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Rösler W, Altenbuchinger M, Baeßler B, Beissbarth T, Beutel G, Bock R, von Bubnoff N, Eckardt JN, Foersch S, Loeffler CML, Middeke JM, Mueller ML, Oellerich T, Risse B, Scherag A, Schliemann C, Scholz M, Spang R, Thielscher C, Tsoukakis I, Kather JN. An overview and a roadmap for artificial intelligence in hematology and oncology. J Cancer Res Clin Oncol 2023; 149:7997-8006. [PMID: 36920563 PMCID: PMC10374829 DOI: 10.1007/s00432-023-04667-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 02/23/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it often remains unclear what AI can and cannot do, and what are promising areas for a sensible application of AI in hematology and oncology. Finally, the limits and perils of using AI in oncology are not obvious to many healthcare professionals. METHODS In this article, we provide an expert-based consensus statement by the joint Working Group on "Artificial Intelligence in Hematology and Oncology" by the German Society of Hematology and Oncology (DGHO), the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), and the Special Interest Group Digital Health of the German Informatics Society (GI). We provide a conceptual framework for AI in hematology and oncology. RESULTS First, we propose a technological definition, which we deliberately set in a narrow frame to mainly include the technical developments of the last ten years. Second, we present a taxonomy of clinically relevant AI systems, structured according to the type of clinical data they are used to analyze. Third, we show an overview of potential applications, including clinical, research, and educational environments with a focus on hematology and oncology. CONCLUSION Thus, this article provides a point of reference for hematologists and oncologists, and at the same time sets forth a framework for the further development and clinical deployment of AI in hematology and oncology in the future.
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Affiliation(s)
- Wiebke Rösler
- Department for Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Altenbuchinger
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Bettina Baeßler
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Tim Beissbarth
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Gernot Beutel
- Department for Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Robert Bock
- IMMS Institute for Microelectronics and Mechatronics Systems GmbH (NPO), Ilmenau, Germany
| | - Nikolas von Bubnoff
- Department of Hematology and Oncology, Medical Center, University of Schleswig Holstein, Campus Lübeck, Lübeck, Germany
| | - Jan-Niklas Eckardt
- Department of Medicine 1, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
- Else Kroener Fresenius Center for Digital Health (EFFZ), Technical University Dresden, Dresden, Germany
| | - Sebastian Foersch
- Institute of Pathology, University Medical Center Mainz, Mainz, Germany
| | - Chiara M L Loeffler
- Department of Medicine 1, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
- Else Kroener Fresenius Center for Digital Health (EFFZ), Technical University Dresden, Dresden, Germany
| | - Jan Moritz Middeke
- Department of Medicine 1, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
- Else Kroener Fresenius Center for Digital Health (EFFZ), Technical University Dresden, Dresden, Germany
| | | | - Thomas Oellerich
- Medizinische Klinik 2-Haematology/Oncology, University Hospital, Frankfurt am Main, Germany
| | - Benjamin Risse
- Computer Vision and Machine Learning Systems Group, Institute for Geoinformatics, University of Münster, Münster, Germany
| | - André Scherag
- Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | | | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Rainer Spang
- Department of Statistical Bioinformatics, University of Regensburg, Regensburg, Germany
| | | | - Ioannis Tsoukakis
- Department of Hematology and Oncology, Sana Klinikum Offenbach, Offenbach, Germany
| | - Jakob Nikolas Kather
- Department of Medicine 1, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany.
- Else Kroener Fresenius Center for Digital Health (EFFZ), Technical University Dresden, Dresden, Germany.
- Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany.
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Zaccaria GM, Vegliante MC, Mezzolla G, Stranieri M, Volpe G, Altini N, Gargano G, Pappagallo SA, Bucci A, Esposito F, Opinto G, Clemente F, Negri A, Mondelli P, De Candia MS, Bevilacqua V, Guarini A, Ciavarella S. A Decision-tree Approach to Stratify DLBCL Risk Based on Stromal and Immune Microenvironment Determinants. Hemasphere 2023; 7:e862. [PMID: 37038464 PMCID: PMC10082248 DOI: 10.1097/hs9.0000000000000862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 02/06/2023] [Indexed: 04/12/2023] Open
Affiliation(s)
- Gian Maria Zaccaria
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
- Transfer Technology Office, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | | | - Giuseppe Mezzolla
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy
| | - Marianna Stranieri
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy
| | - Giacomo Volpe
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Nicola Altini
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy
| | - Grazia Gargano
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
- INDAM-GNCS Research Group, Rome, Italy
- Department of Mathematics, University of Bari Aldo Moro, Italy
| | | | - Antonella Bucci
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Flavia Esposito
- INDAM-GNCS Research Group, Rome, Italy
- Department of Mathematics, University of Bari Aldo Moro, Italy
| | - Giuseppina Opinto
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Felice Clemente
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Antonio Negri
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Paolo Mondelli
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Maria Stella De Candia
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Vitoantonio Bevilacqua
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy
| | - Attilio Guarini
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
| | - Sabino Ciavarella
- Hematology and Cell Therapy Unit, IRCCS Istituto Tumori "Giovanni Paolo II," Bari, Italy
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Lin M, Ma S, Sun L, Qin Z. The prognostic value of tumor-associated macrophages detected by immunostaining in diffuse large B cell lymphoma: A meta-analysis. Front Oncol 2023; 12:1094400. [PMID: 36741724 PMCID: PMC9895774 DOI: 10.3389/fonc.2022.1094400] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 12/29/2022] [Indexed: 01/22/2023] Open
Abstract
Background The prognostic implication of tumor-associated macrophages (TAMs) in the microenvironment of diffuse large B cell lymphoma (DLBCL) remains controversial. Methods A systematic and comprehensive search of relevant studies was performed in PubMed, Embase and Web of Science databases. The quality of the included studies was estimated using Newcastle-Ottawa Scale (NOS). Results Twenty-three studies containing a total of 2992 DLBCL patients were involved in this study. They were all high-quality studies scoring ≥ 6 points. High density of M2 TAMs in tumor microenvironment significantly associated with both advanced disease stage (OR= 1.937, 95% CI: 1.256-2.988, P = 0.003) and unfavorable overall survival (OS) (HR = 1.750, 95% CI: 1.188-2.579, P = 0.005) but not associated with poor progression free survival (PFS) (HR = 1.672, 95% CI: 0.864-3.237, P = 0.127) and international prognostic index (IPI) (OR= 1.705, 95% CI: 0.843-3.449, P = 0.138) in DLBCL patients. No significant correlation was observed between the density of CD68+ TAMs and disease stage (OR= 1.433, 95% CI: 0.656-3.130, P = 0.366), IPI (OR= 1.391, 95% CI: 0.573-3.379, P = 0.466), OS (HR=0.929, 95% CI: 0.607-1.422, P = 0.734) or PFS (HR= 0.756, 95% CI: 0.415-1.379, P = 0.362) in DLBCL patients. Conclusion This meta-analysis demonstrated that high density of M2 TAMs in the tumor microenvironment was a robust predictor of adverse outcome for DLBCL patients. Systematic review registration https://www.crd.york.ac.uk/PROSPERO, identifier CRD42022343045.
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Affiliation(s)
- Mei Lin
- Department of Pathology, School of Basic Medicine, Qingdao University, Qingdao, Shandong, China
| | - Shupei Ma
- Department of Hematology, Qingdao Municipal Hospital, Qingdao, Shandong, China
| | - Lingling Sun
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Zhiqiang Qin
- Department of Pathology, People Hospital of Changzhi, Changzhi, Shanxi, China
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Chen H, Qin Y, Liu P, Yang J, Gui L, He X, Zhang C, Zhou S, Zhou L, Yang S, Shi Y. Genetic Profiling of Diffuse Large B-Cell Lymphoma: A Comparison Between Double-Expressor Lymphoma and Non-Double-Expressor Lymphoma. Mol Diagn Ther 2023; 27:75-86. [PMID: 36401148 DOI: 10.1007/s40291-022-00621-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2022] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Data are limited regarding the genetic profiling of diffuse large B-cell lymphoma (DLBCL) with double expression of MYC and BCL2 proteins without underlying rearrangements (double-expressor lymphoma [DEL]). This study aimed to describe the genetic profiling and determine the prognostic significance in patients with DEL and in those with non-DEL. METHODS Capture-based targeted sequencing was performed on 244 patients with de novo DLBCL, not otherwise specified. Immunohistochemistry staining was performed for evaluating the MYC and BCL2 expression. RESULTS Among 244 patients, 46 patients had DEL, and 198 had non-DEL. KMT2D, CD58, EP300, PRDM1, TNFAIP3 and BCL2 gain or amplification (BCL2GA/AMP) were significantly more frequently altered in the DEL group. Alterations in the BCR/TLR (p = 0.021), B-cell development and differentiation (p = 0.004), and NF-κB (p = 0.034) pathways occurred more frequently in patients with DEL. Thirty-seven DEL patients and 132 non-DEL patients were included for survival analyses. DEL was not significantly associated with progression-free survival (PFS) (p = 0.60) and overall survival (OS) (p = 0.49). In DEL patients, after adjusting for the International Prognostic Index, BCL2 alteration (HR 2.516, 95% CI 1.027-6.161; p = 0.044) remained an independent predictor of inferior PFS. BCL2GA/AMP also predicted poor PFS, but with marginal statistical significance (HR 2.489, 95% CI 0.995-6.224; p = 0.051). CONCLUSION There was difference in profiling of altered genes and signaling pathways between the DEL group and the non-DEL group. The presence of DEL alone should not be considered as an adverse prognostic indicator, and BCL2 alteration could define a subset of patients with poor prognosis within DEL.
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Affiliation(s)
- Haizhu Chen
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Yan Qin
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Peng Liu
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Jianliang Yang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Lin Gui
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Xiaohui He
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Changgong Zhang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Shengyu Zhou
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Liqiang Zhou
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Sheng Yang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
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Miyawaki K, Sugio T. Lymphoma Microenvironment in DLBCL and PTCL-NOS: the key to uncovering heterogeneity and the potential for stratification. J Clin Exp Hematop 2022; 62:127-135. [PMID: 36171096 DOI: 10.3960/jslrt.22027] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) and peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) are the most common subtypes of mature B cell neoplasm and T/NK cell lymphoma, respectively. They share a commonality in that they are, by definition, highly heterogeneous populations. Recent studies are revealing more about the heterogeneity of these diseases, and at the same time, there is an active debate on how to stratify these heterogeneous diseases and make them useful in clinical practice. The various immune cells and non-cellular components surrounding lymphoma cells, i.e., the lymphoma microenvironment, have been the subject of intense research since the late 2000s, and much knowledge has been accumulated over the past decade. As a result, it has become clear that the lymphoma microenvironment, despite its paucity in tissues, significantly impacts the lymphoma pathogenesis and clinical behavior, such as its prognosis and response to therapy. In this article, we review the role of the lymphoma microenvironment in DLBCL and PTCL-NOS, with particular attention given to its impact on the prognosis and stratification.
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Affiliation(s)
- Kohta Miyawaki
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Takeshi Sugio
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
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de Groot FA, de Groen RAL, van den Berg A, Jansen PM, Lam KH, Mutsaers PGNJ, van Noesel CJM, Chamuleau MED, Stevens WBC, Plaça JR, Mous R, Kersten MJ, van der Poel MMW, Tousseyn T, Woei-a-Jin FJSH, Diepstra A, Nijland M, Vermaat JSP. Biological and Clinical Implications of Gene-Expression Profiling in Diffuse Large B-Cell Lymphoma: A Proposal for a Targeted BLYM-777 Consortium Panel as Part of a Multilayered Analytical Approach. Cancers (Basel) 2022; 14:cancers14081857. [PMID: 35454765 PMCID: PMC9028345 DOI: 10.3390/cancers14081857] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/25/2022] [Accepted: 03/29/2022] [Indexed: 02/04/2023] Open
Abstract
Gene-expression profiling (GEP) is used to study the molecular biology of lymphomas. Here, advancing insights from GEP studies in diffuse large B-cell lymphoma (DLBCL) lymphomagenesis are discussed. GEP studies elucidated subtypes based on cell-of-origin principles and profoundly changed the biological understanding of DLBCL with clinical relevance. Studies integrating GEP and next-generation DNA sequencing defined different molecular subtypes of DLBCL entities originating at specific anatomical localizations. With the emergence of high-throughput technologies, the tumor microenvironment (TME) has been recognized as a critical component in DLBCL pathogenesis. TME studies have characterized so-called "lymphoma microenvironments" and "ecotypes". Despite gained insights, unexplained chemo-refractoriness in DLBCL remains. To further elucidate the complex biology of DLBCL, we propose a novel targeted GEP consortium panel, called BLYM-777. This knowledge-based biology-driven panel includes probes for 777 genes, covering many aspects regarding B-cell lymphomagenesis (f.e., MYC signature, TME, immune surveillance and resistance to CAR T-cell therapy). Regarding lymphomagenesis, upcoming DLBCL studies need to incorporate genomic and transcriptomic approaches with proteomic methods and correlate these multi-omics data with patient characteristics of well-defined and homogeneous cohorts. This multilayered methodology potentially enhances diagnostic classification of DLBCL subtypes, prognostication, and the development of novel targeted therapeutic strategies.
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Affiliation(s)
- Fleur A. de Groot
- Department of Hematology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (F.A.d.G.); (R.A.L.d.G.)
| | - Ruben A. L. de Groen
- Department of Hematology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (F.A.d.G.); (R.A.L.d.G.)
| | - Anke van den Berg
- Department of Pathology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (A.v.d.B.); (J.R.P.); (A.D.)
| | - Patty M. Jansen
- Department of Pathology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands;
| | - King H. Lam
- Department of Pathology, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands;
| | - Pim G. N. J. Mutsaers
- Department of Hematology, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands;
| | - Carel J. M. van Noesel
- Department of Pathology, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands;
| | - Martine E. D. Chamuleau
- Cancer Center Amsterdam and LYMMCARE, Department of Hematology, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (M.E.D.C.); (M.J.K.)
| | - Wendy B. C. Stevens
- Department of Hematology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Jessica R. Plaça
- Department of Pathology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (A.v.d.B.); (J.R.P.); (A.D.)
| | - Rogier Mous
- Department of Hematology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands;
| | - Marie José Kersten
- Cancer Center Amsterdam and LYMMCARE, Department of Hematology, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (M.E.D.C.); (M.J.K.)
| | - Marjolein M. W. van der Poel
- Department of Internal Medicine, Division of Hematology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands;
| | - Thomas Tousseyn
- Department of Pathology, University Hospitals Leuven, 3000 Leuven, Belgium;
| | | | - Arjan Diepstra
- Department of Pathology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (A.v.d.B.); (J.R.P.); (A.D.)
| | - Marcel Nijland
- Department of Hematology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands;
| | - Joost S. P. Vermaat
- Department of Hematology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (F.A.d.G.); (R.A.L.d.G.)
- Correspondence:
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Plaça JR, Diepstra A, Los T, Mendeville M, Seitz A, Lugtenburg PJ, Zijlstra J, Lam K, da Silva WA, Ylstra B, de Jong D, van den Berg A, Nijland M. Reproducibility of Gene Expression Signatures in Diffuse Large B-Cell Lymphoma. Cancers (Basel) 2022; 14:cancers14051346. [PMID: 35267654 PMCID: PMC8909016 DOI: 10.3390/cancers14051346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/24/2022] [Accepted: 03/01/2022] [Indexed: 12/24/2022] Open
Abstract
Multiple gene expression profiles have been identified in diffuse large B-cell lymphoma (DLBCL). Besides the cell of origin (COO) classifier, no signatures have been reproduced in independent studies or evaluated for capturing distinct aspects of DLBCL biology. We reproduced 4 signatures in 175 samples of the HOVON-84 trial on a panel of 117 genes using the NanoString platform. The four gene signatures capture the COO, MYC activity, B-cell receptor signaling, oxidative phosphorylation, and immune response. Performance of our classification algorithms were confirmed in the original datasets. We were able to validate three of the four GEP signatures. The COO algorithm resulted in 94 (54%) germinal center B-cell (GCB) type, 58 (33%) activated B-cell (ABC) type, and 23 (13%) unclassified cases. The MYC-classifier revealed 77 cases with a high MYC-activity score (44%) and this MYC-high signature was observed more frequently in ABC as compared to GCB DLBCL (68% vs. 32%, p < 0.00001). The host response (HR) signature of the consensus clustering was present in 55 (31%) patients, while the B-cell receptor signaling, and oxidative phosphorylation clusters could not be reproduced. The overlap of COO, consensus cluster and MYC activity score differentiated six gene expression clusters: GCB/MYC-high (12%), GCB/HR (16%), GCB/non-HR (27%), COO-Unclassified (13%), ABC/MYC-high (25%), and ABC/MYC-low (7%). In conclusion, the three validated signatures identify distinct subgroups based on different aspects of DLBCL biology, emphasizing that each classifier captures distinct molecular profiles.
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Affiliation(s)
- Jessica Rodrigues Plaça
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9712 Groningen, The Netherlands; (J.R.P.); (A.D.); (A.S.); (A.v.d.B.)
- Center for Cell-Based Therapy, National Institute of Science and Technology in Stem Cell and Cell Therapy (INCT/CNPq), Ribeirão Preto 14051-060, Brazil;
| | - Arjan Diepstra
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9712 Groningen, The Netherlands; (J.R.P.); (A.D.); (A.S.); (A.v.d.B.)
| | - Tjitske Los
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, 1105 Amsterdam, The Netherlands; (T.L.); (M.M.); (B.Y.); (D.d.J.)
| | - Matías Mendeville
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, 1105 Amsterdam, The Netherlands; (T.L.); (M.M.); (B.Y.); (D.d.J.)
| | - Annika Seitz
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9712 Groningen, The Netherlands; (J.R.P.); (A.D.); (A.S.); (A.v.d.B.)
| | - Pieternella J. Lugtenburg
- Department of Hematology, Erasmus MC Cancer Institute, University Medical Center, 3015 Rotterdam, The Netherlands;
| | - Josée Zijlstra
- Department of Hematology, Amsterdam UMC, 1105 Amsterdam, The Netherlands;
| | - King Lam
- Department of Pathology, Erasmus MC, 3015 Rotterdam, The Netherlands;
| | - Wilson Araújo da Silva
- Center for Cell-Based Therapy, National Institute of Science and Technology in Stem Cell and Cell Therapy (INCT/CNPq), Ribeirão Preto 14051-060, Brazil;
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto 14049-900, Brazil
| | - Bauke Ylstra
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, 1105 Amsterdam, The Netherlands; (T.L.); (M.M.); (B.Y.); (D.d.J.)
| | - Daphne de Jong
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, 1105 Amsterdam, The Netherlands; (T.L.); (M.M.); (B.Y.); (D.d.J.)
| | - Anke van den Berg
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9712 Groningen, The Netherlands; (J.R.P.); (A.D.); (A.S.); (A.v.d.B.)
| | - Marcel Nijland
- Department of Hematology, University Medical Center Groningen, University of Groningen, 9712 Groningen, The Netherlands
- Correspondence: ; Tel.: +31-50-361-2354
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Xu-Monette ZY, Wei L, Fang X, Au Q, Nunns H, Nagy M, Tzankov A, Zhu F, Visco C, Bhagat G, Dybkaer K, Chiu A, Tam W, Zu Y, Hsi ED, Hagemeister FB, Sun X, Han X, Go H, Ponzoni M, Ferreri AJM, Møller MB, Parsons BM, van Krieken JH, Piris MA, Winter JN, Li Y, Xu B, Albitar M, You H, Young KH. Genetic Subtyping and Phenotypic Characterization of the Immune Microenvironment and MYC/BCL2 Double Expression Reveal Heterogeneity in Diffuse Large B-cell Lymphoma. Clin Cancer Res 2022; 28:972-983. [PMID: 34980601 DOI: 10.1158/1078-0432.ccr-21-2949] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 10/25/2021] [Accepted: 12/27/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. EXPERIMENTAL DESIGN We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. RESULTS We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. CONCLUSIONS Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.
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Affiliation(s)
- Zijun Y Xu-Monette
- Hematopathology Division and Department of Pathology, Duke University Medical Center, Durham, North Carolina.
| | - Li Wei
- Hematopathology Division and Department of Pathology, Duke University Medical Center, Durham, North Carolina.,Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaosheng Fang
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Qingyan Au
- NeoGenomics Laboratories, Aliso Viejo, California
| | - Harry Nunns
- NeoGenomics Laboratories, Aliso Viejo, California
| | - Máté Nagy
- NeoGenomics Laboratories, Aliso Viejo, California
| | - Alexandar Tzankov
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Feng Zhu
- Hematopathology Division and Department of Pathology, Duke University Medical Center, Durham, North Carolina
| | | | - Govind Bhagat
- Columbia University Irving Medical Center and New York Presbyterian Hospital, New York, New York
| | | | | | - Wayne Tam
- Weill Medical College of Cornell University, New York, New York
| | - Youli Zu
- The Methodist Hospital, Houston, Texas
| | | | - Fredrick B Hagemeister
- Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Xiaoping Sun
- Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Xin Han
- Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Heounjeong Go
- Asan Medical Center, Ulsan University College of Medicine, Seoul, Republic of South Korea
| | | | | | | | | | - J Han van Krieken
- Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Miguel A Piris
- Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Jane N Winter
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Yong Li
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Bing Xu
- The First Affiliated Hospital of Xiamen University, Xiamen, Fujian, China
| | - Maher Albitar
- Genomic Testing Cooperative, LCA, Irvine, California
| | - Hua You
- Children's Hospital of Chongqing Medical University, Chongqing, China.
| | - Ken H Young
- Hematopathology Division and Department of Pathology, Duke University Medical Center, Durham, North Carolina. .,Duke Cancer Institute, Durham, North Carolina
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9
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Yan J, Yuan W, Zhang J, Li L, Zhang L, Zhang X, Zhang M. Identification and Validation of a Prognostic Prediction Model in Diffuse Large B-Cell Lymphoma. Front Endocrinol (Lausanne) 2022; 13:846357. [PMID: 35498426 PMCID: PMC9048048 DOI: 10.3389/fendo.2022.846357] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous group with varied pathophysiological, genetic, and clinical features, accounting for approximately one-third of all lymphoma cases worldwide. Notwithstanding that unprecedented scientific progress has been achieved over the years, the survival of DLBCL patients remains low, emphasizing the need to develop novel prognostic biomarkers for early risk stratification and treatment optimization. METHOD In this study, we screened genes related to the overall survival (OS) of DLBCL patients in datasets GSE117556, GSE10846, and GSE31312 using univariate Cox analysis. Survival-related genes among the three datasets were screened according to the criteria: hazard ratio (HR) >1 or <1 and p-value <0.01. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis were used to optimize and establish the final gene risk prediction model. The TCGA-NCICCR datasets and our clinical cohort were used to validate the performance of the prediction model. CIBERSORT and ssGSEA algorithms were used to estimate immune scores in the high- and low-risk groups. RESULTS We constructed an eight-gene prognostic signature that could reliably predict the clinical outcome in training, testing, and validation cohorts. Our prognostic signature also performed distinguished areas under the ROC curve in each dataset, respectively. After stratification based on clinical characteristics such as cell-of-origin (COO), age, eastern cooperative oncology group (ECOG) performance status, international prognostic index (IPI), stage, and MYC/BCL2 expression, the difference in OS between the high- and low-risk groups was statistically significant. Next, univariate and multivariate analyses revealed that the risk score model had a significant prediction value. Finally, a nomogram was established to visualize the prediction model. Of note, we found that the low-risk group was enriched with immune cells. CONCLUSION In summary, we identified an eight-gene prognostic prediction model that can effectively predict survival outcomes of patients with DLBCL and built a nomogram to visualize the perdition model. We also explored immune alterations between high- and low-risk groups.
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Affiliation(s)
- Jiaqin Yan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei Yuan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, China
| | - Junhui Zhang
- Otorhinolaryngology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ling Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lei Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xudong Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingzhi Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Mingzhi Zhang,
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10
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Schrod S, Schäfer A, Solbrig S, Lohmayer R, Gronwald W, Oefner PJ, Beißbarth T, Spang R, Zacharias HU, Altenbuchinger M. OUP accepted manuscript. Bioinformatics 2022; 38:i60-i67. [PMID: 35758796 PMCID: PMC9235492 DOI: 10.1093/bioinformatics/btac221] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Estimating the effects of interventions on patient outcome is one of the key aspects of personalized medicine. Their inference is often challenged by the fact that the training data comprises only the outcome for the administered treatment, and not for alternative treatments (the so-called counterfactual outcomes). Several methods were suggested for this scenario based on observational data, i.e. data where the intervention was not applied randomly, for both continuous and binary outcome variables. However, patient outcome is often recorded in terms of time-to-event data, comprising right-censored event times if an event does not occur within the observation period. Albeit their enormous importance, time-to-event data are rarely used for treatment optimization. We suggest an approach named BITES (Balanced Individual Treatment Effect for Survival data), which combines a treatment-specific semi-parametric Cox loss with a treatment-balanced deep neural network; i.e. we regularize differences between treated and non-treated patients using Integral Probability Metrics (IPM). RESULTS We show in simulation studies that this approach outperforms the state of the art. Furthermore, we demonstrate in an application to a cohort of breast cancer patients that hormone treatment can be optimized based on six routine parameters. We successfully validated this finding in an independent cohort. AVAILABILITY AND IMPLEMENTATION We provide BITES as an easy-to-use python implementation including scheduled hyper-parameter optimization (https://github.com/sschrod/BITES). The data underlying this article are available in the CRAN repository at https://rdrr.io/cran/survival/man/gbsg.html and https://rdrr.io/cran/survival/man/rotterdam.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- S Schrod
- To whom correspondence should be addressed. E-mail: or
| | - A Schäfer
- Department of Physics, Institute of Theoretical Physics, University of Regensburg, Regensburg 93051, Germany
| | - S Solbrig
- Department of Physics, Institute of Theoretical Physics, University of Regensburg, Regensburg 93051, Germany
| | - R Lohmayer
- Leibniz Institute for Immunotherapy, Regensburg 93053, Germany
| | - W Gronwald
- Institute of Functional Genomics, University of Regensburg, Regensburg 93053, Germany
| | - P J Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg 93053, Germany
| | - T Beißbarth
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen 37077, Germany
| | - R Spang
- Department of Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Regensburg 93053, Germany
| | - H U Zacharias
- Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
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11
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Huang Q, Lin J, Huang S, Shen J. Impact of Qi-Invigorating Traditional Chinese Medicines on Diffuse Large B Cell Lymphoma Based on Network Pharmacology and Experimental Validation. Front Pharmacol 2021; 12:787816. [PMID: 34955857 PMCID: PMC8699731 DOI: 10.3389/fphar.2021.787816] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 11/15/2021] [Indexed: 12/31/2022] Open
Abstract
Background: It has been verified that deficiency of Qi, a fundamental substance supporting daily activities according to the Traditional Chinese Medicine theory, is an important symptom of cancer. Qi-invigorating herbs can inhibit cancer development through promoting apoptosis and improving cancer microenvironment. In this study, we explored the potential mechanisms of Qi-invigorating herbs in diffuse large B cell lymphoma (DLBCL) through network pharmacology and in vitro experiment. Methods: Active ingredients of Qi-invigorating herbs were predicted from the Traditional Chinese Medicine Systems Pharmacology Database. Potential targets were obtained via the SwissTargetPrediction and STITCH databases. Target genes of DLBCL were obtained through the PubMed, the gene-disease associations and the Malacards databases. Overlapping genes between DLBCL and each Qi-invigorating herb were collected. Hub genes were subsequently screened via Cytoscape. The Gene Ontology and pathway enrichment analyses were performed using the DAVID database. Molecular docking was performed among active ingredients and hub genes. Hub genes linked with survival and tumor microenvironment were analyzed through the GEPIA 2.0 and TIMER 2.0 databases, respectively. Additionally, in vitro experiment was performed to verify the roles of common hub genes. Results: Through data mining, 14, 4, 22, 22, 35, 2, 36 genes were filtered as targets of Ginseng Radix et Rhizoma, Panacis Quinquefolii Radix, Codonopsis Radix, Pseudostellariae Radix, Astragali Radix, Dioscoreae Rhizoma, Glycyrrhizae Radix et Rhizoma for DLBCL treatment, respectively. Then besides Panacis Quinquefolii Radix and Dioscoreae Rhizoma, 1,14, 10, 14,13 hub genes were selected, respectively. Molecular docking studies indicated that active ingredients could stably bind to the pockets of hub proteins. CASP3, CDK1, AKT1 and MAPK3 were predicted as common hub genes. However, through experimental verification, only CASP3 was considered as the common target of Qi-invigorating herbs on DLBCL apoptosis. Furthermore, the TIMER2.0 database showed that Qi-invigorating herbs might act on DLBCL microenvironment through their target genes. Tumor-associated neutrophils may be main target cells of DLBCL treated by Qi-invigorating herbs. Conclusion: Our results support the effects of Qi-invigorating herbs on DLBCL. Hub genes and immune infiltrating cells provided the molecular basis for each Qi-invigorating herb acting on DLBCL.
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Affiliation(s)
- Qian Huang
- Fujian Institute of Hematology, Fujian Medical Center of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jinkun Lin
- Fujian Institute of Hematology, Fujian Medical Center of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Surong Huang
- Fujian Institute of Hematology, Fujian Medical Center of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jianzhen Shen
- Fujian Institute of Hematology, Fujian Medical Center of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
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12
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A Germinal Center-Associated Microenvironmental Signature Reflects Malignant Phenotype and Outcome of DLBCL. Blood Adv 2021; 6:2388-2402. [PMID: 34638128 PMCID: PMC9006269 DOI: 10.1182/bloodadvances.2021004618] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 08/29/2021] [Indexed: 12/03/2022] Open
Abstract
The DLBCL microenvironment signature scoring system was established using nCounter-based profiling of GC-related microenvironmental genes. DMS scores stratified DLBCL patients with different prognosis independently of existing prognostic models.
Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy, with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin (COO), genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using the nCounter-based gene expression profiling of untreated DLBCL tissues, we assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.
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13
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Croci GA, Au-Yeung RKH, Reinke S, Staiger AM, Koch K, Oschlies I, Richter J, Poeschel V, Held G, Loeffler M, Trümper L, Rosenwald A, Ott G, Spang R, Altmann B, Ziepert M, Klapper W. SPARC-positive macrophages are the superior prognostic factor in the microenvironment of diffuse large B-cell lymphoma and independent of MYC rearrangement and double-/triple-hit status. Ann Oncol 2021; 32:1400-1409. [PMID: 34438040 DOI: 10.1016/j.annonc.2021.08.1991] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/04/2021] [Accepted: 08/16/2021] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with respect to outcome. Features of the tumor microenvironment (TME) are associated with prognosis when assessed by gene expression profiling. However, it is uncertain whether assessment of the microenvironment can add prognostic information to the most relevant and clinically well-established molecular subgroups when analyzed by immunohistochemistry (IHC). PATIENTS AND METHODS We carried out a histopathologic analysis of biomarkers related to TME in a very large cohort (n = 455) of DLBCL treated in prospective trials and correlated with clinicopathologic and molecular data, including chromosomal rearrangements and gene expression profiles for cell-of-origin and TME. RESULTS The content of PD1+, FoxP3+ and CD8+, as well as vessel density, was not associated with outcome. However, we found a low content of CD68+ macrophages to be associated with inferior progression-free survival (PFS) and overall survival (OS; P = 0.023 and 0.040, respectively) at both univariable and multivariable analyses, adjusted for the factors of the International Prognostic Index (IPI), MYC break and BCL2/MYC and BCL6/MYC double-hit status. The subgroup of PDL1+ macrophages was not associated with survival. Instead, secreted protein acidic and cysteine rich (SPARC)-positive macrophages were identified as the subtype of macrophages most associated with survival. SPARC-positive macrophages and stromal cells directly correlated with favorable PFS and OS (both, P[log rank] <0.001, P[trend] < 0.001). The association of SPARC with prognosis was independent of the factors of the IPI, MYC double-/triple-hit status, Bcl2/c-myc double expression, cell-of-origin subtype and a recently published gene expression signature [lymphoma-associated macrophage interaction signature (LAMIS)]. CONCLUSIONS SPARC expression in the TME detected by a single IHC staining with fair-to-good interobserver reproducibility is a powerful prognostic parameter. Thus SPARC expression is a strong candidate for risk assessment in DLBCL in daily practice.
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Affiliation(s)
- G A Croci
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Division of Pathology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - R K H Au-Yeung
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany; Department of Pathology, Queen Mary Hospital, The University of Hong Kong, Hong Kong
| | - S Reinke
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - A M Staiger
- Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany; Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart and University of Tuebingen, Tübingen, Germany
| | - K Koch
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - I Oschlies
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - J Richter
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - V Poeschel
- Department of Internal Medicine 1 (Oncology, Hematology, Clinical Immunology, and Rheumatology), Saarland University Medical School, Homburg/Saar, Germany
| | - G Held
- DSHNHL Studiensekretariat, Universitätsklinikum des Saarlandes, Homburg, Germany
| | - M Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - L Trümper
- Department of Hematology and Oncology, Georg-August Universität, Göttingen, Germany
| | - A Rosenwald
- Institute of Pathology, Universität Würzburg and Comprehensive Cancer Center Mainfranken (CCCMF), Würzburg, Germany
| | - G Ott
- Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany; Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart and University of Tuebingen, Tübingen, Germany
| | - R Spang
- Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - B Altmann
- DSHNHL Studiensekretariat, Universitätsklinikum des Saarlandes, Homburg, Germany
| | - M Ziepert
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - W Klapper
- Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
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14
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Pollari M, Leivonen SK, Leppä S. Testicular Diffuse Large B-Cell Lymphoma-Clinical, Molecular, and Immunological Features. Cancers (Basel) 2021; 13:cancers13164049. [PMID: 34439203 PMCID: PMC8392512 DOI: 10.3390/cancers13164049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/06/2021] [Accepted: 08/10/2021] [Indexed: 12/16/2022] Open
Abstract
Simple Summary Testicular diffuse large B-cell lymphoma (T-DLBCL) is a rare and aggressive lymphoma entity that mainly affects elderly men. It has a high relapse rate with especially the relapses of the central nervous system associating with dismal outcome. T-DLBCL has a unique biology with distinct genetic characteristics and clinical presentation, and the increasing knowledge on the tumor microenvironment of T-DLBCL highlights the significance of the host immunity and immune escape in this rare lymphoma, presenting in an immune-privileged site of the testis. This review provides an update on the latest progress made in T-DLBCL research and summarizes the clinical perspectives in T-DLBCL. Abstract Primary testicular lymphoma is a rare lymphoma entity, yet it is the most common testicular malignancy among elderly men. The majority of the cases represent non-germinal center B-cell-like (non-GCB) diffuse large B-cell lymphoma (DLBCL) with aggressive clinical behavior and a relatively high relapse rate. Due to the rareness of the disease, no randomized clinical trials have been conducted and the currently recognized standard of care is based on retrospective analyses and few phase II trials. During recent years, the tumor microenvironment (TME) and tumor-related immunity have been the focus of many tumor biology studies, and the emergence of targeted therapies and checkpoint inhibitors has significantly modulated the field of cancer therapies. Testicular DLBCL (T-DLBCL) is presented in an immune-privileged site of the testis, and the roles of NF-κB pathway signaling, 9p24.1 aberrations, and tumor-infiltrating immune cells, especially immune checkpoint expressing lymphocytes and macrophages, seem to be unique compared to other lymphoma entities. Preliminary data on the use of immune checkpoint inhibitors in the treatment of T-DLBCL are promising and more studies are ongoing.
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Affiliation(s)
- Marjukka Pollari
- Research Program Unit, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland; (S.-K.L.); (S.L.)
- Department of Oncology, Tays Cancer Center, Tampere University Hospital, 33521 Tampere, Finland
- Correspondence:
| | - Suvi-Katri Leivonen
- Research Program Unit, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland; (S.-K.L.); (S.L.)
- Department of Oncology, Comprehensive Cancer Center, Helsinki University Hospital, 00029 Helsinki, Finland
| | - Sirpa Leppä
- Research Program Unit, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland; (S.-K.L.); (S.L.)
- Department of Oncology, Comprehensive Cancer Center, Helsinki University Hospital, 00029 Helsinki, Finland
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15
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Papageorgiou SG, Thomopoulos TP, Katagas I, Bouchla A, Pappa V. Prognostic molecular biomarkers in diffuse large B-cell lymphoma in the rituximab era and their therapeutic implications. Ther Adv Hematol 2021; 12:20406207211013987. [PMID: 34104369 PMCID: PMC8150462 DOI: 10.1177/20406207211013987] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Accepted: 04/12/2021] [Indexed: 12/17/2022] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) represents a group of tumors characterized by substantial heterogeneity in terms of their pathological and biological features, a causal factor of their varied clinical outcome. This variation has persisted despite the implementation of rituximab in treatment regimens over the last 20 years. In this context, prognostic biomarkers are of great importance in order to identify high-risk patients that might benefit from treatment intensification or the introduction of novel therapeutic agents. Herein, we review current knowledge on specific immunohistochemical or genetic biomarkers that might be useful in clinical practice. Gene-expression profiling is a tool of special consideration in this effort, as it has enriched our understanding of DLBCL biology and has allowed for the classification of DLBCL by cell-of-origin as well as by more elaborate molecular signatures based on distinct gene-expression profiles. These subgroups might outperform individual biomarkers in terms of prognostication; however, their use in clinical practice is still limited. Moreover, the underappreciated role of the tumor microenvironment in DLBCL prognosis is discussed in terms of prognostic gene-expression signatures, as well as in terms of individual biomarkers of prognostic significance. Finally, the efficacy of novel therapeutic agents for the treatment of DLBCL patients are discussed and an evidence-based therapeutic approach by specific genetic subgroup is suggested.
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Affiliation(s)
- Sotirios G. Papageorgiou
- Second Department of Internal Medicine and Research Unit, University General Hospital ‘Attikon’, 1 Rimini Street, Haidari, Athens 12462, Greece
| | - Thomas P. Thomopoulos
- Second Department of Internal Medicine and Research Unit, Hematology Unit, University General Hospital, ‘Attikon’, Haidari, Athens, Greece
| | - Ioannis Katagas
- Second Department of Internal Medicine and Research Unit, Hematology Unit, University General Hospital, ‘Attikon’, Haidari, Athens, Greece
| | - Anthi Bouchla
- Second Department of Internal Medicine and Research Unit, Hematology Unit, University General Hospital, ‘Attikon’, Haidari, Athens, Greece
| | - Vassiliki Pappa
- Second Department of Internal Medicine and Research Unit, Hematology Unit, University General Hospital, ‘Attikon’, Haidari, Athens, Greece
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Pileri SA, Tripodo C, Melle F, Motta G, Tabanelli V, Fiori S, Vegliante MC, Mazzara S, Ciavarella S, Derenzini E. Predictive and Prognostic Molecular Factors in Diffuse Large B-Cell Lymphomas. Cells 2021; 10:cells10030675. [PMID: 33803671 PMCID: PMC8003012 DOI: 10.3390/cells10030675] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/10/2021] [Accepted: 03/12/2021] [Indexed: 11/17/2022] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) is the commonest form of lymphoid malignancy, with a prevalence of about 40% worldwide. Its classification encompasses a common form, also termed as “not otherwise specified” (NOS), and a series of variants, which are rare and at least in part related to viral agents. Over the last two decades, DLBCL-NOS, which accounts for more than 80% of the neoplasms included in the DLBCL chapter, has been the object of an increasing number of molecular studies which have led to the identification of prognostic/predictive factors that are increasingly entering daily practice. In this review, the main achievements obtained by gene expression profiling (with respect to both neoplastic cells and the microenvironment) and next-generation sequencing will be discussed and compared. Only the amalgamation of molecular attributes will lead to the achievement of the long-term goal of using tailored therapies and possibly chemotherapy-free protocols capable of curing most (if not all) patients with minimal or no toxic effects.
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Affiliation(s)
- Stefano A. Pileri
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
- Correspondence: or
| | - Claudio Tripodo
- Tumor Immunology Unit, University of Palermo, 90133 Palermo, Italy;
- Tumor and Microenvironment Histopathology Unit, IFOM, the FIRC Institute of Molecular Oncology, 20139 Milan, Italy
| | - Federica Melle
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
| | - Giovanna Motta
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
| | - Valentina Tabanelli
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
| | - Stefano Fiori
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
| | - Maria Carmela Vegliante
- Hematology and Cell Therapy Unit, IRCCS-Istituto Tumori ‘Giovanni Paolo II’, Viale Flacco 65, 70124 Bari, Italy; (M.C.V.); (S.C.)
| | - Saveria Mazzara
- Division of Haematopathology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy; (F.M.); (G.M.); (V.T.); (S.F.); (S.M.)
| | - Sabino Ciavarella
- Hematology and Cell Therapy Unit, IRCCS-Istituto Tumori ‘Giovanni Paolo II’, Viale Flacco 65, 70124 Bari, Italy; (M.C.V.); (S.C.)
| | - Enrico Derenzini
- Division of Haemato-Oncology, European Institute of Oncology, IEO IRCCS, Via Ripamonti 435, 20141 Milan, Italy;
- Department of Health Sciences, University of Milan, Via di Rudinì 8, 20146 Milan, Italy
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17
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The "Burkitt-like" immunophenotype and genotype is rarely encountered in diffuse large B cell lymphoma and high-grade B cell lymphoma, NOS. Virchows Arch 2021; 479:575-583. [PMID: 33655392 DOI: 10.1007/s00428-021-03050-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 01/27/2021] [Accepted: 02/01/2021] [Indexed: 10/22/2022]
Abstract
Burkitt lymphoma (BL) is a B cell lymphoma composed of monomorphic medium-sized blastic cells with basophilic cytoplasm and a high proliferation index. BL has a characteristic immunophenotype of CD10 and BCL6 positive and BCL2 negative and harbours MYC gene rearrangements (MYCR) in >90% of the cases. Owing to its highly aggressive nature, intensified chemotherapy regimens are usually administered, requiring an exact diagnosis. Since the diagnosis usually warrants an integration of morphologic, immunophenotypic and genetic findings and because there is a morphologic overlap with the new WHO category of high-grade B cell lymphoma, not otherwise specified (HGBL, NOS) and some cases of diffuse large B cell lymphoma (DLBCL), we wanted to test the distinctiveness of the CD10+, BCL6+, BCL2- and MYCR positive immunopheno-genotype in a large cohort of >1000 DLBCL and HGBL. Only 9/982 DLBCL classified by an expert panel of haematopathologists (0.9%) displayed a single MYCR and were CD10+, BCL6+ and BCL2-. In a similar fashion, only one out of 32 HGBL, NOS (3%) displayed the "Burkitt-like" genetic/immunophenotypic constitution. The samples of non-BL showing the BL-typic immunopheno-genotype, interestingly, harboured higher copy number variations (CNV) by OncoScan analysis (mean 7.3 CNVs/sample; range: 2-13 vs. 2.4; range 0-6) and were also distinct from pleomorphic BL cases regarding their mutational spectrum by NGS analysis. This implies that the characteristic immunophenotype of BL, in concert with a single MYCR, is uncommon in these aggressive lymphomas, and that this constellation favours BL.
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Nordmo C, Glehr G, Altenbuchinger M, Spang R, Ziepert M, Horn H, Staiger AM, Ott G, Schmitz N, Held G, Einsele H, Topp M, Rosenwald A, Rauert-Wunderlich H. Identification of a miRNA based model to detect prognostic subgroups in patients with aggressive B-cell lymphoma. Leuk Lymphoma 2020; 62:1107-1115. [PMID: 33353431 DOI: 10.1080/10428194.2020.1861268] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In order to differentiate prognostic subgroups of patients with aggressive B-cell lymphoma, we analyzed the expression of 800 miRNAs with the NanoString nCounter human miRNA assay on a cohort of 228 FFPE samples of patients enrolled in the RICOVER-60 and MegaCHOEP trials. We identified significant miRNA signatures for overall survival (OS) and progression-free survival (PFS) by LASSO-penalized linear Cox-regression. High expression levels of miR-130a-3p and miR-423-5p indicate a better prognosis, whereas high levels of miR-374b-5p, miR-590-5p, miR-186-5p, and miR-106b-5p increase patients' risk levels for OS. Regarding PFS high expression of miR-365a-5p in addition to the other two miRNAs improves the prognosis and high levels of miR374a-5p, miR-106b-5p, and miR-590-5p, connects with increased risk and poor prognosis. We identified miRNA signatures to subdivide patients into two different risk groups. These prognostic models may be used in risk stratification in future clinical trials and help making personalized therapy decisions.
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Affiliation(s)
- Carmen Nordmo
- Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany.,Institute of Pathology, University of Würzburg and Comprehensive Cancer Center (CCC) Mainfranken, Würzburg, Germany
| | - Gunther Glehr
- Institute of Functional Genomics, Statistical Bioinformatics, University of Regensburg, Regensburg, Germany
| | - Michael Altenbuchinger
- Institute of Functional Genomics, Statistical Bioinformatics, University of Regensburg, Regensburg, Germany
| | - Rainer Spang
- Institute of Functional Genomics, Statistical Bioinformatics, University of Regensburg, Regensburg, Germany
| | - Marita Ziepert
- Institute of Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Heike Horn
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany and University of Tuebingen, Tuebingen, Germany.,Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany
| | - Annette M Staiger
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany and University of Tuebingen, Tuebingen, Germany.,Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany
| | - German Ott
- Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany
| | - Norbert Schmitz
- Department of Medicine A, University Hospital Münster, Münster, Germany
| | - Gerhard Held
- DSHNHL Studiensekretariat, Westpfalz Klinikum GmbH, Kaiserslautern, Germany
| | - Hermann Einsele
- Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Max Topp
- Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Andreas Rosenwald
- Institute of Pathology, University of Würzburg and Comprehensive Cancer Center (CCC) Mainfranken, Würzburg, Germany
| | - Hilka Rauert-Wunderlich
- Institute of Pathology, University of Würzburg and Comprehensive Cancer Center (CCC) Mainfranken, Würzburg, Germany
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19
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Ziepert M, Lazzi S, Santi R, Vergoni F, Granai M, Mancini V, Staiger AM, Horn H, Löffler M, Pöschel V, Held G, Wulf G, Trümper LH, Schmitz N, Rosenwald A, Sabattini E, Naresh KN, Stein H, Ott G, Leoncini L. A 70% cut-off for MYC protein expression in diffuse large B cell lymphoma identifies a high-risk group of patients. Haematologica 2020; 105:2667-2670. [PMID: 33131258 PMCID: PMC7604633 DOI: 10.3324/haematol.2019.235556] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Marita Ziepert
- University of Leipzig - Institute of Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
| | - Stefano Lazzi
- Department of Medical Biotechnology, Section of Pathology, University of Siena, Siena, Italy
| | - Raffaella Santi
- Department of Pathology, Careggi University Hospital, University of Firenze, Firenze, Italy
| | - Federica Vergoni
- Department of Pathology, Careggi University Hospital, University of Firenze, Firenze, Italy
| | - Massimo Granai
- Department of Medical Biotechnology, Section of Pathology, University of Siena, Siena, Italy
| | - Virginia Mancini
- Department of Medical Biotechnology, Section of Pathology, University of Siena, Siena, Italy
| | - Annette M. Staiger
- Department of Clinical Pathology, Robert- Bosch-Krankenhaus, Stuttgart, Germany
- Dr. Margarete Fischer- Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany and University of Tübingen, Germany
| | - Heike Horn
- Department of Clinical Pathology, Robert- Bosch-Krankenhaus, Stuttgart, Germany
- Dr. Margarete Fischer- Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany and University of Tübingen, Germany
| | - Markus Löffler
- Institute for Medical Informatics Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Viola Pöschel
- DSHNHL Studiensekretariat, Universitätsklinikum des Saarlandes, Homburg; Germany
| | - Gerhald Held
- DSHNHL Studiensekretariat, Universitätsklinikum des Saarlandes, Homburg; Germany
| | - Gerald Wulf
- Department of Hematology and Oncology, Georg-August Universität, Göttingen, Germany
| | - Lorenz H. Trümper
- G-CCC (Göttingen Comprehensive Cancer Center), University Medicine Göttingen, Göttingen, Germany
| | - Norbert Schmitz
- Department of Medicine A, University Hospital Münster, Münster, Germany
| | - Andreas Rosenwald
- Institute of Pathology, Universität Würzburg and Comprehensive Cancer Center Mainfranken (CCCMF), Würzburg, Germany
| | - Elena Sabattini
- Institute of Hematology "L. and A. Seràgnoli", S. Orsola - Malpighi Hospital, Bologna, Italy
| | | | | | - German Ott
- Department of Clinical Pathology, Robert- Bosch-Krankenhaus, Stuttgart, Germany
| | - Lorenzo Leoncini
- Department of Medical Biotechnology, Section of Pathology, University of Siena, Siena, Italy
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20
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Ennishi D, Hsi ED, Steidl C, Scott DW. Toward a New Molecular Taxonomy of Diffuse Large B-cell Lymphoma. Cancer Discov 2020; 10:1267-1281. [DOI: 10.1158/2159-8290.cd-20-0174] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 05/04/2020] [Accepted: 05/07/2020] [Indexed: 11/16/2022]
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21
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Opinto G, Vegliante MC, Negri A, Skrypets T, Loseto G, Pileri SA, Guarini A, Ciavarella S. The Tumor Microenvironment of DLBCL in the Computational Era. Front Oncol 2020; 10:351. [PMID: 32296632 PMCID: PMC7136462 DOI: 10.3389/fonc.2020.00351] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 02/27/2020] [Indexed: 12/12/2022] Open
Abstract
Among classical exemplifications of tumor microenvironment (TME) in lymphoma pathogenesis, the “effacement model” resembled by diffuse large B cell lymphoma (DLBCL) implies strong cell autonomous survival and paucity of non-malignant elements. Nonetheless, the magnitude of TME exploration is increasing as novel technologies allow the high-resolution discrimination of cellular and extra-cellular determinants at the functional, more than morphological, level. Results from genomic-scale studies and recent clinical trials revitalized the interest in this field, prompting the use of new tools to dissect DLBCL composition and reveal novel prognostic association. Here we revisited major controversies related to TME in DLBCL, focusing on the use of bioinformatics to mine transcriptomic data and provide new insights to be translated into the clinical setting.
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Affiliation(s)
- Giuseppina Opinto
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
| | - Maria Carmela Vegliante
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
| | - Antonio Negri
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
| | - Tetiana Skrypets
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy.,CHIMOMO Department, University of Modena and Reggio Emilia, Modena, Italy
| | - Giacomo Loseto
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
| | - Stefano Aldo Pileri
- Division of Haematopathology, European Institute of Oncology-IRCCS, Milan, Italy
| | - Attilio Guarini
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
| | - Sabino Ciavarella
- Unit of Hematology and Cell Therapy, Laboratory of Hematological Diagnostics and Cell Characterization, Istituto Tumori "Giovanni Paolo II"-IRCCS, Bari, Italy
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