Identification of a Novel Gene Expression Signature in Mantle Cell Lymphoma from the Fondazione Italiana Linfomi (FIL)-MCL-0208 Trial: A Focus on the B Cell Receptor Pathway

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 701-701
Author(s):  
Riccardo Bomben ◽  
Simone Ferrero ◽  
Michele Dal Bo ◽  
Tiziana D'Agaro ◽  
Alessandro Re ◽  
...  
Keyword(s):  
Gene Expression ◽  
Board Of Directors ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Gene Signature ◽  
Advisory Committees ◽  
Expression Signature ◽  
Qrt Pcr ◽  
Mantle Cell ◽  
Bcr Signaling

Abstract Background. The aggressive clinical behavior of mantle cell lymphoma (MCL) is attributed to specific genetic and molecular mechanisms involved in its pathogenesis, mainly the t(11;14)(q13;q32) traslocation and cyclin D1 (CCND1) overexpression. Nevertheless, evidence of a certain degree of clinical/biological heterogeneity has been disclosed by gene expression profile (GEP) and (immuno)genetic/immunohistochemistry studies. Aim. To use a GEP approach to identify MCL subsets with peculiar clinical/biological features in the context of MCL patients treated homogeneously with an autologous transplantation-based program. Methods. The study was based on a cohort of 42 MCL cases enrolled in the Fondazione Italiana Linfomi (FIL)-MCL-0208 randomized Italian clinical trial. Purified clonal CD19+ MCL cells were obtained by high-speed cell sorting of peripheral blood MCL samples. GEP experiments were performed in 30 cases, with Agilent platform. Bioinformatics analyses were performed by Gene Springs and Gene Set Enrichment Analysis (GSEA) software. Gene signature validations were performed by quantitative real time PCR (QRT-PCR). Results. i)Unsupervised and supervised analyses. Unsupervised analysis by principal component analysis (PCA) was able to divide the cohort in two main subgroups named PCA1 (12 cases) and PCA2 (18 cases). Supervised analysis by segregating cases according to the PCA1 and PCA2 classification defined a gene expression signature of 710 gene (234 up-regulated) that highlighted a constitutive overexpression of genes of the BCR signaling pathway. Consistently,GSEA showed a significant enrichment of genes belonging to 3 gene sets related to BCR signaling. ii) Identification of a "PCA2-type" gene signature. By merging the list of differentially expressed genes according to supervised analysis of GEP data and the gene list related to BCR signaling according to GSEA, a group of 9 genes, all overexpressed in PCA2 cases, i.e. AKT3, BLNK, BTK, CD79B, PIK3CD, SYK, BCL2, CD72, FCGR2B, was obtained. Among these genes, a subgroup of 6 genes, i.e. AKT3, BLNK, BTK, CD79B, PIK3CD, SYK, was selected for the direct involvement in the BCR pathway, and utilized for further validations. iii) Generation of a 6-gene prediction model. The selected 6 genes were then utilized to generate a prediction model by using 20 cases as training sub-cohort and the remaining 10 cases as validation cohort. By this approach, 9/10 cases of the validation cohort were correctly assigned according to the PCA2/PCA1 classification. The model was re-tested by QRT-PCR in 24 cases used in the GEP (16 for training and 8 for validation), and again, 7/8 cases of the validation sub-cohort were correctly classified. QRT-PCR was then utilized to classify further 12 cases (7 cases defined as PCA2) not employed for GEP analysis. Overall, in the 42 cases, 23 cases were considered as PCA2 with the GEP/QRT-PCR approach. iv) Clinical/biological correlations. No association was found between the 6-gene signature and IGHV status (22/30 unmutated IGHV cases) or between the signature and the overexpression of SOX11 (17/30 cases over the median value). In addition, no association was found with the presence of the main recurrent mutations of the ATM, BIRC3, CCND1, KMTD2, NOTCH1, TP53, TRAF2, WHSC1 genes. Finally, an "ad-interim" analysis of progression free survivals (PFS) (Cortelazzo et al EHA, 2015) suggested a trend for a shorter PFS (2-years PFS 45% vs 72%, p=0.08) for cases classified as PCA2 by the GEP/QRT-PCR approach. v) 6-gene signature and sensitivity to the BCR inhibitor ibrutinib. The finding that PCA2 cases overexpressed BCR-related genes and had a more aggressive clinical course prompted us to investigate the 6-gene signature in the context of ibrutinib sensitive/resistant MCL cell lines. To do this, the proliferation rate of the MCL cell lines REC1, JEKO1, UPN1, GRANTA, JVM2, Z138 was investigated either in presence or in absence of ibrutinib 10 nanoM for 7 days. REC1, JEKO1 were selected as responsive by showing ≥80% inhibition upon ibrutinib. Of note, responsive cell lines showed higher expression levels of the 6-gene signature then the resistant counterpart, as evaluated by QRT-PCR. Conclusions. A novel 6-gene expression signature related to the BCR pathway has been found to characterize MCL cells with peculiar clinical/biological features and sensitivity to BCR inhibitors. Disclosures Luminari: Roche: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees.

scholarly journals A Gene Expression Signature to Predict Nucleotide Excision Repair Defects and Novel Therapeutic Approaches

2021 ◽  
Vol 22 (9) ◽  
pp. 5008
Author(s):  
Rongbin Wei ◽  
Hui Dai ◽  
Jing Zhang ◽  
David J. H. Shih ◽  
Yulong Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nucleotide Excision Repair ◽  
Cell Lines ◽  
Excision Repair ◽  
Gene Expression Signature ◽  
Gene Signature ◽  
Expression Signature ◽  
Nucleotide Excision ◽  
Functionally Impaired ◽  
Synthetically Lethal

Nucleotide excision repair (NER) resolves DNA adducts, such as those caused by ultraviolet light. Deficient NER (dNER) results in a higher mutation rate that can predispose to cancer development and premature ageing phenotypes. Here, we used isogenic dNER model cell lines to establish a gene expression signature that can accurately predict functional NER capacity in both cell lines and patient samples. Critically, none of the identified NER deficient cell lines harbored mutations in any NER genes, suggesting that the prevalence of NER defects may currently be underestimated. Identification of compounds that induce the dNER gene expression signature led to the discovery that NER can be functionally impaired by GSK3 inhibition, leading to synergy when combined with cisplatin treatment. Furthermore, we predicted and validated multiple novel drugs that are synthetically lethal with NER defects using the dNER gene signature as a drug discovery platform. Taken together, our work provides a dynamic predictor of NER function that may be applied for therapeutic stratification as well as development of novel biological insights in human tumors.

A 20 Gene Expression Signature That Predicts Early Molecular Response Failure in Chronic Phase CML Patients Treated with Frontline Imatinib

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 596-596 ◽  
Author(s):  
Chung Hoow Kok ◽  
Tamara M Leclercq ◽  
Dale Watkins ◽  
David T Yeung ◽  
Verity A Saunders ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Board Of Directors ◽  
Clinical Outcomes ◽  
Research Funding ◽  
Chronic Phase ◽  
Gene Expression Signature ◽  
Gene Signature ◽  
Molecular Response ◽  
Advisory Committees

Abstract BACKGROUND: In chronic phase chronic myeloid leukemia (CP-CML) patients treated with frontline imatinib, failure to achieve early molecular response (EMR failure: BCR-ABL1 >10% at 3 months) predicts for subsequent inferior outcomes. Identifying patients at high-risk of EMR failure provides an opportunity to improve outcomes by personalising treatment at the time of diagnosis, as intervention after EMR failure may be less effective. AIM: To utilise a predictive gene signature to identify CP-CML patients at diagnosis, who are at high risk of EMR failure and inferior clinical outcomes. METHODS: Peripheral blood mononuclear cells collected from 119 patients enrolled in the TIDEL-II study were subjected to gene expression microarray profiling (GEP) Illumina HT12. Validations of the identified microarray genes were performed using Taqman qPCR. All patients commenced imatinib treatment, and switched to nilotinib with or without an antecedent trial of high dose imatinib if they failed to achieve time dependent molecular targets. Clinical outcomes included EMR and cumulative incidence of MMR and MR4.5 (BCR-ABL1 ≤0.1% and ≤0.0032% on the international scale, respectively), and comparisons were made using Fine and Gray test. Competing risks included permanent trial discontinuation for any reason (including death or progression). Event-free survival (EFS) and failure-free survival (FFS) were performed using Kaplan-Meier and comparisons were made using the log-rank test. RESULTS: Fourteen of the 119 patients demonstrated EMR failure (12%). Comparing the GEP of these patients with those that achieved EMR identified 4456 aberrantly expressed genes in the EMR failure group. This gene set was significantly enriched for stem cell phenotype/signalling (e.g. Myc, β-catenin, Hoxa9/Meis1), cell cycle, and reduced immune response pathways associated with adverse prognosis in other cancers. From these genes, 20 genes (IGFBP2, CD3E, RASGRP1, BNIP3L, ETS1, PDK1, METTL7A, HECA, COL8A2, PRSS57, TMEM167A, SPAST, FZD7, VPS41, CDKN1B, CPXM1, SEPT7, RPS28, SLX4IP, and SRSF11) validated by qPCR were selected by nearest shrunken centroid model as the high-risk gene expression signature (high-riskGES) to predict EMR failure. Patients who had a high-riskGES exhibited significantly higher rates of EMR failure compared to those with low-riskGES (training cohort: 73.3% vs 8.0%; p<0.0001; n=40, Hazard Ratio (HR): 4.1). This was validated on an independent patient cohort (validation cohort: 50.0% vs 14.8%; p=0.018; n=39; HR: 3.2). Overall, when both cohorts were combined, patients who had a high-riskGES exhibited significantly higher rates of EMR failure compared to those with low-riskGES (63.0% vs 11.5%; p<0.0001; n=79, HR: 3.3; Figure 1A). The overall prediction accuracy of the signature was 80% (82% specificity, 74% sensitivity). Additionally, patients with a high-riskGES demonstrated significantly worse clinical outcome than those with low-riskGES by 24 months (MMR: 41% vs 83%, p=0.0003; MR4.5: 4% vs 42%, p=0.0004; EFS: 52% vs 92%, p<0.0001; FFS: 44% vs 89%, p<0.0001) (Figure 1B-E). This high-riskGES was confirmed as an independent predictor for EMR failure, when Sokal, age and gender were added as covariates based on the Cox-proportional multivariate analysis (HR: 0.34, p=0.003). Patients who had a high-riskGES also had significant inferior outcomes even if they subsequently achieved EMR, compared to the low-riskGES patient group that subsequently achieved EMR (MR4.5: 10% vs 48%, p=0.034; EFS: 68% vs 96%, p=0.0099; FFS: 60% vs 91%, p=0.011). Furthermore, this 20-gene signature compared favourably to Sokal, EUTOS, Hasford, and OCT-1 Activity in predicting EMR failure based on assessing their respective overall performance F -score (harmonic mean of precision and sensitivity). EMR failure was observed in 15% (n=33) of low Sokal score patients overall and 12% of the low-riskGES group (n=49) but amongst patients who had both low-riskGES and a low Sokal score, 0/25 experienced EMR failure. SUMMARY: For the first time in the CML setting, we have identified and validated a 20-gene signature to predict, at the time of diagnosis, patients at high risk of EMR failure and subsequent inferior clinical outcomes. The ability to predict high risk patients at diagnosis may facilitate the assessment of novel therapeutic approaches designed to improve clinical outcomes for patients with aggressive disease. Disclosures Yeung: BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. White:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Hughes:ARIAD: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.

Use of predictive gene expression signature from advanced-stage serous papillary ovarian cancer to identify biologically relevant molecular targets for chemoresponse

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5500-5500
Author(s):  
L. Ozbun ◽  
T. Bonome ◽  
M. Radonovich ◽  
C. Pise-Masison ◽  
J. Brady ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Cell Lines ◽  
Ovarian Cancer Cell ◽  
Gene Expression Signature ◽  
Advanced Stage ◽  
Expression Signature ◽  
Qrt Pcr ◽  
Ovarian Cancer Cell Lines ◽  
Cisplatin Sensitivity

5500 Background: The aim of our study was to develop and validate a gene expression signature predictive for chemoresponse in advanced stage serous papillary ovarian cancer. Methods: Gene expression profiling was performed on 52 chemonaive, microdissected advanced stage, high-grade papillary serous ovarian cancers using Affymetrix whole-genome microarrays. Patient samples were grouped based on chemoresponse. 19 nonresponders were refractory to chemotherapy, 14 responders relapsing 6 months were considered chemosensitive. Each group was divided into training/validation sets. To generate a predictive gene signature, class prediction algorithms were applied to genes differentially expressed between chemosensitive/resistant or chemosensitive/refractory tumors (p<0.001) using leave-one-out cross-validation. Array validation was performed by qRT-PCR. Select genes underwent biological validation in a series of ovarian cancer cell lines. Results: 31 genes predictive for resistance and 105 genes predictive for refractory to chemotherapy were identified. Percentages of arrays accurately predicted in independent validation sets were 90% (9/10) for resistant and 92% (12/13) for refractory gene signatures. Correlations between microarray/qRT-PCR data were robust for both resistant (17/23 genes) and refractory gene signatures (25/34 genes). Data mining of the predictive signatures using PathwayStudio software identified several biological processes (collagen regulation, apoptosis, cell survival, and DNA repair) implicated in conferring resistance to chemotherapy. We transiently transfected RNAi molecules to silence several signature genes and determine their contribution to taxol/cisplatin sensitivity in a series ofl ovarian cancer cell lines. Preliminary data showed DUSP1 gene expression knockdown potentiated cisplatin sensitivity in SKOV3/OVCA429 cell lines, while POLH knockdown potentiated cisplatin sensitivity in OVCA429/OVCA420 cell lines. Conclusions: A gene expression signature predicts for chemoresponse in ovarian cancers, and has identified novel targets of biological/therapeutic interest. No significant financial relationships to disclose.

scholarly journals B-Cell Receptor Driven MALT1 Activity Regulates MYC Signaling in Mantle Cell Lymphoma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 611-611
Author(s):  
Beiying Dai ◽  
Michael Grau ◽  
Mélanie Juilland ◽  
Pavel Klener ◽  
Elisabeth Höring ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Board Of Directors ◽  
Research Funding ◽  
Cell Lymphoma ◽  
Cell Receptor ◽  
B Cell Receptor ◽  
Advisory Committees ◽  
Mantle Cell ◽  
Bcr Signaling

Abstract Mantle cell lymphoma (MCL) is a mature B-cell lymphoma characterized by poor prognosis. Recent studies revealed the importance of constitutive B-cell receptor (BCR) signaling in maintaining survival of a subset of MCLs. MALT1 is an essential component of the CARD11-BCL10-MALT1 (CBM) complex that links BCR signaling to the nuclear factor kappa-B (NF-κB) pathway. Additionally, MALT1 functions as a protease that cleaves various substrates to promote proliferation and survival. However, its role in the molecular pathogenesis of MCL is unknown. To elucidate the functional role of MALT1 in the biology of MCL, we determined its proteolytic activity in primary MCL cells and in MCL derived cell lines. A large fraction of MCLs displayed constitutive activity of MALT1. This MALT1 activity is driven by constitutive BCR signaling, as we were able to show that RNA interference-mediated knockdown of central components of the BCR cascade abolished MALT1 activity. To gain insights into the functional significance of MALT1 in MCL, we knocked down its expression by different MALT1 shRNAs. Transduction of these shRNAs induced cytotoxicity in models that are characterized by constitutive MALT1 activity, whereas no effect on survival was observable in MCLs without MALT1 activation. To determine if this MALT1 addiction translates into an in vivosetting, we knocked down MALT1 in mouse MCL models and detected a significant inhibition of tumor growth. This indicates that MALT1-activated MCLs are dependent on the function of MALT1. These results were confirmed as pharmacologic inhibition of MALT1 significantly reduced cell viability in MALT1-activated MCLs, implying that MALT1 inhibition might represent a promising therapeutic strategy for MCL patients. To understand which biologic processes are regulated by MALT1 in MCL, we profiled gene expression changes at different time points following MALT1 inhibition. An unbiased gene set enrichment analysis identified various previously described MYC gene expression signatures to be among the top downregulated signatures, suggesting that MALT1 regulates MYC expression. MYC downregulation following MALT1 inhibition or MALT1 knockdown was confirmed at the protein level and various analyses revealed that MALT1 regulates MYC expression posttranslationally by preventing its proteasomal degradation. These results were further confirmed in primary mouse splenocytes, indicating that this novel molecular mechanism of regulating MYC expression is not restricted to MCL. To confirm that MYC is indeed expressed in primary MCLs, we determined MYC expression in 234 primary MCL samples by immunohistochemistry. These analyses revealed that 75 samples (32.1%) displayed an intermediate and 55 samples (23.5%) a high MYC positivity, suggesting that MYC is expressed in a substantial number of primary MCLs. As common alterations such as MYC high-levelamplifications and translocations determined by FISH occurred extremely rarely in our primary MCL samples (1% of samples), it is conceivable that BCR-driven MALT1 signaling is the predominant mechanism of MYC upregulation in MCL. In summary, we report for the first time that a substantial fraction of MCLs is addicted to constitutive MALT1 signaling. Thus, MCLs can be divided based on their MALT1 activation status into two distinct subgroups. We further identified a novel regulatory mechanism of MYC expression by MALT1. Thus, our study provides a strong mechanistic rationale to investigate the therapeutic efficacy in targeting the MALT1-MYC axis in MCL patients. Disclosures Trneny: Janssen Research & Development: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Dreyling:Roche: Consultancy, Honoraria, Research Funding, Speakers Bureau. Tzankov:Novartis: Speakers Bureau; Abbott: Speakers Bureau.

IKZF3 Overexpression Phenocopies Gain-of-Function Mutation in Chronic Lymphocytic Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 9-9
Author(s):  
Shanye Yin ◽  
Gregory Lazarian ◽  
Elisa Ten Hacken ◽  
Tomasz Sewastianik ◽  
Satyen Gohil ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
Dna Binding ◽  
B Cell ◽  
Board Of Directors ◽  
Research Funding ◽  
Lymphocytic Leukemia ◽  
Advisory Committees ◽  
Bcr Signaling ◽  
Experimental Group

A hotspot mutation within the DNA-binding domain of IKZF3 (IKZF3-L162R) has been identified as a putative driver in chronic lymphocytic leukemia (CLL); however, its functional effects are unknown. We recently confirmed its role as a CLL driver in a B cell-restricted conditional knock-in model. IKZF3 mutation altered mature B cell development and signaling capacity, and induced CLL-like disease in elderly mice (~40% penetrance). Moreover, we found IKZF3-L162R acts as a gain-of-function mutation, altering DNA binding specificity and target selection of IKZF3, and resulting in overexpression of multiple B-cell receptor (BCR) genes. Consistent with the murine data, RNA-sequencing analysis showed that human CLL cells with mut-IKZF3 [n=4] have an enhanced signature of BCR-signaling gene expression compared to WT-IKZF3 [n=6, all IGHV unmutated] (p&lt;0.001), and also exhibited general upregulation of key BCR-signaling regulators. These results confirm the role of IKZF3 as a master regulator of BCR-signaling gene expression, with the mutation contributing to overexpression of these genes. While mutation in IKZF3 has a clear functional impact on a cardinal CLL-associated pathway, such as BCR signaling, we note that this driver occurs only at low frequency in patients (~3%). Because somatic mutation represents but one mechanism by which a driver can alter a cellular pathway, we examined whether aberrant expression of IKZF3 could also yield differences in BCR-signaling gene expression. We have observed expression of the IKZF3 gene to be variably dysregulated amongst CLL patients through re-analysis of transcriptomic data from two independent cohorts of human CLL (DFCI, Landau et al., 2014; ICGC, Ferreira et al., 2014). We thus examined IKZF3 expression and BCR-signaling gene expression, or the 'BCR score' (calculated as the mean expression of 75 BCR signaling-associate genes) in those cohorts (DFCI cohort, n=107; ICGC cohort, n=274). Strikingly, CLL cells with higher IKZF3 expression (defined as greater than median expression) had higher BCR scores than those with lower IKZF3 expression (&lt;median) (p=0.0015 and p&lt;0.0001, respectively). These findings were consistent with the notion that IKZF3 may act as a broad regulator of BCR signaling genes, and that IKZF3 overexpression, like IKZF3 mutation, may provide fitness advantage. In support of this notion, our re-analysis of a gene expression dataset of 107 CLL samples (Herold Leukemia 2011) revealed that higher IKZF3 expression associated with poorer prognosis and worse overall survival (P=0.035). We previously reported that CLL cells with IKZF3 mutation appeared to increase in cancer cell fraction (CCF) with resistance to fludarabine-based chemotherapy (Landau Nature 2015). Instances of increase in mut-IKZF3 CCF upon treatment with the BCR-signaling inhibitor ibrutinib have been reported (Ahn ASH 2019). These studies together suggest an association of IKZF3 mutation with increased cellular survival following either chemotherapy or targeted treatment. To examine whether higher expression of IKZF3 was associated with altered sensitivity to ibrutinib, we performed scRNA-seq analysis (10x Genomics) of two previously treatment-naïve patients undergoing ibrutinib therapy (paired samples, baseline vs. Day 220). We analyzed an average of 11,080 cells per patient (2000 genes/cell). Of note, following ibrutinib treatment, remaining CLL cells expressed higher levels of IKZF3 transcript compared to pretreatment baseline (both p&lt;0.0001), whereas no such change was observed in matched T cells (n ranging between 62 to 652 per experimental group, p&gt;0.05), suggesting that cells with high expression of IKZF3 were selected by ibrutinib treatment. Moreover, we showed that ibrutinib treatment resulted in consistent upregulation of BCR-signaling genes (e.g., CD79B, LYN, GRB2, FOS, RAC1, PRKCB and NFKBIA) (n ranging between 362 to 1374 per experimental group, all p&lt;0.0001), which were likewise activated by mutant IKZF3. Altogether, these data imply that IKZF3 mutation or overexpression may influence upregulation of BCR-signaling genes and enhance cellular fitness even during treatment with BCR-signaling inhibitors. We highlight our observation that IKZF3 mutation appears to be phenocopied by elevated IKZF3 expression, and suggest that alterations in mRNA or protein level that mimic genetic mutations could be widespread in human cancers. Disclosures Kipps: Pharmacyclics/ AbbVie, Breast Cancer Research Foundation, MD Anderson Cancer Center, Oncternal Therapeutics, Inc., Specialized Center of Research (SCOR) - The Leukemia and Lymphoma Society (LLS), California Institute for Regenerative Medicine (CIRM): Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VelosBio: Research Funding; Oncternal Therapeutics, Inc.: Other: Cirmtuzumab was developed by Thomas J. Kipps in the Thomas J. Kipps laboratory and licensed by the University of California to Oncternal Therapeutics, Inc., which provided stock options and research funding to the Thomas J. Kipps laboratory, Research Funding; Ascerta/AstraZeneca, Celgene, Genentech/F. Hoffmann-La Roche, Gilead, Janssen, Loxo Oncology, Octernal Therapeutics, Pharmacyclics/AbbVie, TG Therapeutics, VelosBio, and Verastem: Membership on an entity's Board of Directors or advisory committees. Wu:BionTech: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding.

The Expression Signature of M3 AML Suggests Direct and Indirect Effects of PML-RARA on Target Genes.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 719-719 ◽  
Author(s):  
Jacqueline E. Payton ◽  
Nicole R. Grieselhuber ◽  
Li-Wei Chang ◽  
Mark A. Murakami ◽  
Wenlin Yuan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Cell Lines ◽  
Binding Sites ◽  
Expression Profiles ◽  
Gene Expression Signature ◽  
Myeloid Cell ◽  
Expression Signature ◽  
Signature Genes ◽  
Cell Fractions

Abstract In order to better understand the pathogenesis of acute promyelocytic leukemia (APL, FAB M3), we sought to determine its gene expression signature by comparing the expression profiles of 14 APL samples to that of other AML subtypes (M0, M1, M2, M4, n=62) and to fractionated normal whole bone marrow cells (CD34 cells, promyelocytes, PMNs, n=5 each). We used ANOVA and SAM (Significance Analysis of Microarrays) to select genes that were highly expressed in APL cells and that displayed low to no expression in other AML subtypes. The APL signature was then further refined by filtering genes whose expression in APL was not significantly different from that of normal promyelocytes, yielding 1121 annotated genes that reliably distinguish APL from the other FAB subtypes using unsupervised hierarchical clustering, both in training and validation datasets. Fold change differences in expression between M3 and other AML FAB classes were striking, for example: GABRE 35.4, HGF 21.3, ANXA8 21.3, PTPRG 16.9, PTGDS 12.1, PPARG 11.1, STAB1 9.8. A large proportion of the APL versus other FAB dysregulome was recapitulated when we compared APL expression to that of the normal pattern of myeloid development. We identified 733 annotated genes with significantly different expression in APL versus normal myeloid cell fractions. These dysregulated genes were assigned to 4 classes: persistently expressed CD34 cell-specific genes, repressed promyelocyte-specific genes, prematurely expressed neutrophil-specific genes and genes with high expression in APL and low/no expression in normal myeloid cell fractions. Expression differences in several of the most dysregulated genes were validated by qRT-PCR. We then examined the expression of the APL signature genes in myeloid cell lines and tumors from a murine APL model. The bona fide M3 signature was not apparent in resting NB4 cells (which contain t(15;17), and which express PML-RARA), nor in PR-9 cells following Zn induction of PML-RARA expression, suggesting that neither cell line accurately models the gene expression signature of primary APL cells. Most of the nodal genes of the mCG-PML-RARA murine APL dysregulome (Yuan, et al, 2007) are similarly dysregulated in human M3 cells; however, the human and mouse dysregulomes do not completely coincide. Finally, we have begun investigating which APL signature genes are direct transcriptional targets of PML-RARA. The promoters of the APL signature genes were analyzed for the presence of known PML-RARA binding sites using multiple computational methods. The analyses demonstrated that several transcription factors (EBF3, TWIST1, SIX3, PPARG) have putative retinoic acid response elements (RAREs) in their upstream regulatory regions. Additionally, we examined the promoters of some of the most upregulated genes (HGF, PTGDS, STAB1) for known consensus sites of these transcription factors, and found that all have putative binding sites for at least one. These results suggest that PML-RARA may initiate a transcriptional cascade that relies not only on its own activity, but also on the actions of downstream transcription factors. In summary, our studies indicate that primary APL cells have a gene expression signature that is consistent and highly reproducible, but different from commonly used human APL cell lines and a mouse model of APL. The molecular mechanisms that govern this unique signature are currently under investigation.

A High-Risk Survival Classifier for Multiple Myeloma

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1800-1800
Author(s):  
Rowan Kuiper ◽  
Annemiek Broyl ◽  
Yvonne de Knegt ◽  
Martin H. van Vliet ◽  
Erik H. van Beers ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Board Of Directors ◽  
Gene Signature ◽  
Hazard Ratio ◽  
High Risk Population ◽  
Newly Diagnosed ◽  
Advisory Committees ◽  
Cytogenetic Aberrations ◽  
Standard Risk

Abstract Abstract 1800 Introduction: Survival of patients with newly diagnosed multiple myeloma (MM) is highly variable and currently used clinical prognostic markers such as the international staging system (ISS) and cytogenetic markers are insufficiently adequate for defining individual patient prognosis. We established a prognostic signature based on gene expression profiling. Methods: The signature was generated using a training set of 290 newly diagnosed MM patients included in the multicenter, prospective open-label randomized phase 3 HOVON65/GMMG-HD4 trial. Gene expression profiles, obtained from purified plasma cells, were generated using the Affymetrix GeneChip® Human Genome U133 Plus 2.0 platform (GSE19784; Broyl et al.,Blood 2010; 14:2543–2553). The model predictive for survival was built by supervised principal component analysis (Bair et al., J. Amer. Statistical Assoc. 2006;101:119–37) and further optimized by simulated annealing. The generated survival signature was compared to six previously reported MM gene expression signatures (i.e. UAMS-70, UAMS-17 (Shaughnessy et al., Blood. 2007;109:2276–84), gene expression-based proliferation index (GPI, Hose et al., Haematol. 2010; 96: 87–95), MRC-IX-6 gene (Dickens et al., Clin. Cancer Res. 2010;16:1856–1864), Millennium (Mulligan et al., Blood 2007; 109:3177–3188) and IFM (Decaux et al., J. Clin. Oncol. 2008; 26:4798–4805). Results: A signature of 92 probe sets (EMC-92-gene signature) was highly discriminative for high-risk MM patients, defined as overall survival (OS) < 2 yr (21.7%) vs. standard-risk MM. This performance was confirmed in independent validation datasets of newly diagnosed MM patients (UAMS-TT2, n=351, GSE2658; MRC-IX, n=247, GSE15695) and relapse MM patients (APEX, n=264, GSE9782). In the UAMS-TT2 dataset, a high-risk population of 19.1% was identified which had a hazard-ratio of 3.52 (P = 2.5 × 10−8). In the MRC-IX study, 20.2% of patients were identified as high risk with a hazard-ratio of 2·38 (P = 3·6 × 10−6; Figure 1a) The high-risk signature was able to identify patients with significantly shorter survival in both the transplant-eligible and non-transplant-eligible patients included in the MRC-IX study. In non-transplant-eligible patients, 23.8% high risk patients were identified with a hazard-ratio of 2.38 (P = 4.3 × 10−4), whereas 17.5% of transplant-eligible patients were high-risk with a hazard-ratio of 2.54 (P = 1.5 × 10−3). The difference between survival in high-risk and standard risk was not restricted to newly diagnosed patients, as 15.9% of patients included in the APEX relapse study were designated high-risk with a hazard-ratio of 3·14 (P = 5·3 × 10−9; Figure 1b). In all sets the signature gave consistent and significant results and had good performance in comparison to other published high-risk gene signatures (Figure 2). In a pair-wise comparison to other high-risk gene signatures the EMC-92-gene showed to be among the top performing signatures and independent of all other signatures. In multivariate analyses, the EMC-92-gene signature proved an independent and superior predictor against clinical and cytogenetic variables such as the ISS and unfavourable cytogenetic aberrations including del(17p). Using the independent MRC-IX set, poor prognostic cytogenetic aberrations 1q gain, del(17p), t(4;14), t(14;16), t(14;20) and del(13q), were enriched in high-risk patients, whereas the frequency of standard risk cytogenetic aberrations such as t(11;14) was lower in the high-risk populations. Although enriched in the high-risk population, still more than half of patients in the standard risk group showed one or more poor prognostic cytogenetic markers Conclusions: We developed a high-risk signature highly discriminative for patients with high-risk versus standard-risk MM, irrespective of treatment regime, age and relapse setting. Use of this signature in the clinical setting may lead to a more informed treatment choice and potentially better outcome for the patient. Disclosures: van Vliet: Skyline Diagnostics: Employment. van Beers:Skyline Diagnostics: Employment, Patents & Royalties. Mulligan:Millennium Pharmaceuticals, Inc.: Employment. Morgan:Millennium Pharmaceuticals, Inc: Honoraria. Gregory:Celgene: Honoraria. Goldschmidt:Johnson& Johnson: Membership on an entity's Board of Directors or advisory committees. Lokhorst:Genmab: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Sonneveld:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Skyline Diagnostics: Membership on an entity's Board of Directors or advisory committees.

The Combination Of Hypomethylating Agents and Histone Deacetylase Inhibitors(HDACi) Are Synergistically Cytotoxic and Reverse The Malignant Phenotype In Preclinical Models Of T-Cell Lymphoma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 646-646 ◽  
Author(s):  
Owen A. O'Connor ◽  
Enrica Marchi ◽  
Kelly Zullo ◽  
Luigi Scotto ◽  
Jennifer E. Amengual ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Board Of Directors ◽  
Cell Lines ◽  
Single Agent ◽  
Hematologic Malignancies ◽  
Advisory Committees ◽  
Methylation Array ◽  
Simultaneous Exposure ◽  
The Mean

Abstract Both HDAC inhibitors (HDACIs) and DNA methyltransferase inhibitors (DNMTIs) are known to influence global expression patterns in hematologic malignancies. Little is known about the combination of these two drug classes in lymphoid malignancies. HDACIs have marked single agent activity in the T- cell lymphomas (TCL), although the mechanism of action is not well defined. DNMTIs affect cytosine methylation of genomic DNA and have activity mainly restricted to the myeloid derived hematologic malignancies. The single agent efficacy and synergistic interaction of a panel of HDACIs (panobinostat, belinostat, romidepsin and vorinostat) and DNMTIs (decitabine (DEC), 5-azacytadine (5-AZA)) was evaluated in models of TCL. The molecular basis for the synergistic effect of HDACIs and DNMTIs was evaluated by gene expression profiling (GEP) and CpG methylation CTCL. Single agent concentration and time effect relationships were generated for 2 CTCL (HH, H9) and 2 T-ALL (P12, PF382) cell lines. Romidepsin and belinostat were the most potent HDACIs with the mean 48 hour IC50 of 8.8 nM (range 1.7-2.7 nM) and 85 nM (range 36-136 nM), respectively. Cell viability was not affected by treatment with DEC or 5-AZA at 24 and 48 hours at concentrations as high as 20 μM. Reduction in viability was first demonstrated after 72 hours of exposure to DEC, with the mean IC50 of 14.8 μM (range 0.4 μM- >20uM). Simultaneous exposure of combinations of DEC plus romidepsin or DEC plus belinostat at their IC10, IC20, and IC50 produced marked synergy in all TCL derived cell lines. Simultaneous exposure of DEC plus romidepsin demonstrated the deepest synergy at 72 hours with synergy coefficients in the range of 0.3. Cells treated with the combination of DEC plus romidepsin also demonstrated significant induction of apoptosis as evaluated by annexinV/propridium iodide via FACS analysis and an increase in acetylated histone 3 by immunoblot. The in vivo activity of the combination of DEC plus belinostat was investigated in a xenograft model of CTCL using HH, the most resistant TCL derived cell line. Mice were treated with DEC 1.5 mg/kg (day 29, 33, 35, 37, 39, 41, 43) and/or belinostat 100 mg/kg (day 29-day 47). The combination mouse cohort demonstrated statistically significant tumor growth delay compared to DEC alone (p=0.002) and belinostat alone (p=0.001). The interaction of DEC and romidepsin was analyzed by GEP and methylation array. Interestingly, the baseline malignant phenotype seen in the CTCL cell-lines was reversed. A significant down-regulation of genes involved in biosynthetic pathways including protein and lipid synthesis, and a significant up-regulation of genes responsible for cell cycle arrest were seen. The vast majority (114/138; 92%) of genes modulated by the single agents were similarly modulated by the combination. However, the latter induced a further significant change in the transcriptome, affecting an additional 390 genes. Similarly, methylation array data was analyzed following treatment of these drugs alone and in combination. DEC induced de-methylation of 190 different gene regions corresponding to 175 genes and an additional 335 loci. Interestingly, when combined with romidepsin the number of demethylated gene regions decreased to 85 corresponding to 79 genes, 78 of which were common with DEC and 148 additional loci. The comparison of gene expression and methylation demonstrated a significant inverse relationship (R2 = 0.657) with genes found to be differentially expressed in GEP and methylation analysis. (Figure 1)Figure 1Summary of gene expression and methylation analysis.Figure 1. Summary of gene expression and methylation analysis. These data support the observation that DNMTIs in combination with HDACIs produces significant synergistic activity in models of TCL. Further evaluation of the mechanism of action with DNMTIs in combination with HDACIs is ongoing, and a clinical trial of the combination is now open. Disclosures: O'Connor: Celgene Pharmaceuticals: Consultancy; Spectrum Pharmaceuticals: Membership on an entity’s Board of Directors or advisory committees; Allos Therapeutics: Consultancy, Membership on an entity’s Board of Directors or advisory committees. Off Label Use: Hypomethylating Agents in T-cell lymphoma. Amengual:Acetylon Pharmacueticals, INC: Membership on an entity’s Board of Directors or advisory committees, Research Funding.

A gene expression signature to predict high-grade prostate cancer response to oxaliplatin.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 150-150
Author(s):  
Philippe Pourquier ◽  
Stephane Puyo ◽  
Pierre Richaud ◽  
Jacques Robert ◽  
Nadine Houede
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Clinical Trials ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Chemotherapeutic Agents ◽  
Low Grade ◽  
Gleason Grade ◽  
High Grade ◽  
Expression Signature

150 Background: Prostate cancer (PCa) is one of the leading causes of death from cancer in men. High Gleason grade prostate cancers are characterized by aggressive tumors with poorly differentiated cells and a high metastatic potential. They are often refractory to chemical castration but still treated with hormone therapy to which docetaxel or cabazitaxel are added when they become resistant to the anti-androgen. Despite many clinical trials with other chemotherapeutic agents, response rates remain low. Moreover, none of these trials took into account the tumor grade. Methods: We used an in silico approach to screen for drug candidates that could be used as an alternative to taxanes, based on a 86 genes signature which could distinguish between low-grade and high-grade tumors. We extracted from the NCI60 panel databases the expression profiles of the 86 genes across 60 human tumor cell lines and the corresponding in vitro cytotoxicity data of 152 drugs and looked for correlation between their expression level and cell sensitivity to each of these drugs. Results: Among the 86 genes, we identified 9 genes (PCCB, SHMT2, DPM1, RHOT2, RPL13, CD59, EIF4AI, CDKN2C, JUN) for which expression levels across the 60 cell lines was significantly correlated (p< 0.05) to oxaliplatin but not to cisplatin sensitivity. This signature was validated at the functional level since repression of each of these genes conferred a significant change in the sensitivity of PCa cell lines to oxaliplatin but not cisplatin. Conclusions: Our results provide a proof of concept that gene expression signature specific from high grade PCa could be used for the identification of alternative therapies to taxanes. They could also be used to select patients for further clinical trials and as predictive markers of response to these drugs, which represents a further step forward towards personalized therapy of PCa.

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