Search

Your search keyword '"Tzankov, Alexandar"' showing total 1,600 results
Start Over Author "Tzankov, Alexandar"
1,600 results on '"Tzankov, Alexandar"'

3. A multicenter phase II trial of anti-EGFR-immunoliposomes loaded with doxorubicin in patients with advanced triple negative breast cancer

Author

Mamot, Christoph, Wicki, Andreas, Hasler-Strub, Ursula, Riniker, Salome, Li, Qiyu, Holer, Lisa, Bärtschi, Daniela, Zaman, Khalil, von Moos, Roger, Dedes, Konstantin J., Boos, Laura A., Novak, Urban, Bodmer, Alexandre, Ritschard, Reto, Obermann, Ellen C., Tzankov, Alexandar, Ackermann, Christoph, Membrez-Antonioli, Véronique, Zürrer-Härdi, Ursina, Caspar, Clemens B., Deuster, Stefanie, Senn, Martin, Winterhalder, Ralph, and Rochlitz, Christoph

Published
2023
Full Text
View/download PDF

5. Inflammation and vascular remodeling in COVID-19 hearts

Author

Werlein, Christopher, Ackermann, Maximilian, Stark, Helge, Shah, Harshit R., Tzankov, Alexandar, Haslbauer, Jasmin Dinonne, von Stillfried, Saskia, Bülow, Roman David, El-Armouche, Ali, Kuenzel, Stephan, Robertus, Jan Lukas, Reichardt, Marius, Haverich, Axel, Höfer, Anne, Neubert, Lavinia, Plucinski, Edith, Braubach, Peter, Verleden, Stijn, Salditt, Tim, Marx, Nikolaus, Welte, Tobias, Bauersachs, Johann, Kreipe, Hans-Heinrich, Mentzer, Steven J., Boor, Peter, Black, Stephen M., Länger, Florian, Kuehnel, Mark, and Jonigk, Danny

Published
2023
Full Text
View/download PDF

6. ZEB1 shapes AML immunological niches, suppressing CD8 T cell activity while fostering Th17 cell expansion

Author

Bassani, Barbara, Simonetti, Giorgia, Cancila, Valeria, Fiorino, Antonio, Ciciarello, Marilena, Piva, Annamaria, Khorasani, Arman Mandegar, Chiodoni, Claudia, Lecis, Daniele, Gulino, Alessandro, Fonzi, Eugenio, Botti, Laura, Portararo, Paola, Costanza, Massimo, Brambilla, Marta, Colombo, Giorgia, Schwaller, Juerg, Tzankov, Alexandar, Ponzoni, Maurilio, Ciceri, Fabio, Bolli, Niccolò, Curti, Antonio, Tripodo, Claudio, Colombo, Mario P., and Sangaletti, Sabina

Published
2024
Full Text
View/download PDF

7. Determinants of SARS-CoV-2 entry and replication in airway mucosal tissue and susceptibility in smokers

Author

Nakayama, Tsuguhisa, Lee, Ivan T, Jiang, Sizun, Matter, Matthias S, Yan, Carol H, Overdevest, Jonathan B, Wu, Chien-Ting, Goltsev, Yury, Shih, Liang-Chun, Liao, Chun-Kang, Zhu, Bokai, Bai, Yunhao, Lidsky, Peter, Xiao, Yinghong, Zarabanda, David, Yang, Angela, Easwaran, Meena, Schürch, Christian M, Chu, Pauline, Chen, Han, Stalder, Anna K, McIlwain, David R, Borchard, Nicole A, Gall, Phillip A, Dholakia, Sachi S, Le, Wei, Xu, Le, Tai, Chih-Jaan, Yeh, Te-Huei, Erickson-Direnzo, Elizabeth, Duran, Jason M, Mertz, Kirsten D, Hwang, Peter H, Haslbauer, Jasmin D, Jackson, Peter K, Menter, Thomas, Andino, Raul, Canoll, Peter D, DeConde, Adam S, Patel, Zara M, Tzankov, Alexandar, Nolan, Garry P, and Nayak, Jayakar V

Subjects
Dental/Oral and Craniofacial Disease, Tobacco, Prevention, Biodefense, Pneumonia & Influenza, Emerging Infectious Diseases, Infectious Diseases, Pneumonia, Tobacco Smoke and Health, Clinical Research, Vaccine Related, Lung, 2.1 Biological and endogenous factors, Aetiology, 2.2 Factors relating to the physical environment, Infection, Respiratory, Good Health and Well Being, Aged, Aged, 80 and over, Angiotensin-Converting Enzyme 2, COVID-19, Female, Gene Expression Regulation, Humans, Male, Middle Aged, Nasal Cavity, Respiratory Mucosa, SARS-CoV-2, Serine Endopeptidases, Smokers, Trachea, Viral Tropism, ACE2, IFN-β1, TMPRSS2, ciliated epithelial cell, nasal cavity, smoking, trachea, upper airway
Abstract

Understanding viral tropism is an essential step toward reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, decreasing mortality from coronavirus disease 2019 (COVID-19) and limiting opportunities for mutant strains to arise. Currently, little is known about the extent to which distinct tissue sites in the human head and neck region and proximal respiratory tract selectively permit SARS-CoV-2 infection and replication. In this translational study, we discover key variabilities in expression of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), essential SARS-CoV-2 entry factors, among the mucosal tissues of the human proximal airways. We show that SARS-CoV-2 infection is present in all examined head and neck tissues, with a notable tropism for the nasal cavity and tracheal mucosa. Finally, we uncover an association between smoking and higher SARS-CoV-2 viral infection in the human proximal airway, which may explain the increased susceptibility of smokers to developing severe COVID-19. This is at least partially explained by differences in interferon (IFN)-β1 levels between smokers and non-smokers.

Published
2021

8. SARS-CoV-2 infects human pancreatic β cells and elicits β cell impairment

Author

Wu, Chien-Ting, Lidsky, Peter V, Xiao, Yinghong, Lee, Ivan T, Cheng, Ran, Nakayama, Tsuguhisa, Jiang, Sizun, Demeter, Janos, Bevacqua, Romina J, Chang, Charles A, Whitener, Robert L, Stalder, Anna K, Zhu, Bokai, Chen, Han, Goltsev, Yury, Tzankov, Alexandar, Nayak, Jayakar V, Nolan, Garry P, Matter, Matthias S, Andino, Raul, and Jackson, Peter K

Subjects
Diabetes, Pneumonia & Influenza, Prevention, Lung, Autoimmune Disease, Pneumonia, Infectious Diseases, Emerging Infectious Diseases, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, A549 Cells, Adult, Aged, Aged, 80 and over, Angiotensin-Converting Enzyme 2, Antigens, CD, Apoptosis, Apoptosis Regulatory Proteins, COVID-19, Case-Control Studies, Diabetes Mellitus, Female, Host-Pathogen Interactions, Humans, Insulin, Insulin-Secreting Cells, Male, Middle Aged, Neuropilin-1, Receptors, Transferrin, Receptors, Virus, SARS-CoV-2, Serine Endopeptidases, Spike Glycoprotein, Coronavirus, Virus Internalization, ACE2, SARS-CoV-2 spike protein, apoptosis, insulin, neuropilin 1, pancreatic beta cell, phosphoproteomics, type 1 diabetes, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Endocrinology & Metabolism
Abstract

Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic β cells can be infected by SARS-CoV-2 and cause β cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in β cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic β cells in patients who succumbed to COVID-19 and selectively infects human islet β cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic β cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce β cell killing.

Published
2021

12. SARS-CoV-2 activates the TLR4/MyD88 pathway in human macrophages: A possible correlation with strong pro-inflammatory responses in severe COVID-19

Author

Sahanic, Sabina, Hilbe, Richard, Dünser, Christina, Tymoszuk, Piotr, Löffler-Ragg, Judith, Rieder, Dietmar, Trajanoski, Zlatko, Krogsdam, Anne, Demetz, Egon, Yurchenko, Maria, Fischer, Christine, Schirmer, Michael, Theurl, Markus, Lener, Daniela, Hirsch, Jakob, Holfeld, Johannes, Gollmann-Tepeköylü, Can, Zinner, Carl P., Tzankov, Alexandar, Zhang, Shen-Ying, Casanova, Jean-Laurent, Posch, Wilfried, Wilflingseder, Doris, Weiss, Guenter, and Tancevski, Ivan

Published
2023
Full Text
View/download PDF

14. Morphologic and molecular analysis of liver injury after SARS-CoV-2 vaccination reveals distinct characteristics

Author

Uzun, Sarp, Zinner, Carl P., Beenen, Amke C., Alborelli, Ilaria, Bartoszek, Ewelina M., Yeung, Jason, Calgua, Byron, Reinscheid, Matthias, Bronsert, Peter, Stalder, Anna K., Haslbauer, Jasmin D., Vosbeck, Juerg, Mazzucchelli, Luca, Hoffmann, Tobias, Terracciano, Luigi M., Hutter, Gregor, Manz, Michael, Panne, Isabelle, Boettler, Tobias, Hofmann, Maike, Bengsch, Bertram, Heim, Markus H., Bernsmeier, Christine, Jiang, Sizun, Tzankov, Alexandar, Terziroli Beretta-Piccoli, Benedetta, and Matter, Matthias S.

Published
2023
Full Text
View/download PDF

15. ACE2 localizes to the respiratory cilia and is not increased by ACE inhibitors or ARBs.

Author

Lee, Ivan T, Nakayama, Tsuguhisa, Wu, Chien-Ting, Goltsev, Yury, Jiang, Sizun, Gall, Phillip A, Liao, Chun-Kang, Shih, Liang-Chun, Schürch, Christian M, McIlwain, David R, Chu, Pauline, Borchard, Nicole A, Zarabanda, David, Dholakia, Sachi S, Yang, Angela, Kim, Dayoung, Chen, Han, Kanie, Tomoharu, Lin, Chia-Der, Tsai, Ming-Hsui, Phillips, Katie M, Kim, Raymond, Overdevest, Jonathan B, Tyler, Matthew A, Yan, Carol H, Lin, Chih-Feng, Lin, Yi-Tsen, Bau, Da-Tian, Tsay, Gregory J, Patel, Zara M, Tsou, Yung-An, Tzankov, Alexandar, Matter, Matthias S, Tai, Chih-Jaan, Yeh, Te-Huei, Hwang, Peter H, Nolan, Garry P, Nayak, Jayakar V, and Jackson, Peter K

Subjects
Goblet Cells, Respiratory System, Lung, Cilia, Endothelial Cells, Humans, Pneumonia, Viral, Coronavirus Infections, Sinusitis, Peptidyl-Dipeptidase A, Angiotensin-Converting Enzyme Inhibitors, Smoking, Age Factors, Sex Factors, Gene Expression, Angiotensin Receptor Antagonists, Pandemics, COVID-19, Angiotensin-Converting Enzyme 2, Pneumonia, Viral
Abstract

The coronavirus SARS-CoV-2 is the causative agent of the ongoing severe acute respiratory disease pandemic COVID-19. Tissue and cellular tropism is one key to understanding the pathogenesis of SARS-CoV-2. We investigate the expression and subcellular localization of the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), within the upper (nasal) and lower (pulmonary) respiratory tracts of human donors using a diverse panel of banked tissues. Here, we report our discovery that the ACE2 receptor protein robustly localizes within the motile cilia of airway epithelial cells, which likely represents the initial or early subcellular site of SARS-CoV-2 viral entry during host respiratory transmission. We further determine whether ciliary ACE2 expression in the upper airway is influenced by patient demographics, clinical characteristics, comorbidities, or medication use, and show the first mechanistic evidence that the use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARBs) does not increase susceptibility to SARS-CoV-2 infection through enhancing the expression of ciliary ACE2 receptor. These findings are crucial to our understanding of the transmission of SARS-CoV-2 for prevention and control of this virulent pathogen.

Published
2020

17. The NFIA-ETO2 fusion blocks erythroid maturation and induces pure erythroid leukemia in cooperation with mutant TP53

Author

Piqué-Borràs, Maria-Riera, Jevtic, Zivojin, Bagger, Frederik Otzen, Seguin, Jonathan, Sivalingam, Rathick, Bezerra, Matheus Filgueira, Louwagie, Amber, Juge, Sabine, Nellas, Ioannis, Ivanek, Robert, Tzankov, Alexandar, Moll, Ute M., Cantillo, Oriano, Schulz-Heddergott, Ramona, Fagnan, Alexandre, Mercher, Thomas, and Schwaller, Juerg

Published
2023
Full Text
View/download PDF

19. A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL

Author

Xu-Monette, Zijun Y, Zhang, Hongwei, Zhu, Feng, Tzankov, Alexandar, Bhagat, Govind, Visco, Carlo, Dybkaer, Karen, Chiu, April, Tam, Wayne, Zu, Youli, Hsi, Eric D, You, Hua, Huh, Jooryung, Ponzoni, Maurilio, Ferreri, Andrés JM, Møller, Michael B, Parsons, Benjamin M, van Krieken, J Han, Piris, Miguel A, Winter, Jane N, Hagemeister, Fredrick B, Shahbaba, Babak, De Dios, Ivan, Zhang, Hong, Li, Yong, Xu, Bing, Albitar, Maher, and Young, Ken H

Subjects
Orphan Drug, Human Genome, Hematology, Cancer, Rare Diseases, Lymphoma, Biotechnology, Genetics, Generic health relevance, Good Health and Well Being, Artificial Intelligence, B-Lymphocytes, Germinal Center, High-Throughput Nucleotide Sequencing, Humans, Lymphoma, Large B-Cell, Diffuse
Abstract

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routine practice by the World Health Organization classification for biological and therapeutic insights. Genetic subtypes uncovered recently are based on distinct genetic alterations in DLBCL, which are different from the COO subtypes defined by gene expression signatures of normal B cells retained in DLBCL. We hypothesize that classifiers incorporating both genome-wide gene-expression and pathogenetic variables can improve the therapeutic significance of DLBCL classification. To develop such refined classifiers, we performed targeted RNA sequencing (RNA-Seq) with a commercially available next-generation sequencing (NGS) platform in a large cohort of 418 DLBCLs. Genetic and transcriptional data obtained by RNA-Seq in a single run were explored by state-of-the-art artificial intelligence (AI) to develop a NGS-COO classifier for COO assignment and NGS survival models for clinical outcome prediction. The NGS-COO model built through applying AI in the training set was robust, showing high concordance with COO classification by either Affymetrix GeneChip microarray or the NanoString Lymph2Cx assay in 2 validation sets. Although the NGS-COO model was not trained for clinical outcome, the activated B-cell-like compared with the germinal-center B-cell-like subtype had significantly poorer survival. The NGS survival models stratified 30% high-risk patients in the validation set with poor survival as in the training set. These results demonstrate that targeted RNA-Seq coupled with AI deep learning techniques provides reproducible, efficient, and affordable assays for clinical application. The clinical grade assays and NGS models integrating both genetic and transcriptional factors developed in this study may eventually support precision medicine in DLBCL.

Published
2020

25. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data

Author

Arber, Daniel A., Orazi, Attilio, Hasserjian, Robert P., Borowitz, Michael J., Calvo, Katherine R., Kvasnicka, Hans-Michael, Wang, Sa A., Bagg, Adam, Barbui, Tiziano, Branford, Susan, Bueso-Ramos, Carlos E., Cortes, Jorge E., Dal Cin, Paola, DiNardo, Courtney D., Dombret, Hervé, Duncavage, Eric J., Ebert, Benjamin L., Estey, Elihu H., Facchetti, Fabio, Foucar, Kathryn, Gangat, Naseema, Gianelli, Umberto, Godley, Lucy A., Gökbuget, Nicola, Gotlib, Jason, Hellström-Lindberg, Eva, Hobbs, Gabriela S., Hoffman, Ronald, Jabbour, Elias J., Kiladjian, Jean-Jacques, Larson, Richard A., Le Beau, Michelle M., Loh, Mignon L.-C., Löwenberg, Bob, Macintyre, Elizabeth, Malcovati, Luca, Mullighan, Charles G., Niemeyer, Charlotte, Odenike, Olatoyosi M., Ogawa, Seishi, Orfao, Alberto, Papaemmanuil, Elli, Passamonti, Francesco, Porkka, Kimmo, Pui, Ching-Hon, Radich, Jerald P., Reiter, Andreas, Rozman, Maria, Rudelius, Martina, Savona, Michael R., Schiffer, Charles A., Schmitt-Graeff, Annette, Shimamura, Akiko, Sierra, Jorge, Stock, Wendy A., Stone, Richard M., Tallman, Martin S., Thiele, Jürgen, Tien, Hwei-Fang, Tzankov, Alexandar, Vannucchi, Alessandro M., Vyas, Paresh, Wei, Andrew H., Weinberg, Olga K., Wierzbowska, Agnieszka, Cazzola, Mario, Döhner, Hartmut, and Tefferi, Ayalew

Published
2022
Full Text
View/download PDF

27. Clinical relevance of molecular characteristics in Burkitt lymphoma differs according to age

Author

Burkhardt, Birgit, Michgehl, Ulf, Rohde, Jonas, Erdmann, Tabea, Berning, Philipp, Reutter, Katrin, Rohde, Marius, Borkhardt, Arndt, Burmeister, Thomas, Dave, Sandeep, Tzankov, Alexandar, Dugas, Martin, Sandmann, Sarah, Fend, Falko, Finger, Jasmin, Mueller, Stephanie, Gökbuget, Nicola, Haferlach, Torsten, Kern, Wolfgang, Hartmann, Wolfgang, Klapper, Wolfram, Oschlies, Ilske, Richter, Julia, Kontny, Udo, Lutz, Mathias, Maecker-Kolhoff, Britta, Ott, German, Rosenwald, Andreas, Siebert, Reiner, von Stackelberg, Arend, Strahm, Brigitte, Woessmann, Wilhelm, Zimmermann, Martin, Zapukhlyak, Myroslav, Grau, Michael, and Lenz, Georg

Published
2022
Full Text
View/download PDF

29. Genomic analysis of focal nodular hyperplasia with associated hepatocellular carcinoma unveils its malignant potential: a case report

Author

Ercan, Caner, Coto-Llerena, Mairene, Gallon, John, Fourie, Lana, Marinucci, Mattia, Hess, Gabriel F., Vosbeck, Jürg, Taha-Mehlitz, Stephanie, Boldanova, Tuyana, Meier, Marie-Anne, Tzankov, Alexandar, Matter, Matthias S., Hoffmann, Martin H. K., Di Tommaso, Luca, von Flüe, Markus, Ng, Charlotte K. Y., Heim, Markus H., Soysal, Savas D., Terracciano, Luigi M., Kollmar, Otto, and Piscuoglio, Salvatore

Published
2022
Full Text
View/download PDF

30. Severe Neuro-COVID is associated with peripheral immune signatures, autoimmunity and neurodegeneration: a prospective cross-sectional study

Author

Etter, Manina M., Martins, Tomás A., Kulsvehagen, Laila, Pössnecker, Elisabeth, Duchemin, Wandrille, Hogan, Sabrina, Sanabria-Diaz, Gretel, Müller, Jannis, Chiappini, Alessio, Rychen, Jonathan, Eberhard, Noëmi, Guzman, Raphael, Mariani, Luigi, Melie-Garcia, Lester, Keller, Emanuela, Jelcic, Ilijas, Pargger, Hans, Siegemund, Martin, Kuhle, Jens, Oechtering, Johanna, Eich, Caroline, Tzankov, Alexandar, Matter, Matthias S., Uzun, Sarp, Yaldizli, Özgür, Lieb, Johanna M., Psychogios, Marios-Nikos, Leuzinger, Karoline, Hirsch, Hans H., Granziera, Cristina, Pröbstel, Anne-Katrin, and Hutter, Gregor

Published
2022
Full Text
View/download PDF

31. The diagnosis of Burkitt lymphoma: how do pathologists apply criteria in daily practice?

Author

Brand, Michiel van den, Tzankov, Alexandar, Scheijde-Vermeulen, Marijn, Barbé, Ellis, Dirnhofer, Stefan, Stenner, Frank, Hebeda, Konnie, Chamuleau, Martine, and Jong, Daphne de

Subjects
*NON-Hodgkin's lymphoma, *BURKITT'S lymphoma, *CORE needle biopsy, *MEDICAL genetics, *GENE expression profiling
Abstract

This letter to the editor published in the journal Leukemia & Lymphoma discusses the challenges in diagnosing Burkitt lymphoma (BL) and the results of a study on the diagnostic concordance for BL among experienced hematopathologists. The study found that initial consensus for BL diagnosis was low, but improved with additional information from immunohistochemistry and clinical data. The letter emphasizes the need for additional techniques to improve the reliability of distinguishing BL from other lymphomas and highlights the importance of multidisciplinary meetings for accurate diagnosis and treatment decisions. References to previous studies and classifications of lymphomas are provided for further research. [Extracted from the article]

Published
2024
Full Text
View/download PDF

32. Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning.

Author

Schmidt-Barbo, Paul, Kalweit, Gabriel, Naouar, Mehdi, Paschold, Lisa, Willscher, Edith, Schultheiß, Christoph, Märkl, Bruno, Dirnhofer, Stefan, Tzankov, Alexandar, Binder, Mascha, and Kalweit, Maria

Subjects
B cells, MACHINE learning, B cell receptors, B cell lymphoma, LYMPHOMAS, CHRONIC lymphocytic leukemia, DIFFUSE large B-cell lymphomas
Abstract

The classification of B cell lymphomas—mainly based on light microscopy evaluation by a pathologist—requires many years of training. Since the B cell receptor (BCR) of the lymphoma clonotype and the microenvironmental immune architecture are important features discriminating different lymphoma subsets, we asked whether BCR repertoire next-generation sequencing (NGS) of lymphoma-infiltrated tissues in conjunction with machine learning algorithms could have diagnostic utility in the subclassification of these cancers. We trained a random forest and a linear classifier via logistic regression based on patterns of clonal distribution, VDJ gene usage and physico-chemical properties of the top-n most frequently represented clonotypes in the BCR repertoires of 620 paradigmatic lymphoma samples—nodular lymphocyte predominant B cell lymphoma (NLPBL), diffuse large B cell lymphoma (DLBCL) and chronic lymphocytic leukemia (CLL)—alongside with 291 control samples. With regard to DLBCL and CLL, the models demonstrated optimal performance when utilizing only the most prevalent clonotype for classification, while in NLPBL—that has a dominant background of non-malignant bystander cells—a broader array of clonotypes enhanced model accuracy. Surprisingly, the straightforward logistic regression model performed best in this seemingly complex classification problem, suggesting linear separability in our chosen dimensions. It achieved a weighted F1-score of 0.84 on a test cohort including 125 samples from all three lymphoma entities and 58 samples from healthy individuals. Together, we provide proof-of-concept that at least the 3 studied lymphoma entities can be differentiated from each other using BCR repertoire NGS on lymphoma-infiltrated tissues by a trained machine learning model. Author summary: Lymphoma, a complex group of malignant blood cancers, poses a significant diagnostic challenge due to its diverse subtypes. Yet, precise classification is crucial for tailored treatment. In our research, we developed a machine learning algorithm and conducted comprehensive validation to discern distinct B cell lymphoma subtypes. We therefore leveraged B cell repertoires of lymphoma-infiltrated tissue, as ascertained through next-generation sequencing. Our data offers three key insights: We detail the creation and training of our machine learning algorithm, explaining how we selected features and designed the model. We demonstrate the algorithm's diagnostic precision using sequencing data from a test-set of patient samples. Moreover, through a deep dive into the most distinguishing aspects of our algorithm, we unveil distinctive disease-related patterns present within the malignant B cell and its surrounding environment. This analysis showed that both the malignant lymphoma cell, but also healthy bystander immune cells contribute to the distinctive architecture that characterizes a specific lymphoma subtype. We hope our work will contribute towards creating tools to diagnose lymphoma more easily and accurately ultimately leading to better outcomes for patients with this type of cancer. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

37. Aplastic Anemia

Author

Menter, Thomas, Tzankov, Alexandar, van Krieken, J. H. J. M., Series Editor, and Molina, Thierry J., editor

Published
2020
Full Text
View/download PDF

41. Bone Marrow Mesenchymal Stem Cells Support Acute Myeloid Leukemia Bioenergetics and Enhance Antioxidant Defense and Escape from Chemotherapy

Author

Forte, Dorian, García-Fernández, María, Sánchez-Aguilera, Abel, Stavropoulou, Vaia, Fielding, Claire, Martín-Pérez, Daniel, López, Juan Antonio, Costa, Ana S.H., Tronci, Laura, Nikitopoulou, Efterpi, Barber, Michael, Gallipoli, Paolo, Marando, Ludovica, Fernández de Castillejo, Carlos López, Tzankov, Alexandar, Dietmann, Sabine, Cavo, Michele, Catani, Lucia, Curti, Antonio, Vázquez, Jesús, Frezza, Christian, Huntly, Brian J., Schwaller, Juerg, and Méndez-Ferrer, Simón

Published
2020
Full Text
View/download PDF

42. Praktische Aspekte von COVID-19-Obduktionen

Author

Boor, Peter, Eichhorn, Philip, Hartmann, Arndt, Lax, Sigurd F., Märkl, Bruno, Menter, Thomas, Skok, Kristijan, Slotta-Huspenina, Julia, von Stillfried, Saskia, Tzankov, Alexandar, and Weirich, Gregor

Published
2021
Full Text
View/download PDF

46. Determining clinical course of diffuse large B-cell lymphoma using targeted transcriptome and machine learning algorithms

Author

Albitar, Maher, Zhang, Hong, Goy, Andre, Xu-Monette, Zijun Y., Bhagat, Govind, Visco, Carlo, Tzankov, Alexandar, Fang, Xiaosheng, Zhu, Feng, Dybkaer, Karen, Chiu, April, Tam, Wayne, Zu, Youli, Hsi, Eric D., Hagemeister, Fredrick B., Huh, Jooryung, Ponzoni, Maurilio, Ferreri, Andrés J. M., Møller, Michael B., Parsons, Benjamin M., van Krieken, J. Han, Piris, Miguel A., Winter, Jane N., Li, Yong, Xu, Bing, and Young, Ken H.

Published
2022
Full Text
View/download PDF

48. Primary bone diffuse large B‐cell lymphoma (PB‐DLBCL): a distinct extranodal lymphoma of germinal centre origin, with a common EZB‐like mutational profile and good prognosis

Author

Ivanova, Vanesa‐Sindi, primary, Davies, John, additional, Menter, Thomas, additional, Wild, Damian, additional, Müller, Anne, additional, Krasniqi, Fatime, additional, Stenner, Frank, additional, Papachristofilou, Alexandros, additional, Dirnhofer, Stefan, additional, and Tzankov, Alexandar, additional

Published
2023
Full Text
View/download PDF

50. The Impact of Genetic Subtypes of Diffuse Large B-Cell Lymphoma for Outcome Prediction and Interpretation of FDG-PET treatment Response Monitoring

Author

Ylstra, Bauke, primary, Mendeville, Matias, additional, Janssen, Jurriaan, additional, Vries, G. Tjitske Los-de, additional, Dijk, Erik van, additional, Richter, Julia, additional, Nijland, Marcel, additional, Roemer, Margaretha, additional, Stathi, Phylicia, additional, Hijmering, Nathalie, additional, Bladergroen, Reno, additional, Pelaz, Diego, additional, Diepstra, Arjan, additional, Eertink, Corinne, additional, Burggraaff, Coreline, additional, Kim, Yongsoo, additional, Lugtenburg, Pieternella, additional, Berg, Anke van den, additional, Tzankov, Alexandar, additional, Dirnhofer, Stephan, additional, Duhrsen, Ulrich, additional, Hüttmann, Andreas, additional, Klapper, Wolfram, additional, Zijlstra-Baalbergen, Josée, additional, and de Jong, Daphne, additional

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results