ALBERT

Description: Our group and others have shown that acute myeloid leukemia (AML) cells have unique mitochondrial characteristics with an increased reliance on oxidative phosphorylation. Through an shRNA screen for new biological vulnerabilities in the mitochondria of AML cells, we identified the mitochondrial protease, neurolysin (NLN). NLN is a zinc metalloprotease whose mitochondrial function is not well understood and whose role in AML growth and viability has not been previously reported. We analyzed the expression of NLN in AML cells and normal hematopoietic cells. By immunoblotting, NLN was overexpressed in 80% of primary AML patient samples compared to normal hematopoietic cells. Likewise, in an analysis of gene expression databases, NLN mRNA was increased in a subset of AML patient samples, compared to normal hematopoietic cells. Next, we assessed the effects of knocking down NLN in AML cell lines (OCI-AML2, NB4, and MV4-11) using three independent shRNAs in lentiviral vectors. Target knockdown was confirmed by immunoblotting. NLN knockdown reduced growth in all three tested cell lines by 50-70%. NLN knockdown also targeted the leukemia initiating cells in vitro and in vivo as NLN knockdown reduced the clonogenic growth of AML cells (40-75%) and the engraftment of TEX cells into immune deficient mice by 85%. Taken together, these data suggest that NLN is necessary for the growth of AML cells. The role of NLN in the mitochondria is not well understood. To gain insight into NLN's mitochondrial function, we investigated NLN's protein interactors using proximity-dependent biotin labeling (BioID). The top hits in the protein-protein interaction screen were mitochondrial matrix proteins and respiratory chain subunits were particularly enriched. Therefore, we measured the effects of NLN knockdown on mitochondrial structure and function. Knockdown of NLN in AML cells reduced basal oxygen consumption without altering reactive oxygen species generation, mitochondrial membrane potential, or mitochondrial mass. No changes were seen in the total levels of respiratory chain complex subunits as measured by immunoblotting on denaturing gels. Respiratory chain complexes assemble into higher order supercomplex structures that maintain the integrity of the mitochondria and promote efficient oxidative metabolism. Therefore, we tested whether NLN is required for the formation of respiratory chain supercomplexes. As measured by blue native polyacrylamide gel electrophoresis, knockdown of NLN impaired the formation of respiratory chain supercomplexes. Through our BioID analysis, we also identified the mitochondrial Ca2+/H+ antiporter, LETM1 (leucine zipper-EF-hand containing transmembrane protein 1) as a top interactor with NLN. LETM1 is a known regulator of respiratory chain supercomplex formation. We showed that knockdown of NLN impaired LETM1 assembly, potentially explaining how NLN regulates supercomplex formation. Finally, we tested if hypoxia influences respiratory chain supercomplex formation and sensitivity to NLN inhibition. OCI-AML2 cells cultured for 72 hours under hypoxic conditions (0.2% O2) showed impaired assembly of respiratory chain supercomplexes, decreased levels of LETM1 protein, and resistance to NLN knockdown. Thus, we discovered that the mitochondrial protease NLN regulates oxidative metabolism by controlling the assembly of respiratory chain supercomplexes. Moreover, we highlight NLN as a potential new therapeutic target for AML. Disclosures Schimmer: Otsuka Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Medivir AB: Research Funding; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees.

Description: Immunotherapy targeting individual antigens in acute myeloid leukemia (AML) has shown promise. However, in view of leukemia heterogeneity and the loss of tumor antigen expression by AML, it is unlikely that any single antigen will be consistently expressed by all leukemia cells. This highlights the need to identify additional antigens in AML that can be targeted. Azurophil granule proteases have been shown to be effective immunotherapeutic targets. Proteinase 3 and neutrophil elastase, the parent proteins for the HLA-A2 restricted peptide PR1, have been targeted successfully in myeloid leukemia using immunotherapy. We recently discovered the HLA-A2 restricted peptide CG1 (FLLPTGAEA), which is derived from the azurophil granule protease cathepsin G (CG). We showed that CG is highly expressed by AML blasts and leukemia stem cells in a limited number of AML samples and showed that CG1 can be targeted in vitro using CG-specific cytotoxic T lymphocytes (CTL). We sought to determine whether CG1 can be targeted in vivo and to characterize the expression of CG in a large cohort of AML patients. To assess the efficacy of targeting CG1 in vivo, we used a NOD scid gamma (NSG) mouse model engrafted with the human HLA-A2+ AML cell line U937 (U937-A2), which is known to express CG. Mice were injected with U937-A2 (0.5 x 106) cells and on the following day were treated with either CG1-CTL (0.25 x 106), negative control HIV-CTL expanded from the same donor or were left untreated. Mice treated with CG1-CTL demonstrated a significantly greater reduction in U937-A2 in the bone marrow (BM) (8% residual AML; P

Description: Treatment of AML is guided by cytogenetics, age, patients’ medical condition and increasingly, new molecular markers. However, no definitive algorithms and biomarkers predicting response to induction chemotherapy exist. We recently showed that distinct protein profiles of AML correlate with cytogenetics, FAB classes and treatment outcome for a class/group of patients as a whole (Tibes, ASH 2005; Kornblau, ASH 2006 and manuscript in submission). To further individualize therapy, we applied a set-based decision modeling methodology based on the Rough Set Theory (RST) to our initial proteomic dataset of 34 (phospho)-proteins for 96 samples from 73 patients (Tibes, ASH 2005). The first model was built based on partitioning discretized protein expression levels of proteins for the 96 samples into 2 outcome categories: complete remission (CR) vs. refractory to treatment; we generated reducts for all proteins and computed pseudo-cores. Several proteins (incl. phospho-NPM1, PTEN, phospho-AKT, p53, cyclin D1 etc.) were able to distinguish outcomes in terms of CR and refractoriness. A second model based on discretized clinical condition attributes (e.g., blast %, FAB, cytogenetics, age, sex, blood counts etc.) yielded the most important clinical reducts. In a third model, protein expression and clinical attributes were combined to generate decision rules to predict outcome to induction therapy for each patient. For proof-of-concept purposes, the data set was divided into a training set and a test set. Prediction accuracy for CR vs. refractory state was in the 75% range for individual patients based on their pre-treatment clinical and proteomic attributes. In conclusion, predictive models obtained with RST yield reducts corresponding to a small but significant number of proteins (6–8) and clinical parameters which can further be used to derive association rules, capable of accurately predicting a patient’s response to induction therapy. The availability of several dozens of distinct decisions rules within each group (CR vs. refractory) based on protein expression and clinical characteristics, allows an individualized approach for each patient. This preliminary study is now being expanded on an independent proteomic dataset of 52 proteins for 258 AML samples (Kornblau, ASH 2006) to be presented at the Annual Meeting. The clinical utility lies in the fact that measuring expression levels of our protein biomarker profiles can be adopted to routine clinical testing (e.g., immunohistochemistry on diagnosis marrows) and potentially help to direct patients towards standard chemotherapy, upfront treatment on a clinical trial or evaluation for early transplant depending on the chance of response and relapse. Lastly, this model can be applied to predict other clinical outcomes (relapse vs. continuous CR), as well as to derive predictive signatures of gene expression datasets.

Description: Survivin, a member of the inhibitors of apoptosis protein family, plays important roles in cell proliferation and survival and is highly expressed in various malignancies, including leukemias. To better understand its role in acute myeloid leukemia (AML), we profiled survivin expression in samples obtained from 511 newly diagnosed AML patients and in CD34+38− AML stem/progenitor cells using a validated reverse-phase protein array; we correlated its levels with clinical outcomes and with levels of other proteins in the same sample set. We found that survivin levels were higher in bone marrow than in paired peripheral blood leukemic cells (n = 140, P = .0001) and that higher survivin levels significantly predicted shorter overall (P = .016) and event-free (P = .023) survival in multivariate Cox model analysis. Importantly, survivin levels were significantly higher in CD34+38− AML stem/progenitor cells than in bulk blasts and total CD34+ AML cells (P 〈 .05). Survivin expression correlated with the expressions of multiple proteins involved with cell proliferation and survival. Particularly, its expression strongly correlated with HIF1α in the stem/progenitor cell compartment. These results suggest that survivin is a prognostic biomarker in AML and that survivin, which is overexpressed in AML stem/progenitor cells, remains a potentially important target for leukemia therapy.

Description: Sequence-specific single-stranded DNA binding protein 2 (SSBP2) is a candidate tumor suppressor gene, located at chromosome 5q13.3, that is thought to regulate hematopoietic growth and differentiation. Loss of SSPB2 expression is associated with deletions of chromosome 5 and replacement in cell lines induces partial differentiation and loss of clonogencity. Using a highly specific antibody, we studied the level of expression and prognostic relevance of SSBP2 protein expression (along with 51 other total and phospho proteins as described in ASH abstract #107, 2006) in leukemia-enriched samples from 423 patients (258 newly diagnosed, 47 primary refractory, 118 relapse 1, 2 or refractory) using high-throughput reverse phase protein array technology (RPPA). Levels of SSBP2 were lower, equal and higher than that of normal CD34+ cells in 2.7%, 58.7% and 11.6% of cases respectively. All 7 cases with low levels were female and 21/30 with high levels were male. The expression of SSBP2 was not equally distributed in the different FAB subtypes with the lowest median levels in M5 and the highest in M0, M1 and M2. Levels were significantly higher in favorable cytogenetics (t(8;21) and Inv (16) compared to intermediate (p=0.05) or unfavorable (p=0.008) cytogenetics. Median levels were lowest in cases with cytogenetic abnormalities on chromosome 5 or with an 11q23 abnormality. Levels were significantly higher in primary refractory and relapse samples compared to diagnostic samples. The levels of SSBP2 expression was strongly positively correlated with expression levels of anti-apoptotic proteins BCL2, Bcl-XL, caspase inhibitors SMAC, Survivin and XIAP, and inversely correlated with inactivated Bad-p112. Expression also was positively correlated with proliferation regulating proteins β-Catenin, Cyclin D, GSK3, Myc, P27, as well as VEGF receptor neuropilin and P53. Levels were strongly negatively correlated with activated signal transduction proteins (STP) including phosphorylated AKT (phosphorylated on threonine 308 or serine 473), pMEK, pERK2, pP38, pPKCα and as well as activated P70S6K. For outcome analysis martingale residuals were utilized to define an optimal cutpoint for dichotomization into groups with higher (n=130, 111 treated) vs. lower (n=128, 106 treated) SSBP2. Complete remission rates (58% vs. 63%, p=0.39), relapse rates (53% vs. 49%, P=0.59, and median remission duration (37 vs. 39 weeks, p=0.37) did not differ between patients with lower vs. higher SSBP2. However patients with higher SSPB2 levels had significantly longer median survival (40 vs. 31 weeks, p=0.015) compared to patients with lower SSBP2 levels. In summary, SSBP2 expression is heterogeneous in AML ranging from low in the poor and mixed prognosis subsets and high in the good prognosis t(8;21). Consistent with its demonstrated role in hematopoietic differentiation, the levels correlate negatively with expression of proliferation enhancing and STP. Nonetheless, the significance of positive correlation with antiapoptotic proteins is unclear at present. But the association with favorable longer overall survival suggests that therapeutic agents targeting the SSBP2 pathway function might have efficacy in AML.

Description: We have used Reverse Phase Protein Arrays (RPPA) to perform proteomic profiling in Acute Myelogenous Leukemia (AML) focusing on cell cycle, apoptosis and signal transduction pathway proteins (ASH 2006, abstract #107). Protein expression signatures were derived from this dataset of 436 AML patients, analyzed for 30 total and 22 phopho- proteins. The predictive ability of these RPPA derived protein expression signatures has not been prospectively tested to determine if they are valid. This dataset presented an opportunity to validate this as there was a population of patients with known FLT3-ITD and D835 mutation status (n=297) and another population where the status was unknown (n=139), among which 55 had sufficient sample available for mutation analysis. Prior to performing the mutation analysis a predictive model was built using linear regression with part of the data utilized for training and the reminder for validation. The model was designed to predict for the presence of mutation, either ITD or D835, although there are differences int eh signature of each. The total population had 85 cases with FLT3-ITD and 15 with the D835 mutation. The optimal model that was developed, using 30%, 50% and 70% of the samples for training and the remainder for validation, had a median validation accuracy of 68%, 70% and 72% respectively. Prospective predictions of FLT3-ITD or D835 mutation status were then made for all samples lacking FLT3-ITD or D835 mutation data. Mutation analysis was then performed using PCR amplification followed by 2-D gel electrophoresis (FLT3-ITD) to evaluate for PCR product size, or sequencing (D835) on 55 samples. This revealed 9 cases with FLT3-ITD, 3 with a D835 mutation, 1 with both and 43 without mutation. Among these 55 cases the model correctly predicted that 8 of the 12 mutant cases would be mutant including 8 of 10 with a FLT3-ITD, but 0 of 2 with only the D835 mutation. Among the 43 wildtype cases 36 were accurately predicted to be wildtype, while 7 were incorrectly predicted to have the mutation mutant. This yields an overall accuracy (OA) of 80%, Sensitivity =66%, Specificity=90%, Positive Predictive Value (PPV) of 53%, False positive rate of (FPR) of 16%. Since most patients with FLT3-ITD have Diploid cytogenetics we also looked at the predictive accuracy of the protein expression signature in that population. Among 23 patients with Diploid cytogenetics the overall accuracy was OA) of 83%, Sensitivity =75%, Specificity=87%, Positive Predictive Value (PPV) of 75%, False positive rate of (FPR) of 13%. Since FLT3-ITD and D835 carry different prognostic impact, and had different protein expression signatures, greater accuracy might be achieved if separate models were developed for each mutation individually. The model demonstrated that RPPA derived protein expression signatures can accurately be used to predict mutation status providing the first prospective validation of protein expression signatures in AML.

Description: Functional activation of the PI3K/AKT signaling pathway provides survival signals to leukemic cells and pathway blockade may facilitate cell death. We have previously demonstrated that activation of AKT (phosphorylated on threonine 308 and serine 473 [pAKT308 & pAKT473]) pathway is a frequent event with adverse prognostic consequences in AML. To further explore the upstream regulation and downstream consequences of activation of this pathway in AML we assessed the level of expression and activation of PTEN/phosphoPTEN (pPTEN) (which controls AKT activation), P53 and DJ1 (which regulates PTEN), along with targets of activated AKT including proteins regulating proliferation (S6RP, Cyclin D1, GSK3, MTOR), and apoptosis (MCL, BAD, XIAP, BCL2). Total and phospho-protein levels from 258 leukemia-enriched samples of newly diagnosed, untreated AML patients were measured using high-throughput reverse phase protein array technology (RPPA). High P53 expression negatively correlated with PTEN levels (p=0.001). Almost all cases with very high P53 had unfavorable cytogenetics with complex karyotypes, and P53 mutations were found in 54% cases (see accompanying abstract). AKT activation, determined as high ratios of phospho to total (P/T) pAKT473 and pAKT308 were strongly correlated with loss of PTEN expression or increased PTEN phosphorylation,(p=0.0006 & 0.006) but not with increased levels of PTEN suppressor DJ1 (P=0.33 & 0.34). AKT activation (pAKT473 & pAKT308 P/T ratios) was associated with increased signaling through mTOR kinase (increased phosphorylation of S6RP on p236, p240, p244, p