ALBERT

Description: Introduction Increased complexity of sub-clonal architecture has been associated with poor outcome in AML (Papaemmanuil et al. NEJM 2016). Currently, assessment of intra-tumor genetic heterogeneity is performed with next-generation sequencing (NGS) using bulk tumor samples and relies on the variance of variant allele frequency among the individual mutations. However, this analysis is inherently confounded by the tumor purity and zygosity of the mutations. To overcome these limitations, we recently developed a high-throughput single-cell DNA sequencing platform using droplet microfluidics (Mission Bio Inc.) and showed the feasibility of genotyping primary AML samples at single-cell resolution (Pellegrino et al. Genome Research 2018). Here we used this novel platform in a large cohort of AML samples to characterize the clonal heterogeneity of AML and its evolution at relapse. Methods In total, 76 bone marrow (BM) samples from 68 AML patients (pts) were single-cell genotyped using the Mission Bio platform. In order to avoid allelic imbalance, most of the samples (66/76, 87%) were obtained from normal karyotype (NK) AML pts. The platform covered 40 amplicons in 19 recurrently mutated AML genes (median 31x coverage/amplicon/cell [IQR 22-41]). Fastq files were processed using the proprietary pipeline for adapter trimming, sequence alignment, barcode demultiplexing, and genotype and variant calling. Loom files were loaded to Tapestri Insights software for variant filtering. As a reference, all samples were concurrently sequenced by the conventional bulk NGS using targeted capture sequencing (N=64) or whole exome sequencing (N=12). An average allele drop-out (ADO) rate was inferred by the genotype of known single nucleotide polymorphisms that were incorporated into the platform. Results In total, 333,731 cells were genotyped from 76 AML samples (median 4,423 cells/sample [IQR 2,801-5,844]). The single-cell DNA sequencing detected 208 driver mutations in 76 samples with median 3 mutations per sample (IQR: 2-3). Most commonly detected mutations were NPM1 (N = 28, 13%), followed by DNMT3A (N = 24, 12%), SRSF2 (N = 24, 12%), FLT3 (N = 22, 11%), and IDH2 (N = 21, 10%), which is in accordance with the genetic landscape for NK AML. All mutations detected by the single-cell sequencing were also confirmed by the bulk NGS. The median ADO rate was 8.5% (IQR 6.8-10.4). We detected median 5 [IQR 4-8] sub-clones per sample by the single-cell sequencing. The platform unambiguously detected co-occurrence and mutual exclusivity among the driver mutations at a single-cell level. For instance, the single-cell sequencing of the samples carrying NRAS/KRAS, double NRAS, double RUNX1, IDH1/IDH2, FLT3-ITD/FLT3-TKD, or NRAS/PTPN11 mutations showed that these two mutations in the same molecular pathway were in different cellular population. In contrast, the platform also detected co-occurrence of multiple mutations in a single-cell. For example, we detected a single cell population with a clear co-occurrence of DNMT3A,FLT3-ITD, and NPM1, the most commonly co-occurring mutations in AML. Computational analysis of the single-cell genotype data by the stochastic search algorithm generated phylogenetic trees of the driver mutations in AML. DNMT3A, IDH1, IDH2, and U2AF1 were frequently detected as a trunk mutation, while mutations in FLT3, NRAS, and NPM1 were frequently detected as branch mutations. Analysis of 14 baseline and relapse paired samples revealed the remodeling of clonal architecture at relapse in 7 pts. Relapsed samples tended to have simpler clonal architecture with less sub-clones compared to the baseline (7 vs. 4, P = 0.169), suggesting the clonal selection process during the therapy. In 54 pts who were previously untreated and had single-cell genotype information on baseline BM, the pts with ≥ 10 sub-clones had significantly worse overall survival than pts with 〈 10 sub-clones (2-year survival 17% vs. 43%, P = 0.0468). Conclusion The high-throughput single-cell DNA sequencing of 76 AML samples generated an atlas of driver mutations in 333,731 AML cells. The platform uncovered detailed evolutionary history of driver mutations in AML and unambiguously visualized co-occurrence and mutual exclusivity of driver mutations at a single-cell level, features that are not observable with conventional bulk NGS. Our data also suggest the prognostic implication of intra-tumor heterogeneity in AML. Disclosures Durruthy-Durruthy: Mission Bio, Inc.: Employment, Equity Ownership. Parikh:Mission Bio, Inc.: Employment. DiNardo:Agios: Consultancy; Bayer: Honoraria; Karyopharm: Honoraria; Medimmune: Honoraria; Celgene: Honoraria; Abbvie: Honoraria. Ravandi:Bristol-Myers Squibb: Research Funding; Jazz: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Sunesis: Honoraria; Xencor: Research Funding; Sunesis: Honoraria; Seattle Genetics: Research Funding; Abbvie: Research Funding; Abbvie: Research Funding; Xencor: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Seattle Genetics: Research Funding; Jazz: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Research Funding; Orsenix: Honoraria; Orsenix: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Macrogenix: Honoraria, Research Funding; Macrogenix: Honoraria, Research Funding. Jabbour:Abbvie: Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Andreeff:United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; SentiBio: Equity Ownership; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; SentiBio: Equity Ownership; Reata: Equity Ownership; Amgen: Consultancy, Research Funding; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Reata: Equity Ownership; Jazz Pharma: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Oncolyze: Equity Ownership; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Astra Zeneca: Research Funding; Amgen: Consultancy, Research Funding; Oncolyze: Equity Ownership; Celgene: Consultancy; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding. Cortes:Astellas Pharma: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Arog: Research Funding; Pfizer: Consultancy, Research Funding. Konopleva:Stemline Therapeutics: Research Funding. Eastburn:Mission Bio, Inc.: Employment, Equity Ownership.

Description: Background: Myelodysplastic syndromes (MDS) are a collection of clonal diseases of dysfunctional hematopoietic stem cells, characterized by ineffective hematopoiesis, cytopenias, and dysplasia. Increased understanding of the mutational landscape of MDS has led to initial improvements in prognostic models based on clinical and cytogenetic variables. However, bulk sequencing techniques are limited in their ability to delineate clonal complexity and identify rare drug resistant subclones. To better understand clonal heterogeneity and clonal evolution of MDS we applied a high-throughput single cell sequencing technique to both diagnostic and longitudinal MDS samples. Methods: Samples were examined for 5 patients with MDS at diagnosis and, when available, progression. Mutational bulk sequencing was performed by NGS panel sequencing and exon sequencing was available in select cases. Single cell processing was performed using the Tapestri (Mission Bio) platform. Briefly, individual cells were isolated using a microfluidic approach, followed by barcoding and genomic DNA amplification for individual cancer cells confined to droplets. Barcodes are then used to reassemble the genetic profiles of cells from next generation sequencing data. We applied this approach to individual MDS samples, genotyping the most clinically relevant loci across upwards of 10,000 individual cells. Results: Single-cell sequencing was able to be performed successfully on all samples tested and recapitulated bulk sequencing data. We observed high concordance between bulk variant allele frequencies (VAFs) and sample level VAFs derived from single cell sequencing data (r2 = 0.98). Additionally, single cell analysis allowed for resolution of subclonal architecture and tumor phylogenetic evolution beyond what was predicted from bulk sequencing alone. Single-cell SNVs were able to resolve host and donor cell populations after bone marrow transplant and accurately predict chimerism and disease relapse. Furthermore, we were able to resolve the co-occurance of molecular alterations within subclones and establish zygosity of individual mutations at a single cell level. Rare subclones associated with disease relapse, were able to be identified in initial diagnostic samples that were frequently under the limit of detection of bulk NGS. Conclusions: Our results suggest more molecular complexity in MDS tumor samples than implied from bulk sequencing methods alone and indicates utility of single-cell sequencing for identification of resistant clones and longitudinal therapy monitoring. Disclosures Aleshin: Mission Bio, Inc.: Consultancy; Natera, Inc.: Employment. Durruthy-Durruthy:Mission Bio, Inc.: Employment, Equity Ownership. Medeiros:Genentech: Employment; Celgene: Consultancy, Research Funding. Eastburn:Mission Bio, Inc.: Employment, Equity Ownership.

Description: Introduction: Clonal selection occurring under the selective pressure of Fms-like tyrosine kinase 3 (FLT3) tyrosine kinase inhibitor (TKI) therapy is not fully understood. To date, the most common mutations found at the time of resistance to potent and selective type II FLT3 TKIs, like quizartinib, are on-target kinase domain (KD) mutations. Activating RAS pathway mutations are a common mechanism of resistance to type I FLT3 TKIs (McMahon et al., 2019 and Zhang et al., 2019). Changes in the acute myeloid leukemia (AML) genetic landscape at relapse on single agent or combination type II FLT3 TKI therapy have not been well-characterized at the single cell (SC) level. Methods: We performed SC sequencing with a novel high-throughput SC DNA sequencing platform, Mission Bio Tapestri, on bone marrow or peripheral blood samples from 11 patients with FLT3-mutant relapsed/refractory (R/R) AML treated with quizartinib. We analyzed 13 samples from 7 patients treated with quizartinib monotherapy and 12 samples from 4 patients treated with a combination of quizartinib and omacetaxine. Results: We analyzed a mean of 6,636 cells/sample (range 2,437-13,538). Each leukemia was made up of an average of 5 clonal sub-populations (range 2-7). 5/10 patients with serial samples demonstrated increased polyclonality at relapse, with a mean of 4 clones pretreatment (range 2-6) and 5 at relapse (range 2-7). All patients had an internal tandem duplication in FLT3 (FLT3-ITD) in at least 1 clone. Using SC sequencing, we visualized distinct clones with both hetero -and homo-zygous FLT3-ITD mutations. At the time of relapse after quizartinib, 7 patients (6 on monotherapy and 1 with combination therapy) developed at least one additional FLT3 KD mutation. These on-target mutations were found either as co-mutations within the FLT3-ITD clone or in a native FLT3 clone without an ITD. 4 of these 7 patients had polyclonal KD mutations (mean 2 distinct KD mutations; range 1-3), most commonly at the D835 locus. In 6/7 patients, each KD mutation was found in separate cellular subclones. However, 1 patient had multiple KD mutations within the same subclone (at the D835 and S838 loci). In 6/7 patients who relapsed with a KD mutation, the KD mutation was the dominant clone at relapse. No clones with on-target KD mutations were present prior to therapy. However, all relapse clones containing off-target mutations, found in 3/11 patients, were present in small subclones prior to clinical relapse. As an example, 1 patient who relapsed with 2 NRAS mutations had 2 distinct pre-existing clonal NRAS mutant populations, without FLT3-ITD co-mutations, detectable at

Description: AML (acute myeloid leukemia) is increasingly being treated with precision medicine. To better inform treatment, the mutational content of patient samples must be determined. However, current tumor sequencing paradigms are inadequate to fully characterize many instances of the disease. A major challenge has been the unambiguous identification of potentially rare and genetically heterogeneous neoplastic cell populations, capable of critically impacting tumor evolution and the acquisition of therapeutic resistance. Standard bulk population sequencing is unable to identify rare alleles and definitively determine whether mutations co-occur within the same cell. Single-cell sequencing has the potential to address these key issues and transform our ability to accurately characterize clonal heterogeneity in AML. Previous single-cell studies examining genetic variation in AML have relied upon laborious, expensive and low-throughput technologies that are not readily scalable for routine analysis of the disease. We applied a newly developed platform technology to perform targeted single-cell DNA sequencing on over 140,000 cells and generated high-resolution maps of clonal architecture from AML tumor samples. Marrow and/or peripheral blood samples were collected prior to, during treatment, and at clinical progression to the FLT3 inhibitor gilteritinib given on a clinical trial for relapsed/refractory AML with FLT3 mutation. Single-cell sequencing of multiple patient samples demonstrated that relapse clones acquired oncogenic RAS mutations. We utilized the high-throughput and sensitivity of our single-cell approach to more definitively assess where in the course of treatment these RAS mutated clones were acquired. Oncogenic RAS harboring clones, comprising between 0.4%, and 0.1% of tumor populations, were identified in patient samples either prior to or shortly after onset of treatment. Significantly, these RAS variant alleles were not detectable with targeted bulk sequencing. Throughout the course of treatment with the FLT3 inhibitor gilteritinib, the RAS mutant clones selectively expanded and were responsible for resistance to therapy and relapse. These findings point to the presence of underlying genetic heterogeneity in AML and demonstrate the utility of sensitively assaying clonal architecture to better inform patient stratification and therapy selection. Disclosures Eastburn: Mission Bio, Inc.: Employment, Equity Ownership. Durruthy-Durruthy:Mission Bio, Inc.: Employment, Equity Ownership. Smith:Astellas Pharma: Research Funding. Perl:Actinium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; NewLink Genetics: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Consultancy; Arog: Consultancy; Novartis: Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy; AbbVie: Membership on an entity's Board of Directors or advisory committees.

Description: Background: De novo acute myeloid leukemia (AML) is a molecularly heterogeneous disorder with clinically variable outcomes. Recent studies on the mutational landscape of AML have been informative in better stratifying risk of relapse. However, bulk sequencing techniques have been limited in their ability to delineate the true complexity of tumoral molecular heterogeneity and allow for efficient identification of drug resistant subclones. Here, we applied high-throughput single cell sequencing technique to identify patterns of clonal heterogeneity and evolution in longitudinal samples from patients with AML undergoing induction chemotherapy. Methods: Matched diagnosis, remission, and relapse samples were examined for 20 de novo AML cases including 15 relapsed and 5 non-relapsed controls. Mutational bulk sequencing was performed by NGS panel sequencing and exome sequencing was available in select cases. Single cell processing was performed using the Tapestri (Mission Bio) platform. Briefly, individual cells were isolated using a microfluidic approach, followed by barcoding and genomic DNA amplification for individual cancer cells confined to droplets. Barcodes were then used to reassemble the genetic profiles of cells from next generation sequencing data. We applied this approach to individual AML samples, genotyping the most clinically relevant loci across upwards of 10,000 individual cells. Results: Targeted single-cell sequencing was able to recapitulate bulk sequencing data from both peripheral blood and bone marrow aspirate samples. We observed high concordance between bulk VAFs and sample level VAFs derived from single cell sequencing data. Additionally, single cell analysis allowed for resolution of subclonal architecture and tumor phylogenetic evolution beyond what was predicted from bulk sequencing alone. Rare subclones associated with disease relapse, were identified in initial diagnostic samples that were frequently under the limit of detection of bulk NGS. Conclusions:Taken together, our results suggest a greater degree of heterogeneity in de novo AML samples than suggested with bulk sequencing methods alone and shows the utility of single-cell sequencing for longitudinal monitoring and identification of resistant clones prior to therapy initiation in select patients. We show here that this approach is a feasible and effective way to identify and track heterogeneous populations of cells in AML and may be valuable for MRD identification. Disclosures Aleshin: Mission Bio, Inc.: Consultancy; Natera, Inc.: Employment. Durruthy-Durruthy:Mission Bio, Inc.: Employment, Equity Ownership. Liedtke:Prothena: 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, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech/Roche: Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees; Amgen/Onyx: Consultancy, Honoraria, Research Funding; BlueBirdBio: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; celgene: Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Eastburn:Mission Bio, Inc.: Employment, Equity Ownership.