNAZ located at chromosome 22) among down-regulated genes, and ARHGDIA, whose gene product displays anti-apoptotic activities and mediates cellular resistance to chemotherapeutic agents, among up-regulated genes. Notably, CLL cells (n=43) displayed constitutively higher levels of MDM4/MDMX (p<0.0001) and ARHGDIA (p=0.0002) transcripts than purified normal B cells (n=15), irrespectively to the major biologic prognosticators. Conclusions specific gene-sets and GEP were documented to be associated with response or resistance to Nutlin-3 exposure in p53wt or p53del/mut CLL. These findings may help to identify novel molecular targets for CLL therapy. Disclosures: No relevant conflicts of interest to declare.

In-Vivo Study of Erythropoietic Pathway Genes Regulation and Differentiation by Prolonged Simultaneous Administration of Glucocorticoids with Epoietin in Animal Modules

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 4798-4798
Author(s):  
Aref Agheli ◽  
Boris Avezbakiyev ◽  
William Steier ◽  
Madhumati Kalavar ◽  
Chi Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
Mononuclear Cells ◽  
Conflicts Of Interest ◽  
Hemoglobin Concentration ◽  
P Value ◽  
Simultaneous Administration ◽  
Epoetin Alfa ◽  
Rt Pcr ◽  
Gene Expressions

Abstract Abstract 4798 Objectives: The role of steroids in mammalian erythropoiesis has not well defined. We have previously reported our observation on three human cases in which there was a synergism and accelerated response to the Erythropoietic Stimulating Agents (ESA) with simultaneous low and physiologic dose administration of glucocorticoids. In the current study, we investigated the additive effects of different dose schedules of steroids on hematopoietic effects of ESA in animal modules. Methods: A total of 74, four-weeks old male Sprague-Dawley rats were randomized to 6 groups; (A) control, (B) therapeutic doses of either erythropoietin, [Procrit Epoetin Alfa, 100 UI/kg], or (C) dexamethasome (300 mcg/kg), as well as combination of erythropoietin (Epoetin Alfa, 100 UI/kg) with (D) low, [25 mcg/kg], (E) physiologic, [300 mcg/kg], and (F) high, [2.5 mg/kg] doses of dexamethasone through abdominal hypodermal injection three times a week for a total of four weeks. At the conclusion of the study, peripheral blood sample, and Bone marrow mononuclear cells were collected through femur flushing. The samples were lysed and stored in RNA denaturation buffer at –80°C until use. Expressions of multiple hematopoietic major genes were assessed by real-time RT-PCR. Amplification data were processed using ΔΔCt method. Hemoglobin concentration and other CBC parameters were measured at the reference lab. Results: Mean hemoglobin concentrations were significantly higher in groups D (20.76 g/dl, 95% CI 20.08–21.45), E (20.45 g/dl, 95% CI, 19.97–20.94), and F (20.99 g/dl, 95% CI 20.55–21.42), compared to the controlled groups A, B, C (14.57, 15.68, 19.23 g/dl respectively) with two-tailed p-value of <.0001. (Figure-1) Real time RT-PCR based gene expression profiling of major hematopoietic regulators revealed robot increases of JAK2 gene expression in groups of animals treated with EPO only, or even higher increase with EPO plus either low or physiologic doses of dexamethasome. Similarly, GATA-1 levels are increased in groups treated with EPO only, or EPO with low or physiologic doses of dexamethasome. c-kit and NFkB1 expression levels are markedly higher in EPO plus dexamethasome groups. In contrast, the levels of EPOR are generally reduced in all groups receiving ESA. (Figure -2) Conclusion: The findings in this study is suggestive that simultaneous administration of ESAs with glucocorticoids is associated with significant additive elevation of the hemoglobin concentration; however, higher dose of dexamethasone is associated with more frequent adverse side effects such as significant weight loss. It is also suggested that the erythropoietic effect of steroid is concerted by up-regulation of the multiple erythropoietic gene expressions, such as JAK2, GATA-1, c-Kit, and NFkB1, while down regulations of EPOR is uniformly seen in the Epo-treated groups. This novel finding could be clinically utilized to accelerate the erythropoietic response of the ESA in selected cases. Disclosures: No relevant conflicts of interest to declare.

Novel blood biomarker panel detects human colorectal cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 3611-3611
Author(s):  
M. Han ◽  
C. T. Liew ◽  
H. W. Zhang ◽  
K. T. Yip ◽  
Z. Y. Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
B Cell ◽  
Real Time ◽  
Cytidine Deaminase ◽  
Expression Profiles ◽  
The United States ◽  
Rt Pcr ◽  
Human Colorectal Cancer ◽  
Blind Test

3611 Background: Human colorectal cancer (CRC) is the second leading cause of cancer-related death in the United States, and early detection is critical to improve prognosis. To date, we have applied our unique methodology (the Sentinel Principle) to identify blood-based gene expressed biomarkers for several diseases including osteoarthritis, bladder cancer and psychiatric disorders. In the present CRC study, we identified gene signatures from blood cells and characterized a set of biomarkers able to differentiate patients with CRC from controls. Methods: Microarray: 31 blood RNA sample (15 controls; 16 CRC) were profiled using Affymetrix U133Plus2.0 GeneChips. Differentially expressed genes were identified using the non-parametric, Wilcoxon-Mann-Whitney test. SYBR Green real-time RT-PCR: a subset of identified genes was assayed using 115 samples (57 controls; 58 CRC). Logistic regression was used to assess the ability of linear combinations of specific transcripts to distinguish CRC from controls. The diagnostic power for each combination was evaluated by AUC of the Receiver Operating Characteristic (ROC) curve. Blind Test: 83 samples were assayed (45 controls and 38 CRC). Results: Microarray data: 2,779 probes were significantly different in blood gene expression profiles from controls and those from CRC (p<0.05). Real-time RT-PCR: Two up-regulated genes (cytidine deaminase, 1.3 fold with p<0.001; MGC20553 /FERM domain containing 3, 1.2 fold with p=0.031) and three down-regulated genes were validated (B-cell scaffold protein with ankyrin repeats 1, 0.43 fold with p<0.001; B-cell novel protein 1, 0.44 fold with p<0.001; membrane-spanning 4-domains, subfamily A, member 1, 0.44 with p<0.001). Combination analysis: The AUC was 0.883 (95%, C.I. 0.810–0.935) for the best linear combination of these 5 genes. At a cut-off of -1.1, the sensitivity and specificity were 98% and 51%, respectively. Blind Test: The 5-gene set gave sensitivity of 95% (36/38) and specificity of 42% (19/45) with an overall accuracy of 66%. Conclusions: Gene expression signatures from peripheral blood differentiate between CRC patients and controls. The five-gene panel showed high classification performance and could be used as a novel screening tool for CRC. [Table: see text]

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