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

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.

Download Full-text

The Impact of gain1q on Mutational Structure and Clonal Evolution in a Uniformly Treated High-Risk Series of Patients at First Relapse

Blood ◽

10.1182/blood-2021-152123 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 2683-2683

Author(s):

John R Jones ◽

Charlotte Pawlyn ◽

Niels Weinhold ◽

Timothy Cody Ashby ◽

Brian A Walker ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Clonal Evolution ◽

Suppressor Gene ◽

Tumour Suppressor Gene ◽

Mutational Load ◽

Advisory Committees ◽

The Impact ◽

Support Research

Abstract Introduction In Multiple Myeloma (MM) the emergence of treatment resistant clones is a characteristic feature of relapse and this is particularly so for high-risk cases. A key driver event mediating progression, risk status and relapse is gain(1q) (1q+). We report on the impact of 1q+ on the genetic profile seen at first relapse in a uniformly treated, newly diagnosed series of 56 patients enrolled to the NCRI Myeloma XI Trial. Methods We included 56 high risk patients, defined as relapse within 30 months of maintenance randomisation (median 19 months, range 8-51). Of the 56 patients, 30 received lenalidomide maintenance and 26 were observed. Whole exome sequencing was conducted at presentation and relapse to a median depth of 122x for tumour samples and 58x for controls. Libraries were prepared using the SureSelectQXT sample prep kit and SureSelect Clinical Research Exome kit. MuTect was used to determine gene variants and SciClone clustering was undertaken to map mutation variant allele frequencies. MANTA was used to determine translocations and Sequenza for copy number aberrations. Clonal structure and mechanisms of clonal evolution were assessed using kernel density estimation of the cancer clonal fraction for all mutations. Wilcoxon matched-pairs signed rank tests (2-sided) were used to determine the significance between paired data sets, including mutational load. Fishers exact test was used to determine the difference between two nominal variables. Results We looked at mutational, structural and clonal evolution events in all patients based on 1q+ status at relapse. At diagnosis, 34% (19/56) patients had evidence of 1q+, increasing to 46% (26/56) at relapse, with all patients harbouring 1q+ at presentation having the lesion at relapse. There was a significantly higher non-synonymous mutational load at relapse in patients with 1q+, 107 vs 126 (p=0.047), compared to those without 1q+, 36 vs 44 (p=0.140). Twenty two genes known to be significant in MM and mutations within the genes known to be important in IMiD mechanism of action were reviewed. Of the patients with 1q+, 92% (24/26) had at least one mutation during the course of the disease, compared to 77% in those without 1q+ (p=0.15). The impact on tumour suppressor gene regions including deletions of chromosome 1p, 13, 14 and 17p was analyzed. Of the patients with 1q+, 77% (20/26) of patients had a deletion of one of these regions during the disease course, compared to 57% (17/30) of patients without 1q+ (p=0.16). At relapse a change in the profile of these lesions was noted in 23% (6/26) patients with 1q+, compared to 20% (6/30) patients without 1q+ (p=1). Translocations involving MYC (t MYC) were also determined and found in 27% (7/26) of patients with 1q+ and 27% (8/30) of patients without (p=1). As with 1q+, t MYC was always preserved at relapse. Mechanisms of evolution leading to relapse were established for all patients. Branching and linear evolution predominated, noted to be the mechanism leading to relapse in 88% (23/26) patients with 1q+ and 83% (25/30) without (p0.71). Stable evolution was noted in the remaining patients. 1q+ occurring as a new event at relapse was associated with branching or linear evolution in all patients (n=7), consistent with a change in clonal structure. Conclusion These data reveal that 1q+ is conserved throughout the disease course, suggesting it imparts a survival advantage and treatment resistant phenotype to the clone(s) containing it. The presence of 1q+ is associated with a significant increase in mutational load at relapse and a greater incidence of tumour suppressor gene structural deletions, mechanisms that may contribute to clonal evolution and therapeutic escape. Disclosures Jones: BMS/Celgene: Other: Conference fees; Janssen: Honoraria. Pawlyn: Celgene / BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Weinhold: Sanofi: Honoraria. Walker: Sanofi: Speakers Bureau; Bristol Myers Squibb: Research Funding. Cairns: Merck Sharpe and Dohme: Research Funding; Amgen: Research Funding; Takeda: Research Funding; Celgene / BMS: Other: travel support, Research Funding. Kaiser: AbbVie: Consultancy; Seattle Genetics: Consultancy; BMS/Celgene: Consultancy, Other: Travel support, Research Funding; Amgen: Honoraria; Karyopharm: Consultancy, Research Funding; Pfizer: Consultancy; Janssen: Consultancy, Other: Educational support, Research Funding; GSK: Consultancy; Takeda: Consultancy, Other: Educational support. Cook: Pfizer: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria. Drayson: Abingdon Health: Current holder of individual stocks in a privately-held company. Jackson: oncopeptides: Consultancy; takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Speakers Bureau; J and J: Consultancy, Honoraria, Speakers Bureau; celgene BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; amgen: Consultancy, Honoraria, Speakers Bureau; Sanofi: Honoraria, Speakers Bureau. Davies: BMS: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Roche: Consultancy, Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees.

Download Full-text

U2AF1 Mutations in S34 and Q157 Create Distinct Molecular and Clinical Contexts

Blood ◽

10.1182/blood.v128.22.3155.3155 ◽

2016 ◽

Vol 128 (22) ◽

pp. 3155-3155 ◽

Cited By ~ 2

Author(s):

Vera Adema ◽

Cassandra M. Hirsch ◽

Bartlomiej P Przychodzen ◽

Aziz Nazha ◽

Teodora Kuzmanovic ◽

...

Keyword(s):

Board Of Directors ◽

Clinical Outcomes ◽

Research Funding ◽

Gene Mutations ◽

Advisory Committees ◽

Cross Sectional ◽

Downstream Effects ◽

Targeted Deep Sequencing ◽

Sectional Analysis ◽

The Impact

Abstract Background: U2AF1 forms a heterodimer for the recognition of the 3' splice site during pre-mRNA splicing. Somatic U2AF1 mutations are present in approximately 10% of MDS patients. Most U2AF1 mutations are recurrent at 2 highly conserved hotspots, while non-canonical mutations are rare. U2AF1S34 and U2AF1Q157 mutations map within the zinc finger domains of the protein, resulting in distinct downstream effects. We have previously shown that U2AF1Q157 mutant patients have distinct splicing patterns compared to U2AF1WT with a set of misspliced targeted genes, including ARID2 and EZH2. In contrast, recent work focusing on S34 suggests a distinct subset of misspliced genes, including ATG7 (Park SM, Molecular Cell, 2016). The biological and clinical implications of these 2 distinct mutations are unknown. We investigated the differences between these mutations with respect to clinical outcomes and molecular background, including their impact on clonal architecture. Methods: We first collected molecular and clinical data on a cohort of 1700 patients with myeloid neoplasms (median follow up 1.0 year, range 1-5 years), median age was 65 years (range, 11-93). Targeted deep sequencing of a panel of frequently mutated genes (64) was applied. Our analyses included somatic mutational patterns, clonal hierarchy, and mutational correlation of the cohort of patients with U2AF1S34 and U2AF1Q157 and those without mutations in this gene. U2AF1 mutations were found in 5% (78/1700) of patients, all of them were missense and in a heterozygous configuration. Results: Both mutations were equally distributed in the cohort: U2AF1S34 (45%, 35/78), and U2AF1Q157 (46%, 36/78). Other mutations (Q84, E124, E152, and R156) were detected at a lower frequency (9%). We then dissected the clonal hierarchy of both U2AF1 mutations and found that 44% (34/77) were ancestral while 56% (43/77) were secondary. In MDS, most U2AF1 mutations (77%, P=.002) were dominant, while subclonal U2AF1 mutations were evenly distributed between the subentities. U2AF1S34 or U2AF1Q157 were equally likely to be dominant (21% vs. 27%; ancestral events; P=.09, respectively). Similarly, S34 and Q157 mutant clones had similar median variant allele frequencies (3-52% vs. 8-64%). U2AF1 S34 mutant cases had similar OS to patients carrying U2AF1Q157 (N=35 vs. N=36; 10 vs. 15 months; P=.209; LogR=.65). When we compared the impact of ancestral vs. secondary U2AF1S34 and U2AF1Q157 we found that MDS patients carrying ancestral U2AF1 mutations had a shorter OS compared to MDS patients carrying secondary U2AF1 patients (N=26 vs. N=18; 13 vs. 34 months; LogR=.04). Of note, ancestral U2AF1S34 patients had shorter OS compared to ancestral U2AF1Q157 patients (13 vs.11; 10 vs.15 months; P=.03; LogR=.86). Given these differences, we also investigated the mutational spectrum of U2AF1MUT patients. Cross sectional analysis identified that the top genes mutated in the U2AF1 mutant cohort were: ASXL1 (26%), BCOR/L1 (15%), TET2 (13%), DNMT3A and PHF6 (12%), ETV6 (10%), RUNX1 and STAG2 (9%), and SETBP1 (8%). Transcriptional factor and DNA-methylation genes were predominantly mutated in U2AF1MUT patients (35% and 24%, respectively). Exploring the association between S34/Q157 vs. other gene mutations, S34 co-occurred with BCOR/L1 mutations (P=.007, 24%), while Q157 mutations co-occurred with ASXL1 (P=.003, 44%) irrespective of their rank in the clonal hierarchy. When S34 was the dominant mutation, secondary mutations included ETV6, BCOR, and CUX1. In contrast, when Q157 was the ancestral event, secondary mutations included ASXL1 and DNMT3A. Subclonal S34 occurred in the context of ancestral RUNX1, BCOR/L1, CUX1 and DNMT3A, while subclonal Q157 followed ancestral ASXL1, EZH2, PHF6 and TET2. Conclusion: In sum, U2AF1S34 and U2AF1Q157, consistent with their differential missplicing consequences, create a distinct molecular milieu leading to differences in clinical outcomes. Disclosures Makishima: The Yasuda Medical Foundation: Research Funding. Carraway:Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Research Funding, Speakers Bureau; Baxalta: Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees. Maciejewski:Celgene: Consultancy, Honoraria, Speakers Bureau; Alexion Pharmaceuticals Inc: Consultancy, Honoraria, Speakers Bureau; Apellis Pharmaceuticals Inc: Membership on an entity's Board of Directors or advisory committees.

Download Full-text

Prognostic Impact of Bone Marrow Fibrosis in Primary Myelofibrosis: A Study of Agimm Group on 540 Patients

Blood ◽

10.1182/blood.v126.23.351.351 ◽

2015 ◽

Vol 126 (23) ◽

pp. 351-351 ◽

Cited By ~ 1

Author(s):

Paola Guglielmelli ◽

Giada Rotunno ◽

Annalisa Pacilli ◽

Elisa Rumi ◽

Vittorio Rosti ◽

...

Keyword(s):

Bone Marrow ◽

Multivariate Analysis ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Primary Myelofibrosis ◽

Driver Mutations ◽

Prognostic Impact ◽

Advisory Committees ◽

The Impact

Abstract Background. The prognostic significance of bone marrow (BM) fibrosis grade in pts with primary myelofibrosis (PMF) is debated. A fibrosis grade greater than 1 was associated with a 2-fold higher risk of death compared with pts with early/prefibrotic MF (grade 0) [Thiele J, Ann Hematol 2006]. Recent data suggest that more accurate prediction of survival is achieved when fibrosis grade is added to IPSS [Verner C, Blood 2008; Giannelli U, Mod Pathol 2012]. Aim. To analyze the prognostic impact of fibrosis in diagnostic BM samples of 540 WHO-2008 diagnosed PMF pts with extensive clinical and molecular information collected in 6 Italian centers belonging to AGIMM (AIRC-Gruppo Italiano Malattie Mieloproliferative). Methods. The clinical variables assessed were those previously identified as prognostically relevant in the IPSS score. Published methods were used to screen mutations of JAK2, MPL, CALR, EZH2, ASXL1, IDH1/2 and SRSF2. European consensus scoring system was used to grade fibrosis (on a scale of MF-0 to MF-3). The prognostic value of fibrosis with regard to overall survival (OS) was estimated by Kaplan-Meier method and Cox regression. Results. Pts' median age was 61y; median follow-up 3.7y; median OS 10.5y; 184 pts (34.1%) died. IPSS risk category: low 33.7%, Int-1 27.7%, Int-2 19.1%, High-risk 19.5%. Mutational rate: JAK2 V617F 62.6%, CALR 20.7% (type-1/1-like 77.7%, type2/2-like-2 21.4%), MPL W515 5.9%; 62 (11.5%) were triple negative (TN). 171 pts (31.7%) were High-Molecular Risk (HMR) category (Vannucchi AM, Leukemia 2013); mutation rate: EZH2 7.2%, ASXL1 22.2%, IDH1-2 2.4%, SRSF2 8.3%. According to fibrosis grading, 50 pts were MF-0 (9.3%), 180 MF-1 (33.3%), 196 MF-2 (36.3%), 114 MF-3 (21.1%). Compared with both MF-0 and MF-1, MF-2 and MF-3 pts presented more frequently constitutional symptoms (P<.0001), larger splenomegaly (P<.0001), greater risk of developing anemia (P<.0001) or thrombocytopenia (P=.003). We found a significant association (P<.0001) between IPSS higher/Int-2 risk categories and MF-2 and -3 (20.5% and 37.8%, respectively, vs 14.8% and 6.0% for MF-0 and -1). There was no correlation between fibrosis grade and phenotypic driver mutations; in particular, TN pts were equally distributed among MF fibrosis grades (10%, 10.6%, 14.3% and 8.8% from MF-0 to -3, respectively). Conversely, the frequency of HMR pts increased progressively according to fibrosis grade: 8 pts MF-0 (16%), 46 MF-1 (25.6%), 66 MF-2 (33.7%) and 51 MF-3 (44.7%) (P<.0001). In particular, we found a significant association between fibrosis grade and ASXL1 (12%, 15%, 23.5% and 36% from MF-0 to -3; P<.0001) and EZH2 (2%, 3.9%, 8.2%, 13.2%; P=.01) mutations. Also, pts with 2 or more HMR mutated genes were preferentially MF-2 or -3 ( 0%, 4.4% 10.2% and 10.5% from MF-0 to -3; P=.001). Median OS was significantly shorter in pts with MF-2 (OS 6.7y, HR 7.3, IC95% 2.7-20.0; P<.0001) and MF-3 (OS 7.2y, HR 8.7, IC95% 3.1-24.2; P<.0001) compared with MF-1 (14.7y; HR 3.9, IC95% 1.4-10.9, P=.008) and MF-0 (P<.0001) used as reference group (OS not reached) (Figure). Excluding MF-0, MF-2 and -3 maintained negative prognostic impact with HR 1.9 (1.3-2.6; P=.001) and 2.2 (1.5-3.3; P<.0001) respectively vs MF-1. The impact of fibrosis on OS was maintained when analysis was restricted to younger (≤65y) pts. In multivariate analysis using the individual IPSS variables, grade MF-2 and -3 were independently predictive of survival (HR 3.9 (1.4-10.8), and HR 4.2 (1.5-12.0), respectively, P=.008 for both). The negative impact on survival of MF-2/-3 was maintained regardless of IPSS category, HMR status, number of HMR mutated genes and driver mutations, included as covariates (Table). In low, Int-1 and Int-2, but not high-risk IPSS categories, MF-2/-3 associated with reduced survival (P<.03). Conclusions. Overall, these results indicate that higher grades (MF-2 and MF-3) of fibrosis correlate with defined clinical and molecular variables and independently negatively impact on OS in PMF, suggesting the opportunity to explore its value in the setting of clinical and molecular prognostic scores for PMF. Table. Multivariate Analysis Variables HR 95% CI P value HMR status 2.4 1.5-3.7 <.0001 HMR≥2mutations 4.3 2.8-6.4 .009 IPSS scoring Int1 2.9 1.6-5.1 <.0001 Int2 10.0 5.6-17.7 <.0001 High 9.7 5.5-17.2 <.0001 Driver mutations CALR type2 3.4 1.3-8.6 .010 JAK2/MPL 2.4 1.4-4.3 .003 TN 4.5 2.3-8.8 <.0001 Fibrosis MF-2/MF-3 3.8 1.4-10.6 .010 Figure 1. Figure 1. Disclosures Passamonti: Novartis: Consultancy, Honoraria, Speakers Bureau. Barbui:Novartis: Speakers Bureau. Vannucchi:Shire: Speakers Bureau; Novartis: Other: Research Funding paid to institution (University of Florence), Research Funding; Baxalta: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Download Full-text

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.

Download Full-text

Influence of Renal Impairment and Genetic Risk Factors on Response to Induction Therapy in the HD4 and MM5 Trials of the GMMG

Blood ◽

10.1182/blood.v124.21.4777.4777 ◽

2014 ◽

Vol 124 (21) ◽

pp. 4777-4777

Author(s):

Christof Scheid ◽

Thomas Hielscher ◽

Uta Bertsch ◽

Christina Kunz ◽

Hans Salwender ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Renal Impairment ◽

Board Of Directors ◽

Genetic Risk ◽

Research Funding ◽

Response Rates ◽

Genetic Risk Factors ◽

Advisory Committees ◽

Prospective Trials

Abstract Background: In the HOVON65/GMMG HD4 trial in patients with newly diagnosed multiple myeloma we have previously shown that patients with renal impairment (RI) (creatinine > 2 mg/dl) have higher response rates and better survival when receiving bortezomib both in the induction and maintenance therapy before and after high-dose chemotherapy (HDT) (Scheid et al. Haematologica 2014). In addition patients with RI showed a higher prevalence of genetic high-risk features such as del17p or t(4;14). The aim of this analysis was to further elucidate the interaction between renal and genetic risk factors in well defined homogeneously treated myeloma patients. Methods: For this study we selected 2 cohorts of patients entered into 2 consecutive prospective trials with centralised FISH-assessement on CD138-selected bone marrow cells. The first cohort (1) comprises 395 patients from the HOVON65/GMMG HD4 trial having been treated in the German centers and the second cohort (2) consisted in the 601 patients (intention-to-treat population) from the recently closed GMMG MM5 trial. Patients lacking FISH results were excluded from the analysis, which was the case for 53 (13.4%) patients in cohort 1 and 43 (7.2%) patients in cohort 2. In cohort 1 induction treatment was vincristine or bortezomib + doxorubicin and dexamethason followed by tandem HDT followed by bortezomib or thalidomide maintenance. Cohort 2 received doxorubicin or cyclophosphamide + bortezomib and dexamethason as induction followed by 1- 2 HDT and consolidation and maintenance with lenalidomide. Results: In cohort 1 38 (10%) had RI and del 17p was found in 12/33 (36.4%) evaluable patients compared to 24/302 (7.9%) patients without RI (p<0.001). t(4;14) was present in 11/33 (33.3%) patients with RI and 38/304 (12.5%) without RI (p=0.005). Gain of 1q21 (> 2 copies) was present in 14/33 (42.4%) patients with RI and 92/298 (30.9%) without RI (n.s.). In cohort 2 68/601 (11.3%) had RI and 7/63 (11.1%) had del17p compared to 56/495 (11.3%) patients without RI (n.s.) while 29/63 (46%) patients with RI had t(4;14) versus 265/495 (53.5%) without RI (n.s.). Gain1q21 (>2 copies) was found in 36/63 (57.1%) with RI versus 209/495 (42.2%) without RI (p=0.025). In cohort 1 the response rate with at least VGPR after induction was low with and without RI in the VAD arm (15 vs 7.1 %) and reduced in patients with RI in the PAD arm compared to those without RI (22.2 vs 37.9%). This trend was not found in cohort 2: Patients with RI had VGPR or better in 42.4% in the PAD and 52.9% in the VCD arm, compared to 33.5% and 33.1% without RI respectively. Del17p and t(4;14) which were more frequent in patients with RI in cohort 1 did not have a negative impact on response rates after induction. Similarly gain1q was more frequent among patients in cohort 2 with RI but did not impact on response to induction. Conclusions: We analysed the effect of RI and genetic risk factors on the response to induction therapy in two different patient cohorts from two consecutive prospective trials. High-risk genetic features where found more frequently in patients with RI, but the pattern was entirely different between cohort 1 and 2 and they did not seem to influence response rates after induction. Our results confirm that bortezomib-based induction regimens achieve high response rates in myeloma patients with RI similar to those in patients without RI, independent of the presence of genetic risk factors. Disclosures Scheid: Janssen: Honoraria; Celgene: Honoraria. Salwender:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Binding site: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Mai:Janssen: Travel support Other. Hose:Novartis: Research Funding. Weisel:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Onyx: Consultancy, Honoraria; BMS: Consultancy; Noxxon: Consultancy. Duerig:Janssen: Consultancy, Honoraria; Celgene: Honoraria. Goldschmidt:Janssen-Cilag: Honoraria, Research Funding, Speakers Bureau; Polyphor: Research Funding; Celgene: Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Chugai: Research Funding, Speakers Bureau; Onyx: Consultancy, Speakers Bureau; Millenium: Consultancy, Speakers Bureau.

Download Full-text

Characteristics of Different Splicing Factor Mutation Hotspots in Myelofibrosis

Blood ◽

10.1182/blood-2020-140145 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 37-37

Author(s):

Franco Castillo Tokumori ◽

Chetasi Talati ◽

Najla E. Al Ali ◽

David A. Sallman ◽

Seongseok Yun ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Splicing Factor ◽

World Health ◽

Severe Thrombocytopenia ◽

Leukemic Transformation ◽

Advisory Committees ◽

Splicing Mutations ◽

The Impact

CONTEXT: Splicing factor mutations (SRSF2, U2AF1, SF3B1, and ZRSR2) are present in ~50% of myelofibrosis (MF) patients. SRSF2 and U2AF1 Q157 are considered to be high-risk mutations, while the prognostic significance of ZRSR2 and SF3B1 has not been well established. As a group, splicing mutations are associated with cytopenias, the management of which is an area of unmet clinical need in MF. OBJECTIVE: To describe the clinical characteristics, treatment approaches, and outcomes in MF patients with splicing mutations. DESIGN: This is a single-institution, retrospective analysis of 133 MF patients with splicing mutations who presented to our institution between 2006 and 2019. PMF, post-ET MF, and post-PV MF were defined according to the World Health Organization and International Working Group criteria, respectively. Baseline variables were compared between patients harboring different splicing factor mutations and different mutations within the same splicing gene. Median overall survival (OS) was measured from time of diagnosis to date of death or censored at last follow up or date of transplant. Kaplan-Meier plots were created to compare LFS and OS among treatment cohorts, and differences were assessed using Log-rank tests. RESULTS: Among 133 MF patients with a splicing mutation, SRSF2 mutations were most common (n = 48), followed by U2AF1 (n = 36), SF3B1 (n = 27) and ZRSR2 mutations (n = 24). Most SRSF2 mutations occurred at P95 (90%). Thirty (83%) U2AF1 mutations occurred at Q157, with 5 (14%) at S34. Fourteen (63%) SF3B1 mutations occurred K666, with 9 (33%) at K700. Thirteen (54%) ZRSR2 mutations were in-frame insertions/deletions, 4 (17%) frameshift mutations, 3 (13%) nonsense mutations and 4 (17%) missense. All frameshift/nonsense ZRSR2 mutations occurred in males. Spliceosome mutations were mutually exclusive but for 2 cases (one had U2AF1 and SRSF2 mutations and the other had SF3B1 and ZRSR2 mutations). Baseline characteristics were similar between splicing mutations. The presence of a U2AF1 mutation correlated with lower hemoglobin (p 0.018) and U2AF1 Q157 mutations were associated with thrombocytopenia p=0.051) and higher DIPSS-plus scores (p=0.006). Severe thrombocytopenia (platelets < 50 x 109/L) was present in 20 (17%) patients and enriched in those with U2AF1 mutations (n = 9). ASXL1 mutations rarely occurred in conjunction with SF3B1 mutations (p = 0.007). Among all patients with splicing mutations, median OS was 60.6 months. Median OS was decreased in patients with SRSF2 mutations (33 vs 106 months, p=0.001) compared to those with other splicing mutations. Median OS was increased in patients with SF3B1 mutations compared to patients with other splicing mutations (181 mo vs 42 mo, p = 0.002). Median OS for patients with U2AF1 and ZRSR2 mutations was 44 and 106 months, respectively. Among patients with U2AF1 mutations, the presence of severe thrombocytopenia was associated with inferior survival (13.9 mo vs not reached, p = 0.045). The presence of an SRSF2 mutation was associated with an increased risk of leukemic transformation (24% vs 3%, p = 0.002). Among patients with SRSF2 mutations, median OS in those with documented leukemic transformation was 32.9 mo compared to 48.7 mo in those without (p = 0.17). CONCLUSIONS: Splicing mutations in MF have unique phenotypic and prognostic correlations. While SRSF2 mutations appear detrimental, SF3B1 mutations correlate with favorable outcomes. While U2AF1 and SRSF2 mutations are considered high-risk in MF, the impact appears driven by cytopenias in the former and leukemic transformation in the latter. This may hold relevance when considering therapeutic approaches in these patients. Disclosures Talati: AbbVie: Honoraria; Jazz: Speakers Bureau; Astellas: Speakers Bureau; BMS: Honoraria; Pfizer: Honoraria. Sallman:Celgene, Jazz Pharma: Research Funding; Agios, Bristol Myers Squibb, Celyad Oncology, Incyte, Intellia Therapeutics, Kite Pharma, Novartis, Syndax: Consultancy. Sweet:Takeda: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Stemline: Honoraria; Agios: Membership on an entity's Board of Directors or advisory committees; Astellas: Honoraria. Padron:Incyte: Research Funding; Kura: Research Funding; BMS: Research Funding; Novartis: Honoraria. Lancet:Abbvie: Consultancy; Agios Pharmaceuticals: Consultancy, Honoraria; Astellas Pharma: Consultancy; Celgene: Consultancy, Research Funding; Daiichi Sankyo: Consultancy; ElevateBio Management: Consultancy; Jazz Pharmaceuticals: Consultancy; Pfizer: Consultancy. Komrokji:Geron: Honoraria; Novartis: Honoraria; Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau. Kuykendall:Blueprint Medicines: Research Funding; BMS: Research Funding; Incyte: Research Funding; Novartis: Research Funding.

Download Full-text

Negative Prognostic Relevance of a Specific 3-Gene Cluster in Myelodysplastic Syndromes during Azacitidine and Lenalidomide Therapy

Blood ◽

10.1182/blood-2018-99-112062 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4347-4347

Author(s):

Matilde Y Follo ◽

Andrea Pellagatti ◽

Richard N Armstrong ◽

Stefano Ratti ◽

Sara Mongiorgi ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Gene Cluster ◽

Research Funding ◽

Positive Response ◽

Point Mutations ◽

Gene Mutations ◽

Ion Torrent ◽

Advisory Committees ◽

Molecular Analyses

Abstract Background and Rationale. Azacitidine (AZA) is a standard first-line therapy in high-risk MDS. Also its combination with Lenalidomide (LEN) has been tested, but its molecular effect is still under investigation. Here we analyzed the effect of AZA+LEN therapy on gene mutations and microRNA expression in MDS patients. Patients and Methods. This study included 44 high-risk MDS patients treated with AZA (75 mg/m2/day, days 1-5, sc) and LEN (10 mg/day, days 1-21, orally) every 4 weeks. Patients showing complete remission (CR), partial remission (PR) or any hematologic improvement were considered as responders, while patients showing stable disease or disease progression were considered as non responders. Molecular analyses were performed at baseline and during the therapy. Gene mutations were studied by an Illumina Cancer Myeloid Panel and an Ion Torrent specific panel, whereas microRNAs expression was assessed using an Affymetrix miRNA 4.0 array. Results. 34/44 patients were considered evaluable for response, with an overall response rate of 76.25% (26/34 cases). 13 patients showed a positive response within the 4th cycle (T4) and maintained it at T8; 9 patients showed a positive response within T4 and lost response at T8; 4 patients responded after T4 and maintained the response at T8; 8 patients never responded. Molecular analyses were performed on serial samples (baseline, T4 and T8) available for 30 patients. Results from the Illumina analysis on cancer myeloid genes showed that 3/30 cases had no mutations at all, all other cases showed mutations both at baseline and during the therapy. The most frequently mutated genes were ASXL1 (14 cases = 47%), TET2 (11 cases = 37%), RUNX1 (8 cases = 27%) and SRSF2 (5 cases = 17%). All samples with a decreasing variant allele frequency (VAF) had a favourable response at T8 (CR, marrow CR or PR), while none of the non responders showed a decreasing VAF. Ion Torrent analysis of 24 inositide-specific genes showed that all patients had mutations both at baseline and during the therapy. Interestingly, all patients responding at T4 and losing response at T8, as well as cases that did not respond, acquired the same 3 point mutations at T8, affecting respectively PIK3CD (D133E), AKT3 (D280G) and PLCG2 (Q548R) genes. Patients responding at T4 and losing response at T8 showed these mutations even at T4. Kaplan-Meier analyses revealed that the presence of these mutations was significantly associated with a decreased duration of therapy (39.5 vs 8.5 months; p<0.05) and duration of response (36 vs 6 months; p<0.05). As for microRNA profiling, paired analysis between responders and non responders showed specific clusters of up- or down-regulated microRNAs. Interestingly, unpaired analysis on patients responding at T4 and losing response at T8 showed 18 up- and 11 down-regulated microRNAs, like miR-3613-3p and miR-6757-5p, whose predicted targets are our 3 genes among the others. Also in patients never responding to the therapy there was a specific cluster of 3 up- and 12 down-regulated microRNAs and, interestingly, 7 of these microRNAs, like miR-4786-5p or miR-6853-3p, targeting our 3-gene cluster among the others, were altered also in patients losing response. Conclusions. Our results show that the presence of a common cluster of point mutations affecting 3 inositide-specific genes (PI3KCD, AKT3, PLCG2, all regulating cell proliferation), is significantly associated with loss of response to AZA+LEN therapy. Moreover, also a cluster of 7 microRNAs, targeting our 3 genes among the others, is associated with unfavourable outcome. Further studies are warranted to confirm these data, to further analyze the role of this 3-gene cluster and to identify the specific targets for the dysregulated microRNAs identified. Disclosures Gobbi: Janssen: Consultancy; Amgen: Consultancy; Ariad: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfister: Membership on an entity's Board of Directors or advisory committees. Cavo:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Finelli:Janssen: Consultancy, Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Novartis: Consultancy, Speakers Bureau.

Download Full-text

PET-CT Defined Focal Lesions at Baseline and Day 7 Predict Outcome in GEP 70 Defined High Risk Multiple Myeloma Patients

Blood ◽

10.1182/blood.v124.21.3407.3407 ◽

2014 ◽

Vol 124 (21) ◽

pp. 3407-3407

Author(s):

Yogesh Jethava ◽

Rachel Hunter-Merrill ◽

Gareth J Morgan ◽

Rashid Z Khan ◽

Aasiya Matin ◽

...

Keyword(s):

Multiple Myeloma ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Cox Regression ◽

Focal Lesions ◽

Advisory Committees ◽

Early Therapy ◽

Time Points ◽

The Impact

Abstract Introduction: Fluoro-deoxy-glucose (FDG) positron emission tomography (PET) scanning is an important state-of-the-art imaging tool in the initial workup of patients with multiple myeloma (MM). We evaluate the impact of PET focal lesions (FL) at baseline (BL), 7 days after starting induction therapy (D7) and prior to first autologous transplant (pre-ACST) in gene expression profiling (GEP 70) defined high risk (HR) multiple myeloma (MM) patients. Patients and methods: 48 GEP 70 HR MM patients were treated uniformly on IRB approved protocol consisting of tandem transplants with dose reduced Mel-80-VRD-PACE (melphalan, velcade, revlimid, dexamethasone, cisplatin, adreamycin, cyclophosphamide and etoposide) and interspersed Mel-20-VTD-PACE (melphalan, velcade, thalidomide, dexamethasone, cisplatin, adreamycin, cyclophosphamide and etoposide) consolidation and VRD (velcade, revlimid, dexamethasone) maintenance. PET examinations were performed at (BL), D7 and pre-ASCT, enumerating FDG-avid FL, their SUV max and extra-medullary disease (EMD).Of the 48 GEP 70 HR patients, 39 had BL, 28 had D7 and 42 had pre-ASCT PET examinations. 20 patients had examinations at all 3 time points. At BL, there were 24 (50%) patients with B2M >5.5mg/L and 26 (54%) with albumin <3.5g/dL. Metaphase cytogenetic abnormalities were documented in 36 (75%) patients, including deletion 13/hypodiploidy in 30 (63%). EMD was present in 3 (8%) patients, 28 (58%) had diffuse SUV <= 2 (median 2.4; range 1.4 to 9.5) and 14 (29%) had FL max SUV >3.9 (median 4.6; range 1.6 to 14.4). Results: From BL, the 3-yr PFS estimate was 46% for the group with no FL and 29% for those with FL (Figure 1a). The corresponding PFS data for the D7 was 53% for no FL at D7 as opposed to 11% for those with FL (Figure 1b), and for pre-ASCT it was 34% for no FL and 33% for those with FL (Figure 1c). Joint consideration of BL and D7 landmark revealed 3-yr PFS of 54% for those with no FL at BL, compared to 40% for those with resolution of BL FL by D7 and 18% for those whose FL did not resolve (log rank p-value=0.09), confirming the significance of FL resolution. Cox regression of PFS revealed that those with FL at BL had 2.34 times the risk of progression or death compared to those with no FL at BL (p=0.075), while those with FL at D7 had 3.27 times the risk (p=0.033). Diffuse SUV and SUV max had no impact on PFS at the three time points. Figure 1 Figure 1. Figure 2 Figure 2. Figure 3 Figure 3. Fig 1a- PFS from baseline PET Fig 1b- PFS from D7 PET Fig 1c- PFS from pre-ASCT PET Conclusion: The prognosis of GEP 70 HR MM is dominantly affected by BL indicators of MM metabolism, as revealed by FDG uptake in FL. Our analysis in HR GEP70 MM patients confirms that early suppression of FL by D7 was key to improved PFS. MM patients who had absence of FL resolution from BL to D7 had poorer PFS and are candidates for early therapy change. Disclosures Morgan: Celgene Corp: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Myeloma UK: Membership on an entity's Board of Directors or advisory committees; International Myeloma Foundation: Membership on an entity's Board of Directors or advisory committees; The Binding Site: Membership on an entity's Board of Directors or advisory committees; MMRF: Membership on an entity's Board of Directors or advisory committees. Zangari:Norvartis: Membership on an entity's Board of Directors or advisory committees; Onyx: Research Funding; Millennium: Research Funding. van Rhee:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees.

Download Full-text

The Impact of Combination Chemotherapy and Tandem Stem Cell Transplant on Clonal Substructure and Mutational Pattern at Relapse of MM

Blood ◽

10.1182/blood.v126.23.372.372 ◽

2015 ◽

Vol 126 (23) ◽

pp. 372-372 ◽

Cited By ~ 1

Author(s):

Christoph Heuck ◽

Niels Weinhold ◽

Erich Allen Peterson ◽

Michael Bauer ◽

Caleb K. Stein ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Clonal Evolution ◽

Advisory Board ◽

Proliferation Index ◽

University Of Arkansas ◽

Medical Sciences ◽

Advisory Committees ◽

The Impact

Abstract Introduction: Next generation sequencing of over 800 newly diagnosed multiple myeloma (NDMM) cases has established the mutational landscape and key cancer driver pathways. The mutational basis of relapse has not been systematically studied. Two previous studies (Keats et al.; Bolli et al.) identified 4 patterns of clonal evolution. Neither study included uniformly treated patients and looked at the impact of therapy on clonal structure at relapse. Understanding the mutational patterns underlying relapse and how they relate to specific therapies is crucial in order to improve MM outcomes, especially for high-risk (HR) MM. In this study we compare the clonal structure at presentation (PRES) and at relapse (REL), after exposure to Total Therapy (TT). Materials and Methods: We studied 33 pairs of tumor samples collected at PRES and REL. 9 patients were treated on TT2, 13 on TT3, 10 on TT4 and 1 on TT5-like regimen. Eleven patients had HR disease at PRES. DNA was extracted from CD138+ selected cells from random bone marrow aspirates. Germline controls were obtained from leukapheresis products. Whole exome sequencing libraries were prepared using the Agilent qXT kit and the Agilent SureSelect Clinical Research Exome kit with additional baits covering the Ig and MYC loci. All samples were sequenced on an Illumina HiSeq2500 to a median depth of 120x. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were called using MuTect. Translocations were identified using MANTA. Copy number variations were inferred using TITAN. Gene expression profiles (GEP), generated using the Affymetrix U133plus2 microarray, were available for all tumor samples. Nonnegative matrix factorization (NMF) was used to define mutation signatures. Results: The median time to progression was 30 months with a median follow up of 9.5 years. 22 cases achieved a complete remission (CR) or near CR. There were 11 cases of HR at PRES. Of the 22 cases with low risk (LR) MM, 7 relapsed with HR disease. There were on average 478 SNVs per sample at PRES and 422 at REL. All but 2 cases had evidence of new mutations at REL. There were no consistent patterns or number of mutation associated with REL or GEP-defined risk. Patients of the MF molecular subgroup had more mutations compared to other molecular subgroups (657 vs. 379) and were enriched for mutations with an APOBEC signature. We did not detect any mutation signature consistent with chemotherapy-induced alterations, providing evidence that TT itself does not cause additional mutations. Primary recurrent IgH translocations called by MANTA were confirmed by GEP data. A number of new translocations were identified , several only at REL. In particular we demonstrate a case with a newly acquired MYC translocation at relapse, indicating that it contributed to progression. We identified 5 patterns of clonal evolution (Figure 1): A) genetically distinct relapse in 3 patients, B) linear evolution in 8 patients, C) clonal selection in 9 patients, D) branching evolution in 11 patients, and E) stable clone(s) in 2 patients. Patterns A (distinct) and B (linear) were associated with low risk and longer survival, whereas patterns D (branching) and E (stable) were associated with high risk and shorter time to relapse and overall survival (Table 1). Conclusion: This is the first study to systematically analyze the pattern of clonal evolution using NGS in patients treated with combination chemotherapy and tandem ASCT. We identified 5 patterns of evolution, which correlate with survival. We identified 3 cases with a loss of the original clone and emergence of a new clone, suggesting high effectiveness of Total Therapy for those patients. The persistence of major clones despite multi agent chemotherapy in most other cases supports a concept of a tumor-initiating cell population that persist in a protective niche, for which new therapies are needed. Table 1. Pattern of Evolution GEP70 Pres.(high risk: ≥0.66) Proliferation Index Pres. GEP70 Rel.(high risk: ≥0.66) Proliferation Index Rel Mean OS Mean TTR A: distinct (n=3) -0.690 -3.34 -0.015 2.04 8.18 5.00 B: linear (n=8) -0.171 -0.34 0.618 9.22 5.70 4.05 C: selection (n=9) 0.366 3.20 0.569 6.97 3.95 2.64 D: branching (n=11) 0.710 5.17 1.173 11.15 3.84 2.21 E: stable (n=2) 1.532 7.42 1.124 2.54 0.96 0.35 Pres.: Presentation; Rel.: Relapse; OS: Overall Survival; TTR: Time to Relapse Figure 1. Patterns of Relapse Figure 1. Patterns of Relapse Disclosures Heuck: Foundation Medicine: Honoraria; Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Chavan:University of Arkansas for Medical Sciences: Employment. Stephens:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Onyx: Research Funding; Novartis: Research Funding. Matin:University of Arkansas for Medical Sciences: Employment. Petty:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Millenium: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Celgene: Consultancy. Epstein:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Weismann Institute: Honoraria; MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Download Full-text

The Impact of Letermovir (LTV) Prophylaxis on Early Cytomegalovirus Infection (CMVi) and Outcomes in the Adult Allogeneic Hematopoietic Cell Transplantation (alloHCT) Recipients with High-Risk Donor Type

Blood ◽

10.1182/blood-2021-153784 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1776-1776

Author(s):

Sanjeet S Dadwal ◽

Dongyun Yang ◽

Guido Marcucci ◽

Sally Mokhtari ◽

Bernard Tegtmeier ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Acute Gvhd ◽

Chronic Gvhd ◽

Standard Of Care ◽

Advisory Committees ◽

Donor Type ◽

The Impact ◽

Grade Iii

Abstract CMV recipient seropositivity (R+) and CMVi are independent risk factors for increased mortality after alloHCT. Preemptive therapy (PET) was standard of care until LTV approval by the FDA in November 2017 for CMVi prevention in CMV R+ alloHCT patients (pts). In a registration trial, LTV led to a significant reduction in clinically significant CMVi (CS-CMVi) defined as CMVi requiring PET in both high-risk (HR) or low-risk (LR) recipients. In the HR-group, defined as mismatched related / unrelated donor with at least one mismatch in one of the four HLA-gene loci of HLA-A, -B, -C or -DRB1, haploidentical donor, umbilical cord source or grade ≥2 acute graft-versus-host disease (aGVHD) at randomization, the impact of LTV on CS-CMVi was more robust. Small studies have confirmed the positive impact of LTV on CS-CMVi. Here, we compared the natural history of CMVi and CS-CMVi between the pre-LTV and LTV era in the first 100 days after HR-alloHCT. We also explored the impact on non-relapse mortality (NRM), overall survival (OS), disease free survival (DFS), and incidence of aGVHD between the two eras. In this IRB approved retrospective study, we identified 450 consecutive HR-alloHCT pts who underwent their first HCT from 1/1/2016 to 12/31/2020 at our center. Pre-LTV era was from 1/1/2016 to 2/28/2018 and LTV era was from 3/1/2018 onwards when prophylaxis became standard of care (SOC) for all R+ alloHCT at our institution. In the HR-alloHCT, the uptake of the new SOC was consistent in all HR-R+ pts beginning LTV prophylaxis on day +7 post-HCT. We defined R+ HR-alloHCT pts at high-risk for CMVi or CS-CMVi as described above except for aGVHD (not recorded at time of institution of LTV). CMVi was defined as first time viral load (VL) of >500 genomic copies/ml (gc/ml). CS-CMVi was defined as a VL >500 gc/ml (910 IU/ml) on two consecutive tests done atleast 48 hours apart, that triggered PET (ganciclovir, valganciclovir, foscarnet, cidofovir), or had identification of CMV end organ disease . The incidence of CMVi and CS-CMVi in R+ allo-HCT was compared by LTV era using Gray test. Kaplan-Meier curves and log-rank tests were used for OS and DFS by LTV era. NRM, relapse, acute and chronic GVHD were compared using cumulative incidence curves and Gray test. All tests were 2-sided at 0.05 level. Of the 450 HR-alloHCT pts, 146 were R+ in pre-LTV vs. 246 R+ in LTV era. R+ patient, their eligible underlying disease, and HCT characteristics are shown in Table 1. There was a significant reduction in both CMVi and CS-CMVi in LTV era vs pre-LTV era (24.1% vs 45.2%, and 22.3% vs 44.5% respectively; p <0.001 for both outcomes) in the first 100 days. Compared to pre LTV era, LTV era was associated with significantly reduced CS-CMVi among R+ pts (HR=0.39, 95%CI: 0.26-0.58, p <0.001) in the multivariable Fine and Gray model adjusted for primary diagnosis, donor type and acute GVHD. CMVi was also reduced in the multivariable model (HR=0.41 and 95%CI: 0.28-0.61, p<0.001). Although there were no significant differences in OS, DFS, NRM, relapse, and chronic GVHD between the two eras at 6, 12, and 18 months post-HCT in R+ pts, a trend towards improved OS and DFS in LTV era was noted (p=0.06 and p=0.07) in this patient population. There was a significantly lower rate of grade III-IV acute GVHD in the LTV era (9.2% vs 17.8% at day 100, p=0.012 with HR = 0.49). No case of CMV disease was identified in the first 100 days. LTV has substantially reduced CS-CMVi in the first 100 days post-HCT in HR-R+ pts and resultant burden from PET. We identified a significant reduction in grade III - IV aGVHD in LTV era suggesting that with reduced CMVi, LTV may have a salutary impact on development of aGVHD; this is in agreement with studies showing bidirectional relationship between CMVi and onset of aGVHD. We did not observe a significant difference in OS, DFS, NRM amongst the two eras but there was trend towards higher OS and DFS in LTV era that requires further assessment in a larger multicenter cohort. Lastly, significant burden persists from CS-CMVi in this patient population during the first 100 days of alloHCT that underscores the need of efforts to identify other novel methods to mitigate it. One of the limitations in the LTV era is identifying the clinical scenarios surrounding the CMVi and CS-CMVi that may relate to compliance, absorption from gastrointestinal tract, and affordability or coverage of LTV after discharge from hospital. Figure 1 Figure 1. Disclosures Dadwal: Astellas: Speakers Bureau; Aseptiscope: Consultancy; AlloVir: Research Funding; Shire/Takeda: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Other: Investigator; Karius: Other: Investigator. Marcucci: Novartis: Other: Speaker and advisory scientific board meetings; Agios: Other: Speaker and advisory scientific board meetings; Abbvie: Other: Speaker and advisory scientific board meetings. Taplitz: Merck: Membership on an entity's Board of Directors or advisory committees. 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. Forman: Allogene: Consultancy; 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. Al Malki: Neximmune: Consultancy; Jazz Pharmaceuticals, Inc.: Consultancy; CareDx: Consultancy; Rigel Pharma: Consultancy; Hansa Biopharma: Consultancy.

Download Full-text