Single Cell Mutation Analysis Delineates Clonal Architecture in Leukemic Transformation of Myeloproliferative Neoplasms

Abstract Introduction. Myeloproliferative neoplasms (MPN) are clonal disorders of hematopoietic stem cells that include polycythemia vera, essential thrombocythemia, and primary myelofibrosis. 10-20% of MPN pts transform to secondary acute myeloid leukemia (sAML), unresponsive to conventional therapy and associated with dismal outcome (Dunbar A, 2020). In addition to somatic driver mutations affecting JAK2, CALR or MPL, several additional variants are harbored by MPN pts inb chronic phase, and a restricted set of them were associated with risk of leukemic evolution (Vannucchi AM, Leukemia 2013; Tefferi A, Blood ASdv 2016) However, the molecular mechanisms underlying leukemic transformation remain largely unknown. Although bulk next generation sequencing (NGS) highlights the overall mutation landscape, it cannot distinguish which mutations occur in the same clone(s), nor elucidate the order of mutations or resolve clonal complexity. Conversely, single-cell sequencing (SCS) might allow to resolve clonal heterogeneity and reconstruct clonal phylogenies at each disease phase (Parenti, NPJ Prec Onc 2021)). Aim: To delineate the clonal landscape of sAML, we performed single-cell mutational profiling in 10 pts with MPNs who progressed to sAML. Methods. There were 2 set of samples/approaches: (i) 15 paired samples (chronic (CP)/blast phase (BP)) from 7 pts were analyzed using the Mission-Bio Tapestri platform and the Myeloid panel in order to target SNVs and indels across 45 myeloid genes with 312 amplicons. In one pt we also analyzed an intermediate phase corresponding to progression from PV to PPV-MF before BP development. (ii) 7 further paired CD34+ samples from 3 pts were analyzed using a 239-amplicon custom panel including 29 genes frequently mutated in myeloid neoplasms. SCS libraries were sequenced on Illumina Novaseq. Data were processed by using Mission Bio's Tapestri Pipeline and analyzed with Mission Bio's Tapestri Insights software package and R software. CNV analysis was performed by using an integrated pipeline for multiomics analysis (Mosaic, Mission Bio) Results. (i) A total of 78,354 single cells were sequenced (average 5,223) using Tapestri Myeloid panel, with an average of 28,303 reads per cell and coverage of 97X. SCS was able to identify 17 low-frequency variants not detected in bulk analysis; however, it failed to discriminate homopolymeric regions including the ASXL1 G646Wfs*12. (ii) A total of 25,417 single cells were sequenced (average 3636) using a custom panel, with a coverage of 186X and an average Allele Dropout Rate of 8.6%. This panel was able to identify ASXL1 G646Wfs*12 variant. Overall, we found a significant correlation of variant allele frequency (VAF) measured by bulk and SCs approach (R =0.84, p<.0001). Epigenetic variants (i.e. ASXL1, TET2, EZH2) account for around half of the mutations and affect a large fraction of CP cells (3 representative samples in Fig.1). In 8/10 pts, leukemic clone emerged from a driver mutation-positive cells (JAK2V617F n=4; CALR Type1 n=4). In all pts we are able to identify at least 3 mutated clones and in 7 pts the dynamics of the clones allowed to identify the one(s) responsible for evolution to sAML. In 7/10 pts, the leukemic clones were already detectable at low frequency (<2%) at CP and became dominant in BP; these low-frequency clones were missed by bulk sequencing. Furthermore, SCS revealed acquisition of 3 mutually exclusive mutations in RAS pathway in one pt: two NRAS mutations and a KRAS mutation. Copy number variation (CNV) could be assessed in 4 pts. Of note, during progression to sAML, we found single cells with amplification of ETV6 (>20 copies in 2 pts), NRAS (8 copies in 2pts) and BRAF (8 copies in 2pts). Other subclonal ploidy abnormalities were also observed in RUNX1, EZH2, U2AF1 and ZRSR2 (5-18 copies). Conclusions. Together, these data suggest that MPN present a complex clonal combination evolving over time. SCS allows to resolve this milieu, that is largely missed by conventional bulk NGS, in particularly SCS identifies rare leukemia-driving clones that were already present in chronic phase and describes their dynamics during leukemic progression. Leukemic transformation after MPN is a highly heterogeneous process with mutations and CNVs acquired in different genes and different clones. Overall, our findings provide further insights into the pathogenesis of AML transformation of MPN. Supported by AIRC, Mynerva project no.21267 Figure 1 Figure 1. Disclosures Vannucchi: BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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The JAK2V617F Stem Cell Burden Is Mosaic, Dynamic and Correlates with Clinical Disease Burden in the MPN: An Exploitable Target

Blood ◽

10.1182/blood.v126.23.4090.4090 ◽

2015 ◽

Vol 126 (23) ◽

pp. 4090-4090

Author(s):

Alison R Moliterno ◽

Donna Marie Williams ◽

Jonathan M. Gerber ◽

Michael A McDevitt ◽

Ophelia Rogers ◽

...

Keyword(s):

Stem Cells ◽

Stem Cell ◽

Single Cell ◽

Board Of Directors ◽

Disease Burden ◽

Disease Duration ◽

Single Cells ◽

Advisory Committees ◽

Allele Burden ◽

Wide Range

Abstract Introduction: Essential thrombocytosis (ET), polycythemia vera (PV), and myelofibrosis (MF; post ETMF, post PVMF and primary MF) share the JAK2V617F mutation, but differ with regard to clinical phenotype, rate of disease progression, and risk of transformation. Variation in the JAK2V617F neutrophil allele burden does not account for these observed differences in clinical behavior or natural history. We therefore investigated the JAK2V617F burden and JAK2 genotype composition in the hematopoietic stem cell (HSC) population of MPN patients. Methods: We studied 47 JAK2V617F-positive MPN patients during 51 distinct disease phases. Circulating CD34+ cells were flow-sorted based on the stem cell markers CD34, CD38 and aldehyde dehydrogenase (ALDH). CD34+ CD38- ALDH+ HSC were sorted into 96 well plates and single cell JAK2 genotypes (average 40 single cells genotyped/patient with >1000 total single cells genotyped) were obtained using a nested PCR assay. Additional genomic lesions and chromosomal copy number variation were investigated in the sorted, single cell fractions in informative patients by FISH or multiplex single cell PCR. Distribution of JAK2V617F stem cell genotypes were correlated with disease phenotype, neutrophil JAK2V617F allele burden, splenomegaly, white cell count, chemotherapy requirement and disease evolution. Results: In all MPN cases, regardless of disease class, the JAK2V617F mutation was detected in the CD34+ CD38- ALDH+ fraction - the same population in which normal HSC reside. All ET and MF patients, and the majority of PV patients, had three JAK2 genotypes coexisting in their respective HSC populations. ET was characterized by a high percentage of JAK2WT stem cells (>75%) despite the concomitant presence of JAK2V617F homozygous clones and disease durations >15 years. Importantly, in the ET patients where JAK2WT clones fell to less than 50%, a PV phase followed. MF was characterized by a relatively low percentage of JAK2WT stem cells (median 24%), regardless of disease duration. PV had the most variable JAK2 genotypes with a wide range of JAK2WT stem cells (4%-92%) and a wide range of JAK2V617F homozygous stem cells (2-100%), and in 5/16 PV cases, only JAK2WT and JAK2V617F homozygous stem cells were identified. PV patients with JAK2V617F homozygous clones comprising more than 50% of their stem cells, regardless of disease duration, had higher white cell counts, higher neutrophil allele burdens, larger spleens and higher prevalence of chemotherapy compared to PV patients who had less than 50% JAK2V617F homozygous HSCs. The percentage of JAK2V617F homozygous HSC did not correlate with disease duration: some PV patients with a disease duration of >18 years had less than 10 % JAK2V617F homozygous HSC. A JAK2V617F - positive PV patient with a high JAK2V617F HSC burden and a high neutrophil JAK2V617F burden transformed to a JAK2V617F-negative chronic myelomonocytic leukemia (CMMoL); at the time of HSC analysis, the neutrophil JAK2V617F allele burden was 0% (previously 90%) and the HSC JAK2V617F homozygous percentage fell to 3% (previously 60%). While this patient's CMMoL was molecularly undefined, lesions identified in other JAK2V617F-positive patients (including mutations of ASXL1, TET2, deletion of 5q, 7q and 11q, trisomy 8 and 9), were also found in the CD34+ CD38- ALDH+ HSCs using single cell techniques, sometime coexistent with JAK2V617F-positive HSC, and sometimes in JAK2WT HSC. Conclusion: Driver and progression lesions in the JAK2V617F-positive MPN are acquired at the primitive HSC level. Despite decades of disease, the HSC pool in the MPN is mosaic for acquired lesions and also retains JAK2WT clones. Dominance of a particular JAK2 genotype at the primitive HSC level is variable, and distinguishes ET, where JAK2WT stem cells outnumber JAK2V617F-positive HSC, from MF, where JAK2WT HSC are the minority. PV is the most variable of the three MPN with regard to JAK2 genotype mosaicism. The allelic burden of HSC JAK2V617F in PV correlates with clinical disease burden. However, neither time nor JAK2V617F genotype determines the HSC burden in ET and PV, indicating that an undefined factor is a modifier of this important disease-defining process. Understanding the biology of HSC JAK2V617F homozygous clonal dominance may define an exploitable target to control disease burden, and to mitigate disease progression and evolution. Disclosures Moliterno: incyte: Membership on an entity's Board of Directors or advisory committees. Spivak:Incyte: Membership on an entity's Board of Directors or advisory committees.

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Comprehensive Genetic Interrogation of Circulating Multiple Myeloma Cells at Single Cell Resolution

Blood ◽

10.1182/blood.v128.22.800.800 ◽

2016 ◽

Vol 128 (22) ◽

pp. 800-800

Author(s):

Jens G Lohr ◽

Sora Kim ◽

Joshua Gould ◽

Birgit Knoechel ◽

Yotam Drier ◽

...

Keyword(s):

Single Cell ◽

Board Of Directors ◽

Rna Sequencing ◽

Research Funding ◽

Single Cells ◽

Advisory Committees ◽

Single Cell Rna Sequencing ◽

Genomic Characterization ◽

Whole Transcriptome

Abstract Continuous genomic evolution has been a major limitation to curative treatment of multiple myeloma (MM). Frequent monitoring of the genetic heterogeneity in MM from blood, rather than serial bone marrow (BM) biopsies, would therefore be desirable. We hypothesized that genomic characterization of circulating MM cells (CMMCs) recapitulates the genetics of MM in BM biopsies, enables MM classification, and is feasible in the majority of MM patients with active disease. Methods: To test these hypotheses, we developed a method to enrich, purify and isolate single CMMCs with a sensitivity of at least 1:10(5). We then performed DNA- and RNA-sequencing of single CMMCs and compared them to single BM-derived MM cells. We determined CMMC numbers in 24 randomly selected MM patient samples and compared them to numbers of circulating MM cells obtained by flow cytometry. We performed single-cell whole genome amplification of single cells from 10 MM patients, and targeted sequencing of the 35 most recurrently mutated loci in MM. A total of 568 single primary cells representing CMMCs, BM MM cells, CD19+ B lymphocytes, CD45+CD138- WBC from these patients were subjected to DNA-sequencing. By processing 80 single cells from four MM cell lines with known mutations we determined the mean sensitivity of mutation detection in single cells to be 93 ± 9%. In addition to DNA-sequencing we also isolated 57 single MM cells from the BM and peripheral blood of two MM patients and performed whole transcriptome single cell RNA-sequencing. Results: In 24 randomly selected MM patient samples we detected >12 CMMCs per 1ml of blood in all 24 patients. In comparison, by flow cytometry, we detected ≥10 CMMCs per 10(5) white blood cells in 10/24 cases (42%), ≥1 CMMC but ≤ 10 CMMCs in 13/24 cases (54%), and < 1 CTCs in 1/24 patients (4%). Mutational analysis of 35 recurrently mutated loci in 335 high quality single MM cells from the blood and BM of 10 patients, including one MGUS patient, revealed the presence of a total of 12 mutations (in KRAS, NRAS, BRAF, IRF4 and TP53). All targeted mutations that were detected by clinical-grade genotyping of bulk BM were also detected in single cell analysis of CMMCs. While in most patients, the fraction of mutated single cells was similar between blood and BM, in three patients, the proportion of MM cells harboring TP53 R273C, BRAF G469A and NRAS G13D mutations was significantly higher in the blood than in the BM, suggesting a different clonal composition. We developed an analytical model to predict whether a genetic locus underwent loss of heterozygosity, using the distribution of known allelic fractions of previously described mutations in MM cell lines as a benchmark. In two patients who simultaneously harbored two mutations, we predicted a BRAF G469E and a KRAS G12C mutation to be heterozygous, whereas the loci harboring a TP53 R273C and a TP53 R280T mutation were predicted to be associated with LOH with high statistical confidence. Whole transcriptome single cell RNA-sequencing of 57 MM cells from the BM and peripheral blood of two patients showed >3,700 transcripts per cell. Single-cell RNA-sequencing allowed for a clear distinction between normal plasma cells and MM cells, either based on analysis of CD45, CD27, and CD56 alone, or by unsupervised hierarchical clustering of detected transcripts in single cells. In addition, single cell CMMC expression analysis could be used to infer the existence of key MM chromosomal translocations. For example, CCND1 and CCND3 were highly upregulated in single MM cells from the blood and BM of two patients, whose MM was found by FISH analysis to harbor a t(11;14) and a t(6;14) translocation, respectively. Conclusion: We demonstrate that extensive genomic characterization of MM is feasible from very small numbers of CMMCs with single cell resolution. Interrogation of single CMMCs faithfully reproduces the pattern of somatic mutations present in MM in the BM, identifies actionable oncogenes, and reveals if somatic mutated loci underwent loss of heterozygosity. Single CMMCs also reveal mutations that are not detectable in the BM either by single cell sequencing or clinical grade bulk sequencing. Single cell RNA-sequencing of CMMCs provides robust transcriptomic profiling, allowing for class-differentiation and inference of translocations in MM patients. Disclosures Raje: Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Research Funding; Eli Lilly: Research Funding.

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Gene Expression Profiling of CD93-Selected CP-CML Stem Cells Confirms Their Quiescent Character and Biomarker Potential

Blood ◽

10.1182/blood.v128.22.4231.4231 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4231-4231

Author(s):

Gillian A. Horne ◽

Chinmay Rajiv Munje ◽

Ross Kinstrie ◽

Eduardo Gómez-Castañeda ◽

Helen Wheadon ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Single Cells ◽

Gene Clustering ◽

Single Cell Level ◽

Cell Level ◽

Advisory Committees ◽

Two Populations

Abstract The introduction of BCR-ABL tyrosine kinase inhibitors has revolutionized the treatment of chronic myeloid leukemia (CML). A major clinical aim remains the identification and elimination of low-level disease persistence, termed "minimal residual disease". Disease persistence suggests, that despite targeted therapeutic approaches, BCR-ABL-independent mechanisms exist which sustain the survival of a small population of cells, termed leukemic stem cells (LSC). We previously identified CD93 expression as a promising biomarker of LSC in chronic phase (CP)-CML. Our group has described the long term self-renewal potential of Lin-CD34+93+ CP-CML cells compared to their Lin-CD34+93- counterparts through LTCIC assays (n=3, p<0.0001) and NSG engraftment models (3.5-30-fold increased in engraftment with Lin-CD34+93+ cells, p<0.03). We hypothesized that CD93+-selected cells would represent a more immature functional phenotype compared to CD93- selected cells. The aim of this study was to characterize differences in the gene expression profile between CD93+ and CD93- CML LSC populations and determine heterogeneity of each population at a single cell level. To interrogate this, we initially identified CP-CML subpopulations with the greatest functional capability compared to normal. Normal and CP-CML samples were FACS-sorted into HSC/LSC, CMP, GMP, and MEP sub-populations. Results suggest a significant change in functional status between normal and CP-CML subpopulations within the HSC/LSC compartment (lin-CD34+CD38-CD45RA-CD90+), where CML LSC demonstrated significantly increased proliferation (14 fold expansion; P<0.001) compared to normal HSC (no expansion) after 5 days in vitro culture in physiological growth factors. In addition, equivalent numbers of CML LSC produce ~4-fold more colonies in colony forming cell (CFC) assays than normal HSC (329±56 versus 86±17 per 2,000 cells, respectively (p<0.05)). Furthermore, fluorescence in situ hybridization demonstrated that >90% of lin-CD34+CD38-CD45RA-CD90+ CML LSC from all patient samples were BCR-ABL positive. Subsequent experiments were confined to the LSC population. We hypothesized that lin-CD34+CD38-CD90+CD93- CML cells would have a more mature gene expression profile compared to lin-CD34+CD38-CD90+CD93+ cells. CP-CML cells were sorted into (1) lin-CD34+, (2) lin-CD34+CD38-CD90+CD93- and (3) lin-CD34+CD38-CD90+CD93+ populations. RNA was harvested at baseline from bulk populations (1) to (3) and cDNA was generated from single cells using the Fluidigm C1 autoprep system. Using Fluidigm technology, quantitative PCR of 90 lineage-specific and cell survival genes was performed within all populations of cells (1) to (3) in 'bulk' samples (n=3), and at single cell level (n=123 CD93+, n=120 CD93-single cells; n=3 samples in total). Bulk sample analysis demonstrated a significant increase in expression of lineage commitment genes within the lin-CD34+CD38-CD90+CD93- population, as shown by increased expression of GATA1 (p=0.0007), and CBX8 (p=0.0002). The lin-CD34+CD38-CD90+CD93+ population displayed a less lineage-restricted profile with increased expression of CDK6 (p=0.05), HOXA6 (ns), CDKN1C (ns) and CKIT (p=0.0014), compared to the lin-CD34+CD38-CD90+CD93- population. Furthermore, the two populations could be segregated by differential gene expression through gene clustering. At a single cell level, differences were noted in the frequency of expression between lin-CD34+CD38-CD90+CD93- and lin-CD34+CD38-CD90+CD93+ populations, particularly in GATA1, TPOR, and VWF. Although a statistically significant change was demonstrated in gene expression between the lin-CD34+CD38-CD90+CD93- and lin-CD34+CD38-CD90+CD93+ populations in a number of genes, we were not able to segregate the populations by differential expression using gene clustering. This highlights the heterogeneous nature of the cell populations and the inability to distinctly characterize between the two populations at a single cell level. Our results validate CD93 as a potential biomarker to separate the primitive CP-CML LSC population and highlight key lineage and cell survival pathways that are altered in CML LSC. The results demonstrate the heterogeneity seen within gene expression at the single cell level, which may allow for further insight into the CML LSC compartment with further analyses. Disclosures Wheadon: GlaxoSmithKline: Research Funding. Copland:Shire: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; ARIAD: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria.

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Mutational Landscape of Patients with Myelofibrosis That Do Not Harbor Mutations in JAK2, MPL and Calreticulin Driver Genes

Blood ◽

10.1182/blood.v126.23.4091.4091 ◽

2015 ◽

Vol 126 (23) ◽

pp. 4091-4091

Author(s):

Giada Rotunno ◽

Paola Guglielmelli ◽

Annalisa Pacilli ◽

Tiziana Fanelli ◽

Carmela Mannarelli ◽

...

Keyword(s):

Board Of Directors ◽

Triple Negative ◽

Cox Regression ◽

Myeloproliferative Neoplasms ◽

Leukemic Transformation ◽

Driver Genes ◽

Advisory Committees ◽

Molecular Landscape ◽

Splicing Machinery

Abstract Background. In primary myelofibrosis (PMF), mutations of JAK2, CALR and MPL driver genes can be detected in about 60%, 20% and 5% of the patients (pts), respectively. Therefore, about 10% of the pts lack any of the 3 driver mutations and are operationally called "triple negative" (TN). TN pts present a higher risk of developing anemia and thrombocytopenia, suffer from reduced overall survival compared to other genotypes, particularly to CALR type1/type1-like mutations, and may be at higher risk of leukemic transformation (Blood 2014; 124:1062; Leukemia 2014; 28:1472; Blood 2014;124:2465). Aims The aim of the study was to analyse the molecular landscape of TN PMF pts by genotyping a set of myeloproliferative-neoplasms associated genes whose mutated status was shown to be prognostically relevant in previous studies (Leukemia 2013;27:1861; Blood 2014;123:2220; Leukemia 2014;28:1804;Leukemia 2014;28:1494). Methods. Diagnosis ofPMF was made according to WHO2008 criteria. All pts provided informed written consent. Previously published methods were used to screen mutations involving JAK2, MPL and CALR. A deep sequencing custom panel was designed to genotype the following genes: EZH2, ASXL1, IDH1/2, SRSF2, TP53, TET2, RUNX1, CBL, NRAS, KRAS, DNMT3A, SF3B1, IKZF1, NFE2, SH2B3. Analysis was performed using the Ion torrent PGM platform. Comparisons of quantitative variables between groups were carried out by the nonparametric Wilcoxon rank-sum test. The prognostic value of the molecular variables with regard to OS was estimated by the Kaplan-Meier method and Cox regression. Results. We analysed 28 TN PMF collected at the time of diagnosis. Median age was 66.7y, 57% were male. Median follow up was 2.1y (0.3-14.5). Overall, 8 patients (28.6%) progressed to AML. Death occurred in 20 pts (71.4%) after a median follow up of 2.3y (1.4-3.3y); progression to leukemia was the cause of death in 5 pts (25%). Overall, 22 pts (78.6%) presented at least one mutation in any of the 15 genes of the panel; 14 pts (50%) presented at least 2 mutations in different genes. The frequency of mutated genes was: SRSF2 39.3%, ASXL1 28.6%, EZH2 21.4%, NRAS 21.4%, TET2 10.7%, CBL 10.7%, IDH 3.6%, DNMT3A 3.6%, SH2B3 3.6%, U2AF1 3.6%. Twenty pts (71.4%) were classified as high molecular risk (HMR: ie, any mutated gene of ASXL1, EZH2, SRSF2, IDH1/2), a proportion significantly higher (P<0.01) than among JAK2 V617F (31.5%), CALR Type1/1-like (22.0%) and CALR Type2-type2-like (5.0%) (Leukemia 2013; 27:1861). Mutated genes were grouped into 3 different pathways: epigenetic regulation (ASXL1, EZH2, TET2, IDH), splicing machinery (SRSF2, U2AF1) and leukemic transformation (NRAS, DNMT3A, SH2B3, CBL). The most frequently mutated pathway was the epigenetic one with mutations in 14 pts (63.6%) of which 3 pts (21.4%) had 2 or more mutated genes of the pathway; 12 pts (54.5%) presented mutations in the splicing machinery and of these 8 pts (66.7%) had 2 or more mutated genes of the pathway; genes involved in leukemic transformation were mutated in 11 pts (50%) and 10 of 11 (90.9%) had 2 or more mutated genes. In three cases (13.6%) all 3 pathways were concurrently involved. Among the mutated genes, SRSF2 was associated with shorter survival [1.9y (1.6-2.2)] compared to pts with un-mutated SRSF2 [3.2y (0.9-5.4y)] (HR 2.3, 95%CI 0.9-6.4). SRSF2 mutations were also associated with shorter leukemia free survival (LFS): LFS not reached in un-mutated pts compared to 2.2y (1.8-2.7y) for mutated pts, with a HR=4.5 (95%CI 10.3-19.9). We also found that in pts with grade 1 bone marrow fibrosis the splicing and the leukemic pathway were more frequently mutated compared to grade 2-3 fibrosis (57% vs 28.5% and 50% vs 28.5% respectively). Conclusions. "Triple-negative" pts with PMF present high rate of mutations of MPN-associated genes, most of them are classified as "high molecular risk" and harbor >2 mutations. Mutated SRSF2 was particularly associated with shorter LFS. Such complex molecular landscape might help to explain the negative outcome of TN PMF pts. Disclosures Vannucchi: Baxalta: Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceuticals Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Shire: Speakers Bureau.

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Single Cell ATAC Lineage Deconvolution Reveals Overlapping Subclones in Epigenetically Distinct AML Samples

Blood ◽

10.1182/blood-2021-154517 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 2381-2381

Author(s):

Deepika Dilip ◽

Richard Koche ◽

Kamal Menghrajani ◽

Ari Melnick ◽

Olivier Elemento ◽

...

Keyword(s):

Dimensionality Reduction ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Single Cells ◽

Great Promise ◽

Sequencing Analysis ◽

Advisory Committees ◽

High Degree ◽

Cluster 2

Abstract Introduction: Acute Myeloid Leukemia (AML) is a biologically diverse disease. Expanded mutation panels and novel epigenetic assays are identifying an increasing number of putative AML subtypes beyond the traditional 'Good', 'Intermediate', and 'Poor' risk designations. Although these approaches show great promise, identifying the relevant underlying disease biology remains difficult. Single cell studies highlight this difficulty, showing dynamic interactions between multiple subclones, each with its own set of cooperating mutations interfering with normal hematopoiesis. We have previously shown that bulk ATAC data can be used to 'deconvolve' and identify hematopoietic state in AML samples. Here we extend this work, showing that this approach can be used to identify normal hematopoietic states with a high degree of accuracy. In addition, we show that AML samples that appear different in bulk actually contain overlapping lineage characteristics at the single cell level. Methods: Single cell ATAC-seq count files were downloaded from GSE74310, GSE96769 as well as corresponding bulk ATAC-seq count files from GSE74912, GSE96771. These data were generated by flow sorting normal specimens into well-known stages of hematopoiesis followed by either bulk or single cell ATAC-seq. A set of AML samples was processed by both single cell and bulk ATAC as well. Bulk ATAC data was normalized using DESeq2 followed by variance stabilizing transformation. Single cell data was processed and normalized using the Seurat pipeline with default parameters. A common peak atlas was created for each dataset, and peaks characteristic of each stage of hematopoiesis were selected using a modified Kruskal-Wallis statistic and optimized using a set of well-characterized in-vitro sample mixtures. Lineage deconvolution was performed using a non-negative least squares regression comparing each unknown sample to the set of normal hematopoietic states. Results: Dimensionality reduction of single cell ATAC-seq using uniform manifold approximation and projection (UMAP) largely recapitulates stages of hematopoiesis used to sort the samples (Figure 1a). Single cell lineage deconvolution is able to identify the purity of these populations more precisely (Figure 1b), with HSC, MPP, LMPP, CLP, GMP, MEP, and Monocytic stages showing relatively pure lineage characteristics. In contrast, the CMP stage appears to be composed of a heterogeneous population, as has been previously shown. Dimensionality reduction of bulk ATAC-seq data using Principle Component Analysis (PCA) illustrates distinct stages of hematopoiesis, and separates the AML samples into two groups (Figure 2c). To further analyze these groups, bulk lineage deconvolution was performed, showing that cluster 1 (purple) has a more differentiated appearance characterized by GMP and Monocyte lineages while cluster 2 also reflects earlier stages of hematopoiesis including HSC, MPP, and LMPP (Figure 2d). One sample from each cluster (highlighted in red in figure 2c,d) was evaluated using single cell ATAC-seq. Lineage deconvolution on the component cells illustrates substantial lineage characteristic overlap between subclones of these samples, with lineage based hierarchical clustering generating two clusters with mixed sample origin (Figure 2e). These clusters are separated into more and less differentiated lineage groups, with the cluster 2 sample cells more commonly having an HSC or MPP dominant lineage. However, some cluster 1 cells do have HSC or MPP lineage features as well, which is reflected by the poor association of cluster with sample (Fisher's exact p=0.8). Conclusions: Lineage deconvolution can be performed on single cell ATAC-seq data with a high degree of precision on normal samples and illustrates clonal lineage heterogeneity in malignant specimens not previously appreciated in bulk sequencing analysis. Analysis of greater numbers of samples and cells are needed to draw general conclusions, but the approach shows promise as a means of computationally identifying or sorting normal single cells and more precisely characterizing leukemias. Figure 1 Figure 1. Disclosures Melnick: Janssen Pharmaceuticals: Research Funding; Sanofi: Research Funding; Daiichi Sankyo: Research Funding; Epizyme: Consultancy; Constellation: Consultancy; KDAC Pharma: Membership on an entity's Board of Directors or advisory committees. Elemento: Johnson and Johnson: Research Funding; Volastra Therapeutics: Consultancy, Other: Current equity holder, Research Funding; Eli Lilly: Research Funding; Janssen: Research Funding; One Three Biotech: Consultancy, Other: Current equity holder; Champions Oncology: Consultancy; Freenome: Consultancy, Other: Current equity holder in a privately-held company; Owkin: Consultancy, Other: Current equity holder; AstraZeneca: Research Funding. Levine: Lilly: Honoraria; Gilead: Honoraria; Janssen: Consultancy; Morphosys: Consultancy; Astellas: Consultancy; Roche: Honoraria, Research Funding; Incyte: Consultancy; Amgen: Honoraria; Celgene: Research Funding; Isoplexis: Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Prelude: Membership on an entity's Board of Directors or advisory committees; Auron: Membership on an entity's Board of Directors or advisory committees; Ajax: Membership on an entity's Board of Directors or advisory committees; Zentalis: Membership on an entity's Board of Directors or advisory committees; Mission Bio: Membership on an entity's Board of Directors or advisory committees; Imago: Membership on an entity's Board of Directors or advisory committees; QIAGEN: Membership on an entity's Board of Directors or advisory committees. Glass: GLG: Consultancy.

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Myeloproliferative Neoplasms (MPN) Clonal Evolution Landscape and Its Impact on Patients' Prognosis

Blood ◽

10.1182/blood-2021-149473 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 317-317

Author(s):

Lin-Pierre Zhao ◽

Marine Cazaux ◽

Nabih Maslah ◽

Rafael Daltro De Oliveira ◽

Emmanuelle Verger ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Cox Regression ◽

Myeloproliferative Neoplasms ◽

Clonal Evolution ◽

Chronic Phase ◽

Driver Mutation ◽

Advisory Committees ◽

Free Survival

Abstract Introduction: Although myeloproliferative neoplasms (MPN) are driven by three mutually exclusive driver mutations (JAK2, CALR and MPL), targeted deep sequencing studies identified multiple additional somatic mutations potentially impacting MPN evolution. Presence of a high molecular risk (HMR: ASXL1, EZH2, SRSF2 and IDH1/2) or a TP53 mutations has been associated with adverse prognosis. However, to date, the effect of clonal evolution (CEv) on MPN patients' outcome has not been evaluated, as most of the studies assessed mutational-based prognosis stratification from single baseline molecular genotyping. The objective of our study was to describe the clinical and molecular characteristics of patients with CEv in a large cohort of MPN patients and analyze its impact on patients' outcome. Methods: A total of 1538 consecutive patients were diagnosed with MPN according to WHO criteria and followed in our hospital between January 2011 and January 2021. From this large retrospective cohort, we included in this study 446 patients who had at least 2 molecular analyses during the chronic phase of MPN, performed at diagnosis and/or during follow-up using next generation sequencing (NGS), targeting a panel of 36 genes involved in myeloid malignancies. Significant variants were retained with a sensitivity of 1%. CEv was defined as the acquisition of a new additional non-driver mutation between baseline and subsequent NGS evaluation. Statistical analyses were performed using the STATA software (STATA 17.0 for Mac Corporation, College Station, TX). Results: The median age at MPN diagnosis in our whole cohort was 51 years [IQR 41 - 60]. Our cohort included 167 (37%), 205 (46%) and 64 (14%) patients with polycythemia vera, essential thrombocythemia and primary myelofibrosis (MF) respectively. With a median interval of 1.6 years [IQR 1.0 - 2.8] between the first and the second NGS analysis in the whole cohort, CEv occurred in 128 patients (29%). Patients with CEv were significantly older compared to patients without CEv (n=318) (p=0.03). MPN diagnosis, the type of driver mutation and complete blood counts at MPN diagnosis did not differ between the 2 groups. Eighty-one (63%) and 198 (62%) patients with or without CEv respectively had at least one additional non-driver mutation at baseline NGS (p=0.59), while the rate of HMR (n=25 (20%) versus n=79 (25%)) or TP53 (n=7 (5%) versus n=20 (6%)) mutations at baseline NGS did not differ between the 2 groups. Thirty six out of 128 (28%) of patients with CEv had more than 1 acquired mutation. Most recurrently acquired mutations involved the epigenetic regulators TET2 and DNMT3A that were mutated in respectively 33% and 25% of patients with CEv (Figure 1A). Moreover, 38% of CEv patients acquired HMR (ASXL1 (14%), EZH2 (6%), SRSF2 (3%), IDH1/2 (2%)) or TP53 (13%) mutations. After a median follow up of 10.8 years [IQR 6.6 - 17.2] in the whole cohort representing a total of 5635 patient years, 32 (7%) patients died, and 11 (2.5%) and 11 (2.5%) patients with at least 2 NGS performed during MPN chronic phase transformed respectively into secondary MF or myelodysplastic syndrome / acute myeloid leukemia (MDS/AML). Interestingly, CEv (HR 11.27, 95%CI [5.09; 24.96], p<0.001) (Figure 1B), age at MPN diagnosis (HR 1.11, 95%CI [1.07; 1.15], p<0.001) and the presence of HMR mutations at baseline NGS (HR 4.48, 95%CI [2.05; 9.77], p <0.001) independently adversely impacted OS in a COX regression multivariate analysis. CEv also independently adversely impacted MDS/AML free survival (HR 13.15, 95%CI [3.88; 44.47], p<0.001) and secondary MF free survival (HR 21.13, 95%CI [6.18; 72.20], p<0.001) in a COX regression multivariate analysis. Conclusion: Our study on a large retrospective clinically and biologically annotated real-life cohort of MPN patients with long-term follow up shows that CEv independently adversely impacts OS, MDS/AML and secondary MF free survivals. CEv occurred in a clinically relevant proportion of MPN patients (28%) and was associated with patients' age. Acquired mutations mainly involved epigenetic regulators, HMR and TP53 genes. These results suggest that serial molecular monitoring using NGS could be routinely implemented in MPN patients follow up, to assess more accurately disease evolution and potentially update therapeutic management. Figure 1 Figure 1. Disclosures Raffoux: PFIZER: Consultancy; CELGENE/BMS: Consultancy; ABBVIE: Consultancy; ASTELLAS: Consultancy. Kiladjian: Novartis: Membership on an entity's Board of Directors or advisory committees; Taiho Oncology, Inc.: Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Membership on an entity's Board of Directors or advisory committees; PharmaEssentia: Other: Personal fees; AOP Orphan: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees. Benajiba: Gilead: Research Funding; Pfizer: Research Funding.

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HSCs Fated to Progress to Blast Phase Can be Detected in Myelofibrosis Patients Several Years Prior to Leukemic Transformation

Blood ◽

10.1182/blood-2019-130923 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1676-1676

Author(s):

Jenny M. Ho ◽

Jessie J.F. Medeiros ◽

Michelle Chan-Seng-Yue ◽

Lauren Hummel ◽

Andrea Arruda ◽

...

Keyword(s):

Board Of Directors ◽

Myeloid Leukemia ◽

Research Funding ◽

Somatic Mutations ◽

Low Frequency ◽

Gene Mutations ◽

Cell Populations ◽

Blast Transformation ◽

Leukemic Transformation ◽

Advisory Committees

In myeloproliferative neoplasms (MPN), somatic mutations in genes recurrently mutated in myeloid leukemia, apart from known MPN driver mutations (JAK2, MPL, CALR), are common and can increase the risk of transformation to acute leukemia, also called blast phase (BP). However, when mutations in these genes are acquired, the nature of the cells bearing these mutations, and how each mutation cooperates to promote blast transformation remains largely unknown. We therefore examined serially collected blood and bone marrow samples from patients with myelofibrosis (MF) who progressed to BP to further elucidate the genetic basis of blast transformation. The aims of our study were to determine the temporal acquisition of mutations during chronic phase (CP) that contribute to blast transformation and to define the cellular origins within the hematopoietic hierarchy of the clone fated to progress to BP (termed BP-fated clone). Our cohort included 9 MF patients (8 JAK2V617Fpositiveand 1 MPLW515Lpositive) who progressed to BP and for whom CP and BP samples were previously collected and banked. The time interval between CP and BP collections ranged between 1.5 to 6.6 years. In 4 patients, additional CP samples were available from intervening time points. Whole genome sequencing (WGS) of leukemic blasts (BP sample), the MPN clone (CP sample), and germline control (T-cells or buccal DNA) was performed to identify somatic mutations. We detected somatic mutations at BP in 19 genes recurrently mutated in myeloid leukemia (ML) with an average of 5.3 (range 2-8) genes mutated per patient. Genes that were mutated in 2 or more BP samples include SRSF2 (n=5), ASXL1 (n=4), TET2 (n=4), IDH1/2 (n=4), RUNX1 (n=4), NRAS (n=4), KRAS (n=2), U2AF1 (n=2), PHF6 (n=2), and STAG2 (n=2). Notably, 73% of ML gene mutations identified at BP were already acquired and present at ≥5% variant allele frequency in CP. The remaining (27%) ML gene mutations were not detected at CP and were, thus, termed BP-specific mutations. To achieve our study aims, we sorted hematopoietic stem and progenitor cell (HSPC) populations (HSC, MPP, LMPP, CMP, MEP, GMP), as well as, mature cell populations (myeloid, erythroid, T-cell, B-cell and NK) from CP samples and performed DNA whole genome amplification. We then interrogated sorted cell populations for BP-specific mutations by droplet digital PCR (ddPCR) to identify low frequency mutations. Our results revealed that BP-specific ML gene mutations could be detected at low frequencies (range between 0.2-5%) in one or more cell populations several years (1.5-3 years) prior to BP diagnosis. Importantly, we detected these low frequency mutations within the HSC population from several patients, indicating that BP-fated clones were derived from an HSC. This finding is being verified in all patients by targeted sequencing of additional BP-specific mutations that were identified by WGS (average of 300 variants per patient, range 37 to 659). In one patient analyzed to date, additional low frequency BP-specific mutations have been detected within the HSC population, and thereby confirm the BP cell of origin as an HSC in this individual. Generalization of this finding will be confirmed by targeted sequencing of sorted populations from the remaining patients. In summary, BP-fated clones often appear several years prior to blast transformation and can be traced back to HSCs. Identification of BP-fated clones that remain dormant strongly suggests that mechanisms beyond the acquisition of somatic mutations in ML genes (including but not limited to epigenetic alterations, acquisition of non-coding mutations, inflammation) are necessary to effectively promote full leukemic transformation. Disclosures McNamara: Novartis Pharmaceutical Canada Inc.: Consultancy. Maze:Pfizer Inc: Consultancy; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Tsui:Novartis: Consultancy, Honoraria. Minden:Trillium Therapetuics: Other: licensing agreement. Gupta:Incyte: Honoraria, Research Funding; Sierra Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding; Sierra Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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A Survey Conducted during COVID-19 Pandemic Among Brazilian Chronic Myeloid Leukemia and Philadelphia-Negative Myeloproliferative Neoplasms Patients

Blood ◽

10.1182/blood-2021-151168 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 4601-4601

Author(s):

Leonardo Fechio ◽

Ana Vitória Ferreira Mota ◽

Jaisson Bortolini ◽

Gislaine B O Duarte ◽

Marcia Delamain ◽

...

Keyword(s):

Board Of Directors ◽

Kinase Inhibitors ◽

Close Contact ◽

Myeloproliferative Neoplasms ◽

Demographic Data ◽

Chronic Phase ◽

Molecular Response ◽

Advisory Committees ◽

Social Distancing ◽

The Impact

Abstract Introduction: COVID-19 has severely affected the Brazilian population. By July 2021, the incidence was 19,9 million cases and 556.000 deaths. Recent studies suggest that patients with MPN have higher infection and death rates than the general population. Older age and comorbidities are risk factors for severe COVID-19 in CML and MPN. Objectives This study aimed to evaluate the incidence and clinical evolution of COVID-19 in a cohort of CML and MPN Brazilian patients. Methods This is a prospective, observational, ongoing study. All patients signed informed consent and answered two structured questionnaires within a six months interval. The questionnaire included questions about patient's behavior during pandemic, symptoms, contacts, COVID-19 infection, and vaccination data in the last six months. In addition, demographic data, CML and NMP treatment, comorbidities, laboratory tests, COVID severity, and outcome were collected from the medical records. Results From September 2020 to July 2021, 370 patients answered the first questionnaire, and 153 answered the second: 225 with CML and 145 with MPN (45% essential thrombocythemia, 27.6%, polycythemia vera, 23% myelofibrosis, and 4.8% not classified). In the CML population, the median age was 56 (19-90). Most were receiving tyrosine kinase inhibitors (88,5%) and 26 (11,5%) no treatment, in treatment-free remission (TFR). 80% of the patients were practicing social distancing, and 30% had at least one family member or close contact diagnosed with COVID-19. Comorbidities: hypertension (35%), diabetes (14%), pulmonary disease (6%), cardiac disease (16%), renal disease (7%), other (18%). A total of 28/225 (12.4%) patients had confirmed COVID-19 diagnosis (by serology or PCR), while 10 were suspect. The median age was 47 years, 68% were male, and 41% were not respecting social distancing. Thirty-five percent had comorbidities: 25% hypertension; 68% had a history of close contact with an infected person. One patient was in the accelerated phase, and 27 were in the chronic phase; 4 had a complete cytogenetic response, 13 major molecular response (MMR), 3 MR4.0, and 7 MR4.5. COVID-19 was mild/moderate in 27 and in severe in one case, resulting in death. This patient was a male, 71-year-old, with hypertension, in MMR with nilotinib. At COVID-19 onset, 16 pts were receiving imatinib, five dasatinib; five nilotinib e 2 were in TFR. There was one reinfection, in a 54 years old male patient, with no comorbidities. To date, 84 (37%) patients (pts) have received vaccines against COVID-19: 32 CORONAVAC (Sinovac/Butantan), 51 ChAdOx1nCov-19-Covishield (Astrazeneca/Oxford), and one BNT162 (Pfizer). All COVID-19 cases occurred before vaccination. Among the 145 MPN pts, the median age was 67 years (29-90), and 86% had comorbidities (52% hypertension, 17.5% diabetes, and 13% cardiac diseases). Social distancing was 83%. Nine out of 145 (6.2%) had confirmed COVID-19 diagnosis, and 3% suspect. The median age of these pts was 43 years (28-80). Seven patients had ET and 2 PV. Seven were female. Four pts received Hydroxyurea (HU) and aspirin, four aspirin, one HU, and one no treatment. There were seven mild and two moderate cases requiring hospitalization, none requiring oxygen or mechanical ventilation, none with thrombosis. Two COVID cases occurred after the first dose of vaccines (CORONAVAC and Covishield). In the whole MPN group, 11% have received two doses (57% CORONAVAC, 40% Covishield, and 3.6% BNT 162). Conclusions COVID-19 cases occurred more frequently in younger patients. COVID-19 incidence was higher in the CML than in the MPN population, probably because MPN patients were less exposed, and the older pts were the first to receive vaccines. The impact of the vaccination on the prevention of new cases will be evaluated during the follow-up. Disclosures Bortolini: Novartis: Speakers Bureau. Pagnano: Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astellas: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pintpharma: Other: Lecture; EMS: Other: Lecture; Jansenn: Other: Lecture.

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Landscape of TP53 Mutations in MPN

Blood ◽

10.1182/blood-2019-132014 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1681-1681

Author(s):

Noushin Farnoud ◽

Christopher Famulare ◽

Elli Papaemmanuil ◽

Erin McGovern ◽

Juan Medina ◽

...

Keyword(s):

Dna Binding ◽

Board Of Directors ◽

Research Funding ◽

Tp53 Mutation ◽

Somatic Mutations ◽

Myeloproliferative Neoplasms ◽

Chronic Phase ◽

Advisory Committees ◽

Tp53 Mutations ◽

Risk Of Progression

Background The Myeloproliferative Neoplasms, including Essential Thrombocythemia (ET), Polycythemia Vera (PV), and Myelofibrosis (MF) are stem cell disorders which carry the risk of progression to accelerated phase or blast-phase (MPN-AP/BP). Among the risk factors for transformation to MPN-AP/BP are TP53 mutations. TP53 mutations are a risk factor for progression to MPN-AP/BP in chronic-phase myeloproliferative neoplasms (MPN) and indeed 30% of patients with MPN-LT bear TP53 mutations. A recent study indicated that TP53 mutations may persist at low levels for years without an immediate risk of progression in some chronic-phase MPN patients [Kubesova et al. Leukemia 2017]. These observations raise the question as to whether the types of TP53 mutations, their frequency, or co-occurring variants differ between MPN subtypes. TP53 mutations are characterized by frameshift, missense, nonsense or silent mutations. Mutations in TP53 have traditionally been considered functionally equivalent in many prognostic studies, but an increased understanding of the effects of distinct mutations on TP53 activity has led to the recognition of the distinct functional significance of these different mutations. The understanding of the landscape of TP53 mutations in MPN and the association between different TP53 mutations and mutational burdens among MPN subtypes may allow more accurate prognostic evaluation and personalized treatment for patients. We therefore sought to assess the landscape of TP53 mutations in MPN subtypes. Methods We performed Next-Generation Sequencing (NGS) on a cohort of 651 samples derived from 439 MPN patients with ET, PV, MF and MPN-AP/BP. The data were from 3 targeted panels with 576, 585 and 156 genes (with 91, 241 and 319 samples; median coverage 500x). Samples were obtained from Memorial Sloan Kettering Cancer Center and the Myeloproliferative Neoplasms Research Consortium. Putative oncogenic mutations were called using a combination of 4 variant callers and by comparison to established cancer databases. The final variants were manually reviewed to guarantee high quality of downstream analysis. Results We identified somatic mutations in 428/439 patients (157 MPN-AP/BP, 140 MF, 67 ET and 64 PV). Of these, 55 patients (~13%) had at least one TP53 mutation with variant allele frequency (VAF) >= 2% (median TP53 VAF= 28%). In total, 68 TP53 somatic mutations were identified. Majority of these patients had a single TP53 mutation (46/55) and some had multiple mutations (7 had two and 2 had four mutations). Mutations were enriched in MPN-AP/BP with 45/68 (66%) occurring in this group followed by 10/68 (15%) in ET, 9/68 (13%) in MF and 4/68 (6%) in PV (panel A). Missense mutations were the most common type of TP53 variants and constituted ~80-90% of all mutations in ET, MF and MPN-AP/BP. Most stop-gains and frameshifts were observed in MF or MPN-AP/BP group. Furthermore, 92% of TP53 mutations are localized on DNA-binding domain (exons 5 to 8; panel B). The latter observation is consistent with results from other human cancers and highlights the role of these mutations in reducing TP53 DNA binding affinity. About 8% of mutations occur in the tetramerization domain of TP53, which is also critical for DNA binding, as well as protein-protein interactions and post-translational modification. We did not identify a significant association between a specific TP53 mutation type and any particular MPN subtype. However, we identified a significant association between TP53 VAF and MPN subtype (panel C); TP53 VAF was significantly higher in MPN-AP/BP compared to ET (p =0.0001) and MF (p =0.016). Conclusion TP53 mutations have important prognostic significance in patients with MPN. However, subgroups of patients with TP53 mutant chronic-phase disease have been observed to have relatively stable clinical course. Our data demonstrate that the spectrum of TP53 mutations, in terms of type and location within the gene, does not appear to differ between ET, PV, MF, or MPN-AP/BP. However, we observe significant difference with regard to the VAF of TP53 mutations, with an association of higher VAF and MPN-AP/BP state. This data argues that the VAF may be an important consideration in assessing the prognostic impact of a TP53 mutation identified in an MPN patient. Data regarding copy number variations in this cohort, co-occurring mutations, and the impact of TP53 mutations on treatment outcomes will be presented. Figure Disclosures Papaemmanuil: Celgene: Research Funding. Rampal:Agios, Apexx, Blueprint Medicines, Celgene, Constellation, and Jazz: Consultancy; Constellation, Incyte, and Stemline Therapeutics: Research Funding. Levine:Prelude Therapeutics: Research Funding; Novartis: Consultancy; Gilead: Consultancy; Loxo: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Research Funding; Qiagen: Membership on an entity's Board of Directors or advisory committees; Lilly: Honoraria; Amgen: Honoraria; Celgene: Consultancy, Research Funding; Isoplexis: Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Imago Biosciences: Membership on an entity's Board of Directors or advisory committees. Mascarenhas:Novartis: Research Funding; Roche: Consultancy, Research Funding; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; CTI Biopharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Promedior: Research Funding; Merus: Research Funding; Pharmaessentia: Consultancy, Membership on an entity's Board of Directors or advisory committees. Hoffman:Merus: Research Funding.

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Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

10.1101/553040 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ning Wang ◽

Andrew E. Teschendorff

Keyword(s):

Transcription Factors ◽

Single Cell ◽

Cell Fate ◽

Regulatory Networks ◽

Large Scale ◽

Single Cells ◽

Differential Expression Analysis ◽

Dropout Rate ◽

Rna Seq ◽

Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

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