scholarly journals Single-Cell Analysis of the Transcriptional Response in AML Patients Treated with BET-Inhibitors

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5120-5120
Author(s):  
Sophia Miliara ◽  
Bogumil Kaczkowski ◽  
Takahiro Suzuki ◽  
Huthayfa Mujahed ◽  
Maasaki Furuno ◽  
...  

Abstract Acute Myeloid Leukemia (AML) is the most common myeloid leukemia in adults. Although substantial progress has been made in recent years, the long-term prognosis for patients remains poor which is mainly due to the dated treatments that consist of cytotoxic drugs with low specificity. AML is a clonal disease with multiple co-existing clones in each patient. Often, patients that initially respond to treatment may develop resistance due to lingering leukemic stem cells (LSC), or sub-clones that survive the treatment and cause a relapse. Therefore, novel therapeutic strategies are needed to fully eradicate all leukemic cells. AML has a strong epigenetic component meaning mutations in genes encoding epigenetic regulators are frequently acquired during early AML development, and are present in the initiating clones. Thus, targeting the epigenetic machinery may offer a new avenue for AML treatment. Among the newer epigenetic drugs are BET inhibitors, which bind reversibly to bromodomains of BRD proteins and prevent protein-protein interactions with acetylated histones and transcriptions factors. One of the most promising BET inhibitors is OTX015, which has already been in Phase II clinical trials for AML in the U.S. (Braun & Gardin, Expert Opinion on Investigational Drugs, 2017). We aim to analyze the heterogeneous response to OTX015 in AML, and normal stem/progenitor, cells in order to dissect the BET-inhibitor response. The main focus is the specific transcriptional signatures at promoters and enhancers as enhancers, and especially super-enhancers, have previously been shown to be sensitive to BET-inhibitors (Loven et al, Cell, 2013). To this effect, we have established a protocol that allowed for the transcriptional profiling of single cells from AML patients that were at different differentiation stages, using FACS- sorting. The patients were obtained from the Swedish Acute Leukemia Registry. To decrease population heterogeneity, the project focused on distinct subgroups of AML that previously has been shown to be sensitive for BET inhibitors. The different isolated AML, and normal progenitor populations, were exposed to OTX015 for 48hrs, and processed with both bulk transcriptional profiling of the general cell population response, and single cell profiling to analyze cell heterogeneity, and single cell response. For the transcriptional profiling, we utilized a unique technique called Cap Analysis of Gene Expression (CAGE), a powerful 5' start profiling technology, that allows for the identification of the transcription start site at base pair resolution, and determination of enhancer activity based on enhancer RNA expression. The single cell profiling was performed using C1 CAGE, which is a single-cell implementation CAGE (Kouno et al, bioRxiv 330845, 2018).We envision that the heterogenic transcriptional drug response, on the single-cell level, in AML and normal stem/progenitor cells will lead to the identification of key genes and pathways involved in the differential drug response. Additionally, the application of CAGE technology will lead to discovery of specific transcriptional signatures at promoters and enhancers that may be predictive of drug resistance. Clinical significance: Leukemic cell heterogeneity remains the main problem in AML, as chemotherapy often fails to completely eradicate all AML sub-clones including LSC, leading to relapses and high mortality of the disease. This study will shed light to the unique features of AML cell heterogeneity and how their drug response differs, not only between AML cells, but also between AML cells and their normal counterparts, on the single-cell level, based on the response to OTX015. The significance will be two-fold: the in-depth characterization of the features in AML populations and normal cells, and the potential this study will provide for novel, more targeted, combination treatments in AML. Disclosures No relevant conflicts of interest to declare.

The Analyst ◽  
2014 ◽  
Vol 139 (22) ◽  
pp. 5709-5717 ◽  
Author(s):  
A. Mareike Schmidt ◽  
Stephan R. Fagerer ◽  
Konstantins Jefimovs ◽  
Florian Buettner ◽  
Christian Marro ◽  
...  

Studying cell-to-cell heterogeneity requires techniques which robustly deliver reproducible results with single-cell sensitivity.


2021 ◽  
Author(s):  
Sheng Zhu ◽  
Qiwei Lian ◽  
Wenbin Ye ◽  
Wei Qin ◽  
Zhe Wu ◽  
...  

Abstract Alternative polyadenylation (APA) is a widespread regulatory mechanism of transcript diversification in eukaryotes, which is increasingly recognized as an important layer for eukaryotic gene expression. Recent studies based on single-cell RNA-seq (scRNA-seq) have revealed cell-to-cell heterogeneity in APA usage and APA dynamics across different cell types in various tissues, biological processes and diseases. However, currently available APA databases were all collected from bulk 3′-seq and/or RNA-seq data, and no existing database has provided APA information at single-cell resolution. Here, we present a user-friendly database called scAPAdb (http://www.bmibig.cn/scAPAdb), which provides a comprehensive and manually curated atlas of poly(A) sites, APA events and poly(A) signals at the single-cell level. Currently, scAPAdb collects APA information from > 360 scRNA-seq experiments, covering six species including human, mouse and several other plant species. scAPAdb also provides batch download of data, and users can query the database through a variety of keywords such as gene identifier, gene function and accession number. scAPAdb would be a valuable and extendable resource for the study of cell-to-cell heterogeneity in APA isoform usages and APA-mediated gene regulation at the single-cell level under diverse cell types, tissues and species.


2020 ◽  
Author(s):  
Maria Anna Rapsomaniki ◽  
Stella Maxouri ◽  
Manuel Ramirez Garrastacho ◽  
Patroula Nathanailidou ◽  
Nickolaos Nikiforos Giakoumakis ◽  
...  

AbstractDNA replication is a complex and remarkably robust process: despite its inherent uncertainty, manifested through stochastic replication timing at a single-cell level, multiple control mechanisms ensure its accurate and timely completion across a population. Disruptions in these mechanisms lead to DNA re-replication, closely connected to genomic instability and oncogenesis. We present a stochastic hybrid model of DNA re-replication that accurately portrays the interplay between discrete dynamics, continuous dynamics, and uncertainty. Using experimental data on the fission yeast genome, model simulations show how different regions respond to re-replication, and permit insight into the key mechanisms affecting re-replication dynamics. Simulated and experimental population-level profiles exhibit good correlation along the genome, which is robust to model parameters, validating our approach. At a single-cell level, copy numbers of individual loci are affected by intrinsic properties of each locus, in cis effects from adjoining loci and in trans effects from distant loci. In silico analysis and single-cell imaging reveal that cell-to-cell heterogeneity is inherent in re-replication and can lead to a plethora of genotypic variations. Our thorough in silico analysis of DNA re-replication across a complete genome reveals that heterogeneity at the single cell level and robustness at the population level are emerging and co-existing principles of DNA re-replication. Our results indicate that re-replication can promote genome plasticity by generating many diverse genotypes within a population, potentially offering an evolutionary advantage in cells with aberrations in replication control mechanisms.


Rheumatology ◽  
2021 ◽  
Author(s):  
Barbora Schonfeldova ◽  
Kristina Zec ◽  
Irina A Udalova

Abstract Despite extensive research, there is still no treatment that would lead to remission in all patients with rheumatoid arthritis as our understanding of the affected site, the synovium, is still incomplete. Recently, single-cell technologies helped to decipher the cellular heterogeneity of the synovium; however, certain synovial cell populations, such as endothelial cells or peripheral neurons, remain to be profiled on a single-cell level. Furthermore, associations between certain cellular states and inflammation were found; whether these cells cause the inflammation remains to be answered. Similarly, cellular zonation and interactions between individual effectors in the synovium are yet to be fully determined. A deeper understanding of cell signalling and interactions in the synovium is crucial for a better design of therapeutics with the goal of complete remission in all patients.


2015 ◽  
Vol 12 (103) ◽  
pp. 20141109 ◽  
Author(s):  
Congzhou Wang ◽  
Christopher J. Ehrhardt ◽  
Vamsi K. Yadavalli

Cell surface carbohydrates are important to various bacterial activities and functions. It is well known that different types of Bacillus display heterogeneity of surface carbohydrate compositions, but detection of their presence, quantitation and estimation of variation at the single cell level have not been previously solved. Here, using atomic force microscopy (AFM)-based recognition force mapping coupled with lectin probes, the specific carbohydrate distributions of N -acetylglucosamine and mannose/glucose were detected, mapped and quantified on single B. cereus surfaces at the nanoscale across the entire cell. Further, the changes of the surface carbohydrate compositions from the vegetative cell to spore were shown. These results demonstrate AFM-based ‘recognition force mapping’ as a versatile platform to quantitatively detect and spatially map key bacterial surface biomarkers (such as carbohydrate compositions), and monitor in situ changes in surface biochemical properties during intracellular activities at the single cell level.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Maria Anna Rapsomaniki ◽  
Stella Maxouri ◽  
Patroula Nathanailidou ◽  
Manuel Ramirez Garrastacho ◽  
Nickolaos Nikiforos Giakoumakis ◽  
...  

Abstract DNA replication is a complex and remarkably robust process: despite its inherent uncertainty, manifested through stochastic replication timing at a single-cell level, multiple control mechanisms ensure its accurate and timely completion across a population. Disruptions in these mechanisms lead to DNA re-replication, closely connected to genomic instability and oncogenesis. Here, we present a stochastic hybrid model of DNA re-replication that accurately portrays the interplay between discrete dynamics, continuous dynamics and uncertainty. Using experimental data on the fission yeast genome, model simulations show how different regions respond to re-replication and permit insight into the key mechanisms affecting re-replication dynamics. Simulated and experimental population-level profiles exhibit a good correlation along the genome, robust to model parameters, validating our approach. At a single-cell level, copy numbers of individual loci are affected by intrinsic properties of each locus, in cis effects from adjoining loci and in trans effects from distant loci. In silico analysis and single-cell imaging reveal that cell-to-cell heterogeneity is inherent in re-replication and can lead to genome plasticity and a plethora of genotypic variations.


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