scholarly journals Clonal Evolution Pattern and Prognostic Significance of Clonal Architecture in KMT2A-Rearranged Acute Myeloid Leukemia

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2358-2358
Author(s):  
Hidemasa Matsuo ◽  
Kenichi Yoshida ◽  
Yasuhito Nannya ◽  
Yuri Ito ◽  
Shoji Saito ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Clonal Evolution ◽  
Prognostic Significance ◽  
High Relapse Rate ◽  
Evolution Pattern ◽  
Transcription Factor Genes ◽  
Otsuka Pharmaceutical ◽  
Matched Data

Abstract MLL (KMT2A) rearrangements are among the most frequent chromosomal abnormalities that occur in acute myeloid leukemia (AML). Mutational landscapes in KMT2A-rearranged AML have been reported; however, most studies are missing data at relapse. Therefore, matched diagnostic and relapse samples were analyzed in this study, and the clonal evolution pattern in KMT2A-rearranged AML was examined. Further, the prognostic significance of the clonal architecture was investigated. Sixty-two diagnostic and 16 relapse samples obtained from pediatric patients with KMT2A-rearranged AML enrolled in the Japan Children's Cancer Group (JCCG) AML-05/AML-99 study were analyzed for 338 genes using targeted sequencing. The data were analyzed with the published data of 105 diagnostic and 9 relapse samples with KMT2A-rearranged AML. Additionally, as a control, the mutation data of matched diagnostic and relapse samples of 107 patients with non-KMT2A-rearranged AML were collected. Among 25 patients with KMT2A-rearranged AML with matched data at diagnosis and relapse, mutations of signaling pathway genes (FLT3, KRAS, NRAS, PTPN11, CBL, and BRAF) were frequently detected in diagnostic samples (25 mutations/25 patients). However, 21 of 25 (84.0%) mutations were lost at relapse. In contrast, 7 of 19 (36.8%) mutations of other pathway genes were lost at relapse, and the percentage was significantly lower than that of mutations in the signaling pathway genes (P = 0.002). Six mutations in the signaling pathway genes and 11 mutations in other pathway genes were acquired at relapse. Particularly, mutations of transcription factor genes (WT1, SPI1, GATA2, and RUNX1) were acquired at relapse: 7 of 8 (87.5%) mutations were detected only at relapse. These results suggest that mutations of signaling pathway genes are unstable in the clonal evolution of KMT2A-rearranged AML. Mutations of other pathway genes, especially those of transcription factor genes, may contribute to relapse in patients with KMT2A-rearranged AML. Next, attention was turned to the KRAS mutations (KRAS-MT) because we have previously shown that KRAS-MT are independent adverse prognostic factors in KMT2A-rearranged AML (Blood Adv. 2020). Among 25 patients with KMT2A-rearranged AML with matched data at diagnosis and relapse, 10 (40.0%) patients harbored KRAS-MT at diagnosis. Interestingly, KRAS-MT were lost at relapse in 9 of 10 (90.0%) patients. Among 107 patients with non-KMT2A-rearranged AML with matched data at diagnosis and relapse, 10 (9.3%) patients harbored KRAS-MT at diagnosis. The frequency of KRAS-MT was significantly higher in KMT2A-rearranged AML (40.0% vs. 9.3%, P = 0.0006). This may be explained on the basis of the fact that KRAS-MT is associated with a high relapse rate in KMT2A-rearranged AML, but not in non-KMT2A-rearranged AML. KRAS-MT was lost at relapse in 5 of 10 (50.0%) patients with non-KMT2A-rearranged AML. The percentage of KRAS-MT loss at relapse was higher in KMT2A-rearranged AML. However, it was not statistically significant (90.0% vs. 50.0%, P = 0.14). Therefore, KRAS-MT may be unstable in clonal evolution regardless of disease subtypes in AML. The underlying mechanisms of the paradox between the high relapse rate in patients with KRAS-MT and frequent loss of KRAS-MT at relapse in patients with KMT2A-rearranged AML should be examined in future studies. The loss of KRAS-MT at relapse suggests that the mutations were in subclones at diagnosis. Therefore, we finally examined the prognosis of 167 patients according to the clonality of KRAS-MT at diagnosis. In patients with KMT2A-MLLT3 (n = 67), those with subclonal KRAS-MT (n = 6) had adverse 5-y event-free survival compared with both patients with wild-type KRAS (KRAS-WT) (n = 56) (KRAS-WT vs. subclonal KRAS-MT: 58.7% vs. 16.7%, P = 0.04) and patients with clonal KRAS-MT (n = 5) (clonal KRAS-MT vs. subclonal KRAS-MT: 80.0% vs. 16.7%, P = 0.07). However, 5-y overall survival (OS) was similar among the three groups. In contrast, among patients with KMT2A-MLLT10 (n = 37), those with clonal KRAS-MT (n = 5) had adverse 5-y OS compared with both patients with KRAS-WT (n = 20) (KRAS-WT vs. clonal KRAS-MT: 59.7% vs. 0.0%, P = 0.006) and patients with subclonal KRAS-MT (n = 12) (subclonal KRAS-MT vs. clonal KRAS-MT: 58.3% vs. 0.0%, P = 0.04). According to these results, the effects of the clonality of KRAS-MT on prognosis may depend on which KMT2A fusion is present. Disclosures Nannya: Otsuka Pharmaceutical Co., Ltd.: Consultancy, Speakers Bureau; Astellas: Speakers Bureau. Saito: Toshiba corporation: Research Funding. Ogawa: Kan Research Laboratory, Inc.: Consultancy, Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; Eisai Co., Ltd.: Research Funding; Ashahi Genomics: Current holder of individual stocks in a privately-held company; ChordiaTherapeutics, Inc.: Consultancy, Research Funding.

scholarly journals Intrapatient Complex Transcriptional Responses to Conventional Chemotherapy in Relapsed Acute Myeloid Leukemia Revealed By Single Cell RNA-Seq Analysis

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1179-1179
Author(s):  
Hideaki Mizuno ◽  
Akira Honda ◽  
Mineo Kurokawa
Keyword(s):  
Single Cell ◽  
Signaling Pathway ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Chemotherapy Resistance ◽  
Rna Seq ◽  
Conventional Chemotherapy ◽  
Chugai Pharmaceutical ◽  
Dna Mutation ◽  
Otsuka Pharmaceutical

Abstract Resistance to anthracycline and cytarabine based conventional chemotherapy often occurs and results in extremely poor prognosis in patients with acute myeloid leukemia (AML). Although chemotherapy resistance is the most critical clinical problem, the mechanisms by which AML confers resistance to conventional chemotherapy are not yet fully understood. In this study, we investigated the key mechanisms of chemotherapy resistance through single cell RNA-sequencing analysis using paired bone marrow AML cells longitudinally collected from two AML-MRC patients at diagnosis and relapse after anthracycline-based chemotherapy. AML blasts were sorted by CD45/SSC gating and subjected to single cell RNA-seq analysis. Single cell RNA-seq was performed using 10x Genomics' Chromium System. Mean estimated number of cells per sample was 3.403 (2,731-4,200) and median detected genes per cell ranged 3,030 to 3,918 among four samples. Data collected from paired samples were combined in following analysis. Transcriptome based clustering following UMAP dimensionality reduction distinguished 5 and 9 cluster groups in each paired sample. Chemotherapy sensitive cluster groups dominant at diagnosis and chemotherapy resistant cluster groups dominant at relapse were clearly divided. In each paired sample, a few AML cells at diagnosis were allocated to chemotherapy resistant cluster groups. This suggested that transcriptionally identifiable less frequent cells resistant to chemotherapy existed at diagnosis and may expand during and/or after chemotherapy maintaining its transcriptional features. Next, to determine whether these transcriptional features are correlated with DNA mutation profiles, we labeled DNA mutation status to each cell and compared frequencies of mutation. As far as we detected, AML recurrent mutations such as DNMT3A R882C and TP53 missense mutation were not related to chemotherapy resistant cluster groups, although this method was relatively limited by the nature of RNA-seq-based mutation detection. Then we sought to determine transcriptional features of resistant clones. Gene set enrichment analysis identified some gene groups such as E2F signaling pathway, MYC signaling pathway, hedgehog signaling pathway and TNFA signaling pathway as transcriptional signatures related to emergence after chemotherapy. Analysis of known hematopoietic differentiation gene signatures showed distinct differentiation profiles in each cluster groups, whereas resistant cluster groups were not necessarily related to hematopoietic stem cell signatures. Intrapatient variations of transcriptional signatures among the resistant cluster groups were detected, which indicated that accurate detection of transcriptional features related to chemotherapy resistance may be difficult by using bulk RNA-seq method. As for other cluster groups which were not dominant both at diagnosis and relapse, these cluster groups hardly changed its frequencies between at diagnosis and relapse, which suggested less proliferative leukemia cells persisted during chemotherapy and have various transcriptional features although whether these persisting cells contribute to relapse was unclear. Since enriched transcriptional signatures in resistant cluster groups were not consistent between the two patients, further analysis using samples collected from more patients would be needed to determine common critical chemotherapy resistant transcriptional signature. In conclusion, our analysis suggested that a transcriptionally identifiable small fraction of cells showing gene signatures related to chemotherapy resistance at diagnosis may expand during chemotherapy and revealed intrapatient transcriptional complexity of response to chemotherapy, which cannot be uncovered by bulk RNA-sequencing. Disclosures Honda: Takeda Pharmaceutical: Other: Lecture fee; Otsuka Pharmaceutical: Other: Lecture fee; Chugai Pharmaceutical: Other: Lecture fee; Ono Pharmaceutical: Other: Lecture fee; Jansen Pharmaceutical: Other: Lecture fee; Nippon Shinyaku: Other: Lecture fee. Kurokawa: MSD K.K.: Research Funding, Speakers Bureau; Kyowa Hakko Kirin Co., Ltd.: Research Funding, Speakers Bureau; Daiichi Sankyo Company.: Research Funding, Speakers Bureau; Astellas Pharma Inc.: Research Funding, Speakers Bureau; Pfizer Japan Inc.: Research Funding, Speakers Bureau; Nippon Shinyaku Co., Ltd.: Research Funding, Speakers Bureau; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding, Speakers Bureau; Otsuka Pharmaceutical Co., Ltd.: Research Funding, Speakers Bureau; Eisai Co., Ltd.: Research Funding, Speakers Bureau; ONO PHARMACEUTICAL CO., LTD.: Research Funding, Speakers Bureau; Teijin Limited: Research Funding, Speakers Bureau; Takeda Pharmaceutical Company Limited.: Research Funding, Speakers Bureau; Chugai Pharmaceutical Company: Research Funding, Speakers Bureau; AbbVie GK: Research Funding, Speakers Bureau.

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

Blood ◽  
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.

scholarly journals Acute Myeloid Leukemia Induced Remodelling of the Human Bone Marrow Niche Predicts Clinical Outcome

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3851-3851
Author(s):  
Yiyang Chen ◽  
Yasmin Zaun ◽  
Lucas Arnold ◽  
Kerstin Weissenfels ◽  
Kurt Werner Schmid ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Human Bone ◽  
Human Bone Marrow ◽  
Murine Models ◽  
High Relapse Rate ◽  
Hsc Niche ◽  
Lower Expression ◽  
First Diagnosis

Abstract The hematopoietic stem cell (HSC) niche consists of different cellular and non-cellular constituents which regulate HSC maintenance and retention in the bone marrow. It has been shown in a number of murine models of myeloid neoplasia how leukemia infiltration alters the HSC niche to reinforce malignancy. Acute myeloid leukemia (AML) is characterized in human by a high relapse rate indicating that leukemia initiating cells are protected by its niche. However, despite our knowledge in murine models little is known about the bone marrow architecture in human and the impact of the leukemic niche on clinical outcome. In this study, we combined immunohistochemical stainings (IHC) with protein and global gene expression analyses together with clinical data to dissect the human bone marrow architecture in AML and assess its clinical impact. Human bone marrow was collected from AML patients at first diagnosis and matching non-leukemic donors. To evaluate the bone marrow architecture CD271+ mesenchymal stem and progenitor cells (MSPCs) were automatically quantified on bone marrow sections. In fact, AML patients showed 1.5-fold increase in bone marrow MSPCs compared to non-leukemic donors (Median (IQR), AML: 5.5% (2.8-9.5), n=36; control: 3.7% (2.1-5.7), n=58; p < 0.01). MSPCs proved to produce reticular fibers, an extracellular matrix protein frequently associated with different malignancies. In AML bone marrow these fibers were also found to be more abundantly expressed (Median (IQR), AML: 3.4% (1.8-4.5), n=37; control: 1.6% (1.1-3.3), n=19; p < 0.05). Next, to globally assess the gene expression profile of MSPCs in AML bone marrow we performed microarray analyses (ClariomTM S Human Assay) of freshly isolated uncultured lineage- CD146+ CD271+ MSPCs. Strikingly, HSC-regulating genes in particular CXCL12, ANGPT1 and VCAM1 showed lower expression in AML MSPCs which correlated with the degree of hematopoietic failure in AML patients. Along with the increased number of MSPCs, geneset enrichment analysis (GSEA) revealed higher proliferation of MSPCs in AML. In murine models loss of quiescence of MSPCs was previously found to be due to bone marrow sympathetic neuropathy. We therefore measured catecholamines and neurotrophic factor in the bone marrow extracellular fluid of AML patients and non-leukemic donors at first diagnosis. In fact, noradrenalin and brain-derived neurotrophic factor (BDNF) showed a 2-fold (p=0.26) resp. 4-fold (p<0.0001) lower expression in AML bone marrow. Importantly, BDNF is proved to be essential for sympathetic neuron proliferation and differentiation. In order to get an overview of alterations of canonical pathways in bone marrow MSPCs upon AML infiltration, we applied QIAGEN's Ingenuity® Pathway Analysis software. Several of the major differently regulated pathways proved to involve differentiation and mineralization of MSPCs. We therefore assessed bone metabolism in AML patients at first diagnosis and quantified serum osteocalcin levels. Notably, AML patients showed 30% lower osteocalcin levels than non-leukemic donors (Median (IQR), AML, 12.15ng/ml (7.53-16.28) n=58; control, 17.2ng/ml (12.5-23.45) n=31; p < 0.05). To evaluate if the deficiency in osteoblast mineralization is specifically due to AML infiltration we performed in vitro co-culture assays. Both MSPCs and an osteoblast-like cell line (SaOS2) showed significant impaired mineralization in presence of certain AML cell lines as well as primary human AML cells, while healthy mononuclear cells did not affect mineralization. Strikingly, this AML-induced defect in osteoblast mineralization proved to be of clinical significance. Patients with low osteocalcin levels (<11ng/ml) showed inferior overall survival with 1-year survival rate of 38.7% while patients with high osteocalcin levels reached 66.8% (n=58; median duration of follow-up 9.7 months). In summary, we globally characterized the bone marrow architecture in AML patients in comparison to non-leukemic donors and assessed its clinical significance. This increasing understanding of the human AML bone marrow microenvironment might open the window for new niche-targeted therapies to eradicate leukemic stem cells and eventually decrease the high relapse rate in AML. Disclosures Duehrsen: Amgen: Research Funding; Roche: Honoraria, Research Funding; Gilead: Consultancy, Honoraria; Celgene: Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Janssen: Honoraria.

Frequency, Clinical Associations, and Prognostic Significance Of Spliceosome Mutations In Patients With Acute Myeloid Leukemia With Myelodysplasia-Related Changes and Therapy-Related Acute Myeloid Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1319-1319
Author(s):  
Young-Uk Cho ◽  
Hyun-Sook Chi ◽  
Sang Hyuk Park ◽  
Young Jin Kim ◽  
Seongsoo Jang ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Prognostic Significance ◽  
Life Sciences ◽  
Myeloproliferative Neoplasm ◽  
Male Dominance ◽  
Prior History ◽  
Clinical Associations ◽  
Acute Myeloid

Abstract Background Recurrent somatic mutation in RNA splicing machinery genes have been identified in a substantial proportion of patients with myelodysplastic syndrome (MDS). The majority of patients with acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) or with therapy-related acute myeloid leukemia (tAML) are associated with multilineage dysplasia. However, the clinical and biologic characteristics of AML-MRC and tAML with spliceosome mutations have not been elucidated. Thus, the objective of this study was to evaluate the frequency, clinical associations, and prognostic significance of spliceosome mutations in patients with AML-MRC and tAML. Methods A total of 224 patients were included in this study, consisting 190 cases of AML-MRC and 34 of tAML. U2AF1, SRSF2, and SF3B1 mutations are the three most frequent genes involved with spliceosome mutations in myeloid malignancies, and these mutations were detected using standard PCR techniques and direct sequencing. Results Spliceosome mutations in U2AF1 (S34 and Q157), SRSF2 (P95), and SF3B1 (primarily K700E) were found in 19 (8.5%), 13 (5.8%), and 7 (3.1%) of the 224 patients, respectively. These mutations were mutually exclusive and 17.4% of the patients had one of these mutations. As shown in Table 1, patients with spliceosome mutations had a higher rate of AML-MRC, a prior history of MDS or MDS/myeloproliferative neoplasm (MPN), and intermediate cytogenetic risk compared to patients without mutations. Only one patient with tAML had a spliceosome mutation. Of the patients with AML-MRC diagnosed based solely on MDS-related cytogenetics, only one patient had the U2AF1 mutation. Within the mutation-positive patients, the U2AF1 mutation was associated with younger age (median 47 vs. 66.5 years for other types; P < 0.001), lower WBC count (median 2.4 vs. 10.75 • 109/L for other types; P < 0.001), and higher rate of trisomy 8 (36.8% vs. 0.0% for other types; P = 0.003). The SRSF2 mutation was associated with normal karyotype (61.5% vs. 23.1% for other types, P = 0.03), and the SF3B1 mutation was associated with the presence of ring sideroblasts (71.4% vs. 18.8% for other types, P = 0.012) and a higher rate of complex karyotype (42.9% vs. 3.1% for other types, P = 0.01). There was a trend of male dominance (76.9%) for SRSF2 mutation and a higher frequency of adverse cytogenetic risk (57.1%) for SF3B1 mutation. At the median follow-up of 7.3 months, 122 (54.5%) deaths and 161 (71.9%) events were documented. Overall survival (P = 0.752) and event-free survival (P = 0.864) were similar among patients with or without one of the three mutations, U2AF1, SRSF2, or SF3B1 mutations. Conclusion U2AF1 was the most frequently mutated spliceosome gene among patients with AML-MRC and tAML. The association of spliceosome mutation with a preceding MDS or MDS/MPN suggests that spliceosome mutation has a unique role in the pathogenesis of progression. Although spliceosome mutations were associated with distinct clinical and biologic features in the cohort presented in this study, none of the features were prognostically relevant. Disclosures: Cho: Asan Institute for Life Sciences: Research Funding. Chi:Asan Institute for Life Sciences: Research Funding. Park:Asan Institute for Life Sciences: Research Funding.

Clonal Heterogeneity As Detected by Metaphase Karyotyping Is an Indicator of Poor Prognosis in Acute Myeloid Leukemia

2013 ◽  
Vol 31 (31) ◽  
pp. 3898-3905 ◽  
Author(s):  
Tilmann Bochtler ◽  
Friedrich Stölzel ◽  
Christoph E. Heilig ◽  
Christina Kunz ◽  
Brigitte Mohr ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Poor Prognosis ◽  
Clonal Evolution ◽  
Prognostic Significance ◽  
Genomic Diversity ◽  
Prognostic Information ◽  
Clonal Heterogeneity ◽  
Landmark Analyses ◽  
Acute Myeloid

Purpose In acute myeloid leukemia (AML), studies based on whole-genome sequencing have shown genomic diversity within leukemic clones. The aim of this study was to address clonal heterogeneity in AML based on metaphase cytogenetics. Patients and Methods This analysis included all patients enrolled onto two consecutive, prospective, randomized multicenter trials of the Study Alliance Leukemia. Patients were newly diagnosed with non-M3 AML and were fit for intensive chemotherapy. Results Cytogenetic subclones were detected in 418 (15.8%) of 2,639 patients from the whole study population and in 418 (32.8%) of 1,274 patients with aberrant karyotypes. Among those, 252 karyotypes (60.3%) displayed a defined number of distinct subclones, and 166 (39.7%) were classified as composite karyotypes. Subclone formation was particularly frequent in the cytogenetically adverse group, with subclone formation in 69.0%, 67.1%, and 64.8% of patients with complex aberrant, monosomal, and abnl(17p) karyotypes (P < .001 each). Two-subclone patterns typically followed a mother-daughter evolution, whereas for ≥ three subclones, a branched pattern prevailed. In non–core binding factor AML, subclone formation was associated with inferior event-free and overall survival and was confirmed as an independent predictor of poor prognosis in multivariate analysis. Subgroup analysis showed that subclone formation adds prognostic information particularly in the cytogenetic adverse-risk group. Allogeneic stem-cell transplantation improved the prognosis of patients with subclone karyotypes as shown in landmark analyses. Conclusion Cytogenetic subclones are frequent in AML and permit tracing of clonal evolution and architecture. They bear prognostic significance with clonal heterogeneity as an independent adverse prognostic marker in cytogenetically adverse-risk AML.

scholarly journals CD56 Is an Unfavorable Prognostic Factor for Acute Promyelocytic Leukemia: Results By Multivariate Analyses in the JALSG-APL204 Study

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2798-2798
Author(s):  
Akihiro Takeshita ◽  
Norio Asou ◽  
Yoshiko Atsuta ◽  
Hiroaki Furumaki ◽  
Toru Sakura ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Maintenance Therapy ◽  
Research Funding ◽  
Prognostic Significance ◽  
Surface Markers ◽  
Free Survival ◽  
Chugai Pharmaceutical ◽  
Otsuka Pharmaceutical ◽  
Cd56 Expression ◽  
Wbc Count

Abstract Background: CD56 expression is reported to be associated with adverse prognosis in patients with acute promyelocytic leukemia (APL) treated with all-trans retinoic acid (ATRA) and chemotherapy (Murray et al, 1999, Ferrara et al, 2000, Montesinos et al, 2011, Ono T et al, 2014). However, the prognostic significance of CD56 has not been elucidated, particularly when more potent agents are used. We recently reported long term analysis of the Japan Adult Leukemia Study Group (JALSG) APL204 study and concluded that maintenance therapy with tamibarotene was more effective than ATRA by reducing relapse in APL patients (Takeshita et al, 2018). In this study, the clinical significance of CD56 was evaluated with other surface markers on APL cells. Patients and Methods: Newly diagnosed APL patients with documented cytogenetic and/or molecular evidence of t(15;17)/PML-RARA were registered to the APL204 study from April 2004 to December 2010. The eligibility criteria included age between 15 and 70 years, ECOG performance status between 0 and 3, and sufficient function of organs. Induction therapy was composed of ATRA and chemotherapy whose dose and duration were based on initial white blood cell (WBC) count. Patients who achieved molecular remission after three courses of consolidation therapy were randomly assigned to maintenance therapy with tamibarotene 6 mg/day for 14 days or ATRA 45 mg/day for 14 days, which was repeated every 3 months for 2 years. The primary endpoint was hematological or molecular relapse-free survival (RFS). Surface markers, including CD56, were defined as positive if more than 10% of the CD45-gated cells expressed a specific antigen. Clinical characteristics were compared by the chi-square test or the Fisher's exact test for categorical data and the Wilcoxon rank-sum test for continuous data. RFS, overall survival (OS) and event-free survival (EFS) were estimated by the Kaplan-Meier method, and compared using the log-rank test. Cumulative incidence of relapse (CIR) was compared by Gray's test. Multivariate analyses were also performed by the Cox-proportional-hazards-model. Clinical outcomes were renewed between January 2016 and June 2017 and the median follow-up period was 7.3 years. This study is registered at the University Hospital Medical Information Network Clinical Trials Registry as C000000154. Results: Of the 344 eligible patients, 319 (93%) achieved CR. After completing consolidation chemotherapy, 269 patients underwent maintenance random assignment; 135 to ATRA, and 134 to tamibarotene. Among 344 eligible patients, 325 were assessable for CD-phenotypes, and 45 (14%) were CD56-positive (CD56+). Among 269 patients who underwent the maintenance assignment, 34 (13%) were CD56+. CD56 expression was significantly associated with obvious bleeding (p<0.001). The CR rate and mortality during induction therapy were not significantly different compared with CD56- APL. RFS and CIR was significantly inferior in CD56+ APL (77% vs. 91%, HR 3.04, 95% CI 1.34-6.90, p=0.005 and 24% vs. 8%, p=0.004, respectively), whereas OS was not significantly different between the two groups 80% vs. 89%, p=0.069). In patients whose initial WBC counts were more than 3.0 x 109/L, RFS for the CD56+ group (n=14) was significantly inferior (64% vs. 87%, p=0.028), while in patients whose initial WBC count was under 3.0 x 109/L (n=20), RFS was not different (85% vs. 93%, p=0.164). Other surface markers such as CD13 and CD33 did not show any prognostic significance except for CD34 (p=0.040). By multivariate analysis, CD56 expression was an independent unfavourable prognostic factor for RFS (HR=3.19, 95% CI 1.40-7.25, p=0.006) together with more than 3.0 x 109/L WBC counts (p=0.001) and the ATRA arm in maintenance therapy (p=0.028). Conclusions: CD56 expression is an independent unfavorable prognostic factor for RFS in APL patients treated with ATRA and chemotherapy followed by ATRA or tamibarotene maintenance therapy, especially in patients whose initial WBC count was more than 3.0 x 109/L. The present study supports the prognostic significance of CD56 in the treatment of APL using more potent agents. Figure. Figure. Disclosures Takeshita: Chugai Pharmaceutical Co. Ltd.: Research Funding; Pfizer Japan Inc.: Research Funding; Astellas Pharma Inc.: Research Funding; Takeda Pharmaceutical Co. Ltd.: Research Funding; Bristol-Myers Squibb Co.: Research Funding; Kyowa Hakko Kirin Co. Ltd.: Research Funding. Asou:Asahi Kasei Pharma Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; SRL Inc.: Consultancy; Yakult Honsha Co., Ltd.: Speakers Bureau; Kyowa Hakko Kirin Co., Ltd.: Speakers Bureau; Astellas Pharma Inc.: Research Funding; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding. Sawa:Celgene Corporation: Honoraria; Takeda Pharmaceutical Company Limited: Honoraria; Bristol-Myers Squibb: Honoraria; Novartis International AG: Honoraria; CHUGAI PHARMACEUTICAL CO., LTD.: Honoraria; Mundipharma K.K.: Honoraria. Dobashi:Celgene Co.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Zenyaku Kogyo Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co. Ltd.: Research Funding; Astellas Pharma Inc.: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Pfizer Inc.: Research Funding; Sysmex Co.: Research Funding. Kobayashi:Pfizer: Research Funding; Ohtuka: Research Funding; Astellas: Research Funding. Kiyoi:Kyowa Hakko Kirin Co., Ltd.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; Bristol-Myers Squibb: Honoraria; FUJIFILM Corporation: Research Funding; Celgene Corporation: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Sanofi K.K.: Research Funding; Astellas Pharma Inc.: Research Funding; Zenyaku Kogyo Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Phizer Japan Inc.: Research Funding; Takeda Pharmaceutical Co., Ltd.: Research Funding; Novartis Pharma K.K.: Research Funding; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding.

scholarly journals Analysis of Clonal Evolution of AML Using Simultaneous Single-Cell DNA/RNA Analysis

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 1-1
Author(s):  
Ryosaku Inagaki ◽  
Masahiro Marshall Nakagawa ◽  
Yasuhito Nannya ◽  
Qi Xingxing ◽  
Lanying Zhao ◽  
...  
Keyword(s):  
Single Cell ◽  
Signaling Pathway ◽  
Research Funding ◽  
Clonal Evolution ◽  
Blast Cell ◽  
Driver Mutations ◽  
Advisory Committees ◽  
Ras Pathway ◽  
Blast Cells ◽  
Blast Count

Background Acute myeloid leukemia (AML) was defined by an increase of immature myeloid cells, or blasts that exceed ≥20% in bone marrow or peripheral blood. Many lines of evidence suggest that the development of AML is shaped by clonal evolution through multiple rounds of positive selection driven by newly acquired mutations, ultimately leading to an increased blast count. This process has been analyzed in detail in the case of progression from myelodysplastic syndromes (MDS) to secondary AML (sAML), which is invariably accompanied by expansion of cells that acquired new driver alterations, generating clonal substructures in many cases (Walter et al. NEJM. 2012, Makishima et al. Nat. Genet. 2015). However, it has not been fully elucidated how these newly acquired mutations contribute to increased blast cells that define AML. Results In order to understand how driver mutations contribute to the phenotype of blasts, we first focused on the driver mutations that have known to be enriched in sAML, including those in IDH1/2, NPM1, FLT3,NRAS, KRAS, PTPN11, CBL and WT1, and compared BM blast count (BC) and mutant cell fraction (MCF) of each driver mutation in 27 cases with sAML. Compared with BC, IDH1- or IDH2-mutated cells exhibited a larger MCF in most cases, suggesting that newly acquired IDH1/2 mutations contribute clonal expansion but only a part of the expanded cells undergo differentiation block and the remaining cells can differentiate into mature cells. Of interest, we observed lower MCFs than BC in approximately half of the cases with signaling pathway mutations, including FLT3 and RAS pathway (NRAS, KRAS, PTPN11 and CBL) mutations, in which MCFs for signaling pathway mutation accounted for less than 2/3 of BC, which was also observed in de novo AML cases. In fact, signaling pathway mutations in two representative cases were confirmed to account only for 30.4% and 3.4% of blast cells, using ddPCR of the blast cells collected as the CD45dim SSClow fraction, which were confirmed to show a blast morphology. These results suggest a possibility that the presence of mutant cells might affect the phenotype of the surrounding unmutated cells. Thus, to investigate the mechanism of such non-cell autonomous effects of mutations on blast cell morphology, we developed an advanced single-cell sequencing platform that enables simultaneous measurements of both mutations and gene expression profiles at a single-cell level and applied this to the analysis of immature (CD34+ Lin-) BM cells from 2 sAML cases with multiple RAS pathway mutations showing disproportionately small MCF compared to BC, in which gene expression of mutated and unmutated cells were evaluated separately. The same BM faction in 13 healthy donors was also analyzed as normal control. In single-cell mutation analysis, multiple RAS pathway mutations in both cases represented independent clones. As expected, cells carrying each RAS pathway mutation at sAML showed an immature myeloid phenotype. However, most of the cells, even carrying MDS mutations alone, also exhibited an immature myeloid phenotype similar to the RAS pathway mutated cells, although the latter cells showed upregulated RAS signaling compared with the former cells. Cells solely carrying MDS mutations in MDS phase showed multi-lineage differentiation, which was no longer observed in those cells in sAML phase. This was in contrast to another case who acquired MYC amplification on sAML progression, where nearly all cells having MYC-amplification showed an immature myeloid phenotype, whereas the remaining MDS clones lacking MYC-amplification retained multilineage differentiation even at the sAML phase. These results suggest that RAS mutants might have a non-cell autonomous effect on the surrounding cells including those hematopoietic cells lacking those mutations and other stromal cells, preventing their differentiation to mature cells, although we cannot exclude another possibility that altered BM microenvironment could influence the phenotype of both mutated and unmutated cells. Conclusions Although an acquisition of new mutations is essential for the progression of MDS to sAML, our results suggest that the blast cell phenotype may not solely be determined by cell-intrinsic effects of such mutations, but non-cell autonomous effects of mutated cells (and possibly also of an altered BM microenvironment) may have a role in increased blast count and therefore AML progression. Disclosures Inagaki: Sumitomo Dainippon Pharma Co., Ltd.: Current Employment. Nakagawa:Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Ogawa:KAN Research Institute, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Eisai Co., Ltd.: Research Funding; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding; Asahi Genomics Co., Ltd.: Current equity holder in private company; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Chordia Therapeutics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding.

scholarly journals Single Cell Sequencing of Pediatric Acute Myeloid Leukemia Reveals Clonal Evolution to Relapse on Combination Chemotherapy with Sorafenib

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3470-3470
Author(s):  
Cheryl A C Peretz ◽  
Vanessa E Kennedy ◽  
Rhonda E. Ries ◽  
Soheil Meshinchi ◽  
Catherine C. Smith
Keyword(s):  
Myeloid Leukemia ◽  
Research Funding ◽  
Pediatric Patients ◽  
Clonal Evolution ◽  
Pediatric Acute Myeloid Leukemia ◽  
Genetic Complexity ◽  
Flt3 Mutations ◽  
Major Clone ◽  
Pediatric Aml ◽  
Relapsed Disease

Abstract Introduction: Relapse of pediatric acute myeloid leukemia (AML) remains a leading cause of childhood cancer mortality, and leukemias with activation of the Fms-like tyrosine kinase 3 (FLT3) are particularly susceptible to relapsed disease. Risk-directed therapy to prevent relapse is based both on genetic changes known to drive drug resistance, and measurable residual disease (MRD) at the end of induction therapy (EOI). In adult AML, resistance to type II FLT3-inhibitors, like sorafenib, is primarily driven by on-target FLT3 kinase domain (KD) mutations. However, the resistance mechanisms for pediatric leukemias, which are treated on combination therapies, have not been fully elucidated. MRD is considered the among the most predictive markers of future relapsed disease. It has been assumed that the major clone at the time of MRD assessment will predict the majority clone at relapse. However, this assumption has not been proven. The definition of the most specific genetic and MRD markers of relapse are essential to prognosticate and personalize therapy to prevent relapsed disease. Methods: We performed single cell sequencing (SCS) with a high-throughput DNA sequencing platform, Mission Bio Tapestri, on bone marrow or peripheral blood samples from 24 samples from 8 pediatric patients treated on COG AAML1031 with serial samples from diagnosis, EOI, and relapse. Results: We analyzed a total of 94,833 cells from 8 pediatric patients (median cells per patient 12,428) all treated on AAML1031. SCS revealed a sensitive and specific description of clonal evolution on the combination of sorafenib with cytotoxic chemotherapy. The FLT3 internal tandem duplication (ITD) was controlled by the therapy in only half of the patients. In five of the patients, the FLT3-ITD was present in multiple clones. The FLT3-ITD co-mutated with additional mutations (NRAS, SH2B3, WT1, TET2, or NPM1) in half of the patients. However, the presence of a co-mutation did not necessarily correlate with whether or not the ITD-containing clone persisted at the time of relapse. Of the leukemias whose relapse was not driven by FLT3, the most likely mutational driver of resistance was NRAS. Notably, however, despite the fact that FLT3 KD mutations make up the bulk of mutational resistance to type II FLT3i such as sorafenib in adult patients, there were no on-target FLT3 mutations found in any of these pediatric patients. Further, SCS allows for an unprecedented depth of analysis of the genetic complexity of pediatric AML. Phylogenic analysis revealed that the same mutations may arise independently in different cells (NPM1 W288fs, NRAS G60E). Additionally, the same gene may be mutated twice within the same cell (WT1, TET2). These data, consistent with our prior work, suggest that some leukemias may have a predilection to mutations within specific loci. Finally, although there is a standing assumption that the dominant MRD population will proliferate into relapsed disease, in 3/8 patients, the dominant MRD clone did not predict the dominant relapse clone. Conclusions: SCS allows for direct measurement of clonal hierarchy and evolution, phylogeny, co-mutational status, and zygosity, which can only be inferred through traditional bulk NGS. The mutational mechanisms of resistance seen in adult leukemias treated with sorafenib monotherapy are not necessarily relevant to the pediatric population; rather than on-target FLT3 mutations, off target mutations including NRAS are found. This corroborates prior findings that off-target RAS pathway mutations may drive resistance to FLT3i. Non-RAS off-target mutations found in this cohort do not necessarily predict sorafenib resistance, so may be passenger mutations. The lack of consistent resistance mutations suggests that other mechanisms of resistance such as epigenetic modifications may also drive resistance to combination chemotherapy with FLT3i in pediatric leukemia. Further, SCS exposes more genetic complexity in pediatric AML than has previously been appreciated: the same mutation may independently arise in more than one cell or the same cell may have multiple mutations within the same gene. Finally, the sensitivity of SCS reveals that the major clone at the time of MRD assessment is not necessarily the major clone at relapse. This suggests a benefit of more frequent MRD monitoring to track clonal evolution in real time. Disclosures Smith: Daiichi Sankyo: Consultancy; Revolutions Medicine: Research Funding; AbbVie: Research Funding; Amgen: Honoraria; FUJIFILM: Research Funding; Astellas Pharma: Consultancy, Research Funding.

scholarly journals Combining the Number of Infectious Episodes and Interval of Chemotherapy to Transplantation May Predict a Transplant Outcome in Patients with Acute Myeloid Leukemia: A Retrospective Analysis of JALSG AML201 Study

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4643-4643
Author(s):  
Satoshi Kaito ◽  
Noriko Doki ◽  
Yuho Najima ◽  
Shigeki Ohtake ◽  
Hitoshi Kiyoi ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Cell Transplantation ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Severe Infection ◽  
Hematopoietic Stem ◽  
Infectious Episode ◽  
Transplant Outcome ◽  
Otsuka Pharmaceutical ◽  
Acute Myeloid

Abstract Background Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a potentially curative therapy for acute myeloid leukemia (AML), but non-relapse mortality (NRM) remains obstacles to this treatments. Therefore, precise comorbidity evaluation before transplantation is crucial for better outcomes. One of the most frequently used tools for assessing the risk profile of transplant recipients is the hematopoietic cell transplantation comorbidity index (HCT-CI), which only incorporates information of the antibiotics use on day 0 as an infection-related factor, however, some important components, such as the number and severity of infectious episodes, are not included. Methods From December 2001 to December 2005, 1,057 newly diagnosed adult AML patients were registered to JALSG AML201 (Blood 2011; 117: 2358-65, 2366-72). Of them, the 121 evaluable patients who underwent allo-HSCT in the first hematological complete remission were analyzed. We have checked the above mentioned components, in addition to the interval from the last chemotherapy to transplantation, in these 121 patients and analyzed whether these factors might affect the subsequent transplant outcome. Results The median age was 37 years (range, 15-61). Regarding cytogenetic risk, 7 (6%), 92 (76%), and 15 (12%) patients were categorized as favorable, intermediate and high risk, respectively. The median follow-up period after transplantation was 939 days (range 19-2204). At 2 years after allo-HSCT, overall survival, leukemia free survival, cumulative incidence of relapse (CIR), and NRM for all patients were 73.2%, 65.4%, 19.4%, and 15.8%, respectively. A total of 106 (88%) patients developed at least one infectious episode as 102 (84%) patients faced to febrile neutropenia (FN), 45 (37%) patients experienced severe infection (≥ grade 3), and 27 (22%) patients eventually developed sepsis. Regarding the episode of FN, 52 (43%) patients experienced more than 2 times during chemotherapy. The median cycles of chemotherapy before transplantation was 4 (range, 1-6) and the median interval from the first day of last chemotherapy to transplantation was 77 days. The ROC curve indicated mild correlations between NRM and the interval with an area under the curve of 52% and the cutoff value at 113 days. The number of infectious episodes or severity of infection did not carry a significant impact on NRM at 2 years as 19.2% in FN with ≥3 episodes vs. 13.2% in FN with 0-2 episodes; p=0.18, 18.0% in patients with severe infection vs. 14.5% in patients without severe infection; p=0.49. However, in view of bone marrow transplant (BMT) recipients (n=76), multiple FN episodes was significantly associated with higher NRM (23.5% vs. 7.2% at 2 years, p=0.029) (Fig 1A). While, the relative shorter interval (<113 days) from the first day of last chemotherapy to transplantation might have a negative impact on NRM as 19.4% vs. 6.2% at 2 years, p=0.054 (Fig 1B), but not affect CIR rate (18.4% vs. 22.3% at 2 years, p=0.67). Furthermore, the relative shorter interval in BMT recipients with multiple FN episodes showed a significant adverse impact on NRM (32.0% vs. 0% at 2 years, p=0.038) (Fig 1C). Conclusion Combining the number of infectious episodes and interval of chemotherapy to transplantation may predict a transplant outcome in AML patients. Providing an adequate interval from the last chemotherapy to transplantation may reduce NRM especially in BMT recipients who developed multiple FN episodes during induction or consolidation chemotherapy. Figure 1. Figure 1. Disclosures Kiyoi: Astellas Pharma Inc.: Research Funding; Novartis Pharma K.K.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; Zenyaku Kogyo Co., Ltd.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Takeda Pharmaceutical Co., Ltd.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Sanofi K.K.: Research Funding; Celgene Corporation: Research Funding; FUJIFILM Corporation: Research Funding; Phizer Japan Inc.: Research Funding; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding; Bristol-Myers Squibb: Honoraria. Naoe:Nippon Shinyaku Co., Ltd.: Research Funding; Astellas Pharma Inc.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Fujifilm Corporation: Patents & Royalties, Research Funding; Pfizer Japan Inc.: Research Funding; Toyama Chemical Co., Ltd.: Research Funding.

scholarly journals Co-Occurring Mutation Clusters Predict Drug Sensitivity in Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 12-13
Author(s):  
Guangrong Qin ◽  
Shmulevich Ilya ◽  
Taek-Kyun Kim ◽  
Bahar Tercan ◽  
Timothy J Martins ◽  
...  
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Drug Sensitivity ◽  
Clonal Evolution ◽  
Transcriptional Dysregulation ◽  
Drug Sensitivity Prediction ◽  
Higher Sensitivity ◽  
Acute Myeloid

Background The molecular origin of cancer drug resistance is not apparent for most cases of acute myeloid leukemia (AML). Clonal evolution appears to be associated with increasing drug resistance. We sought to determine whether the mutation patterns are associated with drug susceptibility in AML. Methods Seventy-two patient blood or marrow samples were enriched for CD34+ blasts by immunomagnetic bead selection. High throughput drug sensitivity screens were performed for 223 drugs after a 72-hour exposure to 8-12 customized drug concentrations (within the range of 5pM to 100µM) of each drug spanning 4-5 logs. Post exposure viability was determined using CellTiter Glo luminescent reagent. XLFit was used to analyze the data and generate dose response curves based on a standard 4-parameter logistic fit. Mutation analysis was performed by MyAML™ utilizing next generation sequencing (NGS) to analyze the 3' and 5' UTRs and exonic regions of 194 AML-associated genes and genomic breakpoints. Co-mutation and mutual exclusivity scores of gene aberrations were computed using three different statistical methods on three large publicly available datasets: 1) TCGA-AML, 2) BeatAML, and 3) data from 1540 patients (Moritz Gerstung, et al., Nat Genet. 2017). The scores for each co-mutation or mutually exclusive gene pair were then logarithmically transformed from the aggregated p-value using a robust rank aggregation method and used to construct a graph from which communities of co-mutated genes could be detected, resulting in higher mutual exclusivity between modules and higher co-occurrence within modules. Results We identified five main groups of co-mutations, including the following: 1) RUNX1 group, 2) CEBPA group, 3) NPM1 group, 4) TP53 group, and 5) RAS group (see Fig 1A). The co-mutation community in the RUNX1 group is featured with transcriptional dysregulation (RUNX1, ASXL1 and EZH2), and dysregulation in splicing (U2AF1, SRSF2 or SF3B1). The TP53 and CEBPA groups exhibit transcriptional dysregulation, and transcription factor alterations. The NPM1 and RAS groups exhibit signaling alteration, particularly the Ras/MAPK signaling pathway. Among each co-mutation community, the variant allele frequencies (VAFs) exhibited differences for specific mutations. For example, in the NPM1 group, FLT3 exhibits the lowest VAF, followed by NPM1 while DNMT3A shows the highest VAF. The five co-mutation groups are associated with different overall survival, including better survival for the CEBPA group and poorer survival for the TP53 group. Within each co-mutation group, specific associations with overall survival were detected, including better survival for NPM1-RAD21 co-mutated vs. wild type (WT), better survival for WT vs. ASXL1-RUNX1 co-mutated, worse survival for DNMT3A-FLT3 co-mutated vs. WT, and others. We also found that the co-mutation clusters were different between the de novo and relapse groups. Most importantly, we found significant correlations with drug sensitivity for the different co-occurring mutation groups. Cells from patients with mutations in the NPM1 co-mutation group show higher sensitivity to most of the drugs, including the tyrosine kinases inhibitors and PI3K-AKT-MTOR inhibitors. Cells from patients with mutations in the RAS cluster exhibited sensitivity to MEK inhibitors (Fig 1B), while cells from patients with mutations in the TP53 cluster show resistance to many drugs, including the MDM2 inhibitor AMG232 (Fig 1C). By mapping the mutated genes and drug targets into signaling pathways, we found that mutations in downstream signaling of the drug target exhibited resistance, while mutations in upstream signaling conferred higher sensitivity. We also constructed drug sensitivity prediction models based on the co-mutation groups. Conclusion We detected co-mutation groups through integrative analysis of large publicly available AML data sets. Patients with mutations in different groups of genes show different overall survival, while cells from patients with mutations in different co-mutation groups show different drug sensitivity. The co-mutation groups may not only reflect the clonal evolution history of AML, but also serve as important features for drug sensitivity prediction. Disclosures Carson: Invivoscribe, Inc: Current Employment. Patay:Invivoscribe, Inc: Current Employment. Becker:Cardiff Oncology: Research Funding; Novartis: Research Funding; SecuraBio: Research Funding; JW Pharmaceutical: Research Funding; Glycomimetics: Research Funding; Abbvie: Research Funding; Bristol Myers Squibb: Research Funding; Pfizer: Research Funding; Invivoscribe: Research Funding; Accordant Health Services/Caremark: Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: There are ~200 drugs on the screening panel, and many would be off label for acute myeloid leukemia.

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