ALK-Negative Anaplastic Large Cell Lymphomas with 6p25.3 Translocations Show a Histone-Modifying Gene Expression Signature

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 88-88
Author(s):  
Andrew L. Feldman ◽  
Gaofeng Huang ◽  
Julie C Porcher ◽  
Sertac Kip ◽  
Stephen M Ansell ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Pathway Analysis ◽  
Gene Expression Signature ◽  
Unsupervised Clustering ◽  
Multiple Testing Correction ◽  
Modifying Genes ◽  
Expression Signature ◽  
Qrt Pcr ◽  
T Cell Lymphomas

Abstract Abstract 88 Introduction: The biology and genetics of anaplastic large T-cell lymphomas (ALCLs) lacking ALK translocations remain poorly defined. We recently identified recurrent translocations involving the DUSP22-IRF4 locus on 6p25.3 in ALK-negative ALCL (Blood 2011;117:915–9). This translocation is present in about 20% of ALK-negative ALCLs and is absent in other T-cell lymphomas; however, the biologic consequences are unknown. In this study, we utilized gene expression profiling (GEP) to compare T-cell lymphomas with and without this translocation. Methods: cDNA was prepared from total RNA extracted from frozen tissue from 25 T-cell lymphoma patients under a Mayo Clinic IRB-approved protocol as follows: 5 ALK-negative ALCLs with 6p25.3 translocations (2 systemic, 3 cutaneous), 12 ALK-negative ALCLs without 6p25.3 translocations (11 systemic, 3 cutaneous), 5 ALK-positive ALCLs, and 3 CD30-positive peripheral T-cell lymphomas (1 transformed mycosis fungoides and 2 not otherwise specified). Partner loci in cases with 6p25.3 translocations were 7p32.3 in 2, 9p24.3 in 1, and unknown in 2. GEP data (Affymetrix U133 plus 2.0) were analyzed by unsupervised clustering; in addition, a GEP signature was developed using genes with raw values >200 in at least 2 cases with at least 2-fold, statistically significantly different expression between 6p25.3-translocated and non-translocated cases (p<0.05 after Benjamini-Hochberg multiple testing correction). Representative overexpressed genes were confirmed by quantitative real-time (qRT-) PCR. Supervised pathway analysis was performed using signatures derived from other studies or curated from public pathway databases. Results: By unsupervised clustering, the 5 cases with 6p25.3 translocations clustered together (281 probe sets). A GEP signature segregating translocated from non-translocated cases included 283 genes (195 up- and 88 down-regulated). Key features of this signature included altered expression of histone-modifying genes (e.g. EZH2, SUZ12, MLLT3, MLL; HDAC4) and up-regulation of cancer-testis antigen (CTA) genes (e.g. SSX4, TEX14, MAGEA12, SSX1, CTAG2). The signature included down-regulation of DUSP22 but not of other genes on 6p25 in the signature. Additional overexpressed genes were validated by qRT-PCR (relative expression: TEX14, 2.9, p=0.01, t test; MAL, 6.5, p=0.003; CCR8, 7.6, p=0.0004). Supervised pathway analysis demonstrated a high proliferation signature in cases with 6p25.3 translocations (p=0.006 vs. untranslocated cases). Conclusions: ALK-negative ALCLs with translocations involving the DUSP22-IRF4 locus on 6p25.3 have a distinct gene expression signature characterized by alterations of histone-modifying genes and CTA genes (which typically are regulated epigenetically, either through histone modifications or changes in methylation). This signature appears independent of anatomic site (systemic vs. cutaneous) and partner locus (7p32.3 vs. other). DUSP22, encoding a dual-specificity phosphatase involved in modulating mitogen-activated protein kinase (MAPK) signaling, is significantly down-regulated in translocated cases; however, pathway analysis did not show significant alterations in MAPK-associated genes. Other known genes in the region of the breakpoint on 6p25 were not affected substantially. These findings suggest the possibility of an unrecognized function of DUSP22. Contributions of the varying partner loci remain unclear. The distinct GEP signature associated with 6p25.3 translocations provides strong support for their biologic relevance. Finally, the genes involved in the histone-modifying signature show overlap with histone-modifying genes mutated in B-cell lymphomas, suggesting potential commonalities in the biology and possibly targeted treatment of B- and T-cell lymphomas. Disclosures: No relevant conflicts of interest to declare.

PI3KCA and PIM Inhibitors in Peripheral T-Cell Lymphomas

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4917-4917
Author(s):  
Esperanza Martin-Sanchez ◽  
Socorro M. Rodriguez-Pinilla ◽  
Luis Lombardia ◽  
Margarita Sanchez-Beato ◽  
Beatriz Dominguez-Gonzalez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
T Cell ◽  
Cell Cycle Arrest ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Dependent Manner ◽  
Expression Signature ◽  
Cycle Arrest ◽  
T Cell Lymphomas

Abstract Abstract 4917 T-cell lymphomas (TCL) are a heterogeneous group of aggressive malignancies lacking specific and efficient therapy. Unfortunately, there are neither animal models nor representative cell lines for most TCL types, making functional and pharmacogenomics studies even more difficult. PI3K and PIM are kinases involved in cell proliferation, frequently altered in human cancer that seems to play a critical role in T-cell development and activation. Genomic studies have identified PIK3CD subunit to be significantly associated with in activation of CD40, NF-kB and TCR-pathways. The aim of this project is to determine the efficiency of PI3K inhibitors (PI3Ki) and PIM inhibitors (PIMi) in TCL, looking for biomarkers of their mechanism of action and to identify markers that could identify responders from non-responders. Twenty PTCL and seven reactive lymph nodes were studied using gene expression microarrays. We performed an in silico analysis using the Connectivity Map program to identify drugs that could potentially reverse PTCL gene expression signature. Among them, several PI3K/mTOR inhibitors were found. A panel of 6 TCL cell lines belonging to different TCL subgroups were treated with 3 PI3Ki (LY294002, ETP-45658, GDC-0941) and one PIMi (ETP-39010). Functional studies were also done to establish the role of each of the targeted genes. In vitro studies showed that PI3Ki induced G1 cell cycle arrest in all cell lines, and apoptosis in a portion of them, in a time/dose-dependent manner. We also observed a decrease in the levels of pAKT(S473), pGSK3B(S9) and p-p70S6K(T389) after treatment. In addition, both the analysis of the PTCL gene expression signature as well as western blot studies on TCL cell lines has shown overexpression of PIM family genes, A decrease in cell viability, and a strong induction of apoptosis in all cell lines was seen after PIM inhibition, without cell cycle arrest. Several diagnostic and pharmacodynamic biomarkers of PIMi have been identified at the mRNA and protein level in both cell lines In conclusion, our results indicate that PI3Ki and PIMi are effective therapeutic approaches for TCLs, identifying potential markers for patient's stratification and pharmacodynamic assessment. Disclosures: No relevant conflicts of interest to declare.

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus

2018 ◽  
Vol 100 (6) ◽  
pp. 575-583
Author(s):  
Lei-lei Zhou ◽  
Xiao-yue Xu ◽  
Jie Ni ◽  
Xia Zhao ◽  
Jian-wei Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Bioinformatics Analysis ◽  
Gene Expression Signature ◽  
Gene Expression Omnibus ◽  
Expression Signature ◽  
T Cell Lymphomas

scholarly journals A Gene Expression Signature That Correlates with CD8+ T Cell Expansion in Acute EBV Infection

2015 ◽  
Vol 195 (9) ◽  
pp. 4185-4197 ◽  
Author(s):  
Thomas C. Greenough ◽  
Juerg R. Straubhaar ◽  
Larisa Kamga ◽  
Eric R. Weiss ◽  
Robin M. Brody ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Cell Expansion ◽  
Gene Expression Signature ◽  
Cd8 T Cell ◽  
Expression Signature ◽  
Ebv Infection ◽  
T Cell Expansion

Association between stromal/TGF-β/EMT gene expression signature and response to pembrolizumab monotherapy in cisplatin-ineligible patients with locally advanced (unresectable) or metastatic urothelial carcinoma.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 433-433 ◽  
Author(s):  
Petros Grivas ◽  
Daniel E. Castellano ◽  
Peter H. O'Donnell ◽  
Razvan Cristescu ◽  
Tara L. Frenkl ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Urothelial Carcinoma ◽  
Cox Regression ◽  
Performance Status ◽  
Locally Advanced ◽  
Gene Expression Signature ◽  
P Value ◽  
Expression Signature ◽  
Ecog Ps

433 Background: PD-L1 immunohistochemistry and an 18-gene T cell–inflamed gene expression profile (GEP) are associated with response to anti–PD-1/PD-L1 therapy across tumor types, including urothelial carcinoma. A gene expression signature representing convergent biology related to stromal/EMT/TGF-β pathways was developed and prespecified for testing for association with pembrolizumab response in urothelial carcinoma patients treated on the KEYNOTE-052 trial (NCT02335424). Methods: KEYNOTE-052 was a single-arm phase 2 trial of pembrolizumab in cisplatin-ineligible patients with previously untreated, advanced urothelial carcinoma. Primary objective of this analysis was to assess the association between the Stromal/EMT/TGF-β signature and outcomes (best overall response [BOR], PFS, OS) as an independent biomarker and to understand its potential prognostic/predictive role beyond the T cell–inflamed GEP score or PD-L1 assessed using combined positive score (CPS). Cox regression models for PFS and OS and a logistic regression model for BOR evaluated associations between Stromal/EMT/TGF-β signature and outcomes adjusting for ECOG performance status (PS) and level of the GEP or CPS (1-sided P value). Results: RNA-Seq data from baseline tumor specimens were available for 187/370 patients on KEYNOTE-052. Lower Stromal/EMT/TGF-β score was associated with favorable BOR rate ( P < 0.001), PFS ( P < 0.001), and OS ( P = 0.002) after adjustment for ECOG PS and GEP (which remained significant at the 0.05 level in all cases). The patterns indicated a very consistent downward trend in the distribution of the Stromal/EMT/TGF-β score for responders versus nonresponders, regardless of GEP. In models that adjusted for both ECOG PS and PD-L1 CPS, the Stromal/EMT/TGF-β score remained significant (BOR rate, P = 0.002; PFS, P = 0.013; OS, P = 0.029). Conclusions: Higher Stromal/EMT/TGF-β signature was associated with resistance to pembrolizumab independently of GEP or PD-L1 in urothelial carcinoma patients on the KEYNOTE-052 trial. Clinical trial information: NCT02335424.

A blood-based gene expression signature of early-stage non-small cell lung cancer.

2012 ◽  
Vol 30 (30_suppl) ◽  
pp. 69-69
Author(s):  
Melissa Rotunno ◽  
Nan Hu ◽  
Hua Su ◽  
Chaoyu Wang ◽  
Pier Alberto Bertazzi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Predictive Accuracy ◽  
Early Stage ◽  
Single Gene ◽  
Gene Expression Signature ◽  
Mrna Levels ◽  
Healthy Controls ◽  
Expression Signature ◽  
Qrt Pcr

69 Background: Accurate blood-based biomarker for early cancer detection could be an easier and more convenient screening option than monitoring the target organ via tissue or imaging. We recently identified and validated eight genetic biomarkers of early-stage lung adenocarcinoma detectable in both peripheral whole blood (PWB) and lung tissue of smokers. Since biomarkers distinguishing benign disease versus lung malignancy across all cell types are needed in the diagnostic clinical setting, it is important to test the identified biomarkers in other lung cancer histologies, particularly in squamous cell carcinoma (SQCC), the second most common lung cancer histology after adenocarcinoma (AD). Methods: Using Real-Time Quantitative PCR (qRT-PCR), we measured mRNA levels for the eight candidate genes in PWB of 48 randomly sampled stage I SQCC cases, in addition to previously analyzed 82 AD cases and 130 age, sex, and smoking frequency matched healthy controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study. The qRT-PCR data were analyzed using the 2-ΔΔCtmethod to compare SQCC cases with controls. The area under the receiver operating characteristic curve (AUC) was computed to assess the predictive accuracy of the candidate biomarkers in SQCC separately, and in SQCC and AD together. Results: Expression of TGFBR3, RUNX3, TRGC2, TRGV9, TARP, and TSTA3 genes, significantly differentiated SQCC cases versus controls, while ACP1 and VCAN gene expression did not. The eight genes combined discriminated patients with lung cancer from healthy controls with similarly high accuracy in SQCC and overall (AUC = 0.80 ± 0.1). RUNX3 showed the highest single gene accuracy for SQCC (AUC = 0.78). Conclusions: We showed that the previously identified gene expression signature of early-stage lung AD also differentiated early stage SQCC from healthy controls and demonstrated its sensitivity and specificity as a potential diagnostic lung cancer biomarker. Since lung cancer is the most common cause of cancer mortality worldwide and current smokers are at very high risk, our smoking-specific findings, if confirmed and translated into screening approaches, have the potential to impact public health.

Data Mining of Hematopoietic Stem Cell Microarray Studies Reveals a Novel Stem Cell Gene Expression Signature and Demonstrates Feasibility of Integrating Data from Different Labs and Different Microarray Platforms.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4073-4073
Author(s):  
D. Sohal ◽  
A. Yeatts ◽  
K. Ye ◽  
A. Pellagatti ◽  
L. Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Stem Cell ◽  
Hematopoietic Stem Cell ◽  
Missing Values ◽  
Gene Expression Signature ◽  
Unsupervised Clustering ◽  
Biological Information ◽  
Hematopoietic Stem ◽  
Expression Signature

Abstract Microarray based studies of global Gene Expression (GE) have led to dramatic advances in our understanding of various biological processes and have resulted in a large amount of data in public repositories, like the Gene Expression Omnibus (GEO). Metaanalysis of this data has the potential to yield important biological information, but is hampered by technical issues due to different platforms and gene annotations used in various studies. In an attempt to conduct a metaanalysis, a total of 69 individual normal hematopoietic stem cell (HSC) GE datasets (9 whole bone marrow, 57 CD34+ cell studies) were identified in GEO. These had been done on 3 microarray platforms (Affymetrix U95, U133 A/B and U133 Plus 2.0). Since the probe identifiers and complementary cDNAs were different on these platforms, we integrated the data using both Unigene and RefSeq protein IDs and obtained a total of 8598 common Unigene and 8345 RefSeq probes after removing missing values. Unsupervised clustering of normalized GE values demonstrated that experimental conditions, lab where the experiments were performed and different microarray platforms can result in variability in GE patterns from similar sources of cells. To determine the degree of dissimilarity of these datasets from those obtained from biologically distinct tissues, GE profiles from various human tissues (brain, heart, kidney, etc.) were obtained from GEO and compared with hematopoietic stem cells. Unsupervised clustering showed that samples from the same tissue of origin clustered together despite different platforms/labs, demonstrating that our approach can group biologically distinct tissues together in spite of experimental and platform variability. To further test the discriminatory ability of the metaanalysis, we took datasets from hematologic malignancies and normal hematopoietic and non-hematopoietic tissues analyzed with the same platform (U133). We observed greater similarity between leukemias, myelodysplasia (MDS) and normal HSCs when compared to non-hematopoietic tissues, again validating the discriminatory power of this metaanalysis. In fact, some datasets from bone marrow samples from MDS were very similar to normal CD34+ cells and clustered within their groups. We believe this was a strong validation of our analysis as MDS is a preleukemic disorder with varying levels of pathology and can have cases that are genetically very similar to normal hematopoietic stems. We next attempted to search for a gene expression signature characteristic of HSCs by finding genes that were uniformly enriched in HSC datasets and at the same time differentially expressed when compared to normal non-hematopoietic tissues. We found 46 such “stemness” genes in our dataset. Functional pathway analysis by Ingenuity revealed that these genes were part of cell cycle and hematopoiesis pathways, thus decreasing the likelihood of our findings to be due to chance. In addition to known genes such as Gata2, Myb, Lyn kinase and Stat5A; several novel functional genes like SWI/SNF family member SMARCE1, Bone marrow stromal antigen 2, Septin 6, Topoisomerase II and H2A histone proteins were found to be enriched in HSCs by our analysis. Thus, we demonstrate a feasible and valid approach for metaanalysis of publicly available gene expression data that can yield further insights into human physiology and disease.

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.

Synergistic Targeting of Protein Translation and Inhibition of NOTCH Signaling in T-ALL

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3719-3719
Author(s):  
Marta Sanchez-Martin ◽  
Alberto Ambesi-Impiombato ◽  
Luyao Xu ◽  
Yue Qin ◽  
Daniel Herranz ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Notch Signaling ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Protein Translation ◽  
Withaferin A ◽  
Antileukemic Activity ◽  
Expression Signature ◽  
Gene Expression Signatures

Abstract Oncogenic NOTCH signaling is a major driver of T-cell transformation in T-cell acute lymphoblastic leukemia (T-ALL). However, clinical studies testing the efficacy of NOTCH1 inactivation with γ-secretase inhibitors (GSIs) have shown limited antileukemic activity for these drugs as single agents. Here we used an expression-based virtual screening approach and network perturbation analyses to identify and functionally characterize new highly active antileukemic drugs synergistic with NOTCH1 inhibition in T-ALL. Gene expression profiling studies have shown a prominent gene expression signature dominated by genes involved in growth and metabolism downstream of NOTCH1 in T-ALL. Notably, loss of the PTEN tumor suppressor gene confers resistance to GSI therapy and effectively rescues the gene expression signature induced by NOTCH1 inhibition in T-ALL. We hypothesized that drugs inducing transcriptional programs overlapping with those driven by NOTCH1 inhibition and antagonizing those resulting from PTEN loss could have synergistic antileukemic effects with GSIs in PTEN wild type and PTEN null leukemia cells. To address this question we generated gene expression signatures from Pten conditional-inducible knockout NOTCH1-driven leukemias in basal condition, upon NOTCH1 inhibition by GSI treatment and upon deletion of Pten. Connectivity Map (cMAP) analysis in this series identified 17 high scoring compounds as candidate antileukemic drugs (p<0.01). Reassuringly these included two inhibitors of the mTOR/PI3K/AKT pathway (rapamycin, wortmannin), but also histone deacetylase inhibitors (vorinostat, trichostatin A and valproic acid), phenothiazine antipsychotic drugs (trifluoperazine and thioridazine), antimalarial agents (astemizole, mefloquine) and compounds with less characterized activities such as withaferin A, parthenolide and pyrvinium pamoate. Transcriptional profiling followed by pairwise gene set enrichment analysis of these compounds identified groups of drugs with highly interconnected transcriptional programs suggestive of an overlapping mechanism of action (e.g. mTOR/PI3K inhibitors, HDAC inhibitors and phenothiazines), as well as compounds with more unique expression signatures suggestive of a more distinct mode of action (e.g. withaferin A, astemizole and mefloquine). Detailed characterization of the antileukemic effects of these 17 cMAP hits alone and in combination with the GSI DBZ in a broad panel of human NOTCH1-mutated T-ALL cell lines, identified withaferin A, rapamycin, wortmannin, parthenolide and vorinostat as the most active (lethal dose 50 <0.5 µM) and GSI-synergistic (combination index <0.4) drugs in this series. Among these, withaferin A, stood out as the most cytotoxic and GSI-synergistic compound against both PTEN positive and PTEN null T-ALL cell lines. Moreover, withaferin A treatment of primary mouse NOTCH1-induced T-ALLs and primary human T-ALL xenografts demonstrated strong and GSI-synergistic antileukemic activity in vivo. To address the mechanisms mediating the antileukemic effects of withaferin A we performed a detailed analysis of the gene expression signatures induced by this drug in T-ALL lymphoblasts. These studies revealed a strong enrichment of downregulated genes involved in translation regulation in T-ALL cells upon treatment with withaferin A (p<0.001). Mechanistically, transcriptional network perturbation analysis identified the eIF2A translation initiation complex as a potential effector of the antileukemic effects of withaferin A, and withaferin A treatment induced strong dose dependent phosphorylation of eIF2S1 in position S51, a modification responsible for blocking the activity of the eIF2A complex. Consistently, polysome profiling and nascent-protein assays revealed decreased translation in T-ALL cells treated with withaferin A. In this context, expression a phosphomimetic mutant form of eIF2S1 (S51D) impaired leukemia cell viability. Moreover, expression of a non-phosphorylatable form of eIF2S1 (eIF2S1 S51A) in T-ALL cells abrogated the antileukemic effects of withaferin A.These results support a direct role of eIF2S1 phosphorylation and the inhibition of eIF2A-dependent translation as a critical mediators of the antileukemic effects of withaferin A in T-ALL and a role for the combination of GSIs and inhibitors of protein translation for the treatment of high risk T-ALL. Disclosures Califano: Therasis Inc: Employment; Cancer Genetics Inc: Consultancy; Ipsen pharmaceuticals: Consultancy; Thermo Fischer Scientific: Consultancy.

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