Greipp, Patricia T.

AbstractT‐lymphoblastic leukemia/lymphoma (T‐ALL/LBL) accounts for approximately 15% of pediatric and 25% of adult ALL. While the underlying frequency of KMT2A (MLL) gene rearrangements has been identified in approximately 4‐8% of T‐ALL/LBL cases, a paucity of literature is available to characterize further the KMT2A rearrangements in pediatric/young adult T‐ALL/LBL. A 10‐year retrospective review was performed to identify KMT2A rearrangements in specimens sent for T‐ALL/LBL fluorescence in situ hybridization studies in patients under the age of 30 years. Of 806 T‐ALL/LBL FISH studies performed on unique individuals, 27 (3.3%) harbored KMT2A rearrangements. Nineteen patients were male and eight were female (M:F ratio, 2.4:1) with ages ranging from 1 to 20 years (mean 12, median 12). Of the 27 cases, nine (33%) had KMT2A/MLLT1 fusions, eight (30%) had KMT2A/AFDN fusions, two (7%) had KMT2A/ELL fusions, and one (4%) had a KMT2A/MLLT10 fusion. In addition, five (19%) had KMT2A rearrangements with unidentified gene fusion partners and two (7%) had 3’KMT2A deletions. Our results indicate that MLLT1 and AFDN account for the majority (63%) of KMT2A gene partners in pediatric/young adult T‐ALL/LBL, while no KMT2A/AFF1 or KMT2A/MLLT3 fusions were observed despite their common identification in B‐ALL and acute myeloid leukemia, respectively. In addition to diagnostic and prognostic value, detecting specific KMT2A fusions may also be of clinical importance in the era of targeted therapies.

e18560 Background: Myelodysplastic syndromes (MDS) are rare hematological neoplasms typically seen in the elderly. Young MDS (yMDS) patients ( < 50 years old) have been reported to comprise between 3-6% in the Surveillance, Epidemiology and End Results (Ma X et al, Cancer 2007; Rollison R et al, Blood 2008) with a better overall survival (OS). Methods: 1012 MDS patients from 1993 to 2015 were found after IRB approval was obtained. All cases had their bone marrow slides reviewed at our institution. yMDS Patients were included as cohort 1, while the rest as cohort 2. Survival estimates were calculated using Kaplan-Meier curves and univariate and multivariate analyses was based on log-rank testing using JMP software version 10. Results: We found 68 (7%) yMDS patients with a median age of 42 years (range, 18-49). Female gender was more common (43% vs 31%, p = 0.05) while platelets were lower in yMDS (61 vs 102, p < 0.0001). Therapy related MDS (t-MDS) was more frequent (33% vs 17%, p = 0.005), as was transformation to acute myeloid leukemia (AML) in yMDS (28 % vs 11%, p = 0.0004). Allogenic hematopoietic cell transplantation (HCT) was more frequent in yMDS (42% vs 4%, p < 0.0001). Survival outcome: Median OS was longer for cohort 1 vs cohort 2 but did not reach statistical significance (43 vs 21 months, p = 0.1). Median progression free survival (PFS) was shorter for cohort 1 vs cohort 2 but also did not reach statistical significance (8 vs 12 months, p = 0.3). Median OS for cohort 1 based on R-IPSS was 44, 105, 40, 18, and 12 months for very low, low, intermediate, high and very high risk groups, respectively (p = 0.09). Median OS was shorter in t-MDS vs de novo MDS in yMDS (13 vs 47 months, p = 0.04). yMDS patients who transformed to AML had worse median OS (18 vs 93 months, p = 0.001). On multivariate analysis neither t-MDS nor R-IPSS had a statistically significant impact on OS. Conclusions: MDS is rarely diagnosed under the age of 50 with IPSS-R being less powerful in detecting mOS. Among yMDS patients, there was a higher proportion of t-MDS compared to older patients with subsequent higher rates of AML transformation and higher rates of allogeneic HCT. In our study, we did not find an improved OS for yMDS patients compared to older patients.

Abstract Introduction: Hyperdiploidy on FISH portends a good prognosis in myeloma. We compared hyperdiploidy determined by MFC to that by conventional FISH. Methods: We studied 1711 patients with plasma cell disorders who had simultaneous FISH and DNA index testing. Monotypic plasma cells in bone marrow are identified by MFC with antibodies to CD19, CD38, CD45, CD138, kappa and lambda; followed by staining by DAPI. DNA index is determined by dividing the measured DNA content of the G0/G1 abnormal plasma cells by the DNA content of the normal G0/G1 plasma cells present. Plasma cells with DNA content index of &lt;0.95 are hypodiploid and G0/G1 DNA content index of &gt;1.05 are considered hyperdiploid. Results: Distribution DNA index and FISH results are described in Table 1. Sensitivity and specificity of DNA index by hyperdiploidy was 86% and 83%. Cohen's Kappa coefficient for concordance was 0.69. Sensitivity increased to 94% for those with 2 or more trisomies and 97% for 3 or more trisomies. Of the 104 patients with trisomy and non-hyperdiploid DNA index, 62% patients had monosomy (mono) or deletion (del) 13q. Overall, DNA index was lower in patients with mono 13/del 13q (1.01; 0.97-1.11) compared to those without (1.07; 1.0-1.19), p&lt;0.001. After excluding patients with mono 13/del 13q, sensitivity and specificity of hyperdiploidy by DNA index were 92% and 82%, kappa = 0.73. Hyperdiploidy was seen in 55% of 272 patients with newly diagnosed myeloma. Sensitivity and specificity were 88% and 93%, kappa = 0.78. After median follow-up of 2.3 yrs, those with hyperdiploid DNA index had better progression free survival at 2,3 and 5 years, 62%, 45% and 21% compared to 50%, 33% and 13% in non-hyperdiploid group, p=0.05. Median overall survival (OS) was not reached; estimated 2, 3 and 5 year OS was 83%, 76% and 63% vs. 76%, 64% and 44%, respectively; p=0.08. Conclusions: DNA index by MFC is a rapid method to determine hyperdiploidy, with potential for replacing trisomy testing by FISH, especially when coupled with monosomy FISH probes. Hyperdiploid N=768 n/N (%)Diploid N=762 n/N (%)Hypodiploid N=78 n/N (%)P1P2Any trisomy 619/765 (81)96/758(13)8/76 (11)&lt;0.001&lt;0.001One chromosome42587733191429-111362Others12204Two chromosomes8525-Three or more chromosomes492131Any translocation124/744 (17)566/748 (76)53/74 (72)&lt;0.001&lt;0.001t(4;14)106313t(11;14)2240127t(14;16)5325t(14;20)38-t(6;14)8104Unknown partner76524Trisomy + Translocation95/743 (13)60/744 (8)6/74 (8)0.0090.002Monosomy 13/17 or deletion 13q/17p252/759 (33)295/744 (40)54/74 (73)&lt;0.0010.0001Monosomy 13/Deletion 13q208/717 (29)282/718 (39)20/70 (29)Monosomy 17/Deletion 17p70/749 (9)50/735 (7)20/72 (28)P1= three groups; P2= hyperdiploid vs. non-hyperdiploid Citation Format: Surbhi Sidana, Nidhi Tandon, Dragan Jevremovic, Rhett P. Ketterling, Angela Dispenzieri, Morie A. Gertz, Francis K. Buadi, Martha Q. Lacy, William Morice, Curtis A. Hanson, Michael Timm, Patricia Greipp, Linda B. Baughn, David Dingli, Suzanne R. Hayman, Wilson I. Gonsalves, Prashant Kapoor, Robert A. Kyle, Nelson Leung, Ronald S. Go, John A. Lust, S.Vincent Rajkumar, Shaji K. Kumar. Hyperdiploidy in plasma cell disorders using multi-parametric flow cytometry (MFC) vs. FISH [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 655.