Molecular Characterization of Relapsed Core-Binding Factor (CBF) Acute Myeloid Leukemia (AML)

Abstract Background: CBF-AML is defined by recurrent genetic abnormalities which encompass t(8;21)(q22;q22), inv(16)(p13.1q22) or less frequently t(16;16)(p13.1;q22). Most frequent secondary chromosome aberrations in t(8;21) AML are del(9q) or loss of a sex chromosome, and in inv(16)/t(16;16) AML trisomy 22 or trisomy 8. At the molecular level mutations involving KIT, FLT3, or NRAS were identified as recurrent lesions in CBF-AML. However, the underlying genetic alterations which might trigger relapse in CBF-AML are not well delineated. Thus, the aim of our study was to characterize the clonal architecture of relapsed CBF-AML. Methods: We performed mutational profiling (KIT, FLT3-ITD, FLT3-TKD, NRAS, ASXL1) in paired samples obtained at diagnosis and at relapse from 66 adults with CBF-AML [inv(16), n=43; t(8;21), n=23] who all were treated within the AMLSG studies. Results: In inv(16) AML, the following mutation pattern was identified at diagnosis: KIT 13/40 (33%; exon 8, n=6; exon 17, n=5; exon 8+17, n=1; exon 11, n=1; missing data, n=3), NRAS 18/43 (42%), FLT3-TKD 4/43 (9%); none of the pts harboured FLT3-ITD or ASXL1 mutations. At the time of relapse, there was a shift in the mutation pattern in 26 pts (60%): KIT mutations (exon 8, n=5; exon 17, n=2; exon 8+17, n=1) were lost in 8 pts and 1 pt acquired an exon 17 KIT mutation; similarly, 15 pts lost and 1 pt gained NRAS mutation, respectively. Of note, all FLT3-TKD mutations were lost at the time of relapse, and only one pt gained a FLT3-ITD mutation. Based on these findings we calculated the stability in inv(16) AML for KIT, NRAS and FLT3-TKD mutations as 38%, 17%, and 0%, respectively. AML with t(8;21) presented a different diagnostic mutation profile: KIT 9/23 (39%; exon 17, n=8; exon 11, n=1), FLT3 -ITD 3/23 (13%), NRAS 2/23 (9%), and ASXL1 1/23 (4%); there were no FLT3-TKD mutations. At the time of relapse, the mutation pattern changed in 9 pts (39%); KIT mutations were lost in 4 pts (exon 17, n=3; exon 11, n=1), but acquired in 2 pts with both of them located in exon 17; only 1 pt lost the NRAS mutation. FLT3-ITD was lost in 2 and gained in 3 pts. There was no change in the ASXL1 mutation status. Thus, the stability for KIT, NRAS, FLT3-ITD and ASXL1 mutations in t(8;21) AML was calculated as 56%, 50%, 33% and 100%, respectively. Of note, mutations affecting the KIT and NRAS gene were almost mutually exclusive; there were only 3 pts with concurrent KIT and NRAS mutations at diagnosis [inv(16), n=2; t(8;21), n=1]. Conclusion: CBF-AML cases display a high degree of molecular heterogeneity with shift of the mutation pattern at relapse in both CBF-AML subtypes. The frequent loss of KIT and NRAS mutations at relapse suggests that there might be other important secondary lesions driving relapse. Ongoing high-resolution genome-wide profiling will further unravel the clonal hierarchy and genomic landscape in CBF-AML. Disclosures Götze: Novartis: Honoraria; Celgene Corp.: Honoraria. Greil:Celgene: Consultancy; Ratiopharm: Research Funding; Sanofi Aventis: Honoraria; Pfizer: Honoraria, Research Funding; Boehringer-Ingelheim: Honoraria; Astra-Zeneca: Honoraria; GSK: Research Funding; Novartis: Honoraria; Genentech: Honoraria, Research Funding; Janssen-Cilag: Honoraria; Merck: Honoraria; Mundipharma: Honoraria, Research Funding; Eisai: Honoraria; Amgen: Honoraria, Research Funding; Cephalon: Consultancy, Honoraria, Research Funding; Bristol-Myers-Squibb: Consultancy, Honoraria; AOP Orphan: Research Funding; Roche, Celgene: Honoraria, Research Funding. Schlenk:Boehringer-Ingelheim: Honoraria; Teva: Honoraria, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Research Funding; Arog: Honoraria, Research Funding.

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Pre-Clinical Efficacy of Co-Treatment with KDM1A (LSD1) Inhibitor and Ruxolitinib or BET Inhibitor Against Post-MPN-sAML Blast Progenitor Cells

Blood ◽

10.1182/blood-2019-130783 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1274-1274

Author(s):

Warren Fiskus ◽

Christopher Peter Mill ◽

Vrajesh Karkhanis ◽

Bernardo H Lara ◽

Prithviraj Bose ◽

...

Keyword(s):

Growth Inhibition ◽

Progenitor Cells ◽

Board Of Directors ◽

Research Funding ◽

Amine Oxidase ◽

Genetic Alterations ◽

Advisory Committees ◽

Bet Inhibitor ◽

Oncology Research ◽

Differentiation Block

LSD1 (KDM1A) is an FAD-dependent amine-oxidase that demethylates mono and dimethyl histone H3 lysine 4 (H3K4Me1 and H3K4Me2), which regulates active enhancers and transcription in AML stem/progenitor cells (LSCs). LSD1 is part of the repressor complexes involving HDACs, CoREST or GFI1, mediating transcriptional repression and differentiation block in LSCs that persist in the minimal residual disease (MRD) following attainment of clinical complete remission, leading to relapse and poor outcome in AML. In AML LSCs, genetic alterations and epigenetic dysregulation of enhancers affect levels of myeloid transcriptional regulators, including c-Myc, PU.1, GATA 2 and CEBPα, and their target genes, which are involved in differentiation block in LSCs. Our present studies demonstrate that CRISPR/Cas9-mediated knockout of LSD1 in the AML OCI-AML5 cells significantly increased the permissive H3K4Me2/3-marked chromatin, reduced H3K27Ac occupancy at super-enhancers and enhancers (SEs/Es) (by ChIP-Seq), especially of c-Myc and CDK6, as well as repressed CoREST, c-Myc, CDK6, and c-KIT, while inducing p21, CD11b, and CD86 levels (log2 -fold change by RNA-Seq, and protein expression by Western analyses). This led to significant growth inhibition, differentiation and loss of viability of OCI-AML5 and patient-derived AML blasts (p < 0.01). Similar effects were observed following exposure of OCI-AML5 (96 hours) to tet-inducible shRNA to LSD1. Knock-down of GFI1 by shRNA (by 90%) also inhibited growth and induced differentiation, associated with upregulation of PU.1, p21 and CD11b levels. Treatment with irreversible (INCB059872, 0.25 to 1.0 µM) or reversible (SP2577, 1.0 to 2.0 µM) LSD1 inhibitor (LSD1i) inhibited binding of LSD1 to CoREST, and significantly induced growth inhibition, differentiation and loss of viability (over 96 hours) of the OCI-AML5, post-myeloproliferative neoplasm (post-MPN) sAML SET2 and HEL92.1.7 cells, as well as patient-derived AML and post-MPN sAML blasts (p < 0.01). Co-treatment with INCB059872 and ruxolitinib synergistically induced apoptosis of the post-MPN sAML SET2 and HEL92.1.7 cells and patient-derived CD34+ post-MPN sAML blasts (combination indices < 1.0). Notably, pre-treatment with the LSD1i for 48 hours significantly re-sensitized ruxolitinib-persister/resistant SET2 and HEL92.1.7 cells to ruxolitinib (p < 0.001). We previously reported that treatment with the BET inhibitor (BETi) JQ1 or OTX015 represses SE/E-driven AML-relevant oncogenes including MYC, RUNX1, CDK6, PIM1, and Bcl-xL, while inducing p21 and p27 levels in post-MPN sAML blasts (Leukemia 2017;31:678-687). This was associated with inhibition of colony growth and loss of viability of AML and post-MPN sAML blasts (p < 0.01). Here, we determined that INCB059872 treatment induced similar levels of lethality in BETi-sensitive or BETi-persister/resistant AML and post-MPN sAML cells. Since BETi treatment also depleted LSD1 protein levels, co-treatment with the BETi OTX015 and LSD1i INCB059872 or SP2577 induced synergistic lethality in AML and post-MPN sAML blasts (combination indices < 1.0). Co-treatment with INCB059872 (1.5 mg/kg) and OTX015 (50 mg/kg) both orally for 21 days, compared to each agent alone or vehicle control, significantly reduced the sAML burden and improved survival of immune-depleted mice engrafted with HEL92.1.7 or HEL92.1.7/OTX015-resistant-GFP/Luc sAML xenografts (p < 0.01). Collectively, these findings strongly support further in vivo testing and pre-clinical development of LSD1i-based combinations with ruxolitinib against post-MPN sAML and with BETi against AML or post-MPN sAML cells. Disclosures Bose: CTI BioPharma: Research Funding; Astellas: Research Funding; NS Pharma: Research Funding; Promedior: Research Funding; Constellation: Research Funding; Incyte Corporation: Consultancy, Research Funding, Speakers Bureau; Celgene Corporation: Consultancy, Research Funding; Blueprint Medicine Corporation: Consultancy, Research Funding; Kartos: Consultancy, Research Funding; Pfizer: Research Funding. Kadia:Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding; Bioline RX: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees. Bhalla:Beta Cat Pharmaceuticals: Consultancy. Khoury:Stemline Therapeutics: Research Funding; Angle: Research Funding; Kiromic: Research Funding. Verstovsek:Ital Pharma: Research Funding; Pharma Essentia: Research Funding; Astrazeneca: Research Funding; Incyte: Research Funding; CTI BioPharma Corp: Research Funding; Promedior: Research Funding; Gilead: Research Funding; Celgene: Consultancy, Research Funding; NS Pharma: Research Funding; Protaganist Therapeutics: Research Funding; Constellation: Consultancy; Pragmatist: Consultancy; Sierra Oncology: Research Funding; Genetech: Research Funding; Blueprint Medicines Corp: Research Funding; Novartis: Consultancy, Research Funding; Roche: Research Funding.

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PD-L1 and PD-L2 Genetic Alterations Define Classical Hodgkin Lymphoma and Predict Outcome

Blood ◽

10.1182/blood.v126.23.176.176 ◽

2015 ◽

Vol 126 (23) ◽

pp. 176-176

Author(s):

Margaretha GM Roemer ◽

Ranjana H Advani ◽

Azra H. Ligon ◽

Yasodha Natkunam ◽

Robert A Redd ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Early Stage ◽

Prognostic Significance ◽

Genetic Alterations ◽

Genetic Alteration ◽

Newly Diagnosed ◽

Advisory Committees ◽

Therapy Regimen ◽

Clinical Risk

Abstract Introduction. Classical Hodgkin Lymphomas (cHL) include small numbers of malignant Reed-Sternberg (RS) cells within an extensive but ineffective inflammatory/immune cell infiltrate. In cHL, chromosome 9p24.1 alterations increase the abundance of the PD-1 ligands, PD-L1 and PD-L2, and their further induction via JAK2-STAT signaling. PD-1 ligands engage the PD-1 receptor on T-cells and induce PD-1 signaling and T-cell exhaustion. Tumor cells expressing PD-1 ligands on their surface utilize the PD-1 pathway to evade an effective immune response. In recent pilot studies, PD-1 blockade was associated with high response rates and durable remissions in relapsed/refractory cHL. The unique composition of cHL limits its analysis with high throughput genomic assays. Therefore, the precise incidence, nature and prognostic significance of PD-L1 and PD-L2 alterations in cHL remain undefined. Herein, we utilize a recently developed fluorescence in situ hybridization (FISH) assay to characterize 9p24.1/PD-L1/PD-L2 alterations in a cohort of 108 newly diagnosed cHL patients (pts) who were uniformly treated with StanfordV (a combined modality therapy regimen) and have longterm followup. Methods. Pts were characterized as Ann Arbor early stage I/II favorable risk (ES-F), early stage unfavorable risk (bulk ≥ 10cm or ≥ .33 mediastinal dimension and/or B symptoms) (ES-U) or advanced stage III/IV (AS). ES-F pts received 8 weeks of Stanford V and 30 Gy involved field radiation (IFR); ES-U and AS pts received 12 weeks of Stanford V and 36 Gy IFR to initial sites > 5 cm. FISH was performed on formalin-fixed paraffin-embedded diagnostic biopsy specimens using bacterial artificial chromosome probes which covered CD274/PD-L1 (labeled with spectrum orange) and PDCD1LG2/PD-L2 (labeled with spectrum green) and a control centromeric probe (spectrum aqua-labeled CEP9, from 9p11-q11). Malignant RS cells were identified by their nuclear morphologic features and 50 RS cells/case were analyzed. Nuclei with a target:control probe ratio of at least 3:1 were defined as amplified (amp), those with a probe ratio of more than 1:1 but less than 3:1 were classified as relative copy gain, and those with a probe ratio of 1:1 but more than 2 copies of each probe were defined as polysomic for chromosome 9p. In each case, the percent and magnitude of disomy, polysomy, copy gain and amp were noted. In accordance with clinically approved diagnostic criteria, cases were classified by the highest observed level of 9p24.1 alteration. Specifically, cases with polysomy lacked copy gain or amp and cases with copy gain lacked amp. Immunohistochemical staining for PD-L1/PAX5 was performed as previously described and PD-L1 expression in PAX5 dim+ malignant RS cells and PAX5- infiltrating normal cells was assessed separately. Results. Almost all newly diagnosed cHL pts in this series had concordant alterations of the PD-L1 and PD-L2 loci; disomy was found in only 1% (1/108), polysomy in 5% (5/108), copy gain in 56% (61/108) and amp in 36% (39/108) of study pts. There was a correlation between intensity of PD-L1 protein expression and relative genetic alterations in this series. Two additional pts had translocations of PD-L1 or PD-L2 (2%, 2/108). We next assessed the association between specific types of PD-L1/PD-L2 alterations, clinical risk factors and outcome. Overall, the progression-free survival (PFS) was significantly lower for AS pts compared to ES-F/U pts (p=0.017). A model of PFS for the cHL pts by genetic alteration indicated that PFS was also significantly lower for pts with amp (p=0.02). Consistent with these findings, the incidence of 9p24.1 amp increased by clinical risk group: ES-F, 24%; ES-U, 34%; and AS, 50% (p=0.024, Kruskal-Wallis test). Therefore, we fit a full model of clinical and genetic factors including B-symptoms, bulk, stage and amp. Despite the association of amp with increased clinical risk groups, the genetic alteration further delineated PFS in the multivariate model (p=0.075). Conclusions. PD-L1/PD-L2 alterations are a defining feature of cHL with rare polysomy and more frequent copy gain and amp. There is an increased incidence of amp in pts with AS disease and a highly significant association of PD-L1/PD-L2 amp with PFS. These findings underscore the importance of genetically defined PD-1 mediated immune evasion in cHL and provide a rationale for the efficacy of PD-1 blockade in this disease. Disclosures Rodig: Perkin Elmer: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding. Shipp:BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding; Gilead: Consultancy; Merck: Membership on an entity's Board of Directors or advisory committees.

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Novel BET Protein Degrader-Based Combinations Exert Lethality Against Human AML Resistant to BET Inhibitors Due to Increased Activity of β-Catenin-TCF7L2- MYC Axis

Blood ◽

10.1182/blood-2018-177 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 177-177

Author(s):

Dyana T. Saenz ◽

Warren Fiskus ◽

Taghi Manshouri ◽

David N Saenz ◽

Raffaella Soldi ◽

...

Keyword(s):

Transcription Factor ◽

Progenitor Cells ◽

Board Of Directors ◽

Research Funding ◽

Genetic Alterations ◽

Advisory Committees ◽

Lethal Effects ◽

Bet Inhibitors ◽

Nuclear Levels ◽

And Control

Abstract Bromodomain and extra-terminal protein (BETP) inhibitors (BETis) disrupt the chromatin binding and activity of the BETP BRD4 in facilitating RNA pol II-mediated mRNA transcription, thereby depleting levels of active oncoproteins including c-Myc, CDK6, BCL2, PIM1 and MCL1. BETi treatment also increases protein levels of p21, p27 and HEXIM1, thereby causing growth inhibition and apoptosis of AML blast progenitor cells (BPCs), including post-MPN, secondary AML (sAML) BPCs. Treatment with BETi (e.g., OTX015) has been shown to reduce AML burden and induce clinical remissions. However, BETi-refractory AML develops uniformly. Previous reports utilizing mouse AML models have highlighted that persister-resistance to BETi (BETi-P/R) in AML stem progenitor cells is observed despite BETi treatment and reduction of BRD4 occupancy on the chromatin. This is mediated by re-expression of c-Myc due to transcriptional activity of WNT-β-catenin. In the present studies, we developed human sAML models of BETi-P/R to elucidate the mechanisms and develop targeted therapies against BETi-P/R sAML BPCs. Utilizing human sAML control (parental) SET2 and HEL92.1.7 cells and subjecting them to at least 10 exposures to 1.0 µM of the BETi OTX015 for 48 hours followed by full recovery, we first generated the BETi-P/R SET2-P/R and HEL-P/R cells. These cells were > 10-fold resistant to OTX015 and exhibited cross-resistance to other BETis, including JQ1 and ABBV-075. As compared to the control sAML cells, SET2-P/R and HEL-P/R cells neither exhibited additional genetic alterations by NextGen whole-exome sequencing, nor showed altered levels of TRIM33, SPOP or phosphorylated BRD4 (previously described mechanisms of BETi-resistance). In contrast, compared to the control, SET2-P/R and HEL-P/R cells demonstrated significantly higher nuclear levels and binding of β-catenin to the transcription factor TCF7L2 (TCF4) and TBL1X (TBL1), associated with increased expression of TCF4 targets, including c-Myc, Cyclin D1, TERT and Survivin. ATAC-Seq and ChIP-Seq (H3K27Ac mark) analyses showed significant gain of peaks and active enhancers in HEL-P/R over HEL92.1.7 cells, including enrichment of the STAT5, MYC, PU.1, GATA2 and MYB transcription factor binding sites, as well as newly gained peaks in the enhancers of JAK1/2, RUNX1, PU.1, MYC, BCL2L1 and CTNNB1. RNA-Seq analysis showed significant increase/decrease in mRNA expressions (340/247), with increased expression of gene-sets involving MYC/MAX, STAT5, NFkB and TCF4 targets. QPCR and Western analyses confirmed significant perturbation in gene expressions, with increase in TCF4, c-Myc, Survivin and PIM1 in HEL-P/R over HEL92.1.7 cells. Consistent with the finding that shRNA-mediated knockdown of BRD4 exerted similar lethal effects in BETi-P/R versus control cells, we also discovered that BETP-PROTAC (proteolysis targeting chimera) ARV-771 (Arvinas, Inc.) that degraded BRD4/3/2 was equipotent in inducing apoptosis of BETi-P/R and control sAML cells. Also, consistent with increased nuclear levels and binding (utilizing confocal microscopy) of β-catenin with TBL1 and TCF4 in BETi-P/R sAML BPCs, β-catenin inhibitor BC2059 (Beta-Cat Pharma), which disrupts the binding of nuclear β-catenin with TBL1 and TCF4 and depletes β-catenin levels, exerted similar lethal effects in BETi-P/R sAML and control sAML cells. Consistent with these findings, we also determined that co-treatment with ARV-771 and BC2059 exerted synergistic in vitro lethality against BETi-P/R sAML BPCs (combination indices < 1.0), which was associated with greater reduction in levels of c-Myc, TCF4, Survivin, CDK6, PIM1 and Bcl-xL. Co-treatment with ARV-771 and BC2059 was also synergistically lethal against 12 patient-derived samples of CD34+ sAML BPCs. Notably, compared to treatment with each agent alone or vehicle control, in vivo treatment with ARV-771 (30 mg/kg SQ daily x 5, per week) and BC2059 (30 mg/kg IP BIW per week) for 3 weeks, significantly reduced the sAML burden and improved survival of the NSG mice engrafted with luciferase-transduced HEL-P/R cells (p < 0.01). These findings demonstrate that increased levels and activity of β-catenin-TCF7L2-MYC axis is mechanistically responsible for BETi-P/R, and co-targeting with BETP degrader and β-catenin-TCF4 inhibitor is synergistically lethal against BETi-P/R sAML BPCs. Disclosures Soldi: Beta Cat Pharma: Employment. Bose:Astellas Pharmaceuticals: Research Funding; Celgene Corporation: Honoraria, Research Funding; Blueprint Medicines Corporation: Research Funding; Pfizer, Inc.: Research Funding; Constellation Pharmaceuticals: Research Funding; CTI BioPharma: Research Funding; Incyte Corporation: Honoraria, Research Funding. Kadia:BMS: Research Funding; Takeda: Consultancy; Novartis: Consultancy; Celgene: Research Funding; BMS: Research Funding; Jazz: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy; Celgene: Research Funding; Jazz: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Pfizer: Consultancy, Research Funding; Abbvie: Consultancy; Abbvie: Consultancy. DiNardo:Abbvie: Honoraria; Medimmune: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria; Bayer: Honoraria; Agios: Consultancy. Horrigan:Beta Cat Pharma: Employment. Khoury:Stemline Therapeutics: Research Funding. Verstovsek:Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Italfarmaco: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy.

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Does Trial Participation Improve Outcomes for Higher-Risk Myelodysplastic Syndromes (MDS) Patients Treated at Specialty Centers?

Blood ◽

10.1182/blood-2018-99-117174 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3096-3096

Author(s):

Sudipto Mukherjee ◽

David P. Steensma ◽

Rami S. Komrokji ◽

Amy E. DeZern ◽

Gail J. Roboz ◽

...

Keyword(s):

Clinical Trials ◽

Board Of Directors ◽

Research Funding ◽

Standard Of Care ◽

Wald Test ◽

Genetic Alterations ◽

Cancer Center ◽

Trial Participation ◽

Advisory Committees ◽

Risk Categories

Abstract Background: For some rare cancers, better outcomes have been reported for patient (pts) treated at high volume or specialty centers compared to pts who did not receive such care. Greater availability of interventional clinical trials may be one of the drivers of better outcomes in specialty centers. However, not all pts referred to specialty centers are eligible or willing to participate in trials, and it is not known how outcomes compare for pts treated at specialty centers on clinical trials versus standard of care. In this study, we compared the outcomes of higher-risk MDS pts treated in and out of clinical trials at MDS specialty centers. Methods: Pts treated at MDS Clinical Research Consortium institutions (Moffitt Cancer Center, Cleveland Clinic, MD Anderson Cancer Center, Cornell University, Dana-Farber Cancer Institute, and Johns Hopkins) from 2006-2016 were included. Pts were diagnosed with MDS according to 2008 WHO criteria and identified as having "higher-risk" disease based on the revised IPSS (IPSS-R) criteria that included Intermediate, High and Very high risk categories. All pts treated outside clinical trials received hypomethylating agents (HMAs), either azacitidine (AZA) or decitabine (DAC). Trial and non-trial pts were matched 1:1 based on age, sex, number of treatment regimens prior to HMA (for non-trial pts) or experimental regimen (for trial pts) and IPSS-R categories. All non-trial pts included in the analysis received at least 4 cycles of AZA or DAC at the same institution. Transplant rates and overall survival (OS) were evaluated for association with trial participation. OS was estimated by the Kaplan-Meier method and compared using Cox proportional hazard regression with two-sided Wald test with adjustment for matching variables. The relative odds of transplant following initial treatment were estimated using logistic regression and compared with two-sided Wald test. Results: Of 774 pts in the MDS CRC database for whom complete data were available, 323 were treated in clinical trials and 451 were treated with AZA or DAC. The trial and non-trial MDS cohorts were well matched with regards to median age (68.5 vs 68.2 yrs; P=0.65), females (28.4% vs 29.9%, P=0.75), numbers of regimens (3 vs 3, P=0.77) and IPSS-R risk categories (P=0.86). Estimated median OS of pts treated in and out of clinical trials was 44.5 and 50.6 months (P=0.67), respectively. Compared to standard of care, trial participation was not associated with any survival advantage [Hazard ratio (HR), 95% CI, 0.94 (0.72-1.24), P=0.67] (Figure 1). Clinical trial participation did not significantly increase the odds of proceeding to transplant [Odds Ratio (OR) (95% CI), 1.5 (0.68, 1.61), P = 0.83)]. As shown in Table 1, in multivariate analyses, among all factors, increasing number of regimens received was significantly associated with better survival, possibly reflecting a bias towards healthier pts who survived longer to receive multiple regimens. Conclusions: In a matched-pair analysis, we found comparable survival outcomes between trial and non-trial higher-risk MDS pts treated at specialty centers. Our matched analysis failed to identify any statistical evidence to suggest that an average patient benefited from trial participation within the MDS CRC sites. Additional research is necessary to interrogate these comparisons for specific patient subpopulations by genetic alterations, co-morbidities and regimen sequence, for which trial participation may have been beneficial. Based on the population-average findings, however, we expect any improvement in survival to be modest. Disclosures Komrokji: Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Roboz:Orsenix: Consultancy; Celltrion: Consultancy; Janssen Pharmaceuticals: Consultancy; Astex Pharmaceuticals: Consultancy; Eisai: Consultancy; Daiichi Sankyo: Consultancy; Novartis: Consultancy; Astex Pharmaceuticals: Consultancy; Celgene Corporation: Consultancy; AbbVie: Consultancy; AbbVie: Consultancy; Eisai: Consultancy; Celltrion: Consultancy; Roche/Genentech: Consultancy; Aphivena Therapeutics: Consultancy; Sandoz: Consultancy; Roche/Genentech: Consultancy; Daiichi Sankyo: Consultancy; Argenx: Consultancy; Jazz Pharmaceuticals: Consultancy; Pfizer: Consultancy; Cellectis: Research Funding; Celgene Corporation: Consultancy; Orsenix: Consultancy; Bayer: Consultancy; Novartis: Consultancy; Bayer: Consultancy; Jazz Pharmaceuticals: Consultancy; Pfizer: Consultancy; Sandoz: Consultancy; Argenx: Consultancy; Otsuka: Consultancy; Aphivena Therapeutics: Consultancy; Janssen Pharmaceuticals: Consultancy; Otsuka: Consultancy; Cellectis: Research Funding. Nazha:MEI: Consultancy. Maciejewski:Apellis Pharmaceuticals: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Ra Pharmaceuticals, Inc: Consultancy; Apellis Pharmaceuticals: Consultancy; Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees.

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NPM1 Variant Allele Frequency and Outcomes in AML

Blood ◽

10.1182/blood-2018-99-112549 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1486-1486 ◽

Cited By ~ 3

Author(s):

Maja Rothenberg-Thurley ◽

Tobias Herold ◽

Dennis Görlich ◽

Cristina Sauerland ◽

Hanna Janke ◽

...

Keyword(s):

Board Of Directors ◽

Induction Chemotherapy ◽

Research Funding ◽

Type A ◽

Genetic Alterations ◽

Type B ◽

Wild Type ◽

Advisory Committees ◽

Allelic Ratio ◽

Leukocyte Counts

Abstract Background: Mutations in the NPM1 gene are among the most common genetic alterations in patients with acute myeloid leukemia (AML). NPM1 mutations predominantly occur in patients with normal or intermediate-risk abnormal cytogenetics, and define a distinct subgroup of AML patients recognized in the 2016 WHO classification. Overall, mutated NPM1 associates with favorable response to induction chemotherapy and relatively favorable overall survival. However, this prognostic impact is modulated by the presence of other gene mutations including FLT3 internal tandem duplications (ITD) and DNMT3A mutations. Recently, Patel and colleagues reported that a high variant allele frequency (VAF) of mutated NPM1 at the time of initial diagnosis associates with unfavorable outcomes in de novo AML (Blood 131:2816-25). This interesting and unexpected observation prompted us to investigate the association between NPM1 VAF and outcomes in a large AML patient cohort. Patients and Methods: We studied NPM1 mutated AML patients who had been enrolled on two successive multicenter phase III trials of the German AML Cooperative Group (AML-CG 1999, NCT00266136; AML-CG 2008, NCT01382147) and genetically characterized by amplicon-based targeted next-generation sequencing (NGS, Agilent Haloplex; Metzeler et al., Blood 128:686-98 and unpublished data). All patients had received induction chemotherapy containing cytarabine with either daunorubicin plus thioguanine or mitoxantrone. The minimum VAF for calling of insertion/deletion variants was 0.05, and samples with NPM1 coverage <100-fold (n=17) were excluded. FLT3 internal tandem duplication (ITD) status and FLT3 ITD-to-wild type allelic ratio were determined by PCR and fragment analysis from gDNA. Results: We identified 417 NPM1-mutated patients (type A mutations, 316; type B, 28; type D, 35; and other types, 38). Median patient age was 56 years (range, 19 - 86 years), and 31/414 patients (7.5%) with cytogenetic data had abnormal karyotypes. The median NPM1 VAF was 0.43 (range, 0.05 to 1.0). Type A NPM1 mutations had significantly higher VAFs than non-type A mutations (median, 0.43 vs. 0.41; P=.0002), while type B mutations had lower VAFs than non-type B mutations (median, 0.34 vs. 0.43; P=.0025) (Figure A). Age or karyotype did not associate with NPM1 VAF. NPM1 VAF, as a continuous variable, did not associate with response to induction chemotherapy (P=.6) or relapse-free survival (P=.22). A higher NPM1 VAF did, however, associate with shorter OS (hazard ratio for an increase in NPM1 VAF equal to the interquartile range, 1.14; 95% confidence interval, 1.00-1.30; P=.049). In particular, patients in the lowest quartile of NPM1 allele burden ('low NPM1 VAF') had longer OS than patients with allele burdens above the 25th percentile ('high NPM1 VAF') (median OS, 63.7 vs. 27.0 months; 5-year OS, 51% vs 42%; P=.05; Figure B). Patients with high NPM1 VAF had higher leukocyte counts (median, 46000/µl vs. 9300/µl; P<.0001) and bone marrow blast percentages (median, 85% vs. 80%; P=.0004) than patients with low NPM1 VAF. On the genetic level, patients with high NPM1 VAF more frequently had concomitant FLT3-ITD (47% vs. 37%; P=.07), and particularly FLT3-ITD with a high (≥0.5) mutant-to-wild type ratio (33% vs. 17%; P=.007), compared to patients with low NPM1 VAF. DNMT3A co-mutation was also more frequent in patients with high vs. low NPM1 VAF (63% vs. 46%; P=.002). In multivariable analyses adjusting for FLT3-ITD allelic ratio and/or DNMT3A mutation status, only the latter genetic alterations but not NPM1 VAF remained associated with OS. Conclusion: Our study confirms the recent report that adult AML patients with high NPM1 mutant allele burden have shorter survival. In our cohort, however, higher NPM1 VAF also associated with higher leukocyte counts and marrow blast percentage, and with prognostically adverse FLT3-ITD and DNMT3A mutations. After adjusting for these confounders, NPM1 allelic burden did not independently predict survival in our analysis. We therefore suspect that high NPM1 VAF may be a surrogate marker of highly proliferative AML subsets, for example those with high allelic ratio FLT3-ITD, rather than a novel independent prognostic factor. Figure. Figure. Disclosures Prassek: Jannsen: Other: Travel support; Celgene: Other: Travel support. Subklewe:Roche: Consultancy, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Hiddemann:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; F. Hoffman-La Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Metzeler:Celgene: Consultancy, Research Funding; Novartis: Consultancy.

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Comprehensive Analyses of Genetic Features Identify Coordinate Signatures in Diffuse Large B-Cell Lymphoma

Blood ◽

10.1182/blood.v126.23.3922.3922 ◽

2015 ◽

Vol 126 (23) ◽

pp. 3922-3922

Author(s):

Bjoern Chapuy ◽

Andrew J Dunford ◽

Chip Stewart ◽

Atanas Kamburov ◽

Jaegil Kim ◽

...

Keyword(s):

B Cell ◽

Board Of Directors ◽

Research Funding ◽

Somatic Mutations ◽

Chromosomal Rearrangements ◽

Low Frequency ◽

B Cell Lymphoma ◽

Genetic Alterations ◽

B Cell Differentiation ◽

Advisory Committees

Abstract Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease characterized by multiple low-frequency alterations including somatic mutations, copy number alterations (CNAs) and chromosomal rearrangements. We sought to identify previously unrecognized low-frequency genetic events, integrate recurrent alterations into comprehensive signatures and associate these signatures with clinical parameters. For these reasons, our multi-institutional international group assembled a cohort of 304 primary DLBCLs from newly diagnosed patients, 87% of whom were uniformly treated with state-of-the-art therapy (rituximab-containing CHOP regimen) and had long term followup. Tumors were subjected to whole exome sequencing with an extended bait set that included custom probes designed to capture recurrent chromosomal rearrangements. In this cohort, 47% of samples had available transcriptional profiling and assignment to associated disease subtypes. Analytical pipelines developed at the Broad Institute were used to detect mutations (MuTect), CNAs (Recapseq+Allelic Capseq) and chromosomal rearrangements (dRanger+Breakpointer) and assess clonality (Absolute). To analyze formalin-fixed paraffin-embedded tumors without paired normals we developed a method which utilized 8334 unrelated normal samples to stringently filter recurrent germline events and artifacts. Significant mutational drivers were identified using the MutSig2CV algorithm and recurrent CNAs were assessed with GISTIC2.0. In addition, we utilized a recently developed algorithm, CLUMPS2, to prioritize somatic mutations which cluster in 3-dimensional protein structure. With this approach, we identified > 90 recurrently mutated genes, 34 focal amplifications and 41 focal deletions, 20 arm-level events and > 200 chromosomal rearrangements in the DLBCL series. Of note, 33% of the mutational drivers were also perturbed by chromosomal rearrangements or CNAs, underscoring the importance of a comprehensive genetic analysis. In the large DLBCL series, we identified several previously unrecognized but potentially targetable alterations including mutations in NOTCH2 (8%) and TET2 (5%). The majority of identified chromosomal rearrangements involved translocations of potent regulatory regions to intact gene coding sequences. The most frequently rearrangements involved Ig regulatory elements which were translocated to BCL2, MYC, BCL6 and several additional genes with known roles in germinal center B-cell biology. After identifying recurrent somatic mutations, CNAs and chromosomal rearrangements, we performed hierarchical clustering and identified subsets of DLBCLs with comprehensive signatures comprised of specific alterations. A large subset of tumors shared recurrent alterations previously associated with follicular lymphoma including mutations of chromatin modifiers such as CREBBP, MLL2, and EZH2 in association with alterations of TNFRSF14 and GNA13 and translocations of BCL2. This cluster was enriched in GCB-type DLBCLs and contained a subset with select genetic alterations associated with an unfavorable outcome. An additional cohort of tumors was characterized by alterations perturbing B-cell differentiation including recurrent BCL6 translocations or alterations of PRDM1. A subset of these DLBCLs had alterations of NOTCH2 and additional pathway components or mutations of MYD88 in association with TNFAIP3, CD70 and EBF1, a master regulator of B-cell differentiation. An additional group of DLBCLs exhibited frequent MYD88 mutations in association with alterations of CD79B, PIM1, TBL1XR1 and ETV6 and BCL2 copy gain; these tumors were highly enriched for ABC-type DLBCLs. This coordinate signature and additional alterations of p53 pathway components were associated with outcome. We explored bases for the identified genetic alterations in DLBCL by performing an in silico mutational signature analysis. The most frequent mutational signatures were those of spontaneous deamination (aging) and AID with rare cases of microsatellite instability. We also assessed the clonality of identified genetic features to define cancer cell fraction and establish the timing of specific genetic events. The comprehensive genetic signatures of clinically annotated DLBCLs provide new insights regarding approaches to targeted therapy. Disclosures Link: Kite Pharma: Research Funding; Genentech: Consultancy, Research Funding. Rodig:Perkin Elmer: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding. Pfreundschuh:Boehringer Ingelheim, Celegene, Roche, Spectrum: Other: Advisory board; Roche: Honoraria; Amgen, Roche, Spectrum: Research Funding. Shipp:Gilead: Consultancy; Sanofi: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Functional Analysis of the CML Blast Crisis Transcriptome and Epigenome Using Crispr-CAS9 and Pharmacologic Approaches

Blood ◽

10.1182/blood.v126.23.2764.2764 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2764-2764

Author(s):

Tun Kiat Ko ◽

Xin Xuan Sheila Soh ◽

Willie Yu ◽

Peter S. Winter ◽

Thushangi Pathiraja ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Blast Crisis ◽

Genetic Alterations ◽

Mapk Signaling ◽

Rational Approach ◽

Structural Variations ◽

Advisory Committees ◽

Paired Samples

Abstract Current models of CML blast crisis (BC) propose that expression of BCR-ABL results in genomic instability and the acquisition of genetic alterations that affect cell proliferation and survival, self-renewal and differentiation. To characterize the molecular events that underlie progression, we performed whole genome sequencing of paired samples of the same patient at CP and at BC (n = 12), as well as expression and methylation arrays of these samples and a larger validation cohort of unpaired CD34-selected samples (n = 38). Contrary to expectations, we found that the CML BC genome is relatively quiescent with regards to SNVs, indels and structural variations. In contrast, we observed widespread hyper-methylation in BC that was associated with distinct changes in expression and was independent of lineage/differentiation state. These findings suggest that in addition to genetic alterations, epigenomic events are likely to contribute substantively to BC progression. To understand the functional effects of the dysregulated transcriptome and epigenome in BC CML, we employed both pharmacologic and genetic methods to target candidate genes of interest identified in our earlier studies. To induce de-methylation of the BC genome, we treated primary samples with low doses of decitabine, a DNMT inhibitor. We found that decitabine impaired colony formation ability of BC CD34+ progenitors and concomitantly activated regulators of myeloid differentiation that were both hyper-methylated and down-regulated in BC CD34+ progenitors, such as MPO and KLF1. These results suggest that hyper-methylation does contribute to BC CD34+ progenitor function, and support the use of epigenetic therapies as a rational approach to targeting BC. The genetic approach we chose was a CRISPR-based in vitro pooled screen. We created a custom library targeting 200 genes, with an average of 5 sgRNAs per gene, and 50 non-targeting controls. We transduced K562 with the library and harvested samples at different time-points post-transduction/selection - Day 0, 7 and 21 - for deep sequencing. As expected, sgRNAs targeting essential genes such as MYC and MCM 2-7 were recurrently depleted in the population over time. More importantly, enriched sgRNAs targeted genes including TET2, which has been previously reported to be inactivated in myeloid malignancies, as well as novel candidates including RREB1, a transcription factor that binds to RAS-responsive elements (RREs) and may be involved in MAPK signaling. We will validate these targets by knocking them out individually and assessing their effect on the ability of CP cells to serially replate and/or engraft immune-deficient mice. Disclosures Chuah: Bristol-Myers Squibb: Honoraria; Novartis: Honoraria; Chiltern International: Honoraria. Takahashi:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Masis: Consultancy; Otsuka: Membership on an entity's Board of Directors or advisory committees; Celgene: Speakers Bureau; Sysmex: Research Funding, Speakers Bureau; Astellas: Speakers Bureau. Valent:Novartis: Consultancy, Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Celgene: Honoraria.

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Genetic Alterations at Diagnosis Predict Outcome of AML Patients Age 60 or Older Undergoing Allogeneic Transplantation in First Remission

Blood ◽

10.1182/blood-2019-125967 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 48-48 ◽

Cited By ~ 1

Author(s):

H. Moses Murdock ◽

Haesook T. Kim ◽

Bryan Hambley ◽

Pankit Vachhani ◽

Nathan Denlinger ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Genetic Risk ◽

Research Funding ◽

Gene Mutations ◽

Genetic Alterations ◽

Advisory Committees ◽

Genetic Characteristics ◽

The Impact ◽

Advisory Role

Background: Older age is associated with inferior outcomes after allogeneic hematopoietic stem cell transplantation (HSCT) for acute myeloid leukemia (AML). High risk genetic characteristics are common among older patients and linked to poor outcomes in the non-transplant setting. An enhanced understanding of genetic risk may thus provide a basis for improving transplant outcomes in these patients. We evaluated the impact of leukemia genetic characteristics at diagnosis on HSCT outcomes in a multi-center cohort of AML patients age 60 or older receiving HSCT in first complete remission (CR1). Methods: We performed targeted sequencing of 112 genes on diagnostic leukemia samples from 257 patients with AML age 60 or older who received allogeneic HSCT in CR1 at 5 US transplant centers. Median age at diagnosis and HSCT were 65 (range 59-76) and 66 (range 60-76), respectively. 31% had clinically defined secondary AML, 11% had therapy-related AML, and 23% had adverse cytogenetics by 2017 ELN classification. Most (84%) were treated with anthracycline-based induction chemotherapy, while 16% received non-intensive induction. Conditioning was either reduced-intensity or non-myeloablative in 94% of patients. Median follow-up for survivors was 3.7 years; 3-year overall survival (OS) and leukemia-free survival (LFS) were 48% and 44%, respectively. Results: All patients had recurrent genetic alterations at the time of diagnosis, including 251 (98%) with gene mutations and 6 with only cytogenetic abnormalities. The most frequent gene mutations were DNMT3A (25%), NPM1 (23%), FLT3-ITD (22%), ASXL1 (21%), TET2 (21%), RUNX1 (20%), and SRSF2 (18%). Secondary-type mutations associated with antecedent MDS occurred in 42%, and 10% had TP53 mutations. As expected, secondary-type and TP53 mutations were associated with clinically-defined secondary AML (p<0.001), need for reinduction (p=0.03), and CR with incomplete count recovery (p= 0.03). Despite the older age at leukemia diagnosis, putative germline pathogenic variants were identified in 22 (8.6%) patients, including 17 (6.6%) with DDX41 mutations (13/17 with somatic mutation of the second allele), and 5 with TERT or TERC variants not found in population databases. We evaluated the impact of gene mutations on LFS using univariable and multivariable Cox models and developed a hierarchical model of 3 molecular genetic risk groups according to the hazard ratios (Fig 1A): (1) patients with TP53 mutation or JAK2 mutation or FLT3-ITD/NPM1-WT (high risk), (2) patients without high risk mutations who have DNMT3A or GATA2 or DDX41 mutations (low risk) (3) patients without high- or low-risk mutations (intermediate risk), with 3-year LFS of 8%, 65%, and 47% (p<0.001), respectively. Next, we combined molecular genetic and cytogenetic risk to derive a final genetic model comprised of 4 groups with distinct 3-year LFS (69%, 50%, 27%, and 0%) (Fig 1B). Poor LFS in the very high-risk group was due almost entirely to relapse (3-year relapse rate > 90%), but was driven by a combination of relapse and non-relapse mortality in the intermediate and high-risk groups (Fig 2). Conclusion: Genetic characteristics at diagnosis are highly associated with OS and LFS in AML patients age 60 or older who undergo allogeneic transplantation in CR1. We identify patients with low genetic risk and remarkably good outcomes who may be candidates for strategies aimed at reducing toxicity, and those with very high-risk genetics who have limited benefit from current transplant approaches. Among intermediate and high-risk patients, the impact of disease genetics on LFS is mostly due to relapse, suggesting that a model incorporating measurement of residual disease in CR1 and after transplantation could enable a more dynamic estimation of risk. Disclosures Perales: Bristol-Meyers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Nektar Therapeutics: 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; Omeros: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bellicum: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; NexImmune: Membership on an entity's Board of Directors or advisory committees; MolMed: Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy, Honoraria; Medigene: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kyte/Gilead: Research Funding; Miltenyi: Research Funding. Koreth:Equillium: Consultancy; Amgen: Consultancy; Cugene: Consultancy. Ho:Jazz Pharmaceuticals: Consultancy. Soiffer:Mana therapeutic: Consultancy; Kiadis: Other: supervisory board; Juno, kiadis: Membership on an entity's Board of Directors or advisory committees, Other: DSMB; Gilead, Mana therapeutic, Cugene, Jazz: Consultancy; Jazz: Consultancy; Cugene: Consultancy. Carroll:Astellas Pharmaceuticals: Research Funding; Incyte: Research Funding; Janssen Pharmaceuticals: Consultancy. Vasu:Boehringer Ingelheim: Other: Travel support; Seattle Genetics: Other: Clinical trial support. Wang:Abbvie: Other: Advisory role; Kite: Other: Advisory role; Jazz: Other: Advisory role; Astellas: Other: Advisory role, Speakers Bureau; celyad: Other: Advisory role; Pfizer: Other: Advisory role, Speakers Bureau; Stemline: Other: Advisory role, Speakers Bureau; Daiichi: Other: Advisory role; Amgen: Other: Advisory role; Agios: Other: Advisory role. Devine:Kiadis Pharma: Other: Protocol development (via institution); Bristol Myers: Other: Grant for monitoring support & travel support; Magenta Therapeutics: Other: Travel support for advisory board; My employer (National Marrow Donor Program) has equity interest in Magenta. Lindsley:Jazz Pharmaceuticals: Research Funding; Takeda Pharmaceuticals: Consultancy; Medlmmune: Research Funding.

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Outcomes of Allogeneic Hematopoietic Cell Transplantation in Adults with Ph-like ALL

Blood ◽

10.1182/blood-2021-153125 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3955-3955

Author(s):

Ibrahim Aldoss ◽

Dongyun Yang ◽

Zhaohui Gu ◽

Vanina Tomazian ◽

Sally Mokhtari ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Relapse Rate ◽

Research Funding ◽

Hematopoietic Cell Transplantation ◽

Conditioning Regimen ◽

Disease Status ◽

R Package ◽

Genetic Alterations ◽

Advisory Committees

Abstract Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) represents 20% of newly diagnosed adults with B cell ALL (B-ALL), with increased frequency in adults with Hispanic ethnicity. Ph-like ALL harbors a diverse range of genetic alterations with CRLF2-rearrangement/overexpression (CRLF2r) being the most common one. When treated with chemotherapy, Ph-like ALL is associated with inferior response, high relapse rate, and low overall survival (OS). Allogenic hematopoietic cell transplantation (alloHCT) is a well-established curative modality for adults with high-risk ALL. Considering that Ph-like ALL is a high-risk leukemia subtype, it is appealing to recommend alloHCT consolidation routinely for this entity in adults. However, large datasets describing alloHCT outcomes in patients with Ph-like ALL is lacking. In this study, we retrospectively analyzed archived DNA samples from 125 consecutive adult patients with Ph-negative ALL who underwent alloHCT in complete remission (CR) at our center between 2006 and 2020. Classification of Ph-like versus non-Ph-like was performed according to WHO 2017 classification using accumulative results from RNAseq, conventional cytogenetics, FISH, and whole genome array studies. A proprietary RNA sequencing assay covering 1,188 genomic regions from 235 genes was designed to detect all the clinically significant fusions and expressions for Ph-like ALLs. In addition, an algorithm employing the RNAseq data was developed to further aid in classification of Ph-like ALL. Boruta feature selection (R package "Boruta" version 7.0.0) was used to identify the most informative genes for prediction with an out-of-bag error of 9.62%. The following 24 genes were identified: CCND2, SOX11, PAX5, DENND3, RARA, MME, ID4, SH3BP5, HOXA9, CA6, MUC4, CYB5R2, CD97, EPOR, IL2RA, RAB29, PDGFRA, MLLT4, RHOA, JAK2, DNM2, ASXL1, BCL2A1, and KDR. The results were used to predict Ph-like status by a Random Forest model (R package "randomForest" version 4.6-14) that generates a probability/similarity score of Ph gene expression profile (Ph score). The testing samples with Ph score over 50% and without other subtype-defining lesions are defined as Ph-like. We identified Ph-like genetic alterations in 66 (53%) patients, of whom 42 (66%) were carrying CRLF2r and 24 (36%) were non-CRLF2r. Compared to non-Ph-like ALL (n=59), Ph-like ALL patients were younger (42 vs 36 years old, p=0.022), more frequently Hispanic (56% vs 83%, p=0.003), less frequently carried high-risk cytogenetics (39% vs 9%, p<0.001), more frequently induced with pediatric-inspired regimens (25% vs 61%, p=0.003) and more likely required >1 regimen to achieve their first complete remission (CR1; 30% vs 55%, p=0.025). However, we did not detect any significant difference between the two groups in disease status (CR1 vs. CD2/3; p=0.81) or minimal residual disease clearance at the time of HCT (negative vs. positive; p=0.17), donor type (match related/unrelated vs mismatch vs haplo vs cord blood; p=0.88), conditioning regimen intensity (myeloablative vs non-myeloablative/ reduced intensity; p=0.59), GVHD prophylaxis (tacrolimus/sirolimus-based vs PTCy-based; p=0.84), Karnofsky Performance Status (KPS; p=0.24) or HCT comorbidity index (0 vs 1-2 vs >2; p=0.42). With the median follow-up of 3.2 years, we observed similar 3-years leukemia-free survival (LFS) (40% vs 47%; p=0.95), OS (44% vs 54%; p=0.96), relapse rate (33% vs 34%; p=0.96) and non-relapse mortality (NRM) (27% vs 19%; p=0.92) between non-Ph-like and Ph-like ALL patients, respectively. (Figure) In multivariable analysis, disease status at the time of HCT (HR=2.63, 95% CI: 1.57-4.41; p<0.001), donor type (p=0.049) and KPS (HR=2.22, 95% CI: 1.05-4.69; p=0.038) influenced OS. LFS was significantly influenced by disease status (HR=2.35, 95% CI: 1.45-3.80); p<0.001) and conditioning regimen intensity (HR=1.84, 95% CI: 1.11-3.04; p=0.017). Relapse rate was associated with disease status (HR=2.06, 95%CI: 1.11-3.84; p=0.23) and conditioning regimen intensity (HR=1.97, 95% CI: 1.03-3.75; p=0.40). Only KPS (HR=6.56, 95% CI: 2.48-17.36; P<0.001) was associated with NRM. In conclusion, our data suggest that alloHCT consolidation results in favorable outcomes in adult patients with Ph-like ALL with comparable outcomes to non-Ph-like ALL. Our data support utilization of alloHCT for adults with Ph-like ALL in CR. Figure 1 Figure 1. Disclosures Al Malki: Neximmune: Consultancy; Rigel Pharma: Consultancy; Jazz Pharmaceuticals, Inc.: Consultancy; Hansa Biopharma: Consultancy; CareDx: Consultancy. Khaled: Omeros: Honoraria; Alexion: Honoraria, Speakers Bureau; Janssen: Current Employment; Astellas: Honoraria; Jazz: Honoraria. Ali: Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Speakers Bureau; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees. Aribi: Seagen: Consultancy. Mei: BMS: Research Funding; Epizyme: Research Funding; TG Therapeutics: Research Funding; EUSA: Honoraria; Janssen: Honoraria; Morphosys: Research Funding; Beigene: Research Funding. Koller: Novartis: Consultancy. Artz: Radiology Partners: Other: Spouse has equity interest in Radiology Partners, a private radiology physician practice. Stein: Amgen: Consultancy, Speakers Bureau; Celgene: Speakers Bureau; Stemline: Speakers Bureau. Marcucci: Abbvie: Other: Speaker and advisory scientific board meetings; Novartis: Other: Speaker and advisory scientific board meetings; Agios: Other: Speaker and advisory scientific board meetings. Forman: Lixte Biotechnology: Consultancy, Current holder of individual stocks in a privately-held company; Mustang Bio: Consultancy, Current holder of individual stocks in a privately-held company; Allogene: Consultancy. Pullarkat: AbbVie, Amgen, Genentech, Jazz Pharmaceuticals, Novartis, Pfizer, and Servier: Membership on an entity's Board of Directors or advisory committees; Amgen, Dova, and Novartis: Consultancy, Honoraria.

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Impact of Gene Mutations on Overall Survival in Older Patients with Acute Myeloid Leukemia (AML) Treated with Azacitidine (AZA) or Conventional Care Regimens (CCR)

Blood ◽

10.1182/blood.v128.22.2859.2859 ◽

2016 ◽

Vol 128 (22) ◽

pp. 2859-2859 ◽

Cited By ~ 4

Author(s):

Lin Tang ◽

Anna Dolnik ◽

Kyle J. MacBeth ◽

Hervé Dombret ◽

John F. Seymour ◽

...

Keyword(s):

Dna Methylation ◽

Overall Survival ◽

Board Of Directors ◽

Older Patients ◽

Research Funding ◽

Gene Mutations ◽

Molecular Heterogeneity ◽

Employment Equity ◽

Advisory Committees ◽

Equity Ownership

Abstract Background: AML is characterized by molecular heterogeneity and specific mutations are prognostically important (Papaemmanuil, Gerstung et al, NEJM,2016). Mutational analysis of NPM1, CEBPA, and FLT3 is included in the 2010 European LeukemiaNet recommendations for AML (Döhner et al, Blood, 2010). Additional recurrently mutated genes have since been identified with potential value for prognosis and prediction of treatment (Tx) response. The phase 3 AZA-AML-001 study showed AZA prolonged median overall survival (OS) vs CCR (10.4 vs 6.5 months [mos]; P=0.101) and improved 1-year survival (46.5% vs 34.2%) in older patients (pts) with AML (Dombret et al, Blood, 2015). Aim: To investigate relationships between gene mutations and OS in the subpopulation of AZA-AML-001 pts with available baseline bone marrow (BM) for molecular analyses ("biomarker" cohort). Methods: Eligible pts were age ≥65 years with newly diagnosed AML (>30% BM blasts), ECOG performance status (PS) score 0-2, WBC count ≤15x109/L, and NCCN-defined intermediate- or poor-risk cytogenetics. Pts received AZA (75 mg/m2/day [d] x 7d/28d cycle) or a preselected CCR: intensive chemotherapy (7 + 3 regimen), low-dose ara-C, or best supportive care only. DNA was isolated from BM mononuclear cells and targeted sequencing of 39 genes was performed with Haloplex target enrichment (Agilent) on Illumina HiSeq 2500 using 2x100bp read lengths. FLT3 tyrosine kinase domain (TKD) mutations were determined by next-generation sequencing (NGS) and internal tandem duplications (ITD) were determined by capillary electrophoresis sizing of PCR amplicons. Target regions varied by gene from all exons to hot-spots. Log-rank test, stratified by ECOG PS score (0-1 vs 2) and cytogenetic risk (intermediate vs poor) at baseline, was used to assess OS of pts with mutations (mut) in genes detected in ≥5 pts vs OS in pts with wild-type (wt) genes within the AZA and CCR arms. Median OS was estimated using Kaplan-Meier methods. Results: The biomarker cohort comprised 156 of all 488 pts in AZA-AML-001 (32%; AZA n=83, CCR n=73). Baseline characteristics and hematologic response rates were well-matched between biomarker and non-biomarker pts. Mutations were detected in 33 of 39 sequenced genes. The most frequently mutated genes were DNMT3A (27%), TET2 (25%), IDH2 (23% [R140 15%, R172 8%]), TP53 (21%), RUNX1 (18%), NPM1 (16%), NRAS (12%), FLT3 (12% [-ITD 10%, -TKD 5%]), ASXL1 (11%), and STAG2 (10%). Stratified log-rank tests showed that median OS was significantly reduced for CCR pts with TP53mut (2.4 vs 12.5 mos with TP53wt; P=0.026) and with NRASmut (4.3 vs 10.3 mos with NRASwt; P=0.020). In the AZA arm, median OS was not significantly different between pts with TP53mutor TP53wt (7.2 vs 12 mos; P=0.40) or between pts with NRASmut or NRASwt (11.8 vs 8.9 mos; P=0.95), but was reduced in pts with FLT3mut (5.4 vs 12.0 mos with FLT3wt; P=0.017). Compared with similar pts treated with CCR, pts with TP53mut and/or NRASmut treated with AZA had nominally better median OS (7.2 vs 2.4 mos for TP53mut; 11.8 vs 4.3 mos for NRASmut), and pts with FLT3mut had nominally worse OS (5.4 vs 6.4 mos) (Table). Median OS was similar for pts with or without mutations in each of the genes known to influence DNA methylation (DNMT3A, IDH1, IDH2, and TET2); however, there was a statistical difference in OS within the AZA arm for pts with TET2mut (P=0.005) despite similar median OS for pts with TET2mut vs TET2wt (9.6 vs 9.5 mos) that was not observed within the CCR arm (P=0.45). Median OS for pts with a mutation in any 1 of the DNA methylation genes listed above was similar in the AZA and CCR arms (Table). Conclusion: These exploratory analyses suggest older AML pts with TP53 or NRAS mutations have a better prognosis when treated with AZA than with CCR. Mutations in genes that regulate DNA methylation did not impact median OS with AZA Tx, although the potential negative effects of TET2mut and FLT3mut warrant further evaluation. Prognostic implications of isolated gene mutations can vary due to co-mutations; larger pt cohorts are needed to establish the influence of recurring co-mutational patterns in AZA-treated pts. Disclosures Tang: Celgene: Employment, Equity Ownership. MacBeth:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties, Research Funding. Dombret:Agios: Honoraria; Sunesis: Honoraria; Ambit (Daiichi Sankyo): Honoraria; Karyopharm: Honoraria; Kite Pharma.: Honoraria, Research Funding; Menarini: Honoraria; Menarini: Honoraria; Astellas: Honoraria; Janssen: Honoraria; Servier: Honoraria; Seattle Genetics: Honoraria; Roche/Genentech: Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria; Ariad: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Consultancy, Honoraria; Jazz Pharma: Honoraria, Research Funding. Seymour:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding, Speakers Bureau; Genentech: 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, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Stone:Pfizer: Consultancy; Sunesis Pharmaceuticals: Consultancy; Karyopharm: Consultancy; ONO: Consultancy; Jansen: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celator: Consultancy; Roche: Consultancy; Agios: Consultancy; Amgen: Consultancy; Novartis: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics: Consultancy; Merck: Consultancy; Seattle Genetics: Consultancy; Xenetic Biosciences: Consultancy. Beach:Celgene Corporation: Employment, Equity Ownership.

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