The Biological Inferences from the Ranking of SF3B1 Mutations in the Clonal Hierarchy of Myeloid Neoplasia

Chromosomal abnormalities can be founder lesions (e.g., t (8; 21), inv (16), inv (3)), initiate or advance disease progression (both founder and secondary hits e.g., ASXL1, TP53, RUNX1) or can be obligatory secondary hits (FLT3, NPM1). Hence, the rank of these mutations may determine the biological properties and clinical outcomes. However, while many mechanistic studies have been undertaken without identifying the key pathogenetic factors resulting from SF3B1 mutations, important biological clues can be derived from the consequences of SF3B1 alterations in the context of the clonal architecture of myeloid neoplasia (MN). SF3B1 mutant patients often have a homogeneous phenotype with isolated erythroid dysplasia, ring sideroblasts (RS) and favorable prognoses. Studies in primary MDS cells have suggested that SF3B1 mutations are initiating lesions and provide a marked clonal advantage to MDS-RS cells by propagating from rare lympho-myeloid hematopoietic stem cells. However, there is significant diversity of clinical phenotypes and outcomes including the observation that the disappearance of RS can be observed during the disease course of clonal MN and might suggest cellular shifts due to acquisition of additional hits. In such scenarios, the cell's fate in the context of SF3B1 mutations is pre-defined by the predominance of expanded hits. We took advantage of our detailed database of molecularly and clinical annotated cases with MN to study the SF3B1 mutatome and describe whether the clonal nature (ancestral vs. secondary) might change the clinical and phenotypic trajectories of MDS cells and whether the concatenation of mutations decreases the competitiveness of SF3B1 clones, leading to the dominance of other driver genes and subsequently to clonal evolution. The clonal hierarchy was resolved using our in-house designed VAF-based bioanalytic method and confirmed by the PyClone pipeline, which showed a high level of concordance. We first assigned clonal hierarchy to SF3B1 mutations by using VAFs (adjusted for copy number and zygosity) and classifying the mutations into dominant (if a cutoff of at least 5% difference between VAFs existed), secondary (any subsequent sub-clonal hit) and co-dominant hits (if the difference of VAFs between two mutations was <5%). In total, we identified 140 dominant (SF3B1DOM), 121 secondary (SF3B1SEC) and 74 co-dominant SF3B1 mutations. For the purpose of this study, we set aside co-dominant SF3B1 mutations. Focusing on SF3B1DOM and SF3B1SEC, SF3B1DOM were often associated with a normocellular bone marrow compared to SF3B1SEC (n=42 vs. 26; P=0.02) and were less likely enriched in multi-dysplastic myeloid cells (29% vs. 53%; P=0.01). As such, SF3B1DOM tended to be more frequently detected in lower-risk MDS (P=0.05) in the subtypes of MDS-RS and MLD-RS (RS≥15%: 67% vs. 41%; P=0.01) compared to other disease subtypes. Twenty-three percent of patients with SF3B1SEC had secondary acute myeloid leukemia (sAML) (P=0.03). SF3B1SEC patients tended to have a lower median platelet count than patients with SF3B1DOM (97 vs. 130 x 109/L; P=0.05). SF3B1SEC was also more associated with bi-cytopenia compared to SF3B1DOM (52% vs. 36%; P=0.01). No specific association was found between SF3B1 clonal nature and cytogenetic abnormalities, suggesting that additional mutations might be the main contributors in the evolution of MDS to AML. Of note, patients with SF3B1SEC had half OS compared to patients with SF3B1DOM (SF3B1SECvs. SF3B1DOM: 15.9 mo. vs. 39.7 mo., P= 0.0001), suggesting that in cases evolving to AML, expanding hits might have dramatically skewed the favorable nature of SF3B1 mutations. Indeed, mutations preceding SF3B1 mainly affected lineage-restricted genes associated with repression of erythroid programs (RUNX1, 23%), terminal monocytic differentiation (TET2, 9%), transcriptional corepressors (BCOR/L1, 8%) and development of leukemia (DNMT3A, 8%). In conclusion, our study of the clonal architecture of SF3B1 mutations highlights that clonal progression of cases with MN harboring SF3B1 mutations might be inferred by the rank of additional genetic lesions cooperating with SF3B1. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Advani:Abbvie: Research Funding; Macrogenics: Research Funding; Pfizer: Honoraria, Research Funding; Amgen: Research Funding; Glycomimetics: Consultancy, Research Funding; Kite Pharmaceuticals: Consultancy. Nazha:Tolero, Karyopharma: Honoraria; Novartis: Speakers Bureau; MEI: Other: Data monitoring Committee; Daiichi Sankyo: Consultancy; Jazz Pharmacutical: Research Funding; Incyte: Speakers Bureau; Abbvie: Consultancy. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Sekeres:Syros: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Maciejewski:Alexion: Consultancy; Novartis: Consultancy.

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Transition of Chronic Myeloid Leukemia to Chronic Myelomonocytic Leukemia As a Tool to Observe Development of Chronic Myelomonocytic Leukemia

Blood ◽

10.1182/blood.v126.23.5223.5223 ◽

2015 ◽

Vol 126 (23) ◽

pp. 5223-5223

Author(s):

Jamshid S Khorashad ◽

Srinivas K Tantravahi ◽

Dongqing Yan ◽

Anna M. Eiring ◽

Hannah M. Redwine ◽

...

Keyword(s):

Board Of Directors ◽

Myeloid Leukemia ◽

Research Funding ◽

Clonal Evolution ◽

Chronic Myelomonocytic Leukemia ◽

Imatinib Treatment ◽

Advisory Committees ◽

Clonal Architecture ◽

Myelomonocytic Leukemia

Abstract Introduction. Development of abnormal Philadelphia (Ph) negative clones following treatment of chronic myeloid leukemia (CML) patients with imatinib has been observed in 3 to 9% of patients. Here we report on a 77 year old male diagnosed with CML that responded to imatinib treatment and subsequently developed chronic myelomonocytic leukemia (CMML). He achieved major cytogenetic response within 3 months but this response coincided with the emergence of monocytosis diagnosed as CMML. Five months after starting imatinib treatment the patient succumbed to CMML. We analyzed five sequential samples to determine whether a chronological order of mutations defined the emergence of CMML and to characterize the clonal evolution of the CMML population. Materials and Method. Five samples (diagnostic and four follow up samples) were available for analysis. CMML mutations were identified by whole exome sequencing (WES) in CD14+ cells following the onset of CMML, using CD3+ cells as constitutional control. Mutations were validated by Sequenom MassARRAY and Sanger sequencing and quantified by pyrosequencing. Deep WES was performed on the diagnostic sample to determine whether the mutations were present at CML diagnosis. To determine the clonal architecture of the emerging CMML, colony formation assays were performed on the diagnostic and the next two follow-up samples (Samples 1-3). More than 100 colonies per sample were plucked for DNA and RNA isolation. The DNA from these colonies were tested for the presence of the confirmed CMML mutations and the RNA was used for detection of BCR-ABL1 transcript using a Taqman real time assay. Results. Four mutations were identified by Sequenom and WES throughout the patient's time course [KRASG12R, MSLNP462H, NTRK3V443I and EZH2I669M ]. Sequenom did not identify these at diagnosis while deep WES did. Clones derived from colony formation assay revealed three distinct clones present in all samples analysed. Clone 1 had only KRASG12R, clone 2 had KRASG12R, MSLNP462H, and NTRK3V443I, and clone 3 had all four mutations. All clones containing any of these four mutations were BCR/ABL1 negative. Analysis of clonal architecture indicated that KRASG12R was acquired first and EZH2I669M last, while MSLNP462H and NTRK3V443I were acquired in between. These CMML clones increased proportionately as clinical CML metamorphosed into clinical CMML after initiation of imatinib therapy. Consistent with the colony data, pyrosequencing revealed that the ratio between the mutants remained largely stable throughout the follow up period. Conclusion. This case illustrates how targeted therapy impacts clonal competition in a heterogeneous MPN. While the CML clone was dominant in the absence of imatinib, it was quickly outcompeted by the CMML clones upon initiation of imatinib therapy. The clonal architecture analysis, in combination with in vivo kinetics data, suggest that the KRASG12R mutation alone was able to produce a CMML phenotype as clones with just KRASG12R remained at a relatively stable ratio during follow up. Unexpectedly, acquisition of additional mutations, including EZH2I669M as the last mutational event identified in this patient, did not increase clonal competitiveness, at least in the peripheral blood. These data show that clonal evolution may not invariably increase clonal fitness, suggesting that factors other than Darwinian pressures contribute to clonal diversity in myeloproliferative neoplasms. Disclosures Deininger: Gilead: Research Funding; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees.

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Myeloproliferative Neoplasm (MPN) Blastic Transformation Occurs at the Level of Hematopoietic Stem Cells

Blood ◽

10.1182/blood-2018-99-117348 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 101-101

Author(s):

Xiaoli Wang ◽

Cing Siang Hu ◽

Joseph Tripodi ◽

Vesna Najfeld ◽

Bruce Petersen ◽

...

Keyword(s):

T Cells ◽

Stem Cell ◽

Board Of Directors ◽

Research Funding ◽

Chromosomal Abnormalities ◽

Myeloproliferative Neoplasm ◽

Leukemic Cells ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Nsg Mice

Abstract Myeloproliferative neoplasm-blast phase (MPN-BP) and de novo acute myeloid leukemia (AML) each have distinct mutational patterns and clinical courses. MPN-BP patients have a particularly dismal prognosis with a median survival of less than 6 months with currently available therapies. So far, the cellular hierarchy that characterizes MPN-BP and the evolution of various leukemia-initiating clones (LIC) in MPN-BP have not been well delineated. We therefore established an in vivo MPN-BP xenograft model to address these questions. Among the 22 patients with MPN-BP studied 11 were cytogenetically normal while the remainder had multiple chromosomal abnormalities including del(5), del(20q), del(14), +1q, del(17p). 86% of the patients had at least 2 myeloid malignancy gene mutations including JAK2, ASXL1,TET2, MPL, SF3B1, RUNX1, U2AF1, PTPN11, IDH1/2, SRSF2 and TP53. These findings indicate that MPN-BP is characterized by multiple mutational events and cytogenetic abnormalities. T cell-depleted mononuclear cells from 8 of 14 patients engrafted in NSG mice {>0.5% hCD45+ cells in bone marrow (BM)}. Among them, samples from 6 patients resulted in a high degree of hCD45+ cell chimerism (34.6±6.4% in BM) and recapitulated numerous aspects of MPN-BP within 4 months, including the presence of at least 20% hCD45dimCD33+ cells or hCD34+ cells, or at least 20% blasts as detected by morphological examination of the marrow and leukemia cell dissemination to the spleen and PB. These mice had a 2.8±0.6- fold increase in splenic weight as compared to mice receiving PBS alone. The leukemic mice were characterized by reduced blood counts, suggesting that MPN-BP cells suppressed normal murine hematopoiesis, or led to cytopenias due to hyper-splenism. Moreover, the greater degrees of blast cell chimerism and the higher frequency of leukemia initiating cells as determined by limiting dilution analyses correlated with a shorter time to leukemia initiation and an inferior clinical outcome of the transplanted NSG mice. Grafts from each of these 6 MPN-BP patients produced a large number of donor-derived myeloid cells and a smaller number of lymphoid cells (mostly CD3+ and few CD19+). Cells belonging to each of these lineages and leukemic cells in primary recipients produced from Pts 4, 5, 6 and 11 had an identical proportion of chromosomally abnormal and mutated cells as primary cells [Pt 4: JAK2V617F, TET2 and PHF6; Pt 5 and 11: Del (20q), +8; Pt 6: +1q, del(17p)], except that a small proportion of T cells from Pts 5 and 11 lacked chromosomal abnormalities. Furthermore, the degree of MPN-BP engraftment and leukemic cell burden increased with the subsequent 3 serial transplantations even when the recipients received progressively smaller numbers of MPN-BP cells from the prior recipient. Primary Pt 6 originally had a JAK2V617F+ PV but lost JAK2V617F at the time the MPN-BP occurred at which time there were two clonal cell populations, one with +1q (12%) and the other del(17p) (80%), the site of the TP53 gene, as well as normal cells (8%). In the primary recipient NSG the donor derived cells were JAK2V617F- but contained +1q (1%) and del(17p) (98.5%) and cytogenetically normal (0.5%). +1q and JAK2V617F were not observed, while cells containing the TP53 deletion alone were detected in donor derived leukemic cells, mature myeloid and T cells in the secondary and subsequent serial recipients. Furthermore, del(17p) was found in phenotypically isolated HSCs, MPPs, MLPs, CMPs, GMPs, MEPs, and mature T cells within the CD33- cell fraction as well as CD45dimCD33+ AML blasts selected from primary MPN-BP cells from Pt6. However, +1q was found exclusively in purified MLPs and MEP. These observations establish that cytogenetic and mutational events that lead to MPN-BP occur at different stages along the developmental HSC hierarchy and that a small population of normal HSCs persist. Furthermore, in JAK2V617F+ MPNs that develop MPN-BP and lose JAK2V617F, additional cytogenetic events occur at different stages along the JAK2V617F- MPN-BP-stem cell hierarchy. Our ability to serially transplant the LIC from these patients has allowed us to create the first MPN-BP PDX model that will not only extend our understanding of MPN-BP stem cell biology but might also prove useful for screening drugs to treat MPN-BP. Disclosures Rampal: Jazz: Consultancy, Honoraria; Incyte: Honoraria, Research Funding; Stemline: Research Funding; Constellation: Research Funding; Celgene: Honoraria. Mascarenhas:Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Roche: Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Promedior: Research Funding; Janssen: Research Funding. Hoffman:Formation Biologics: Research Funding; Summer Road: Research Funding; Merus: Research Funding; Incyte: Research Funding; Janssen: Research Funding.

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Clonal Evolution at First Sight: A Combined Visualization of Diverse Diagnostic Methods Improves Understanding of Leukemia Progression

Blood ◽

10.1182/blood-2021-147187 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1293-1293

Author(s):

Sarah Sandmann ◽

Yvonne Lisa Behrens ◽

Felicitas Thol ◽

Michael Heuser ◽

Doris Steinemann ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Genetic Architecture ◽

Clonal Evolution ◽

Copy Number Variations ◽

Advisory Committees ◽

Time Points ◽

Myeloid Neoplasia ◽

Bioinformatic Approach ◽

Time Point

Abstract Introduction: Myeloid neoplasia, including acute myeloid leukemia and myelodysplastic syndrome are heterogeneous hematopoietic stem cell disorders which are marked by the acquisition of somatic alterations and clonal evolution 1. Patients with myeloid neoplasia are classified due to the WHO classification systems and besides clinical and hematological criteria, cytogenetic and molecular genetic alterations highly impact treatment stratification 2. In routine diagnostics, a combination of methods is used to decipher different types of genetic variants, i.e. single nucleotide variants (SNVs), insertions/deletions (indels), structural variants (SVs) and copy number variations (CNVs) which may not be detected using one single method. Methods: We used a bioinformatic approach to analyze clonal evolution and genetic architecture in patients with myeloid neoplasia using single nucleotide variants (SNVs), insertions/deletions (indels), structural variants (SVs) and copy number variations (CNVs). Six patients were comprehensively analyzed using karyotyping, fluorescence in situ hybridization (FISH), array-CGH and a custom NGS panel with 148 genes/ gene regions that are recurrently affected in patients with hematologic neoplasia. At the initial time point or during disease course all patients showed many genomic variants: Two patients (#1, #2) were analyzed at one time point (initial), two patients (#3, #4) were analyzed at two time points (initial and progression), one patient (#5) was analyzed at four time points (initial, progression, remission, relapse), and one patient (#6) was analyzed at five time points (initial, remission, relapse, progression, remission). Results and Conclusions: Clonal evolution was reconstructed manually, integrating all mutational information on SNVs, indels, SVs and CNVs 3. Cancer cell fractions (CCFs) for SNVs and indels were estimated based on VAFs, assuming heterozygous variants (2*VAF=CCF). CCFs for SVs and CNVs were estimated based on cell counts reported for karyotyping and FISH analyses. For SVs as well as CNVs, which were only detected by array-CGH, CCF was estimated based on logRatio. In case of a CNV overlapping the position of an SNV or indel, calculation of CCF is less straightforward. Altogether, we differentiate between three cases: 1) The CNV occurred prior to the SNV/indel, but in the same cells. 2) The SNV/indel occurred prior to the CNV, but in the same cells. 3) SNV/indel and CNV exist in parallel, independent of each other. The bioinformatic approach reconstructed clonal evolution (linear and/or branching) for all patients and the results were visualized by fishplots. We identified alterations, which play a role in the pathogenesis of the disease (driver) and alterations, which occur during disease development (passenger). On two samples, we showed that reconstruction of clonal evolution is possible even with data from one time point only. For other samples, providing data on more than one time point, the effect of therapy was estimated. This bioinformatic approach offers the possibility of analyzing clonal evolution and genetic architecture at one or more time points of analysis. The visualization of the results in fishplots contributes to a better understanding of genetic architecture and helps to identify possible targets for the disease (personalized therapy). Furthermore, this model can be used to identify markers in order to assess minimal residual disease (MRD). Figure 1 Reconstruction of clonal evolution (time point of analysis: black triangle) for patient #4 (diagnosis: secondary acute myeloid leukemia). References: 1. Doulatov S, Papapetrou EP. Studying clonal evolution of myeloid malignancies using induced pluripotent stem cells. Curr Opin Hematol. 2021;28(1):50-56. 2. Edited by Swerdlow SH CE, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. International Agency for Research on Cancer. 2017;Revised 4th edition. 3. Reutter K, Sandmann S, Rohde J, et al. Reconstructing clonal evolution in relapsed and non-relapsed Burkitt lymphoma. Leukemia. 2021;35(2):639-643. Figure 1 Figure 1. Disclosures Thol: Jazz: Honoraria; BMS/Celgene: Honoraria, Research Funding; Abbvie: Honoraria; Astellas: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Heuser: Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer Pharma AG: Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; Tolremo: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; BergenBio: Research Funding.

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Differential Impact of Interferon Alpha on JAK2V617F and Calr Mutated Hematopoietic Stem and Progenitor Cells in Classical MPN

Blood ◽

10.1182/blood-2018-99-114744 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4333-4333 ◽

Cited By ~ 1

Author(s):

Matthieu Mosca ◽

Lamia Lamrani ◽

Christophe Marzac ◽

Amandine Tisserand ◽

Valérie Edmond ◽

...

Keyword(s):

Board Of Directors ◽

Interferon Alpha ◽

Research Funding ◽

Molecular Response ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Clonal Architecture

Abstract Introduction: Classical BCR-ABL-negative myeloproliferative neoplasms (MPN) include Polycythemia Vera (PV), Essential Thrombocytemia (ET) and Primary Myelofibrosis (PMF). They are acquired clonal disorders of hematopoietic stem cells (HSC) leading to the hyperplasia of one or several myeloid lineages. They are due to three main recurrent mutations affecting the JAK/STAT signaling pathway: JAK2V617F and mutations in the calreticulin (CALR) and thrombopoietin receptor (MPL). Interferon alpha (IFNα) is the only drug that not only induces a hematological response in ET, PV and early MF, but also a significant molecular response on both JAK2V617F or CALR-mutated cells. Our broad aim was to understand the mechanism of action of IFNα. Previously, our group and others have shown that IFNα specifically targets JAK2V617F HSC in a chimeric JAK2V617F knock-in mouse model. In this study, we wanted to know how and how fast IFNα impacts the different mutated human hematopoietic compartments. Methods: A prospective study was performed with a cohort of 47 patients treated by IFNα for 3-5 years. The MPN disease distribution was 40% ET, 49% PV and 11% MF. This cohort included 33 JAK2V617F-mutated patients, 11 CALR-mutated patients (7 type 1/type 1-like and 4 type 2/type 2-like), 2 both JAK2V617F- and CALR-mutated patients and 1 MPLW515K-mutated patient. At 4-month intervals, the JAK2V617F or/and CALR mutation allele frequency was measured in mature cells (granulocytes, platelets). Simultaneously, the clonal architecture was also determined by studying the presence of the JAK2V617F or CALR mutations in colonies derived from the different hematopoietic stem and progenitor cell (HSPC) populations (CD90+CD34+CD38- HSC-enriched progenitors, CD90-CD34+CD38- immature progenitors and CD90- CD34+CD38+ committed progenitors). Results: After a median follow-up of 33 months, IFNα targets more efficiently and rapidly the HSPC particularly in HSC-enriched progenitors, than the mature blood cells in JAK2V617F patients (p<.05). Moreover, homozygous JAK2V617F clones responded more rapidly than heterozygous clones in all hematopoietic cell compartments showing that the intensity of JAK2V617F signaling is correlated with the efficacy of IFNα. This efficacy was slightly increased after a median follow-up of 51 months. In contrast, during a median follow-up of 33 months for CALR-mutated patients, IFNα targeted similarly the HSPC and the mature cells. Moreover, IFNα induced a slower response in targeting CALR-mutated HSPC than the JAK2V617F HSPC (p<.05) (see Figure). The role of associated mutations at diagnosis was also investigated in the IFNα-mediated HSPC molecular responses using a NGS targeted myeloid panel. In JAK2V617F-mutated patients, the number of associated mutations did not impact the HSPC molecular response. In contrast, in CALR-mutated patients, the only molecular responders were not associated with other mutations, although the lower number of cases should be expanded. Using Ba/F3-MPL cellular models and primary cells, we observed that JAK2V617F was more prone to sensitize to IFNα signaling (increased Phospho-STAT1 and IFN-stimulating genes (ISGs)) compared to controls or CALRdel52 mutated cells. Conclusion: Altogether, our results show that IFNα targets more efficiently the human JAK2V617F-HSPCthan the mature cells. Moreover, IFNα has a greater efficacy on JAK2V617F HSPC thanCALR-mutated HSPC. This former result was associated with a greater priming of the IFNα signaling by JAK2V617F than by CALRdel52. The molecular response was dependent not only on mutational status, but also on the presence of other associated mutations for the CALR-mutated HSPC. Patient data are currently incorporated into a mathematical model taking into account clonal architecture and associated mutations to develop an algorythm able to predict patient response. Figure. Figure. Disclosures Kiladjian: Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Long-Term Experience with Large Granular Lymphocytic Leukemia Evolving after Solid Organ and Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood-2019-130167 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1226-1226

Author(s):

Hassan Awada ◽

Reda Z. Mahfouz ◽

Jibran Durrani ◽

Ashwin Kishtagari ◽

Deepa Jagadeesh ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Viral Infections ◽

De Novo ◽

Post Transplantation ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Post Transplant ◽

Stat3 Mutations

T-cell large granular lymphocyte leukemia (T-LGLL) is a clonal proliferation of cytotoxic T lymphocytes (CTL). T-LGLL mainly manifest in elderly and is associated with autoimmune diseases including rheumatoid arthritis (RA), B cell dyscrasias, non-hematologic cancers and immunodeficiency (e.g., hypogammaglobulinemia). LGL manifestations often resemble reactive immune processes leading to the dilemmas that LGLs act like CTL expansion during viral infections (for example EBV associated infectious mononucleosis). While studying a cohort of 246 adult patients with T-LGLL seen at Cleveland Clinic over the past 10 years, we encountered 15 cases of overt T-LGLL following transplantation of solid organs (SOT; n=8) and hematopoietic stem cell transplantation (HSCT; n=7). Although early studies reported on the occurrence of LGL post-transplant, these studies focused on the analysis of oligoclonality skewed reactive CTL responses rather than frank T-LGLL. We aimed to characterize post-transplantation T-LGLL in SOT and HSCT simultaneously and compare them to a control group of 231 de novo T-LGLL (cases with no history of SOT or HSCT). To characterize an unambiguous "WHO-defined T-LGLL" we applied stringent and uniform criteria. All cases were diagnosed if 3 out of 4 criteria were fulfilled, including: 1) LGL count >500/µL in blood for more than 6 months; 2) abnormal CTLs expressing CD3, CD8 and CD57 by flow cytometry; 3) preferential usage of a TCR Vβ family by flow cytometry; 4) TCR gene rearrangement by PCR. In addition, targeted deep sequencing for STAT3 mutations was performed and charts of bone marrow biopsies were reviewed to exclude other possible conditions. Diagnosis was made 0.2-27 yrs post-transplantation (median: 4 yrs). At the time of T-LGLL diagnosis, relative lymphocytosis (15-91%), T lymphocytosis (49-99%) and elevated absolute LGL counts (>500 /µL; 93%) were also seen. Post-transplantation T-LGLL were significantly younger than de novo T-LGLL, (median age: 48 vs. 61 yr; P<.0001). Sixty% of post-transplantation T-LGLL patients were males. Fifteen% of patients had more cytogenetic abnormalities compared to de novo T-LGLL, had a lower absolute LGL count (median: 4.5 vs. 8.5 k/µL) and had less frequent neutropenia, thrombocytopenia and anemia (27 vs. 43%, 33 vs. 35% and 20% vs. 55%; P=.01). TCR Vb analysis identified clonal expansion of ≥1 of the Vb proteins in 60% (n=9) of the patients; the remaining 40% (n=6) of the cases had either a clonal process involving a Vb protein not tested in the panel (20%; n=3) or no clear expansion (20%; n=3). Signs of rejection were observed in 20% (n=3/15) and GvHD in 13% (n=2/15) of the patients. Post-transplantation, 27% of cases presented with neutropenia (absolute neutrophil count <1.5 x109/L; n=4), 33% with thrombocytopenia (platelet count <150 x109/L; n=5) and 25% with anemia (hemoglobin <10 g/dL; n=3). T-LGLL evolved in 10 patients (67%; 10/15) despite IST including cyclosporine (n=5), tacrolimus (n=4), mycophenolate mofetil (n=5), cyclophosphamide (n=1), anti-thymocyte globulin (n=1), and corticosteroids (n=6). Lymphadenopathy and splenomegaly were seen in 13% (n=2) and 33% (n=5) of the patients. Other conditions observed were MGUS (20%; n=3) and RA (7%; n=1). Conventional cytogenetic showed normal karyotype in 89% (n=11, tested individuals 13/15). Somatic STAT3 mutations were identified in 2 patients. Sixty% of cases (n=9) were seropositive for EBV when tested at different time points after transplant. Similarly, 53% (n=8) were seropositive for CMV, of which, 5 were positive post-transplantation and 3 pre-/post-transplantation. The complexity of T-LGLL expansion post-transplantation might be due to several mechanisms including active viral infections, latent oncogenic viral reactivation and graft allo-antigenic stimulation. However, in our cohort graft rejection or GvHD was encountered in a few patients (2 allo-HSCT recipients). Autoimmune conditions were present in 50% of SOT recipients (n=4/ 8, including RA, ulcerative colitis, systemic lupus erythematosus). Some of our patients also had low immunoglobulin levels. Overt EBV (post-transplant lymphoproliferative disorder) and CMV reactivation was diagnosed in only 27% (4/15) of the patients. In sum we report the long term follow up of a cohort of T-LGLL and emphasize the expansion of T-LGLL post-transplant highlighting the difficulty in assigning one unique origin of LGLL. Disclosures Hill: Genentech: Consultancy, Research Funding; Takeda: Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Kite: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Honoraria; Amgen: Research Funding; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; TG therapeutics: Research Funding; AstraZeneca: Consultancy, Honoraria. Majhail:Atara Bio: Consultancy; Mallinckrodt: Honoraria; Nkarta: Consultancy; Anthem, Inc.: Consultancy; Incyte: Consultancy. Sekeres:Syros: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Maciejewski:Alexion: Consultancy; Novartis: Consultancy.

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Patterns of Clonal Evolution Assessed By Whole Exome Sequencing during Progression from MDS to AML Are Related to Therapy

Blood ◽

10.1182/blood.v128.22.4309.4309 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4309-4309

Author(s):

María Abáigar ◽

Jesús M Hernández-Sánchez ◽

David Tamborero ◽

Marta Martín-Izquierdo ◽

María Díez-Campelo ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Clonal Evolution ◽

Clonal Expansion ◽

Driver Mutations ◽

Advisory Committees ◽

Disease Evolution ◽

Mutational Burden ◽

Whole Exome ◽

Leukemic Phase

Abstract Introduction: Myelodysplastic syndromes (MDS) are hematological disorders at high risk of progression to acute myeloid leukemia (AML). Although, next-generation sequencing has increased our understanding of the pathogenesis of these disorders, the dynamics of these changes and clonal evolution during progression have just begun to be understood. This study aimed to identify the genetic abnormalities and study the clonal evolution during the progression from MDS to AML. Methods: A combination of whole exome (WES) and targeted-deep sequencing was performed on 40 serial samples (20 MDS/CMML patients evolving to AML) collected at two time-points: at diagnosis (disease presentation) and at AML transformation (disease evolution). Patients were divided in two different groups: those who received no disease modifying treatment before they transformed into AML (n=13), and those treated with lenalidomide (Lena, n=2) and azacytidine (AZA, n=5) and then progressed. Initially, WES was performed on the whole cohort at the MDS stage and at the leukemic phase (after AML progression). Driver mutations were identified, after variant calling by a standardized bioinformatics pipeline, by using the novel tool "Cancer Genome Interpreter" (https://www.cancergenomeinterpreter.org). Secondly, to validate WES results, 30 paired samples of the initial cohort were analyzed with a custom capture enrichment panel of 117 genes, previously related to myeloid neoplasms. Results: A total of 121 mutations in 70 different genes were identified at the AML stage, with mostly all of them (120 mutations) already present at the MDS stage. Only 5 mutations were only detected at the MDS phase and disappeared during progression (JAK2, KRAS, RUNX1, WT1, PARN). These results suggested that the majority of the molecular lesions occurring in MDS were already present at initial presentation of the disease, at clonal or subclonal levels, and were retained during AML evolution. To study the dynamics of these mutations during the evolution from MDS/CMML to AML, we compared the variant allele frequencies (VAFs) detected at the AML stage to that at the MDS stage in each patient. We identified different dynamics: mutations that were initially present but increased (clonal expansion; STAG2) or decreased (clonal reduction; TP53) during clinical course; mutations that were newly acquired (BCOR) or disappearing (JAK2, KRAS) over time; and mutations that remained stable (SRSF2, SF3B1) during the evolution of the disease. It should be noted that mutational burden of STAG2 were found frequently increased (3/4 patients), with clonal sizes increasing more than three times at the AML transformation (26>80%, 12>93%, 23>86%). Similarly, in 4/8 patients with TET2 mutations, their VAFs were double increased (22>42%, 15>61%, 50>96%, 17>100%), in 2/8 were decreased (60>37%, 51>31%), while in the remaining 2 stayed stable (53>48%, 47>48%) at the AML stage. On the other hand, mutations in SRSF2 (n=3/4), IDH2 (n=2/3), ASXL1 (n=2/3), and SF3B1 (n=3/3) showed no changes during progression to AML. This could be explained somehow because, in leukemic phase, disappearing clones could be suppressed by the clonal expansion of other clones with other mutations. Furthermore we analyzed clonal dynamics in patients who received treatment with Lena or AZA and after that evolved to AML, and compared to non-treated patients. We observed that disappearing clones, initially present at diagnosis, were more frequent in the "evolved after AZA" group vs. non-treated (80% vs. 38%). By contrast, increasing mutations were similar between "evolved after AZA" and non-treated patients (60% vs. 61%). These mutations involved KRAS, DNMT1, SMC3, TP53 and TET2among others. Therefore AZA treatment could remove some mutated clones. However, eventual transformation to AML would occur through persistent clones that acquire a growth advantage and expand during the course of the disease. By contrast, lenalidomide did not reduce the mutational burden in the two patients studied. Conclusions: Our study showed that the progression to AML could be explained by different mutational processes, as well as by the occurrence of unique and complex changes in the clonal architecture of the disease during the evolution. Mutations in STAG2, a gene of the cohesin complex, could play an important role in the progression of the disease. [FP7/2007-2013] nº306242-NGS-PTL; BIO/SA52/14; FEHH 2015-16 (MA) Disclosures Del Cañizo: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansen-Cilag: Membership on an entity's Board of Directors or advisory committees, Research Funding; Arry: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Pegaspargase Can Safely be Administered in Adults Age 40 and Older with Acute Lymphoblastic Leukemia

Blood ◽

10.1182/blood-2019-124727 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 3816-3816 ◽

Cited By ~ 2

Author(s):

Ryan J. Daley ◽

Sridevi Rajeeve ◽

Charlene C. Kabel ◽

Jeremy J. Pappacena ◽

Sarah E. Stump ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Board Of Directors ◽

Research Funding ◽

Lymphoblastic Leukemia ◽

Philadelphia Chromosome ◽

Hypersensitivity Reactions ◽

Newly Diagnosed ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Frontline Treatment

Introduction: Asparaginase (ASP) has demonstrated a survival benefit in pediatric patients (pts) with acute lymphoblastic leukemia (ALL) and is now part of standard-of-care frontline treatment. As a result, asparaginase preparations have been incorporated into the treatment of adult ALL to improve outcomes. Pegaspargase (PEG-ASP), a modified version of asparaginase with prolonged asparagine depletion, appears to be safe in adults up to age 40 (Stock, et al., Blood, 2019), but is associated with a unique spectrum of toxicities, the risks of which appear to increase with age. Therefore, the safety of PEG-ASP remains a significant concern in older adults w/ ALL. Methods: We conducted a single center retrospective chart review of pts age ≥40 years who received PEG-ASP as part of frontline induction/consolidation or reinduction, between March 2008 and June 2018 at Memorial Sloan Kettering Cancer Center. The primary objective was to evaluate the tolerability and toxicity of PEG-ASP based on the incidence and severity of ASP-related toxicities (hypersensitivity reactions, hypertriglyceridemia, hyperbilirubinemia, transaminitis, pancreatitis, hypofibrinogenemia, etc) according to the Common Terminology Criteria for Adverse Events, version 4.03. Laboratory values recorded were either the peak or the nadir, the more appropriate for toxicity assessment, within a 4-week period following PEG-ASP administration. Secondary objectives were to determine the total number of doses of PEG-ASP administered in comparison to the number of doses intended, and to characterize the rationale for PEG-ASP discontinuation when applicable. Fisher's exact test was used to compare the incidence of PEG-ASP toxicities with respect to pt and treatment characteristics (regimen, age, BMI, gender, Philadelphia chromosome positive (Ph+) vs. Ph-, presence of extramedullary disease, PEG-ASP dose). P values were not adjusted for multiple comparisons. Results: We identified 60 pts with ALL (40 B-ALL and 20 T-ALL) who received at least one dose of PEG-ASP. Nine pts were Ph+. The median pt age at initiation of the treatment was 53, (range, 40 to 80), and 19 pts had a BMI ≥30 kg/m2. Forty-four pts received treatment for newly diagnosed ALL, and 16 pts for relapsed disease. Table 1 lists pt baseline characteristics. Among the 44 pts with newly diagnosed ALL, 27 pts received PEG-ASP as part of pediatric or pediatric-inspired regimens at doses of 2000 - 2500 units/m2, and 1 pt received a modified dose of 1000 units/m2 due to age. The remaining 16 pts received PEG-ASP at doses of 1000 - 2000 units/m2 for consolidation, per established adult regimens (ALL-2 and L-20; Lamanna, et al., Cancer, 2013). Grade 3/4 ASP-related toxicities with a >10% incidence included: hyperbilirubinemia, transaminitis, hypoalbuminemia, hyperglycemia, hypofibrinogenemia, and hypertriglyceridemia. Frontline treatment regimens in which PEG-ASP was used in consolidation cycles only (ALL-2, L-20) were associated w/ a lower incidence of hyperbilirubinemia (p=0.009) and hypertriglyceridemia (p<0.001) compared to those regimens that included PEG-ASP during induction (pediatric/pediatric-inspired regimens) (Table 2). Younger age (40-59 vs. ≥60 years) was associated with a greater risk of hypertriglyceridemia (p<0.001) and higher PEG-ASP dose (≥2000 vs. <2000 units/m2) was associated with a greater risk of hypertriglyceridemia and hypofibrinogenemia (p=0.002 and p=0.025, respectively). Thirty-eight pts (63%) received all intended doses of PEG-ASP. Six pts stopped PEG-ASP to proceed to allogeneic hematopoietic stem cell transplantation (5 in CR1, 1 in CR2), and 7 pts stopped for hypersensitivity reactions. Hepatotoxicity was the only ASP-related toxicity that led to PEG-ASP discontinuation occurring in 5 pts (hyperbilirubinemia, N=4; transaminitis, N=1). The total number of intended doses of PEG-ASP based on regimens used was 186, and 112 were administered. Conclusion: PEG-ASP was incorporated into the treatment of 60 adult ALL pts age ≥40, with manageable toxicity. Seven pts discontinued PEG-ASP due to hypersensitivity reactions and 5 discontinued due to hepatotoxicity, but other reported toxicities did not lead to PEG-ASP discontinuation and the majority of the pts completed all intended doses of PEG-ASP. This study suggests that with careful monitoring, PEG-ASP can safely be administered in adults ≥40 years of age. Disclosures Rajeeve: ASH-HONORS Grant: Research Funding. Tallman:UpToDate: Patents & Royalties; Oncolyze: Consultancy, Membership on an entity's Board of Directors or advisory committees; Delta Fly Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellerant: Research Funding; Tetraphase: Consultancy, Membership on an entity's Board of Directors or advisory committees; Nohla: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioLineRx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Orsenix: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Research Funding; Biosight: Research Funding; Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; KAHR: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees. Geyer:Dava Oncology: Honoraria; Amgen: Research Funding. Park:Takeda: Consultancy; Allogene: Consultancy; Amgen: Consultancy; AstraZeneca: Consultancy; Autolus: Consultancy; GSK: Consultancy; Incyte: Consultancy; Kite Pharma: Consultancy; Novartis: Consultancy.

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Lower Hematopoietic Progenitor Cell Counts and Yields at Subsequent Donations Is Influenced By a Shorter Inter-Donation Interval between the First and Subsequent Mobilizations

Blood ◽

10.1182/blood-2019-123492 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1962-1962

Author(s):

Sandhya R. Panch ◽

Brent R. Logan ◽

Jennifer A. Sees ◽

Bipin N. Savani ◽

Nirali N. Shah ◽

...

Keyword(s):

Stem Cell ◽

Board Of Directors ◽

Peripheral Blood ◽

Research Funding ◽

Time Interval ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Peripheral Blood Cd34 ◽

Cell Counts ◽

Cd34 Cells

Introduction: Approximately 7% of unrelated hematopoietic stem cell (HSC) donors are asked to donate a subsequent time to the same or different recipient. In a recent large CIBMTR study of second time donors, Stroncek et al. incidentally found that second peripheral blood stem cell (PBSC) collections had lower total CD34+ cells, CD34+ cells per liter of whole blood processed, and CD34+ cells per kg donor weight. Based on smaller studies, the time between the two independent PBSC donations (inter-donation interval) as well as donor sex, race and baseline lymphocyte counts appear to influence CD34+ cell yields at subsequent donations. Our objective was to retrospectively evaluate factors contributory to CD34+ cell yields at subsequent PBSC donation amongst NMDP donors. Methods. The study population consisted of filgrastim (G-CSF) mobilized PBSC donors through the NMDP/CIBMTR between 2006 and 2017, with a subsequent donation of the same product. evaluated the impact of inter-donation interval, donor demographics (age, BMI, race, sex, G-CSF dose, year of procedure, need for central line) and changes in complete blood counts (CBC), on the CD34+ cell yields/liter (x106/L) of blood processed at second donation and pre-apheresis (Day 5) peripheral blood CD34+ cell counts/liter (x106/L) at second donation. Linear regression was used to model log cell yields as a function of donor and collection related variables, time between donations, and changes in baseline values from first to second donation. Stepwise model building, along with interactions among significant variables were assessed. The Pearson chi-square test or the Kruskal-Wallis test compared discrete variables or continuous variables, respectively. For multivariate analysis, a significance level of 0.01 was used due to the large number of variables considered. Results: Among 513 PBSC donors who subsequently donated a second PBSC product, clinically relevant decreases in values at the second donation were observed in pre-apheresis CD34+ cells (73.9 vs. 68.6; p=0.03), CD34+cells/L blood processed (32.2 vs. 30.1; p=0.06), and total final CD34+ cell count (x106) (608 vs. 556; p=0.02). Median time interval between first and second PBSC donations was 11.7 months (range: 0.3-128.1). Using the median pre-apheresis peripheral blood CD34+ cell counts from donation 1 as the cut-off for high versus low mobilizers, we found that individuals who were likely to be high or low mobilizers at first donation were also likely to be high or low mobilizers at second donation, respectively (Table 1). This was independent of the inter-donation interval. In multivariate analyses, those with an inter-donation interval of >12 months, demonstrated higher CD34+cells/L blood processed compared to donors donating within a year (mean ratio 1.15, p<0.0001). Change in donor BMI was also a predictor for PBSC yields. If donor BMI decreased at second donation, so did the CD34+cells/L blood processed (0.74, p <0.0001). An average G-CSF dose above 960mcg was also associated with an increase in CD34+cells/L blood processed compared to donors who received less than 960mcg (1.04, p=0.005). (Table 2A). Pre-apheresis peripheral blood CD34+ cells on Day 5 of second donation were also affected by the inter-donation interval, with higher cell counts associated with a longer time interval (>12 months) between donations (1.23, p<0.0001). Further, independent of the inter-donation interval, GCSF doses greater than 960mcg per day associated with higher pre-apheresis CD34+ cells at second donation (1.26, p<0.0001); as was a higher baseline WBC count (>6.9) (1.3, p<0.0001) (Table 2B). Conclusions: In this large retrospective study of second time unrelated PBSC donors, a longer inter-donation interval was confirmed to be associated with better PBSC mobilization and collection. Given hematopoietic stem cell cycling times of 9-12 months in humans, where possible, repeat donors may be chosen based on these intervals to optimize PBSC yields. Changes in BMI are also to be considered while recruiting repeat donors. Some of these parameters may be improved marginally by increasing G-CSF dose within permissible limits. In most instances, however, sub-optimal mobilizers at first donation appear to donate suboptimal numbers of HSC at their subsequent donation. Disclosures Pulsipher: CSL Behring: Membership on an entity's Board of Directors or advisory committees; Miltenyi: Research Funding; Bellicum: Consultancy; Amgen: Other: Lecture; Jazz: Other: Education for employees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Medac: Honoraria. Shaw:Therakos: Other: Speaker Engagement.

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Clonal Architecture and Variant Allele Frequency Predict Clinical Outcomes and Drug Response in Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2020-136477 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 2-2

Author(s):

Brooks Benard ◽

Logan Leak ◽

Armon Azizi ◽

Daniel Thomas ◽

Andrew Gentles ◽

...

Keyword(s):

Board Of Directors ◽

Clinical Outcomes ◽

Drug Sensitivity ◽

Clonal Evolution ◽

High Risk Patient ◽

Variant Allele Frequency ◽

Clonal Heterogeneity ◽

Advisory Committees ◽

Clonal Architecture ◽

Linear Evolution

Introduction: AML is an aggressive cancer that develops from the sequential accumulation and clonal expansion of somatic mutations in hematopoietic stem and progenitor cells. Recent next-generation sequencing (NGS) studies of AML have correlated mutations with clinical outcomes and response to targeted therapies. Additionally, emerging reports have suggested that increased clonal heterogeneity and mutation burden tend to correlate with worse survival outcomes. However, due to previous cohort sizes, the architecture of clonal evolution and variant allele frequency (VAF) of recurrent mutations have yet to be robustly correlated with response to therapy or with more granular risk stratification. To address previous limitations, we combined available datasets of sequenced AML to model features of clonality and determine their correlations with clinical outcomes and drug sensitivity. Methods: A systematic literature review was performed to identify cohorts of clinically annotated and genetically profiled adult AML. Studies were included if: (i) their sequencing panel targeted at least 30 of the most commonly mutated genes, (ii) censored overall survival data was reported, and (iii) data were publicly available. An additional cohort of patients profiled at Stanford was also included. Leveraging statistical learning methods and robust clonal modeling algorithms (PyClone and ClonEvol), we performed a meta-analysis of the clonal architecture of mutations, their temporal relationships, sensitivity to drugs, and correlation with outcomes in AML. Results: A total of 12 studies were aggregated into a uniformly annotated database comprising 2,987 AML patient samples profiled with an array of DNA sequencing modalities (2,884 with VAFs) and ex vivo drug screening results (nsamples = 562; ndrugs = 122); survival outcomes were available for 2,606 patients. To investigate broad features of leukemia evolution, we used clonal modeling algorithms to infer clonal architecture. Interestingly, patients exhibiting linear evolution (sequential mutations in the same clone) displayed worse outcomes compared to those with branched architecture (distinct subclonal populations). Additionally, mutational burden and clonal heterogeneity only stratified patients with branched structure. These results motivated us to understand how the temporal acquisition of mutations might further stratify outcomes. Using dynamic VAF thresholds, we identified novel high-risk patient populations for 15 recurrently mutated genes. Greater VAF was associated with statistically significant improved survival in genotypes such as GATA2mut and WT1mut and with worse outcomes for patients with NRAS and NF1 mutations. Next, we leveraged VAFs to infer the temporal ordering of individual mutations and functional mutation categories. Patients where NRAS mutations occurred before GATA2 mutations showed a significant correlation with worse outcomes. We also observed that patients in which (i) DNA methylation mutations occurred before those in tumor suppressors and (ii) splicing factor mutations occurred before RTK/RAS signaling components showed significantly shortened overall survival. These results indicate that patients with the same genotype can be stratified by the timing of mutations in the clonal evolution of their leukemia. Finally, we used linear regression between drug sensitivity and VAF to identify several mutations which predict drug sensitivity exclusively in a VAF-dependent manner. Increased WT1 VAF correlated with sensitivity to ABT-737 and elevated FLT3-TKD VAF predicted sensitivity to cabozantinib, among other clinically notable drug-gene relationships. These results suggest potential biomarkers for clinical response to emerging targeted agents. Conclusions: We show that VAF can identify novel high-risk patient populations at the individual mutation level (e.g. BCOR and NF1) and can also be leveraged to stratify outcomes based on inferring the temporal ordering of mutations (e.g. NRAS and GATA2). Our observation that patients with leukemias exhibiting branched evolution showed improved survival compared to linear evolution was also striking and warrants further experimental and clinical validation. Incorporating these results with our findings of drug sensitivity validate the clinical utility of integrating clonal analysis into the molecular evaluation and treatment of AML. Disclosures Majeti: Zenshine Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Kodikaz Therapeutic Solutions Inc.: Membership on an entity's Board of Directors or advisory committees; Stanford University: Patents & Royalties: pending patent application on CD93 CAR ; Coherus BioSciences: Membership on an entity's Board of Directors or advisory committees; BeyondSpring Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Forty-Seven Inc.: Divested equity in a private or publicly-traded company in the past 24 months; Gilead Sciences, Inc.: Patents & Royalties: inventor on patents related to CD47 cancer immunotherapy; CircBio Inc.: Research Funding.

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Personalized Transcriptomic Analyses Identify Unique Signatures That Correlate with Genomic Subtypes in Acute Myeloid Leukemia (AML) Using Explainable Artificial Intelligence

Blood ◽

10.1182/blood-2020-139522 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 33-34 ◽

Cited By ~ 1

Author(s):

Yazan Rouphail ◽

Nathan Radakovich ◽

Jacob Shreve ◽

Sudipto Mukherjee ◽

Babal K. Jha ◽

...

Keyword(s):

Machine Learning ◽

Board Of Directors ◽

Research Funding ◽

State Of The Art ◽

Data Monitoring Committee ◽

Biological Pathways ◽

Machine Learning Algorithms ◽

Advisory Committees ◽

Altered Expression ◽

Individual Level

Background Multi-omic analysis can identify unique signatures that correlate with cancer subtypes. While clinically meaningful molecular subtypes of AML have been defined based on the status of single genes such as NPM1 and FLT3, such categories remain heterogeneous and further work is needed to characterize their genetic and transcriptomic diversity on a truly individualized basis. Further, patients (pts) with NPM1+/FLT3-ITD- AML have a better overall survival compared to patients with NPM1-/FLT3-ITD+, suggesting that these pts could have different transcriptomic signature that impact phenotype, pathophysiology, and outcomes. Many current transcriptome analytic techniques use clustering analysis to aggregate samples and look at relationships on a cohort-wide basis to build transcriptomic signatures that correlate with phenotype or outcome. Such approaches can undermine the heterogeneity of the gene expression in pts with the same signatures. In this study, we took advantage of state of the art machine learning algorithms to identify unique transcriptomic signatures that correlate with AML genomic phenotype. Methods Genomic (whole exome sequencing and targeted deep sequencing) and transcriptomic data from 451 AML pts included in the Beat AML study (publicly available data) were used to build transcriptomic signatures that are specific for AML patients with NPM1+/FLT3-ITD+ compared to NPM1+/FLT3-ITD, and NPM1-/FLT3-ITD-. We chose these AML phenotypes as they have been described extensively and they correlate with clinical outcomes. Results A total of 242 patients (54%) had NPM1-/FLT3-, 35 (8%) were NPM1+/FLT3-, and 47 (10%) were NPM1+/FLT3+. Our algorithm identified 20 genes that are highly specific for NPM1/FLT3ITD phenotype: HOXB-AS3, SCRN1, LMX1B, PCBD1, DNAJC15, HOXA3, NPTXq, RP11-1055B8, ABDH128, HOXB8, SOCS2, HOXB3, HOXB9, MIR503HG, FAM221B, NRP1, NDUFAF3, MEG3, CCDC136, and HIST1H2BC. Interestingly, several of those genes were overexpressed or underexpressed in specific phenotypes. For example, SCRN1, LMX1B, RP11-1055B8, ABDH128, HOXB8, MIR503HG, NRP1 are only overexpressed or underexpressed in patients with NPM1-/FLT3-, while PCBD1, NDUFAF3, FAM221B are overexpressed or underexpressed in pts with NPM1+/FLT3+. These genes affect several important pathways that regulate cell differentiation, proliferation, mitochondrial oxidative phosphorylation, histone modification and lipid metabolism. All these genes had previously been reported as having altered expression in genomic studies of AML, confirming our approach's ability to identify biologically meaningful relationships. Further, our algorithm can provide a personalized explanation of overexpressed and underexpressed genes specific for a given patient, thus identifying targetable pathways for each pt. Figure 1 below shows three pts with the same genotype (NPM1+/FLT3-ITD+) but demonstrate different transcriptomic patterns of overexpression or underexpression that affect different biological pathways. Conclusions We describe the use of a state of the art explainable machine learning approach to define transcriptomic signatures that are specific for individual pts. In addition to correctly distinguishing AML subtype based on specific transcriptomic signatures, our model was able to accurately identify upregulated and downregulated genes that affecte several important biological pathways in AML and can summarize these pathways at an individual level. Such an approach can be used to provide personalized treatment options that can target the activated pathways at an individual level. Disclosures Mukherjee: Partnership for Health Analytic Research, LLC (PHAR, LLC): Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; EUSA Pharma: Consultancy; Celgene/Acceleron: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squib: Honoraria; Aplastic Anemia and MDS International Foundation: Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Sekeres:BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy. Nazha:Jazz: Research Funding; Incyte: Speakers Bureau; Novartis: Speakers Bureau; MEI: Other: Data monitoring Committee.

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