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Cancers
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Molecular Characterization of Hematological Tumors
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Molecular Characterization of Hematological Tumors

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Tumor Microenvironment".

Deadline for manuscript submissions: closed (1 September 2022) | Viewed by 22394

Special Issue Editor

Dr. Blanca Scheijen

E-Mail Website
Guest Editor
Department of Pathology, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
Interests: lymphoid malignancies; molecular pathogenesis; mutation analysis; therapy resistance; clonal evolution; immune profiling; immunotherapy

Special Issue Information

Dear Colleagues,

In the past two decades, enormous progress has been made in defining the mutational landscape of many different cancer genomes, including most classes of hematological malignancies. This knowledge has enhanced our understanding regarding the molecular pathogenesis of hematopoietic tumors and advanced the diagnostics and treatment of leukemia, lymphoma, and multiple myeloma patients, including improved risk stratification and development of novel targeted therapies. Various high-throughput sequencing applications are currently being employed to molecularly characterize hematological tumors at time of diagnosis and subsequently follow up to address clinically relevant research questions. This Special Issue aims to provide an overview on current developments in the field of hemato-oncology/pathology. We welcome submissions of research articles and reviews that relate to molecular analysis of hematological malignancies, including topics in the field of basic and translational research as well as diagnostic applications.

Dr. Blanca Scheijen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • lymphoma
  • leukemia
  • multiple myeloma
  • mutation analysis
  • gene expression signatures
  • clonality analysis
  • next-generation sequencing
  • circulating tumor DNA
  • predictive markers

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Published Papers (6 papers)

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Research

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37 pages, 6154 KiB  
Article
Classifying Germinal Center Derived Lymphomas—Navigate a Complex Transcriptional Landscape
by Henry Loeffler-Wirth, Markus Kreuz, Maria Schmidt, German Ott, Reiner Siebert and Hans Binder
Cancers 2022, 14(14), 3434; https://doi.org/10.3390/cancers14143434 - 14 Jul 2022
Cited by 11 | Viewed by 3750
Abstract
Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures [...] Read more.
Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures of up- or downregulated genes, competing molecular classifiers were often proposed in the literature by different groups for the same classification tasks to distinguish, e.g., BL versus DLBCL or different DLBCL subtypes. Moreover, rarer sub-entities such as MYC and BCL2 “double hit lymphomas” (DHL), IRF4-rearranged large cell lymphoma (IRF4-LCL), and Burkitt-like lymphomas with 11q aberration pattern (mnBLL-11q) attracted interest while their relatedness regarding the major classes is still unclear in many respects. We explored the transcriptional landscape of 873 lymphomas referring to a wide spectrum of subtypes by applying self-organizing maps (SOM) machine learning. The landscape reveals a continuum of transcriptional states activated in the different subtypes without clear-cut borderlines between them and preventing their unambiguous classification. These states show striking parallels with single cell gene expression of the active germinal center (GC), which is characterized by the cyclic progression of B-cells. The expression patterns along the GC trajectory are discriminative for distinguishing different lymphoma subtypes. We show that the rare subtypes take intermediate positions between BL, DLBCL, and FL as considered by the 5th edition of the WHO classification of haemato-lymphoid tumors in 2022. Classifier gene signatures extracted from these states as modules of coregulated genes are competitive with literature classifiers. They provide functional-defined classifiers with the option of consenting redundant classifiers from the literature. We discuss alternative classification schemes of different granularity and functional impact as possible avenues toward personalization and improved diagnostics of GC-derived lymphomas. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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15 pages, 2402 KiB  
Article
Reproducibility of Gene Expression Signatures in Diffuse Large B-Cell Lymphoma
by Jessica Rodrigues Plaça, Arjan Diepstra, Tjitske Los, Matías Mendeville, Annika Seitz, Pieternella J. Lugtenburg, Josée Zijlstra, King Lam, Wilson Araújo da Silva, Jr., Bauke Ylstra, Daphne de Jong, Anke van den Berg and Marcel Nijland
Cancers 2022, 14(5), 1346; https://doi.org/10.3390/cancers14051346 - 5 Mar 2022
Cited by 2 | Viewed by 3524
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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19 pages, 3932 KiB  
Article
Bone Marrow Stroma-Induced Transcriptome and Regulome Signatures of Multiple Myeloma
by Sebastian A. Dziadowicz, Lei Wang, Halima Akhter, Drake Aesoph, Tulika Sharma, Donald A. Adjeroh, Lori A. Hazlehurst and Gangqing Hu
Cancers 2022, 14(4), 927; https://doi.org/10.3390/cancers14040927 - 13 Feb 2022
Cited by 15 | Viewed by 4103
Abstract
Multiple myeloma (MM) is a hematological cancer with inevitable drug resistance. MM cells interacting with bone marrow stromal cells (BMSCs) undergo substantial changes in the transcriptome and develop de novo multi-drug resistance. As a critical component in transcriptional regulation, how the chromatin landscape [...] Read more.
Multiple myeloma (MM) is a hematological cancer with inevitable drug resistance. MM cells interacting with bone marrow stromal cells (BMSCs) undergo substantial changes in the transcriptome and develop de novo multi-drug resistance. As a critical component in transcriptional regulation, how the chromatin landscape is transformed in MM cells exposed to BMSCs and contributes to the transcriptional response to BMSCs remains elusive. We profiled the transcriptome and regulome for MM cells using a transwell coculture system with BMSCs. The transcriptome and regulome of MM cells from the upper transwell resembled MM cells that coexisted with BMSCs from the lower chamber but were distinctive to monoculture. BMSC-induced genes were enriched in the JAK2/STAT3 signaling pathway, unfolded protein stress, signatures of early plasma cells, and response to proteasome inhibitors. Genes with increasing accessibility at multiple regulatory sites were preferentially induced by BMSCs; these genes were enriched in functions linked to responses to drugs and unfavorable clinic outcomes. We proposed JUNB and ATF4::CEBPβ as candidate transcription factors (TFs) that modulate the BMSC-induced transformation of the regulome linked to the transcriptional response. Together, we characterized the BMSC-induced transcriptome and regulome signatures of MM cells to facilitate research on epigenetic mechanisms of BMSC-induced multi-drug resistance in MM. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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Review

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17 pages, 1725 KiB  
Review
Role of Sirtuins in the Pathobiology of Onco-Hematological Diseases: A PROSPERO-Registered Study and In Silico Analysis
by João Vitor Caetano Goes, Luiz Gustavo Carvalho, Roberta Taiane Germano de Oliveira, Mayara Magna de Lima Melo, Lázaro Antônio Campanha Novaes, Daniel Antunes Moreno, Paola Gyuliane Gonçalves, Carlos Victor Montefusco-Pereira, Ronald Feitosa Pinheiro and Howard Lopes Ribeiro Junior
Cancers 2022, 14(19), 4611; https://doi.org/10.3390/cancers14194611 - 23 Sep 2022
Cited by 2 | Viewed by 2615
Abstract
The sirtuins (SIRT) gene family (SIRT1 to SIRT7) contains the targets implicated in cellular and organismal aging. The role of SIRTs expression in the pathogenesis and overall survival of patients diagnosed with solid tumors has been widely discussed. However, [...] Read more.
The sirtuins (SIRT) gene family (SIRT1 to SIRT7) contains the targets implicated in cellular and organismal aging. The role of SIRTs expression in the pathogenesis and overall survival of patients diagnosed with solid tumors has been widely discussed. However, studies that seek to explain the role of these pathways in the hematopoietic aging process and the consequences of their instability in the pathogenesis of different onco-hematological diseases are still scarce. Therefore, we performed a systematic review (registered in PROSPERO database #CRD42022310079) and in silico analysis (based on GEPIA database) to discuss the role of SIRTs in the advancement of pathogenesis and/or prognosis for different hematological cancer types. In summary, given recent available scientific evidence and in silico gene expression analysis that supports the role of SIRTs in pathobiology of hematological malignances, such as leukemias, lymphomas and myeloma, it is clear the need for further high-quality research and clinical trials that expands the SIRT inhibition knowledge and its effect on controlling clonal progression caused by genomic instability characteristics of these diseases. Finally, SIRTs represent potential molecular targets in the control of the effects caused by aging on the failures of the hematopoietic system that can lead to the involvement of hematological neoplasms. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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16 pages, 1932 KiB  
Review
Novel Approaches in Molecular Characterization of Classical Hodgkin Lymphoma
by Diede A. G. van Bladel, Wendy B. C. Stevens, Michiel van den Brand, Leonie I. Kroeze, Patricia J. T. A. Groenen, J. Han J. M. van Krieken, Konnie M. Hebeda and Blanca Scheijen
Cancers 2022, 14(13), 3222; https://doi.org/10.3390/cancers14133222 - 30 Jun 2022
Cited by 7 | Viewed by 2934
Abstract
Classical Hodgkin lymphoma (cHL) represents a B-cell lymphoproliferative disease characterized by clonal immunoglobulin gene rearrangements and recurrent genomic aberrations in the Hodgkin Reed–Sternberg cells in a reactive inflammatory background. Several methods are available for the molecular analysis of cHL on both tissue and [...] Read more.
Classical Hodgkin lymphoma (cHL) represents a B-cell lymphoproliferative disease characterized by clonal immunoglobulin gene rearrangements and recurrent genomic aberrations in the Hodgkin Reed–Sternberg cells in a reactive inflammatory background. Several methods are available for the molecular analysis of cHL on both tissue and cell-free DNA isolated from blood, which can provide detailed information regarding the clonal composition and genetic alterations that drive lymphoma pathogenesis. Clonality testing involving the detection of immunoglobulin and T cell receptor gene rearrangements, together with mutation analysis, represent valuable tools for cHL diagnostics, especially for patients with an atypical histological or clinical presentation reminiscent of a reactive lesion or another lymphoma subtype. In addition, clonality assessment may establish the clonal relationship of composite or subsequent lymphoma presentations within one patient. During the last few decades, more insight has been obtained on the molecular mechanisms that drive cHL development, including recurrently affected signaling pathways (e.g., NF-κB and JAK/STAT) and immune evasion. We provide an overview of the different approaches to characterize the molecular composition of cHL, and the implementation of these next-generation sequencing-based techniques in research and diagnostic settings. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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23 pages, 1723 KiB  
Review
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
by Fleur A. de Groot, Ruben A. L. de Groen, Anke van den Berg, Patty M. Jansen, King H. Lam, Pim G. N. J. Mutsaers, Carel J. M. van Noesel, Martine E. D. Chamuleau, Wendy B. C. Stevens, Jessica R. Plaça, Rogier Mous, Marie José Kersten, Marjolein M. W. van der Poel, Thomas Tousseyn, F. J. Sherida H. Woei-a-Jin, Arjan Diepstra, Marcel Nijland and Joost S. P. Vermaat
Cancers 2022, 14(8), 1857; https://doi.org/10.3390/cancers14081857 - 7 Apr 2022
Cited by 6 | Viewed by 4246
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Molecular Characterization of Hematological Tumors)
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