Phenotype-based drug screening reveals association between venetoclax response and differentiation stage in acute myeloid leukemia

Ex vivo drug testing is a promising approach to identify novel treatment strategies for acute myeloid leukemia (AML). However, accurate blast- specific drug responses cannot be measured with homogeneous "add-mix-measure" cell viability assays. In this study, we implemented a flow cytometry-based approach to simultaneously evaluate the ex vivo sensitivity of different cell populations in 34 primary AML samples to seven drugs and 27 rational drug combinations. Our data demonstrate that different cell populations present in AML samples have distinct sensitivity to targeted therapies. Particularly, blast cells of FAB M0/1 AML showed high sensitivity to venetoclax. In contrast, differentiated monocytic cells abundantly present in M4/5 subtypes showed resistance to Bcl-2 inhibition, whereas immature blasts in the same samples were sensitive, highlighting the importance of blast-specific readouts. Accordingly, in the total mononuclear cell fraction the highest BCL2/MCL1 gene expression ratio was observed in M0/1 and the lowest in M4/5 AML. Of the seven tested drugs, venetoclax had the highest blast-specific toxicity, and combining venetoclax with either MEK inhibitor trametinib or JAK inhibitor ruxolitinib effectively targeted all venetoclax-resistant blasts. In conclusion, we show that ex vivo efficacy of targeted agents and particularly Bcl-2 inhibitor venetoclax is influenced by the cell type, and accurate blast-specific drug responses can be assessed with a flow cytometry-based approach.Peer reviewe

Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA) genes remains to be dissected in detail. To address this, we followed a data-driven approach and developed a transcript identification, validation and quantification pipeline for characterizing the regulatory domains of pri-miRNAs. Integration of 92 nascent transcriptomes and multilevel data from cells arising from ecto-, endo- and mesoderm lineages reveals cell type-specific expression patterns, allows fine-resolution mapping of transcription start sites (TSS) and identification of candidate regulatory regions. We show that inter- and intragenic pri-miRNA transcripts span vast genomic regions and active TSS locations differ across cell types, exemplified by the mir-29a∼29b-1, mir-100∼let-7a-2∼125b-1 and miR-221∼222 clusters. Considering the presence of multiple TSS as an important regulatory feature at miRNA loci, we developed a strategy to quantify differential TSS usage. We demonstrate that the TSS activities associate with cell type-specific super-enhancers, differential stimulus responsiveness and higher-order chromatin structure. These results pave the way for building detailed regulatory maps of miRNA loci

Hemap: An nteractive online resource for characterizing molecular phenotypes across hematologic malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease contexts for new therapeutic approaches. We analyzed 9,544 transcriptomes from over 30 hematologic malignancies, normal blood cell types and cell lines, and show that the disease types can be stratified in a data-driven manner. We utilized the obtained molecular clustering for discovery of cluster-specific pathway activity, new biomarkers and in silico drug target prioritization through integration with drug target databases. Using known vulnerabilities and available drug screens in benchmarking, we highlight the importance of integrating the molecular phenotype context and drug target expression for in silico prediction of drug responsiveness. Our analysis implicates BCL2 expression level as important indicator of venetoclax responsiveness and provides a rationale for its targeting in specific leukemia subtypes and multiple myeloma, links several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7 and EZH1) with CLL, and supports CDK6 as disease-specific target in AML. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our freely available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies

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Computational textural mapping harmonises sampling variation and reveals multidimensional histopathological fingerprints

Peer reviewe

Editorial for the special issue "Frontiers in spectral imaging and 3D technologies for geospatial solutions"

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.nonPeerReviewe

Hemap : An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies.Peer reviewe