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5 results on '"Skuhrova-Francova, Hana"'

1. Higher-order connections between stereotyped subsets: implications for improved patient classification in CLL

Author

Agathangelidis, Andreas, Chatzidimitriou, Anastasia, Gemenetzi, Katerina, Giudicelli, Veronique, Karypidou, Maria, Plevova, Karla, Davis, Zadie, Yan, Xiao-Jie, Jeromin, Sabine, Schneider, Christof, Pedersen, Lone Bredo, Tschumper, Renee C., Sutton, Lesley-Ann, Baliakas, Panagiotis, Scarfò, Lydia, van Gastel, Ellen J., Armand, Marine, Tausch, Eugen, Biderman, Bella, Baer, Constance, Bagnara, Davide, Navarro, Alba, Langlois de Septenville, Anne, Guido, Valentina, Mitterbauer-Hohendanner, Gerlinde, Dimovski, Aleksandar, Brieghel, Christian, Lawless, Sarah, Meggendorfer, Manja, Brazdilova, Kamila, Ritgen, Matthias, Facco, Monica, Tresoldi, Cristina, Visentin, Andrea, Patriarca, Andrea, Catherwood, Mark, Bonello, Lisa, Sudarikov, Andrey, Vanura, Katrina, Roumelioti, Maria, Skuhrova Francova, Hana, Moysiadis, Theodoros, Veronese, Silvio, Giannopoulos, Krzysztof, Mansouri, Larry, Karan-Djurasevic, Teodora, Sandaltzopoulos, Raphael, Bödör, Csaba, Fais, Franco, Kater, Arnon, Panovska, Irina, Rossi, Davide, Alshemmari, Salem, Panagiotidis, Panagiotis, Costeas, Paul, Espinet, Blanca, Antic, Darko, Foroni, Letizia, Montillo, Marco, Trentin, Livio, Stavroyianni, Niki, Gaidano, Gianluca, Francia di Celle, Paola, Niemann, Carsten, Campo, Elias, Anagnostopoulos, Achilles, Pott, Christiane, Fischer, Kirsten, Hallek, Michael, Oscier, David, Stilgenbauer, Stephan, Haferlach, Claudia, Jelinek, Diane, Chiorazzi, Nicholas, Pospisilova, Sarka, Lefranc, Marie-Paule, Kossida, Sofia, Langerak, Anton W., Belessi, Chrysoula, Davi, Frederic, Rosenquist, Richard, Ghia, Paolo, and Stamatopoulos, Kostas

Published
2021
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3. Single Cell Analysis of IG Genes in CLL: Cases with Multiple IGH Rearrangements Are Constituted of Several Independent Clones Even When Indistinguishable By Flow Cytometry

Author

Brazdilova, Kamila, primary, Plevova, Karla, additional, Skuhrova Francova, Hana, additional, Kockova, Helena, additional, Chmelikova, Magdalena, additional, Borsky, Marek, additional, Burckova, Katerina, additional, Kantorova, Barbara, additional, Tichy, Boris, additional, Skabrahova, Hana, additional, Brychtova, Yvona, additional, Mayer, Jiri, additional, Doubek, Michael, additional, and Pospisilova, Sarka, additional

Published
2015
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4. Monoallelic and biallelic inactivation of TP53gene in chronic lymphocytic leukemia: selection, impact on survival, and response to DNA damage

Author

Malcikova, Jitka, Smardova, Jana, Rocnova, Ludmila, Tichy, Boris, Kuglik, Petr, Vranova, Vladimira, Cejkova, Sona, Svitakova, Miluse, Skuhrova Francova, Hana, Brychtova, Yvona, Doubek, Michael, Brejcha, Martin, Klabusay, Martin, Mayer, Jiri, Pospisilova, Sarka, and Trbusek, Martin

Abstract

Deletion of TP53gene, under routine assessment by fluorescence in situ hybridization analysis, connects with the worst prognosis in chronic lymphocytic leukemia (CLL). The presence of isolated TP53mutation (without deletion) is associated with reduced survival in CLL patients. It is unclear how these abnormalities are selected and what their mutual proportion is. We used methodologies with similar sensitivity for the detection of deletions (interphase fluorescence in situ hybridization) and mutations (yeast functional analysis) and analyzed a large consecutive series of 400 CLL patients; a subset of p53–wild-type cases (n = 132) was screened repeatedly during disease course. The most common type of TP53inactivation, ie, mutation accompanied by deletion of the remaining allele, occurred in 42 patients (10.5%). Among additional defects, the frequency of the isolated TP53mutation (n = 20; 5%) and the combination of 2 or more mutations on separate alleles (n = 5; 1.3%) greatly exceeded the sole deletion (n = 3; 0.8%). Twelve patients manifested defects during repeated investigation; in all circumstances the defects involved mutation and occurred after therapy. Monoallelic defects had a negative impact on survival and impaired in vitro response to fludarabine. Mutation analysis of the TP53should be performed before each treatment initiation because novel defects may be selected by previous therapies.

Published
2009
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5. Higher-order connections between stereotyped subsets

Author

Andrea Patriarca, Marco Montillo, Niki Stavroyianni, Claudia Haferlach, Lesley-Ann Sutton, Livio Trentin, Franco Fais, Raphael Sandaltzopoulos, Arnon P. Kater, Anton W. Langerak, Marine Armand, Davide Rossi, Diane F. Jelinek, Davide Bagnara, Lydia Scarfò, Andreas Agathangelidis, Krzysztof Giannopoulos, Eugen Tausch, Andrey Sudarikov, Silvio Veronese, Salem H. Alshemmari, B V Biderman, Zadie Davis, Chrysoula Belessi, Lisa Bonello, Achilles Anagnostopoulos, Gerlinde Mitterbauer-Hohendanner, David Oscier, Sofia Kossida, Lone Bredo Pedersen, Paolo Ghia, Csaba Bödör, Christian Brieghel, Andrea Visentin, Véronique Giudicelli, Matthias Ritgen, Panagiotis Panagiotidis, Panagiotis Baliakas, Stephan Stilgenbauer, Ellen J van Gastel, Renee C. Tschumper, Christiane Pott, Frederic Davi, Katerina Gemenetzi, Valentina Guido, Elias Campo, Gianluca Gaidano, Irina Panovska, Sabine Jeromin, Karla Plevová, Kostas Stamatopoulos, Kamila Brázdilová, Maria Karypidou, Alba Navarro, Christof W. Schneider, Theodoros Moysiadis, Larry Mansouri, Darko Antic, Cristina Tresoldi, Constance Baer, Šárka Pospíšilová, Maria Roumelioti, Katrina Vanura, Xiao-Jie Yan, Hana Skuhrová Francová, Richard Rosenquist, Blanca Espinet, Paola Francia di Celle, Monica Facco, Paul Costeas, Michael Hallek, Carsten Utoft Niemann, Teodora Karan-Djurasevic, Manja Meggendorfer, Kirsten Fischer, Aleksandar Dimovski, Letizia Foroni, Marie-Paule Lefranc, Mark Catherwood, Anne de Septenville, Anastasia Chatzidimitriou, Sarah Lawless, Nicholas Chiorazzi, Agathangelidis, Andrea, Chatzidimitriou, Anastasia, Gemenetzi, Katerina, Giudicelli, Veronique, Karypidou, Maria, Plevova, Karla, Davis, Zadie A, Yan, Xiao-Jie, Jeromin, Sabine, Schneider, Christof, Pedersen, Lone Bredo, Tschumper, Renee, Sutton, Lesley A, Baliakas, Panagioti, Scarfò, Lydia, van Gastel, Ellen J, Armand, Marine, Tausch, Eugen, Biderman, Bella, Baer, Constance, Bagnara, Davide, Navarro, Alba, de Septenville, Anne, Guido, Valentina, Mitterbauer-Hohendanner, Gerlinde, Dimovski, Aleksandar, Brieghel, Christian, Lawless, Sarah, Meggendorfer, Manja, Stranska, Kamila, Ritgen, Matthia, Facco, Monica, Tresoldi, Cristina, Visentin, Andrea, Patriarca, Andrea, Catherwood, Mark, Bonello, Lisa, Sudarikov, Andrey, Vanura, Katrina, Roumelioti, Maria, Skuhrova Francova, Hana, Moysiadis, Theodoro, Veronese, Silvio M, Giannopoulos, Krzysztof, Mansouri, Larry, Karan-Djurasevic, Teodora, Sandaltzopoulos, Raphael, Bödör, Csaba, Fais, Franco, Kater, Arnon P, Panovska-Stavridis, Irina, Rossi, Davide, Alshemmari, Salem, Panagiotidis, Panagioti, Costeas, Paul A, Espinet, Blanca, Antic, Darko, Foroni, Letizia, Montillo, Marco, Trentin, Livio, Stavroyianni, Niki, Gaidano, Gianluca, Francia di Celle, Paola, Niemann, Carsten Utoft, Campo, Elía, Anagnostopoulos, Achille, Pott, Christiane, Fischer, Kirsten, Hallek, Michael, Oscier, David Graham, Stilgenbauer, Stephan, Haferlach, Claudia, Jelinek, Diane F, Chiorazzi, Nichola, Pospisilova, Sarka, Lefranc, Marie-Paule, Kossida, Sofia, Langerak, Anton W, Belessi, Chrysoula, Davi, Frederic, Rosenquist, Richard, Ghia, Paolo, Stamatopoulos, Kostas, Experimental Immunology, Clinical Haematology, AII - Cancer immunology, CCA - Cancer biology and immunology, and Immunology

Subjects
Chronic lymphocytic leukemia, Immunology, B-cell receptor, Immunoglobulin Variable Region, Disease, Computational biology, Biology, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, hemic and lymphatic diseases, Immunoglobulin, medicine, Humans, Chronic, 030304 developmental biology, Gene Rearrangement, 0303 health sciences, Leukemia, Lymphoid Neoplasia, Repertoire, B-Cell, breakpoint cluster region, Cell Biology, Hematology, Gene rearrangement, Somatic Hypermutation, medicine.disease, Leukemia, Lymphocytic, Chronic, B-Cell, Lymphocytic, Stereotypy (non-human), Immunoglobulin Heavy Chains, Somatic Hypermutation, Immunoglobulin, 030220 oncology & carcinogenesis, IGHV@
Abstract

Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed “satellites,” were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL. Key Points: • In a series of 29 856 CLL patients, the incidence of BcR stereotypy peaked at 41%. • Higher-order relations exist between stereotyped subsets, particularly for those from U-CLL, for which satellite subsets were identified.

Published
2021

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