scholarly journals Single-cell mutational profiling enhances the clinical evaluation of AML MRD

2020 ◽  
Vol 4 (5) ◽  
pp. 943-952 ◽  
Author(s):  
Asiri Ediriwickrema ◽  
Alexey Aleshin ◽  
Johannes G. Reiter ◽  
M. Ryan Corces ◽  
Thomas Köhnke ◽  
...  

Abstract Although most patients with acute myeloid leukemia (AML) achieve clinical remission with induction chemotherapy, relapse rates remain high. Next-generation sequencing enables minimal/measurable residual disease (MRD) detection; however, clinical significance is limited due to difficulty differentiating between pre-leukemic clonal hematopoiesis and frankly malignant clones. Here, we investigated AML MRD using targeted single-cell sequencing (SCS) at diagnosis, remission, and relapse (n = 10 relapsed, n = 4 nonrelapsed), with a total of 310 737 single cells sequenced. Sequence variants were identified in 80% and 75% of remission samples for patients with and without relapse, respectively. Pre-leukemic clonal hematopoiesis clones were detected in both cohorts, and clones with multiple cooccurring mutations were observed in 50% and 0% of samples. Similar clonal richness was observed at diagnosis in both cohorts; however, decreasing clonal diversity at remission was significantly associated with longer relapse-free survival. These results show the power of SCS in investigating AML MRD and clonal evolution.

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Lamia Madaci ◽  
Julien Colle ◽  
Geoffroy Venton ◽  
Laure Farnault ◽  
Béatrice Loriod ◽  
...  

AbstractAfter decades during which the treatment of acute myeloblastic leukemia was limited to variations around a skeleton of cytarabine/anthracycline, targeted therapies appeared. These therapies, first based on monoclonal antibodies, also rely on specific inhibitors of various molecular abnormalities. A significant but modest prognosis improvement has been observed thanks to these new treatments that are limited by a high rate of relapse, due to the intrinsic chemo and immune-resistance of leukemia stem cell, together with the acquisition of these resistances by clonal evolution. Relapses are also influenced by the equilibrium between the pro or anti-tumor signals from the bone marrow stromal microenvironment and immune effectors. What should be the place of the targeted therapeutic options in light of the tumor heterogeneity inherent to leukemia and the clonal drift of which this type of tumor is capable? Novel approaches by single cell analysis and next generation sequencing precisely define clonal heterogeneity and evolution, leading to a personalized and time variable adapted treatment. Indeed, the evolution of leukemia, either spontaneous or under therapy selection pressure, is a very complex phenomenon. The model of linear evolution is to be forgotten because single cell analysis of samples at diagnosis and at relapse show that tumor escape to therapy occurs from ancestral as well as terminal clones. The determination by the single cell technique of the trajectories of the different tumor sub-populations allows the identification of clones that accumulate factors of resistance to chemo/immunotherapy (“pan-resistant clones”), making possible to choose the combinatorial agents most likely to eradicate these cells. In addition, the single cell technique identifies the nature of each cell and can analyze, on the same sample, both the tumor cells and their environment. It is thus possible to evaluate the populations of immune effectors (T-lymphocytes, natural killer cells) for the leukemia stress-induced alteration of their functions. Finally, the single cells techniques are an invaluable tool for evaluation of the measurable residual disease since not only able to quantify but also to determine the most appropriate treatment according to the sensitivity profile to immuno-chemotherapy of remaining leukemic cells.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qingke Duan ◽  
Chao Tang ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
Xiaobin Shang ◽  
...  

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.


2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii408-iii408
Author(s):  
Marina Danilenko ◽  
Masood Zaka ◽  
Claire Keeling ◽  
Stephen Crosier ◽  
Rafiqul Hussain ◽  
...  

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.


Hematology ◽  
2017 ◽  
Vol 2017 (1) ◽  
pp. 205-211 ◽  
Author(s):  
Faith E. Davies

Abstract The increased number of effective therapies and the wider use of combinations that give deeper remissions have resulted in a reassessment of the goals of myeloma therapy. With the advent of new therapeutic strategies and diagnostic tools, achievement of minimal residual disease (MRD)-negative status has become increasingly important, with some even considering it as the primary endpoint for therapy. The level of MRD that is aimed for is a continuous, rather than an absolute variable, with studies in both transplant-eligible and -noneligible patients showing that the level of MRD achieved is predictive of progression-free survival and overall survival, with an improvement in survival of approximately 1 year for each log-depletion in MRD level. The most widely used methods to assess MRD status include flow cytometry and clonality detection, using next-generation sequencing technologies with sensitivity limits of 1:10−3 to 1:10−6. The timing of when to assess MRD depends on the treatment used, as well as the molecular and cytogenetic subgroup of the myeloma itself. It is also becoming clear that the level of MRD negativity, as well as microenvironmental factors, are important prognostically, including the regeneration of normal plasma cells, and the normalization of the immune repertoire. With advances in antibody-based therapy and immunotherapy, the achievement of stable MRD states is now possible for a significant proportion of patients, and is a prerequisite for myeloma cure.


2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1073-1073
Author(s):  
Chaitanya Ramanuj Acharya ◽  
Herbert K Lyerly

1073 Background: The prognostic and predictive value of tumor infiltrating lymphocytes for ICB has been recognized in a variety of tumor types, including TNBC. Nonetheless, our understanding of the mechanistic aspects of T cell activation remains incomplete. We hypothesize that a specific effector phenotype of T cell cytolytic activity (ECA) is a consistent feature of epithelial tumors, possibly varying by tumor types with a range of inflammatory features. Methods: We evaluated 6,311 purified CD3+ single cells from human primary TNBC and computed sample set enrichment scores of a set of previously published immune metagenes. Following unsupervised clustering of the enrichment scores of the entire single cell population, two subgroups of cells with highest and lowest average enrichment score of T cell cytolytic activity formed a basis for detecting functional gene expression modules. Spectral decomposition and Jackstraw analysis estimated eight modules with overlapping sets of genes. Each gene expression module was then used to train a Random Forest classifier of ECA phenotype. Results: We discovered that our module-derived classifiers were prognostic not only in TNBC samples obtained from both TCGA (N = 150) and METABRIC (N = 320) datasets but also in 14 other tumor types encompassing 6,000 samples. For example, patient samples from TCGA dataset predicted to be in group ECA ‘High’ have better progression-free survival (p-value: 0.0098l; HR: 0.30) and better overall survival (p-value: 0.0066; HR: 0.17). In both breast datasets, gene within the classifier are relatively under-expressed in ER+ tumors as opposed to HER2+ and TNBC (p-value < 2.2e-16). In a dataset of normal, pure DCIS and mixed DCIS (GSE26304;N = 114), the same genes were relatively under-expressed in DCIS samples relative to invasive tumors (p-value < 2.2e-16). Additionally, in a pre-therapy tumor dataset of fifty-one advanced melanoma patients treated with Nivolumab, who previously either progressed on ipilimumab or were ipilimumab-naïve, our module-derived classifier was able to classify responders and non-responders with 77% accuracy (p-value = 0.02) and was associated with progression-free survival (p-value = 0.03; HR: 0.28). Conclusions: Our study highlights one important application of single-cell genomics in our understanding of immune microenvironment and potentially identify new immunotherapy targets.


2017 ◽  
Author(s):  
Maurizio Pellegrino ◽  
Adam Sciambi ◽  
Sebastian Treusch ◽  
Robert Durruthy-Durruthy ◽  
Kaustubh Gokhale ◽  
...  

ABSTRACTTo enable the characterization of genetic heterogeneity in tumor cell populations, we developed a novel microfluidic approach that barcodes amplified genomic DNA from thousands of individual cancer cells confined to droplets. The barcodes are then used to reassemble the genetic profiles of cells from next generation sequencing data. Using this approach, we sequenced longitudinally collected AML tumor populations from two patients and genotyped up to 62 disease relevant loci across more than 16,000 individual cells. Targeted single-cell sequencing was able to sensitively identify tumor cells during complete remission and uncovered complex clonal evolution within AML tumors that was not observable with bulk sequencing. We anticipate that this approach will make feasible the routine analysis of heterogeneity in AML leading to improved stratification and therapy selection for the disease.


Author(s):  
Roos Houtsma ◽  
Nisha K. van der Meer ◽  
Kees Meijer ◽  
Linde Morsink ◽  
Shanna M. Hogeling ◽  
...  

Acute myeloid leukemia (AML) often presents as an oligoclonal disease whereby multiple genetically distinct subclones can co-exist within patients. Differences in signaling and drug sensitivity of such subclones complicates treatment and warrants tools to identify them and track disease progression. We previously identified over 50 AML-specific plasma membrane (PM) proteins and seven of these (CD82, CD97, FLT3, IL1RAP, TIM3, CD25 and CD123) were implemented in routine diagnostics in patients with AML (n=256) and MDS (n=33). We developed a pipeline termed CombiFlow in which expression data of multiple PM markers is merged, allowing a Principle Component-based analyses to identify distinctive marker expression profiles and to generate single cell tSNE landscapes to longitudinally track clonal evolution. Positivity for one or more of the markers after 2 courses of intensive chemotherapy predicted a shorter relapse-free survival supporting a role of these markers in measurable residual disease (MRD) detection. CombiFlow also allowed the tracking of clonal evolution in paired diagnosis and relapse samples (n=12). Extending the panel to 36 AML-specific markers further refined the CombiFlow pipeline. In conclusion, CombiFlow provides a valuable tool in the diagnosis, MRD detection, clonal tracking, and the understanding of clonal heterogeneity in AML.


Author(s):  
Daniele Ramazzotti ◽  
Fabrizio Angaroni ◽  
Davide Maspero ◽  
Gianluca Ascolani ◽  
Isabella Castiglioni ◽  
...  

ABSTRACTThe rise of longitudinal single-cell sequencing experiments on patient-derived cell cultures, xenografts and organoids is opening new opportunities to track cancer evolution in single tumors and to investigate intra-tumor heterogeneity. This is particularly relevant when assessing the efficacy of therapies over time on the clonal composition of a tumor and in the identification of resistant subclones.We here introduce LACE (Longitudinal Analysis of Cancer Evolution), the first algorithmic framework that processes single-cell somatic mutation profiles from cancer samples collected at different time points and in distinct experimental settings, to produce longitudinal models of cancer evolution. Our approach solves a Boolean matrix factorization problem with phylogenetic constraints, by maximizing a weighted likelihood function computed on multiple time points, and we show with simulations that it outperforms state-of-the-art methods for both bulk and single-cell sequencing data.Remarkably, as the results are robust with respect to high levels of data-specific errors, LACE can be employed to process single-cell mutational profiles as generated by calling variants from the increasingly available scRNA-seq data, thus obviating the need of relying on rarer and more expensive genome sequencing experiments. This also allows to investigate the relation between genomic clonal evolution and phenotype at the single-cell level.To illustrate the capabilities of LACE, we show its application to a longitudinal scRNA-seq dataset of patient-derived xenografts of BRAFV600E/K mutant melanomas, in which we characterize the impact of concurrent BRAF/MEK-inhibition on clonal evolution, also by showing that distinct genetic clones reveal different sensitivity to the therapy. Furthermore, the analysis of a longitudinal dataset of breast cancer PDXs from targeted scDNA-sequencing experiments delivers a high-resolution characterization of intra-tumor heterogeneity, also allowing the detection of a late de novo subclone.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3834-3834
Author(s):  
Christoph Niemöller ◽  
Sabine Bleul ◽  
Nadja Blagitko-Dorfs ◽  
Christine Greil ◽  
Kenichi Yoshida ◽  
...  

Abstract INTRODUCTION: We recently described the first case of the evolution of inv(16) AML on the background of a clonal hematopoiesis due to a germline CBL mutation (defining the CBL syndrome), and we identified possibly cooperating mutations by exome sequencing (Becker et al. Blood 2014;123:1883-6). Among the mutated genes was PTPRT, encoding a protein tyrosine phosphatase that inhibits STAT3 activity and is commonly mutated in cancer (reviewed by Zhao et al. Oncogene 2015;34:3885-94). Here, we investigated the co-occurrence of mutated PTPRT with other mutated genes by single cell genotyping in order gain insights into the clonal architecture and sequence of mutation acquisition. METHODS: Exome sequencing of the bulk specimens was previously described; germline or somatic origin of mutations was verified in skin fibroblasts (Becker et al. Blood 2014;123:1883-6). For single cell genotyping, Ficoll-enriched bone marrow aspirates were DAPI stained, and single cells were placed into each well of a PCR plate using a MoFlo high speed cell sorter (Beckman Coulter). Genomic DNA was amplified by whole genome amplification (WGA) using the REPLI-g Mini Kit (Qiagen) according to a modified protocol, and subjected to PCR and Sanger sequencing of the respective mutation loci. As WGA can lead to allele dropout (ADO), we also sequenced single nucleotide polymorphisms (SNPs), that were identified by CytoScan HD array (Affymetrix) to be heterozygous in the sample and that were located nearby the respective mutation loci. RESULTS: Exome sequencing allows prediction of a possible clonal architecture based on the variant allele frequencies (VAFs). VAFs of the mutations identified in the AML were as follows: KIF14 p.V341I (VAF 51%), TMEM125 p.D113N (51%), MIOX p.W225R (46%), CAND1 p.E584* (39%), NID2 p.D319N (38%), ARF3 p.N101S (36%), PRSS16 p.R491C (36%), PTPRT p.T844M (33%), DOCK6 p.R1872_K1873insP (33%), ADAM12 p.A222V (21%), CMIP p.T323M (15%) and MYOCD p.D283N (7%); due to its germline nature, all leukemic cells harbored the CBL p.D390V mutation. In order to verify the co-occurrence of mutations in a clone and thus the clonal architecture, we performed single cell genotyping of the mutations in PTPRT as well as CAND1 and DOCK6. CAND1 and DOCK6 were selected in addition to PTPRT since their comparable VAFs did not allow identifying the sequence of acquisition. Moreover, CAND1 and DOCK6 were affected by likely deleterious mutations and were previously found mutated in AML. To control for ADO, we included the heterozygous SNPs rs2867061 (PTPRT), rs1252402 (C AND1), and rs12980863 (DOCK6) in our analyses. We analyzed 19 single cells for the 6 mutations and SNPs. This resulted in 102 successful sequencing reactions, and yielded informative results for at least 2 mutations in 12 cells and for all 3 mutations in 5 cells. Based on the concurrent presence of the wild-type allele at the mutation locus and ADO at the SNP site, 18 mutation analyses were judged to be inconclusive. Overall, our analyses confirmed that the mutations in CAND1, PTPRT and DOCK6 occurred together in the same clone. Moreover, based on the identification of cells with the presence of both CAND1 and DOCK6 mutations but presence or absence of PTPRT mutations, respectively, we concluded that PTPRT mutations were acquired after the mutations in DOCK6 and CAND1. CONCLUSION: Single cell genotyping verified the co-occurrence of PTPRT, CAND1 and DOCK6 mutations in the same AML clone and revealed a clonal hierarchy, as the PTPRT mutation was acquired after the mutations in CAND1 and DOCK6. These insights into the clonal architecture and evolution had not been possible solely based on exome sequencing and suggest that the sequential expression of mutated PTPRT may cooperate with mutated CBL and inv(16) at a late stage of AML development. Disclosures No relevant conflicts of interest to declare.


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