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Dive into the research topics where Jan Stuchly is active.

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Featured researches published by Jan Stuchly.


Blood | 2015

The predictive strength of next-generation sequencing MRD detection for relapse compared with current methods in childhood ALL

Michaela Kotrova; Katerina Muzikova; Ester Mejstrikova; Michaela Novakova; Violeta Bakardjieva-Mihaylova; Karel Fiser; Jan Stuchly; Mathieu Giraud; Mikaël Salson; Christiane Pott; Monika Brüggemann; Marc Füllgrabe; Jan Stary; Jan Trka; Eva Fronkova

To the editor: Minimal residual disease (MRD) monitoring via antigen receptor quantitative polymerase chain reaction (qPCR) is an important predictor of outcome in childhood acute lymphoblastic leukemia (ALL), is rigorously standardized within the EuroMRD consortium and has a greater sensitivity


Apmis | 2011

Plasma EBV‐DNA monitoring in Epstein–Barr virus‐positive Hodgkin lymphoma patients

Martin Spacek; Petr Hubacek; Jana Markova; Miroslav Zajac; Zdenka Vernerová; Katerina Kamaradova; Jan Stuchly; Tomas Kozak

Spacek M, Hubacek P, Markova J, Zajac M, Vernerova Z, Kamaradova K, Stuchly J, Kozak T. Plasma EBV‐DNA monitoring in Epstein–Barr virus‐positive Hodgkin lymphoma patients. APMIS 2010.


Haematologica | 2016

Characterization of leukemias with ETV6-ABL1 fusion

Marketa Zaliova; Anthony V. Moorman; Giovanni Cazzaniga; Martin Stanulla; Richard C. Harvey; Kathryn G. Roberts; Susan L. Heatley; Mignon L. Loh; Marina Konopleva; I-Ming Chen; Olga Zimmermannova; Claire Schwab; Owen P. Smith; Marie-Joelle Mozziconacci; Christian Chabannon; Myungshin Kim; J.H. Frederik Falkenburg; Alice Norton; Karen Marshall; Oskar A. Haas; Julia Starkova; Jan Stuchly; Stephen P. Hunger; Deborah White; Charles G. Mullighan; Cheryl L. Willman; Jan Stary; Jan Trka; Jan Zuna

To characterize the incidence, clinical features and genetics of ETV6-ABL1 leukemias, representing targetable kinase-activating lesions, we analyzed 44 new and published cases of ETV6-ABL1-positive hematologic malignancies [22 cases of acute lymphoblastic leukemia (13 children, 9 adults) and 22 myeloid malignancies (18 myeloproliferative neoplasms, 4 acute myeloid leukemias)]. The presence of the ETV6-ABL1 fusion was ascertained by cytogenetics, fluorescence in-situ hybridization, reverse transcriptase-polymerase chain reaction and RNA sequencing. Genomic and gene expression profiling was performed by single nucleotide polymorphism and expression arrays. Systematic screening of more than 4,500 cases revealed that in acute lymphoblastic leukemia ETV6-ABL1 is rare in childhood (0.17% cases) and slightly more common in adults (0.38%). There is no systematic screening of myeloproliferative neoplasms; however, the number of ETV6-ABL1-positive cases and the relative incidence of acute lymphoblastic leukemia and myeloproliferative neoplasms suggest that in adulthood ETV6-ABL1 is more common in BCR-ABL1-negative chronic myeloid leukemia-like myeloproliferations than in acute lymphoblastic leukemia. The genomic profile of ETV6-ABL1 acute lymphoblastic leukemia resembled that of BCR-ABL1 and BCR-ABL1-like cases with 80% of patients having concurrent CDKN2A/B and IKZF1 deletions. In the gene expression profiling all the ETV6-ABL1-positive samples clustered in close vicinity to BCR-ABL1 cases. All but one of the cases of ETV6-ABL1 acute lymphoblastic leukemia were classified as BCR-ABL1-like by a standardized assay. Over 60% of patients died, irrespectively of the disease or age subgroup examined. In conclusion, ETV6-ABL1 fusion occurs in both lymphoid and myeloid leukemias; the genomic profile and clinical behavior resemble BCR-ABL1-positive malignancies, including the unfavorable prognosis, particularly of acute leukemias. The poor outcome suggests that treatment with tyrosine kinase inhibitors should be considered for patients with this fusion.


Proteomics | 2011

Multiplexed immuno-precipitation with 1725 commercially available antibodies to cellular proteins

Heidi Slaastad; Weiwei Wu; Luiz Goullart; Veronika Kanderová; Geir E. Tjønnfjord; Jan Stuchly; Tomáš Kalina; Anders Holm; Fridtjof Lund-Johansen

Antibody array analysis of complex samples requires capture reagents with exceptional specificity. The frequency of antibodies with label‐based detection may be as low as 5%. Here, however, we show that as many as 25% of commercially available antibodies are useful when biotinylated cellular proteins are fractionated by size exclusion chromatography (SEC) first. A microsphere multiplex with 1725 antibodies to cellular proteins was added to 24 SEC fractions, labelled with streptavidin and analyzed by flow cytometry (microsphere‐based affinity proteomics, MAP) The SEC‐MAP approach resolved different targets captured by each antibody as reactivity peaks across the separation range of the SEC column (10–670kDa). Complex reactivity profiles demonstrated that most antibodies bound more than one target. However, specific binding was readily detected as reactivity peaks common for different antibodies to the same protein. We optimized sample preparation and found that amine‐reactive biotin rarely inhibited antibody binding when the biotin to lysine ratio was kept below 1:1 during labelling. Moreover, several epitopes that were inaccessible to antibodies in native proteins were unmasked after heat denaturation with 0.1% of SDS. The SEC‐MAP format should allow researchers to build multiplexed assays with antibodies purchased for use in e.g. Western blotting.


Nature Methods | 2016

MetaMass, a tool for meta-analysis of subcellular proteomics data

Fridtjof Lund-Johansen; Daniel de la Rosa Carrillo; Adi Mehta; Krzysztof Sikorski; Marit Inngjerdingen; Tomáš Kalina; Kjetil Røysland; Gustavo Antonio de Souza; Andrew Bradbury; Quentin Lecrevisse; Jan Stuchly

We report a tool for the analysis of subcellular proteomics data, called MetaMass, based on the use of standardized lists of subcellular markers. We analyzed data from 11 studies using MetaMass, mapping the subcellular location of 5,970 proteins. Our analysis revealed large variations in the performance of subcellular fractionation protocols as well as systematic biases in protein annotation databases. The Excel and R versions of MetaMass should enhance transparency and reproducibility in subcellular proteomics.


Genes, Chromosomes and Cancer | 2017

ETV6/RUNX1‐like acute lymphoblastic leukemia: A novel B‐cell precursor leukemia subtype associated with the CD27/CD44 immunophenotype

Marketa Zaliova; Michaela Kotrova; Silvia Bresolin; Jan Stuchly; Jan Stary; Ondrej Hrusak; Geertruy te Kronnie; Jan Trka; Jan Zuna; Martina Vaskova

We have shown previously that ETV6/RUNX1‐positive acute lymphoblastic leukemia (ALL) is distinguishable from other ALL subtypes by CD27pos/CD44low‐neg immunophenotype. During diagnostic immunophenotyping of 573 childhood B‐cell precursor ALL (BCP‐ALL), we identified eight cases with this immunophenotype among “B‐other ALL” (BCP‐ALL cases negative for routinely tested chromosomal/genetic aberrations). We aimed to elucidate whether these cases belong to the recently described ETV6/RUNX1‐like ALL defined by the ETV6/RUNX1‐specific gene expression profile (GEP), harboring concurrent ETV6 and IKZF1 lesions. We performed comprehensive genomic analysis using single nucleotide polymorphism arrays, whole exome and transcriptome sequencing and GEP on microarrays. In unsupervised hierarchical clustering based on GEP, five out of seven analyzed CD27pos/CD44low‐neg B‐other cases clustered with ETV6/RUNX1‐positive ALL and were thus classified as ETV6/RUNX1‐like ALL. The two cases clustering outside ETV6/RUNX1‐positive ALL harbored a P2RY8/CRLF2 fusion with activating JAK2 mutations and a TCF3/ZNF384 fusion, respectively, assigning them to other ALL subtypes. All five ETV6/RUNX1‐like cases harbored ETV6 deletions; uniform intragenic ARPP21 deletions and various IKZF1 lesions were each found in three ETV6/RUNX1‐like cases. The frequency of ETV6 and ARPP21 deletions was significantly higher in ETV6/RUNX1‐like ALL compared with a reference cohort of 42 B‐other ALL. In conclusion, we show that ETV6/RUNX1‐like ALL is associated with CD27pos/CD44low‐neg immunophenotype and identify ARPP21 deletions to contribute to its specific genomic profile enriched for ETV6 and IKZF1 lesions. In conjunction with previously published data, our study identifies the ETV6 lesion as the only common genetic aberration and thus the most likely key driver of ETV6/RUNX1‐like ALL.


Oncogene | 2017

An activating mutation of GNB1 is associated with resistance to tyrosine kinase inhibitors in ETV6-ABL1-positive leukemia

O Zimmermannova; E Doktorova; Jan Stuchly; V Kanderova; D Kuzilkova; H Strnad; Julia Starkova; Meritxell Alberich-Jorda; J H F Falkenburg; Jan Trka; Jiri Petrak; Jan Zuna; Marketa Zaliova

Leukemias harboring the ETV6-ABL1 fusion represent a rare subset of hematological malignancies with unfavorable outcomes. The constitutively active chimeric Etv6-Abl1 tyrosine kinase can be specifically inhibited by tyrosine kinase inhibitors (TKIs). Although TKIs represent an important therapeutic tool, so far, the mechanism underlying the potential TKI resistance in ETV6-ABL1-positive malignancies has not been studied in detail. To address this issue, we established a TKI-resistant ETV6-ABL1-positive leukemic cell line through long-term exposure to imatinib. ETV6-ABL1-dependent mechanisms (including fusion gene/protein mutation, amplification, enhanced expression or phosphorylation) and increased TKI efflux were excluded as potential causes of resistance. We showed that TKI effectively inhibited the Etv6-Abl1 kinase activity in resistant cells, and using short hairpin RNA (shRNA)-mediated silencing, we confirmed that the resistant cells became independent from the ETV6-ABL1 oncogene. Through analysis of the genomic and proteomic profiles of resistant cells, we identified an acquired mutation in the GNB1 gene, K89M, as the most likely cause of the resistance. We showed that cells harboring mutated GNB1 were capable of restoring signaling through the phosphoinositide-3-kinase (PI3K)/Akt/mTOR and mitogen-activated protein kinase (MAPK) pathways, whose activation is inhibited by TKI. This alternative GNB1K89M-mediated pro-survival signaling rendered ETV6-ABL1-positive leukemic cells resistant to TKI therapy. The mechanism of TKI resistance is independent of the targeted chimeric kinase and thus is potentially relevant not only to ETV6-ABL1-positive leukemias but also to a wider spectrum of malignancies treated by kinase inhibitors.


Molecular & Cellular Proteomics | 2016

High-resolution Antibody Array Analysis of Childhood Acute Leukemia Cells

Veronika Kanderová; Daniela Kuzilkova; Jan Stuchly; Martina Vaskova; Tomas Brdicka; Karel Fiser; Ondrej Hrusak; Fridtjof Lund-Johansen; Tomáš Kalina

Acute leukemia is a disease pathologically manifested at both genomic and proteomic levels. Molecular genetic technologies are currently widely used in clinical research. In contrast, sensitive and high-throughput proteomic techniques for performing protein analyses in patient samples are still lacking. Here, we used a technology based on size exclusion chromatography followed by immunoprecipitation of target proteins with an antibody bead array (Size Exclusion Chromatography-Microsphere-based Affinity Proteomics, SEC-MAP) to detect hundreds of proteins from a single sample. In addition, we developed semi-automatic bioinformatics tools to adapt this technology for high-content proteomic screening of pediatric acute leukemia patients. To confirm the utility of SEC-MAP in leukemia immunophenotyping, we tested 31 leukemia diagnostic markers in parallel by SEC-MAP and flow cytometry. We identified 28 antibodies suitable for both techniques. Eighteen of them provided excellent quantitative correlation between SEC-MAP and flow cytometry (p < 0.05). Next, SEC-MAP was applied to examine 57 diagnostic samples from patients with acute leukemia. In this assay, we used 632 different antibodies and detected 501 targets. Of those, 47 targets were differentially expressed between at least two of the three acute leukemia subgroups. The CD markers correlated with immunophenotypic categories as expected. From non-CD markers, we found DBN1, PAX5, or PTK2 overexpressed in B-cell precursor acute lymphoblastic leukemias, LAT, SH2D1A, or STAT5A overexpressed in T-cell acute lymphoblastic leukemias, and HCK, GLUD1, or SYK overexpressed in acute myeloid leukemias. In addition, OPAL1 overexpression corresponded to ETV6-RUNX1 chromosomal translocation. In summary, we demonstrated that SEC-MAP technology is a powerful tool for detecting hundreds of proteins in clinical samples obtained from pediatric acute leukemia patients. It provides information about protein size and reveals differences in protein expression between particular leukemia subgroups. Forty-seven of SEC-MAP identified targets were validated by other conventional method in this study.


Nature Methods | 2018

A high-throughput pipeline for validation of antibodies

Krzysztof Sikorski; Adi Mehta; Marit Inngjerdingen; Flourina Thakor; Simon Kling; Tomas Kalina; Tuula A. Nyman; Maria Stensland; Wei Zhou; Gustavo A. de Souza; Lars Holden; Jan Stuchly; Markus F. Templin; Fridtjof Lund-Johansen

Western blotting (WB) is widely used to test antibody specificity, but the assay has low throughput and precision. Here we used preparative gel electrophoresis to develop a capture format for WB. Fractions with soluble, size-separated proteins facilitated parallel readout with antibody arrays, shotgun mass spectrometry (MS) and immunoprecipitation followed by MS (IP-MS). This pipeline provided the means for large-scale implementation of antibody validation concepts proposed by an international working group on antibody validation (IWGAV).This paper describes a platform for carrying out antibody-based capture and mass spectrometry in parallel, and tests the feasibility of this platform for high-throughput validation of antibodies.


Blood | 2016

Distinct bilineal leukemia immunophenotypes are not genetically determined

Michaela Kotrova; Alena Musilova; Jan Stuchly; Karel Fiser; Julia Starkova; Ester Mejstrikova; Jan Stary; Jan Zuna; Ondrej Hrusak; Jan Trka; Marketa Zaliova

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Jan Trka

Charles University in Prague

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Jan Stary

Charles University in Prague

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Tomáš Kalina

Charles University in Prague

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Jan Zuna

Charles University in Prague

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Marketa Zaliova

Charles University in Prague

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Ondrej Hrusak

Charles University in Prague

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Julia Starkova

Charles University in Prague

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Karel Fiser

Charles University in Prague

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Michaela Kotrova

Charles University in Prague

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