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Introduction Juvenile myelomonocytic leukemia (JMML) is a rare and highly aggressive myeloid malignancy of early childhood. Approximately 95% of patients have at least one mutation that leads to hyperactive RAS signaling. Both the presence of multiple mutations at diagnosis as well as altered DNA methylation are associated with a poor prognosis. Whether altered DNA methylation leads to the acquisition of additional genetic mutations or is a secondary event to genetic mutations is unknown. In this study, we analyzed a total of 33 newborn blood screening (NBS) cards from children who went on to develop JMML later in childhood. Using next generation sequencing to detect both genetic mutations and DNA methylation status we sought to determine the sequence of events that lead to the development of JMML. Patients and Methods We identified 33 patients that were born in the state of California from 1990 to 2017 who were confirmed to have JMML and were previously consented to participate in a JMML tissue bank study. Guthrie cards from these 33 patients as well as 12 healthy controls were obtained from the California Biobank Program. DNA samples (20 ng) were sequenced for mutations using a custom amplicon-based sequencing approach (Paragon Genomics, Hayward, CA) targeting 26 genes that are recurrently mutated in JMML. For DNA methylation profiling, 300ng of genomic DNA was processed for bisulfite conversion using the TrueMethyl oxBS Module (Tecan Genomics Inc., Redwood City, CA.) according to manufacturer's guidelines and next generetation sequencing (NGS) libraries were prepared by targeting 3000 CpG loci using custom probes for Targeted Methyl-Seq assay (Tecan Genomics Inc., Redwood City, CA). Sequence reads were trimmed using Cutadapt to remove adapters and methylation status called using Bismark. Samples were classified into one of three methylation subgroups: Low, Intermediate, or High using 1386 probes according to an international consensus definition. Results At diagnosis of JMML, somatic mutations were identified in 32 of 33 patients. Of the 32 patients with a somatic mutation present upon diagnosis, the same mutations were found in NBS cards in 13 (41%) patients using a mutant allele fraction (MAF) cut-off of 1%. Clonal mutations (MAF >15%) were found in 9 of 32 (28%) patients. Patients who had a somatic mutation detected at birth were significantly younger at diagnosis with a median age of 7.1 months (range 2.5-91.6 months) compared to patients who had none (19.8 months; p-value = 0.042). However, no difference was observed in overall or event-free survival for patients with or without somatic mutations at birth. Methylation profiling classified all NBS cards as having "low" DNA methylation using an international, consensus definition (Figure 1A). Of the 33 patients, ten also had DNA methylation profiling performed on their diagnostic JMML sample which were classified as low (LM), intermediate (IM) or high methylation (HM) (Figure 1B). Amongst patients with both NBS and JMML methylation data available, 5 had mutations present in the NBS card and all 5 had lower methylation (β values) in their NBS card compared to their JMML sample (mean 0.38 vs 0.29, p-value = 0.002). Discussion We identified somatic Ras pathway mutations at birth in 13/32 (41%) of newborns that developed JMML later in their childhood. We found that patients with a somatic mutation detected at birth were significantly younger at diagnosis compared to patients who had no mutations at birth. DNA methylation profiling of NBS cards from children who went on to develop JMML revealed methylation signatures that were similar to normal age-matched controls. All newborn cards were classified as low methylation at birth. Specifically, amongst patients who had genetic mutations present at birth, methylation changes that were eventually detected in JMML samples were not present in the NBS cards. Therefore, we conclude that aberrant DNA methylation is a secondary event to genetic changes in JMML. Figure 1: Panel A: Methylation profiling of JMML NBS and control NBS samples, classified according to the international JMML methylation consensus signature. Panel B: Methylation profiling of paired NBS and diagnosis samples from JMML patients. The star indicates the NBS methylation profile. Heatmaps (A and B) show the beta values of 1386 CpG loci used for methylation classification. Figure 1 Disclosures Loh: Pfizer: Other: Institutional Research Funding; Medisix Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Genomic studies have revealed significant branching heterogeneity in cancer. Studies of resistance to tyrosine kinase inhibitor therapy have not fully reflected this heterogeneity because resistance in individual patients has been ascribed to largely mutually exclusive on-target or off-target mechanisms in which tumors either retain dependency on the target oncogene or subvert it through a parallel pathway. Using targeted sequencing from single cells and colonies from patient samples, we demonstrate tremendous clonal diversity in the majority of acute myeloid leukemia (AML) patients with activating FLT3 internal tandem duplication mutations at the time of acquired resistance to the FLT3 inhibitor quizartinib. These findings establish that clinical resistance to quizartinib is highly complex and reflects the underlying clonal heterogeneity of AML.

Introduction: Juvenile myelomonocytic leukemia is a heterogenous disease of early childhood that has both myelodysplastic and myeloproliferative properties. Outcomes range from spontaneous resolution with little to no therapy in some patients while others relapse even after hematopoietic stem cell transplantation. However, there is no single biomarker reliably capable of predicting outcome. Patients and Methods: Our three groups have recently published data regarding the predictive capacity of DNA methylation profiling using the Illumina Infinium Methylation 450k platform. Methylation data along with clinical annotation from 256 JMML patients (126 EWOG/MDS, 93 Japanese and 37 USA) were analyzed and a consensus algorithm to determine DNA methylation clustering was agreed upon. A technical validation of two clinically oriented DNA methylation approaches was undertaken using DNA from 32 patients (12 EWOG/MDS, 5 Japan and 15 USA) included in the previous publications. A biological validation using DNA from additional 48 JMML patients (9 EWOG/MDS, 19 Japan and 20 USA) that were not previously tested was also undertaken to independently validate the DNA methylation subgroups. All 80 patients from the technical and biological cohorts were analyzed for genetic mutations using a custom 25-gene panel next-generation-sequencing (NGS) approach. Informed consent to use of patient material was obtained in accordance with the Declaration of Helsinki and approved by the local institutional review boards. Results: Unsupervised hierarchical consensus clustering of 256 JMML patients using the 5000 CpG sites with the highest standard deviation separated patients into three distinct methylation subgroups using the 450k data. Based on the mean beta-value detected, the subgroups were designated as low methylation (LM), intermediate methylation (IM) and high methylation (HM). Strikingly, when comparing our new DNA methylation subgroup assignments to the published 450k DNA methylation subgroups, only 11 patients (3.86%) were now re-classified into a different methylation subgroup (Figure 1). Next two approaches were taken with the intent of clinical grade implementation of DNA methylation testing. In one approach at EWOG/MDS, a multiclass classification model (XGBoost) was developed based on the 5000 CpGs and tested by classifying the validation cohort into the respective methylation subgroups. When analyzing the relative contribution of each CpG to the model performance (Model Gain), we identified 10 CpG sites which contributed most to the model. Illumina Infinium 850k array testing using XGBoost of the technical cohort provided an accuracy of 90.6% resulting in misclassification of 3/32 patients as compared to the original 450k based designation of methylation subgroups. In the USA, an amplicon based, bisulfite treated, NGS approach (Methyl-NGS) using primers to sequence the top 3000 CpG sites from the meta-analysis was tested in the technical and biological validation cohorts. Using a standard deviation of 0.25 of the most variable probes to determine the methylation clusters, there was 100% concordance between the 450k and the Methyl-NGS designation of methylation subgroups. Conclusions: In this single largest collection of JMML data ever presented, we demonstrate the reproducibility of DNA methylation as a predictive biomarker of outcome across continents, platforms and different patient cohorts. The DNA methylation consensus subgroups generated from 256 JMML patients were associated with previously recognized variables such as age, platelet count, fetal hemoglobin status and the number of genetic alterations at diagnosis. However, DNA methylation cluster designation provided additional prognostic information, in particular in young patients or patients with monosomy 7 where fetal hemoglobin is not interpretable and clarified that not all patients with PTPN11, KRAS or NF1 are classified as IM or HM as might be expected based on genetics alone. Clinical grade implementation of DNA methylation testing using either Infinium based XGBoost or Methyl-NGS both provided a high degree of reproducibility with the original 450k data. Combining DNA methylation with previously recognized variables allows for a robust risk-stratification algorithm that is now ready to be implemented in clinics around the world and integrated into clinical trials. Disclosures Loh: Medisix Therapeutics, Inc.: Membership on an entity's Board of Directors or advisory committees. Niemeyer:Celgene: Consultancy. Lipka:InfectoPharm GmbH: Employment.

Juvenile myelomonocytic leukemia (JMML) is a rare myeloproliferative neoplasm of early childhood characterized by Ras pathway mutations and aberrant DNA methylation. Despite allogeneic hematopoietic stem cell transplantation (HSCT) approx. 30% of patients (pts) succumb to resistant leukemia. Slowly regressing disease in the absence of HSCT is, however, noted in some pts. Mutational patterns and known clinical risk factors are insufficient to fully explain this heterogeneity. Three independent recent studies demonstrated the potential of DNA methylation profiling to identify clinically meaningful risk groups (Lipka et al., Nat Commun 2017; Stieglitz et al., Nat Commun 2017; Murakami et al., Blood 2018). The aim of this work was to establish an international consensus for the classification of JMML based on DNA methylation, to systematically describe the biological and clinical features of the subgroups identified and to develop a molecular classifier that enables the prospective assignment of DNA methylation categories. In a collaborative effort, we re-analyzed three well-annotated Illumina 450k methylation array data sets. In total, data from 292 pts with JMML or Noonan syndrome-associated myeloproliferative disorder (NS/MPD; EWOG-MDS, Europe: 147 pts, Nagoya, Japan: 106 pts, UCSF, USA: 39 pts) were available. Methylation data from 285 pts passed our quality control and were included in the present analysis. Of these, 256 (89.8%) pts had been diagnosed with JMML and 29 (10.2%) with NS/MPD. Mean age at diagnosis was 1.9 yrs. Levels of fetal hemoglobin (HbF) were available in 228/285 pts and elevated for age in 61%. Driver mutations affecting the Ras pathway were identified in 92% of JMML pts (PTPN11: 36%, NF1: 11%, NRAS: 15%, KRAS: 15%, CBL: 14%), and monosomy 7 in 14%. Initial exploratory analysis revealed batch effects that could, at least in part, be explained by the different ethnical backgrounds of the pts but also included a technical component. Therefore, we stringently filtered probes containing SNPs and performed batch correction using an empirical Bayes framework (Combat). CpG dinucleotides (CpGs) showing variable methylation across normal hematopoietic cell types were excluded from the analysis to avoid confounding with differential cell type composition between the samples. Unsupervised consensus clustering using the 5000 most variable CpGs identified three stable methylation clusters in this inter-group patient cohort. According to their DNA methylation levels, the clusters were designated "high methylation" (HM), "intermediate methylation" (IM) and "low methylation" (LM). Overall, 29.5%, 23.5%, and 47.0% of the cohort of JMML and NS/MPD pts were assigned to the HM, IM, and LM clusters, respectively. The methylation clusters showed a highly significant association with specific Ras-pathway mutations and with known clinical risk factors. All NS/MPD pts clustered with the LM subgroup and showed the lowest methylation levels. The HM cluster was enriched for somatic PTPN11 mutations, elevated HbF and older age, while the LM cluster was enriched for NRAS and CBL mutations, normal HbF and age assignments made in the present study to those from the original publications found only 3.9% (11/285) discordant cases. This encouraged us to establish a low-dimensional DNA methylation classifier for JMML that could be applied in a prospective setting. Therefore, we split the intergroup cohort randomly into a training (N=202) and a validation cohort (N=83) and trained an extreme gradient boosting machine (xgboost). When using as few as 10 CpGs, the resulting model predicted methylation clusters with 94% accuracy in the validation cohort. This inter-group meta-analysis is the single largest dataset of JMML patients to date and demonstrates the robustness of the JMML methylation signature across continents of origin and its power to identify biologically and clinically distinct JMML subgroups. Our ongoing efforts include developing a sequencing-based assay to predict DNA methylation clusters and to validate this assay using an independent cohort of 60 pts from the three participating research groups. This assay would allow for inclusion of DNA methylation as a biomarker into prospective clinical trials to assist in molecularly driven risk-stratification of JMML. Disclosures Niemeyer: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Upfront resistance to glucocorticoids (GCs) confers a poor prognosis for children with T-cell acute lymphoblastic leukemia (T-ALL). Using primary diagnostic samples from the Children's Oncology Group trial AALL1231, we previously demonstrated that one-third of patient T-ALL samples are intrinsically resistant to GCs when cultured in the presence of interleukin-7 (IL7), a cytokine that is abundant in the T-ALL microenvironment. Furthermore, we demonstrated that inhibiting JAK/STAT signaling downstream of the IL7 receptor (IL7R) with the JAK1/2 inhibitor ruxolitinib (RUX) overcomes GC resistance in these samples. The objective of the present study was to determine the mechanism of IL7-induced GC resistance in T-ALL and to identify novel therapeutic targets to enhance GC sensitivity. We utilized CCRF-CEM cells, a human T-ALL cell line, as a model system in conjunction with primary patient samples. Exposing CCRF-CEM cells to IL7 induced phosphorylation of STAT5, the predominant downstream effector of IL7R signaling. When cultured in the presence of IL7 and the GC dexamethasone (DEX), CCRF-CEM cells recapitulated the IL7-induced GC resistance phenotype observed in patient samples. This resistance could be overcome with RUX, and Bliss index analysis demonstrated a synergistic relationship between DEX and RUX in the presence of IL7. Furthermore, CRISPR/Cas9 mediated knockout of STAT5 (STAT5 KO) was sufficient to overcome resistance, implicating STAT5 as the critical mediator of IL7-induced GC resistance. DEX exposure potently induced upregulation of IL7R expression in CCRF-CEM cells. Using a luciferase reporter construct containing a series of STAT5 response elements, we demonstrated that in the presence of IL7, DEX-induced upregulation of IL7R expression is associated with increased downstream signal transduction, leading to a significant increase in STAT5 transcriptional output. We then performed RNA-seq to further assess the functional consequences of this enhanced STAT5-mediated transcription. Gene set enrichment analysis (GSEA) revealed that STAT5 target genes were significantly upregulated in cells exposed to DEX and IL7 relative to IL7 alone (normalized enrichment score -2.27; p < 0.001; FDR < 0.001), suggesting that DEX exposure augments activation of the STAT5 transcriptional program. One critical component of this program that was induced by the combination of DEX and IL7 was the anti-apoptotic family member BCL2, which was not induced by DEX alone. Further analysis of its protein expression in CCRF-CEM cells confirmed this paradoxical upregulation of BCL2 specifically by the combination of DEX and IL7. Furthermore, BCL2 was not upregulated by DEX and IL7 in STAT5 KO cells, consistent with this being a STAT5-mediated effect. IL7-induced GC resistance could be overcome with shRNA-mediated knockdown of BCL2 and with pharmacologic inhibition of BCL2 by venetoclax. Similar to the effect observed with RUX, Bliss index analysis demonstrated synergy between DEX and venetoclax in the presence of IL7. Consistent with our observations in CCRF-CEM cells, an analysis of primary diagnostic T-ALL samples revealed DEX-induced upregulation of IL7R expression in samples with IL7-induced GC resistance, which was associated with increased BCL2 expression in the presence of DEX and IL7. Finally, we performed a similar analysis in healthy murine thymocytes, and found that CD4/CD8 double negative (DN) and CD4 or CD8 single positive (SP) thymocytes, but not double positive (DP) thymocytes, exhibited profound IL7-induced GC resistance that was associated with DEX-induced upregulation of IL7R expression and increased BCL2 expression in the presence of DEX and IL7. These data are consistent with the known role of IL7 specifically at the DN and SP stages of development, and suggests that IL7-induced GC resistance is a physiologic mechanism of GC resistance in normal thymocyte development that is retained during leukemogenesis in a subset of T-ALL samples. Taken together, these data demonstrate that GCs paradoxically induce their own resistance in a subset of T-ALLs and in normal developing T-cells by augmenting a STAT5-mediated pro-survival program that results in upregulation of BCL2. Furthermore, we demonstrate that inhibition of JAK/STAT signaling or of BCL2 may have considerable therapeutic benefit to enhance GC sensitivity in T-ALL patients with IL7-induced GC resistance. Disclosures Teachey: La Roche: Consultancy; Amgen: Consultancy.

Despite advances in therapy, many patients with systemic light-chain amyloidosis (AL) die within 3 years from diagnosis. The humanized 2B6 monoclonal antibody (MoAb) is specific for the low-affinity IgG Fc receptor CD32B and effective in a human CD32B+ B-cell lymphoma murine xenograft model. Because MoAb therapy could improve outcomes in AL, we studied CD32B expression by clonal plasma cells obtained from 48 patients with AL. Transcript profiling showed that expression of CD32B was significantly higher than expression of all other Fc receptor family members. Reverse-transcriptase polymerase chain reaction (RT-PCR) using double-enriched CD138+ plasma cells showed uniform expression of the stable cell surface CD32B1 isoform at diagnosis and relapse, and flow cytometry showed intense CD32B cell surface staining on 99% of CD138+ plasma cells at diagnosis and relapse. These data provide a rationale for the novel therapeutic targeting of CD32B using the humanized 2B6 MoAb in patients with systemic AL-amyloidosis.

Although it has been suggested that REL is the critical target gene of 2p12-16 amplification in diffuse large B-cell lymphoma (DLBCL), little experimental evidence supports this notion. In the present study, we sought to evaluate the relationship between REL amplification and REL function in a panel of 46 newly diagnosed DLBCLs and to correlate with DLBCL subgroups as identified by gene expression profiles and clinical features. The results indicate that amplification of the REL locus is not associated with accumulation of the active form of REL, as evaluated by immunofluorescence analysis. Upon subgrouping of the DLBCL cases based on gene expression signatures, REL amplification was detected in all subgroups, while high levels of nuclear-located REL were more frequently detected in activated B-cell–like DLBCL. Correlative analyses of REL copy number and REL nuclear accumulation with clinical parameters did not reveal any significant associations. Together these results indicate that 2p12-16 amplification does not lead to abnormal REL activation, suggesting that REL may not be the functional target of the amplification event. Nonetheless, these data indicate that DLBCLs are heterogeneous with respect to REL and thus nuclear factor–κB (NF-κB) activity.

A number of prognostic factors affect outcome in patients with relapsed or primary refractory diffuse large B-cell lymphoma (DLBCL), including refractory disease and the second-line age-adjusted international prognostic index. In de novo DLBCL, the cell of orgin, as determined by expression microarray analysis or immunohistochemistry (IHC), predicts event-free survival (EFS). We evaluated the cell of origin, as well as other pathologic markers of outcome, on the repeat biopsy specimen of 88 transplantation-eligible patients undergoing ifosfamide, carboplatin, etoposide (ICE) second-line chemotherapy (SLT) followed by high-dose therapy (HDT) and autologous stem cell transplantation (ASCT) to see if were they prognostic in the salvage setting. Pretreatment clinical factors were well balanced between the cohorts. There was no significant difference in response to SLT, HDT, event-free or overall survival based on the cell of origin or any of the common pathologic markers examined. The cell of origin as determined by IHC does not predict outcome in transplantation-eligible patients with relapsed or primary refractory DLBCL.

The presence in mice of progenitors that can give rise selectively to B-1 or B-2 B-cells raised the possibility that B-lymphoid neoplasms may have varied developmental origins. Prior work demonstrated that murine B-1 and B-2 progenitors of mice can both be transformed by the BCR-ABL1 oncogene and that leukemias derived from B-1 progenitors initiated more quickly than leukemias derived from B-2 progenitors (J Immunol. 2014;192:5171-8). We have recently profiled the gene expression patterns of murine B-1 and B-2 progenitors using RNA-seq and have applied the observed divergences in gene expression pattern to investigate whether varied human pediatric B-cell acute lymphoblastic leukemias (B-ALLs) might arise from human B-cell progenitors with characteristics paralleling either mouse B-1 or B-2 progenitors. Underlying these analyses is the concept that pediatric ALLs might arise from progenitors present during development that may not persist into adulthood. In order to assess our hypothesis that human pediatric B-ALLs have common features with either mouse B-1 progenitors or mouse B-2 progenitors, we examined whether gene expression differences observed in the mouse cells could be used to segregate human pediatric ALLs into B-1 progenitor-like or B-2 progenitor-like subsets. We used two different computational approaches to compare gene expression of mouse B-1 and B-2 progenitors to 126 human pediatric B-ALLs (St Jude ALLs: GSE26281, JCI 2013 123:3099-3111). In the first approach, we identified 327 genes that varied between mouse B-1 and B-2 progenitors derived from mice of varied ages (embryonic day 15, post-natal day 1, post-natal day 2, week 9 and week 11 animals). We were able to map 207 of these genes onto probes for human orthologs in the St Jude ALL gene expression microarray dataset. When multiple probes for a gene were present in the human array, the most variable probe was selected for analysis. The human ALLs were analyzed by unsupervised hierarchical clustering using these 207 genes. Of interest, when examining the first bifurcation of the unsupervised clustering diagram, ETV6-RUNX1 leukemias clustered in the same fork as the TCF3-PBX1 leukemias, whereas Hyperdiploid B-ALLs clustered in the same fork as most of the MLL leukemias. Further analysis identified 58 genes that could be used to score the human leukemias as B-1 progenitor-like and B-2 progenitor-like with a Z-score. Examination of the resulting scores showed that TCF3-PBX1 and ETV6-RUNX1 leukemias scored as the most similar to mouse B-1 progenitors, whereas hyperdiploid and MLL ALLs appeared predominantly B-2 like. In our second analytical approach, we identified 574 genes that showed at least a 2 fold difference and a p-value This work was supported by R21-CA173028 from the National Cancer Institute. Disclosures No relevant conflicts of interest to declare.

Intraclonal heterogeneity (IH) in MM may provide a basis for the selection of resistance to therapy that occurs over time. Model systems to study IH in MM have not been defined so we focused on the expression of CD32B, the low-affinity inhibitory Fcγ-receptor that is a key participant in normal plasma cell apoptosis and a potential target for monoclonal antibody therapy. At diagnosis, CD138+ MM marrow cells are largely CD32B+ (n=72; median 94%, range 1–100) while at relapse the CD32B+ MM subpopulation is significantly smaller in both bone marrow (n=25, median 83%, (10–100), P = 0.02) and extramedullary sites (n=8, median 17% (0–78); P << 0.01). Among human MM cell lines only two of ten tested expressed cell-surface CD32B. We hypothesize that the CD32B phenotype of MM subpopulations contributes to the functional heterogeneity that is critical to the selection of resistance, and sought a model system to study CD32B-related IH. The KMS-12BM cell line (BM), a human MM line from marrow, has CD32B+ and CD32B− subpopulations as MM marrows do, while the KMS-12PE cell line (PE), from the pleural fluid of the same patient, is completely CD32B negative, as is often the case in extramedullary MM. Both BM and PE cells share t(11;14), del 17p and other cytogenetic abnormalities, and both contain intact CD32B genes (FCGR2B). We used 3 populations, BM CD32B+, BM CD32B− and PE (CD32B−), as well as sorted patient MM cells, to study the IH associated with CD32B. RNAi studies demonstrated that the expression of FCGR2B in BM cells is dependent on the Ets family transcription factor PU.1, while PE cells do not express PU.1. RT-PCR of patient MM cells sorted into paired CD32B+ and CD32B− fractions showed PU.1 and FCGR2B (CD32B) expression only in CD138+/CD32B+ cells. Cell-tracking studies with CFSE showed that BM CD32B+ cells gave rise to BM CD32B− cells but that the reverse did not occur. Cell-culture studies showed that BM CD32B+ cells have significantly lower apoptotic rates than BM CD32B− cells, while the latter display greater dependence on insulin for survival and on IGF-1 and MIP-1α for proliferation. In order to better understand the differences between CD32B+ and CD32B− populations, we performed transcript profiling. BM CD32B+ cells have significantly higher expression of the activin inhibin, while BM CD32B− cells overexpress insulin-response genes such as the kinase Akt2. Compared to BM cells, PE cells overexpress germ-cell transcription factors and inflammasome-related genes, while BM cells overexpress tetraspanins (CD9, CD37, CD53) and insulin-response genes. Of interest, there are also significant differences in the expression of BMP and Wnt-related genes (but not Hh or Notch genes). BM cells overexpress BMPR1A, FZD2 and Wnt5A while PE cells overexpress CRIM1, FZD1 and LEF1. These data indicate that functional IH exists in MM, that the KMS-12 cell lines provide a useful model for its study, and that MM may originate in a CD32B+ cell that begets CD32B− heirs. We continue to study PU.1 and the generation of CD32B− cells by CD32B+ cells; to validate transcript data using sorted patient specimens; and to assess with RNAi the contributions of BMP, Wnt and insulin-response genes to the survival and proliferation of CD32B+ and CD32B− cells, seeking novel therapeutic targets on which selection of resistance may depend.

Background: Nilotinib (NIL) and dasatinib (DAS) have a 1- and 2-log higher inhibitory potency than imatinib against ABL1 kinase respectively, and are active against all BCRABL1 kinase mutants, except T315I. We investigated the molecular responses to nilotinib and dasatinib in patients (pts) with CML-CP receiving these agents either in the frontline (FL) or the post-imatinib failure (PIF) settings. Methods: 205 pts with CML-CP received either NIL (n=87; 48 FL, 39 PIF) or DAS (n=118; 48 FL, 70 PIF) at various doses in phase II studies. Quantitative reverse transcription PCR in peripheral blood samples was performed prior to NIL or DAS start, after 1 mo of therapy, and every 3 mo thereafter. Results: Table 1 illustrates the BCR-ABL1/ABL1 ratios at different time-points during therapy. No significant differences were observed regarding the median baseline BCRABL1/ ABL1 ratio across groups (p=0.88) or the median at 12 mos between the NIL and the DAS cohorts (p=0.14). We developed an exponential model with one population-based shape parameter and a subject-specific slope and intercept. We estimate the shape parameter, after merging all data from a treatment group, using non-linear least squares. With the shape parameter fixed, we estimate the subject-specific parameters using traditional least squares. A statistically significant difference between the shape parameters of the NIL-FL and the DAS-FL treatments was observed (p=0.005), with NIL inducing a sharper early decline in BCR-ABL1 transcripts. Our exponential model does not fit as well for NIL-PIF vs DAS-PIF, particularly for the latter, possibly due to differences in the number and types of mutations at the start of therapy. Indeed, DAS-resistant mutations (L248V/R, Q252H, E255K, V299L, T315I/A, and F317L/C/I/S/V) were detected in 7 (32%) of 22 patients carrying mutations (all PIF), while NIL-resistant mutations (Q252H, Y253H/F, E255K/V, T315I/A, F359V, V379I) were only found in 1/16 (6%) carrying mutations (all PIF). BCR-ABL1/ABL1 ratio reductions occurred in 73 (87%)of 84 pts who had at least 2 PCR analyses during NIL therapy: 1-log in 16 (19%) pts, >2-logs in 18 (21%) pts, and >3-logs in 32 (38%) pts. BCR-ABL1/ABL1 ratio reductions occurred in 102 (92%) of 111 pts who had at least 2 PCR analyses during DAS therapy: 1-log in 17 (15%) pts, >2-logs in 24 (22%) pts, and >3-logs in 41 (37%) pts. Major molecular response (MMR) and complete molecular response (CMR; undetectable BCR-ABL1 transcripts) rates were 39%/12% and 38%/7% for the NIL and DAS cohorts, respectively (50%/17% and 58%/7% for pts receiving NIL and DAS as frontline therapy). The MMR and CMR response rates for NIL and DAS among pts with mutations at the start of therapy were 19%/6% and 20%/0%, respectively. Conclusion: NIL and DAS induce molecular responses in a significant number of pts, particularly when used in the frontline setting. Although molecular responses occur across a broad variety of BCR-ABL1 kinase mutations, CMR in this setting is a rare occurrence. NIL appears to induce faster molecular responses than DAS, al least in the FL setting. Longer follow-up is necessary to establish the clinical consequences of this phenomenon. Table 1. BCR-ABL1 transcript dynamics by treatment and cohort DRUG/ COHORT DAS DAS-FL DAS-PIF NIL NIL-FL NIL-PIF No. Patients 118 48 70 87 48 39 Baseline median BCR-ABL1/ ABL1 70.65 (0.009–100) 36.27 (0.01–100) 75.04 (0.009–100) 67.71 (0.01–100) 71.26 (0.01–100) 53.15 (0.15–100) Time nadir PCR (mos) 27 24 27 27 21 27 Median BCR-ABL1/ ABL1 (%)nadir 0.05 (0–100) 0.01 (0.001–0.65) 0.08 (0–100) 0.07 (0–30.52) 0.01 (0–0.6) 0.16 (0–30–54) No. Evaluable at nadir PCR 13 21 18 17 3 10 Median BCR-ABL1/ ABL1 (%) at 12 months 0.33 (0–100) 0.155 (0–100) 1.49 (0–100) 0.09 (0–92.29) 0.025 (0.01–16.21) 0.75 (0–92.29)

The tyrosine kinase inhibitor (TKI) imatinib at the standard dose of 400mg/d renders high complete cytogenetic response (CCyR) rates but complete molecular response (CMR, i.e. undetectable BCR-ABL1) occurs only in a small proportion of patients. Therapy with high-dose imatinib (i.e. 800mg/d) has been reported to render significantly higher rates of CMR. The second generation TKIs nilotinib and dasatinib exhibit 1- to 2-log higher potency against BCR-ABL1 kinase in vitro, are active against multiple imatinib-resistant ABL1 kinase domain mutations, and result in high response rates in patients after failure of imatinib therapy. Here, we investigate the dynamics of peripheral blood BCR-ABL1 transcript levels in patients with CML-CP while receiving frontline therapy with highdose imatinib, nilotinib, or dasatinib. A total of 123 patients were investigated. Only timepoints 0, 3, 6, 9, 12, 18, and 24 months were analyzed. To be included in the analysis, patients had to have BCR-ABL1 levels available at least at 0, 3, 6, 9, and 12 months. Our goal was to develop a statistical model for these data depending on at most two subject-specific parameters, since there were typically only 5 to 7 time points per patient (median follow-up for the high-dose imatinib, nilotinib, and dasatinib groups was 48, 13, and 24 months, respectively). As a first step we used the cube root to transform our data, since the measurements are on vastly different scales and some of the observed values are zero. Our initial model on the transformed data was biexponential, which is the sum of two exponentials. We found that one of the exponentials could be replaced with a constant, which saved a parameter with little reduction in the fit. Our resulting model for the ith subject at time t is yi (t)= α0i + α1i exp[–βt], where α0i is the subject-specific intercept, α1i is the subject-specific slope, and β is the population-based shape parameter. A different version of the model is fit to each treatment group. We estimate beta (the shape parameter), after merging all data from a treatment group, using non-linear least squares. With beta fixed, we estimate the subject-specific parameters using traditional least squares. This model fits the data well, with a median R2 greater than 0.9 for all treatment groups. In a three-way comparison among nilotinib (n=23), dasatinib (n=24), and highdose imatinib (n=76), the most different population curves were between nilotinib and dasatinib (p=0.005). The nilotinib curve was also significantly different than the high-dose imatinib curve (p=0.04), while the curves for dasatinib and highdose imatinib were not significantly different (p=0.11). Nilotinib had a sharper earlier decline than dasatinib (beta=0.71 for nilotinib and beta=0.33 dasatinib), and high-dose imatinib was intermediate between the two (beta=0.44 for imatinib). We are currently examining whether there is a relationship between the subject-specific slopes and intercepts and other covariates, such as survival. We are also analyzing the implications of different shaped population curves for the different treatments.

Systemic light-chain amyloidosis (AL) is a protein deposition disorder and a monoclonal plasma cell disease. Treatment of AL has focused on the reduction or elimination of the clonal plasma cells that make amyloid-forming light chains. High-dose melphalan and stem cell transplant (MEL SCT) is an effective therapy for selected AL patients. At 3 months post-SCT, response of the clonal plasma cell disease can be reliably scored; the achievement of a complete response (CR= immunofixation negative) is usually associated with extended survival while no response (NR= < 50% reduction) is not. Many factors likely contribute to this distribution of responses. In order to identify factors specific to clonal plasma cells, gene expression profiles (GEP; Affymetrix U133 PLUS 2.0) were obtained using FACS-sorted CD138+/DAPI- plasma cells (>95% pure) from untreated AL patients before SCT. Supervised analyses were then performed based on responses at 3 months post-SCT, comparing the CR (n=4) and NR (n=5) groups. The basic analysis was a t-test, filtering genes for differential expression at p

Despite stem cell transplant and new therapies, nearly all patients with AL and MM die of disease or complications of treatment. Novel approaches that selectively kill clonal plasma cells are needed. CD32B, the inhibitory Fcγ receptor IIB, is a member of the Fc receptor (FcR) family on chromosome 1q. B-cells and some monocytes and dendritic cell subtypes express cell-surface CD32B, which has a cytoplasmic inhibitory motif important in regulating immune responses. Unlike the CD32B2 isoform on myeloid cells, CD32B1 on B-cells is not internalized, making it a suitable target for monoclonal antibody (MAb) therapy (Blood 2006Jun6 Epub). CD32B has not previously been found on AL and MM plasma cells. We used purified CD138+ marrow and blood cells from AL, MM and plasma cell leukemia (PCL) patients, and 5 human MM cell lines, to evaluate CD32B gene and cell-surface expression with gene expression profiles (GEP) (Affymetrix U133 PLUS 2.0), RT-PCR for CD32B1 and B2, and flow-cytometry with the 2B6 MAb for CD32B. In AL, GEP showed that CD32B expression was significantly higher than other FcR genes (p98% of all AL plasma cells. In MM, public GEP data (http://lambertlab.uams) showed that CD32B expression was significantly higher than other FcR genes while RT-PCR showed CD32B1 message in CD138+ MM and PCL specimens but not in the RPMI 8226 cell line. Cytogenetic analysis then showed that 8226 cells lack t(4;14) but have 4 copies of 1q, implicating segmental uniparental tetrasomy of a mutant allele in the lack of CD32B message. Flow cytometry showed median 96% CD32B expression on CD138+ marrow cells from patients with normal or hyperdiploid cytogenetics, but significantly lower expression (median 69%, p=0.01) in patients with unfavorable cytogenetics (del 13, t(4;14)). CD32B expression was lower still on PCL specimens (median 10%) and nil on MM cell lines. We then investigated the GEP of sorted CD138+/CD32B+ and CD32B− fractions from MM patients. In CD138+/CD32B+ cells, CD45C and CXCR4 were overexpressed. In CD138+/CD32B− cells, genes on chromosome 1q were overexpressed, including those for cancer testis antigens and others possibly associated with biologic aggressivity (Cancer Cell2006;9:313). Notably, the CD32B-specific MAb 2B6 directs human mononuclear cell cytotoxicity against CD32B+ cell lines, reduces tumor growth and improves tumor-free survival in a mouse xenograft model. Moreover, an Fc-engineered humanized variant of 2B6 elicits ADCC-mediated specific cytotoxicity against a low-level CD32B+ MM cell line in vitro. In sum, these data show that CD32B is important in AL and MM; that CD32B on AL and the majority of MM plasma cells provides a target for MAb therapy; and that, given the results in MM, PCL and MM cell lines, CD32B expression is inversely related to biologic aggressivity. Genetic instability of chromosome 1q may provide a direct basis for this relationship thereby mechanistically linking CD32B expression in MM to prognosis. These data support further evaluation of CD32B and clinical studies of anti-CD32B MAb therapy in AL and MM.

Systemic AL amyloidosis is a plasma cell dyscrasia and protein conformation disorder in which Ig light chains (Ig VL) produced by clonal plasma cells form interstitial amyloid in key viscera causing organ dysfunction and death. Patients with AL usually have < 20% marrow plasma cells with low to nil proliferative indices. Paradoxically the plasma cells appear immune to the toxic amyloid-forming Ig VL possibly due to the robust cytoplasmic protein quality-control processes in plasma cells. A standard approach is to treat with high-dose melphalan and stem cell transplant (SCT) without induction therapy. Post-SCT long-term survival depends on significant reductions of the plasma cell disease and Ig VL levels as measured by the serum free light chain (FLC) assay. At 3 months post-SCT responses of the plasma cell dyscrasia are defined both by standard criteria and by normalization of abnormal FLC ratios. By standard criteria, post-SCT one-third fail to achieve a > 50% reduction in plasma cell disease (NR), one-third achieve a > 50% reduction (PR), and one-third achieve clearance of marrow plasma cells and a complete or near complete response (CR). By FLC criteria, post-SCT one-third achieve normalization (N) of the FLC ratio and two-thirds do not (A). Many factors contribute to this distribution of responses. In order to identify factors specific to AL plasma cells, gene expression profiles (GEP; Affymetrix U133 PLUS 2.0) were obtained after double amplification of RNA from FACS-sorted CD138+/DAPI- plasma cells from untreated patients with AL pre-SCT. Data were vetted based on plasma cell lineage gene expression; samples contaminated with monocytes were not used. Supervised analyses were performed based on responses at 3 months post-SCT, comparing CR (n=4) to PR (n=7) and CR to NR (n=5), and FLC N (n=5; one with CR) to A (n=7; two with CR). Differentially expressed genes between paired sets were identified using the t-test. Genes with p < 0.01 were examined using EASE, a program that identifies over-represented gene families. In the CR-PR and CR-NR comparisons, genes involved in translation, RNA ligation and protein degradation, particularly aminoacyl tRNA synthetases, were significantly over-represented with Bonferroni-adjusted EASE scores (like p-values) < 0.05. In the CR set, tryptophanyl tRNA synthetase, a protein that can also be anti-angiogenic, and IDE, an insulin-degrading enzyme that also degrades Aβ amyloid peptides, were among the most over-expressed. In the FLC N-A comparison, protein transport and detoxification gene families were also significantly over-represented with Bonferroni-adjusted EASE scores < 0.001. In the N set, CCT subunits (chaperones), UBE2B (a ubiquitination enzyme and RAD6 homolog) and glyoxalase I (detoxification) were among the most over-expressed. Our initial hypothesis is that the CR and FLC N responses to melphalan have similar but distinctive GEP related to protein folding, ER stress and protein degradation. The responses of AL plasma cells to Ig VL in the ER may influence the patterns observed, possibly modulating melphalan uptake or activity. Further studies of these differences and functional hypothesis testing are currently underway.