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Cancers
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Recent Advances in Diagnostic and Treatment Strategies in Malignant Lymphoma
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Recent Advances in Diagnostic and Treatment Strategies in Malignant Lymphoma

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

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 8958

Special Issue Editor

Prof. Dr. Mathias Witzens-Harig

E-Mail Website
Guest Editor
Medical Faculty, Heidelberg University, Im Neuenheimer Feld 410 Handschuhsheimer Flur, 69120 Heidelberg, Germany
Interests: Lymphoma; multiple myeloma; lung cancer; immunotherapy

Special Issue Information

Dear Colleagues,

 

In the last decade, tremendous progress was achieved in the understanding of the biology of malignant lymphoma. In particular, advances in pathology, genetics, molecular biology and bioinformatics have led to new insights in the way malignant lymphoma arises and evolves. Now this knowledge is transforming the diagnostic and therapeutic landscape of malignant lymphoma in an unprecedented way. In particular, new diagnostic classification systems that are based on genetic and molecular profiling will lead to very tailored, personalized and ultimately patient-specific treatment protocols. Within these protocols, combinations of various approaches, such as targeted therapy, immune therapy, gene therapy and future treatments, have the potential not only to eradicate the disease but also to achieve long-term remissions, or even a cure, for an increasing number of patients. This Special Issue will address in detail the latest exciting developments in the field.

Prof. Dr. Mathias Witzens-Harig
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 short 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
  • pathology
  • genetics
  • molecular biology
  • bioinformatics
  • targeted therapy
  • immunotherapy
  • gene therapy
  • personalized medicine

Published Papers (3 papers)

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Research

13 pages, 898 KiB  
Article
Blinatumomab in Relapsed/Refractory Burkitt Lymphoma
by Jeanne Bohler, Ulrike Bacher, Yara Banz, Raphael Stadelmann, Michael Medinger, Thilo Zander and Thomas Pabst
Cancers 2023, 15(1), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15010044 - 21 Dec 2022
Cited by 2 | Viewed by 2351
Abstract
In patients with relapsed/refractory Burkitt lymphoma (r/r BL), overall survival (OS) is poor, and effective therapies and evidence for the best therapy are lacking. The monoclonal antibody blinatumomab may represent a novel option. However, only limited data on the use of blinatumomab in [...] Read more.
In patients with relapsed/refractory Burkitt lymphoma (r/r BL), overall survival (OS) is poor, and effective therapies and evidence for the best therapy are lacking. The monoclonal antibody blinatumomab may represent a novel option. However, only limited data on the use of blinatumomab in r/r BL are so far available. This multi-center, retrospective case series investigated nine patients with r/r BL treated with blinatumomab. The safety of blinatumomab was assessed with respect to frequency and severity of adverse effects (AEs) infections, cytokine release syndrome (CRS) and neurotoxicity. Progression-free survival (PFS), OS and overall response rate (ORR) were analyzed to assess efficacy. No AEs > grade 2 occurred, and AEs were generally treatable and fully reversible. The best response to blinatumomab was complete remission in 3/9 patients and partial remission in 2/9, whilst 4/9 presented with progressive disease. Median PFS and OS were 2 and 6 months, respectively, ranging from 5 days to 32 months and 11 days to 32 months, respectively. Blinatumomab treatment was a successful bridging treatment to stem cell transplantation in 3/9 patients. The response to blinatumomab varied widely, and only one patient survived longer term, but activity in patients with r/r BL was evident in some patients, with its use being safe, warranting its prospective investigation. Full article
(This article belongs to the Special Issue Recent Advances in Diagnostic and Treatment Strategies in Malignant Lymphoma)
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19 pages, 1945 KiB  
Article
CYCLON and NPM1 Cooperate within an Oncogenic Network Predictive of R-CHOP Response in DLBCL
by Antonin Bouroumeau, Lucile Bussot, Sieme Hamaidia, Andrea Garcìa-Sandoval, Anna Bergan-Dahl, Patricia Betton-Fraisse, Samuel Duley, Cyril Fournier, Romain Aucagne, Annie Adrait, Yohann Couté, Anne McLeer, Edwige Col, Laurence David-Boudet, Tatiana Raskovalova, Marie-Christine Jacob, Claire Vettier, Simon Chevalier, Sylvain Carras, Christine Lefebvre, Caroline Algrin, Rémy Gressin, Mary B. Callanan, Hervé Sartelet, Thierry Bonnefoix and Anouk Emadaliadd Show full author list remove Hide full author list
Cancers 2021, 13(23), 5900; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13235900 - 24 Nov 2021
Cited by 4 | Viewed by 2078
Abstract
R-CHOP immuno-chemotherapy significantly improved clinical management of diffuse large B-cell lymphoma (DLBCL). However, 30–40% of DLBCL patients still present a refractory disease or relapse. Most of the prognostic markers identified to date fail to accurately stratify high-risk DLBCL patients. We have previously shown [...] Read more.
R-CHOP immuno-chemotherapy significantly improved clinical management of diffuse large B-cell lymphoma (DLBCL). However, 30–40% of DLBCL patients still present a refractory disease or relapse. Most of the prognostic markers identified to date fail to accurately stratify high-risk DLBCL patients. We have previously shown that the nuclear protein CYCLON is associated with DLBCL disease progression and resistance to anti-CD20 immunotherapy in preclinical models. We also recently reported that it also represents a potent predictor of refractory disease and relapse in a retrospective DLBCL cohort. However, only sparse data are available to predict the potential biological role of CYCLON and how it might exert its adverse effects on lymphoma cells. Here, we characterized the protein interaction network of CYCLON, connecting this protein to the nucleolus, RNA processing, MYC signaling and cell cycle progression. Among this network, NPM1, a nucleolar multi-functional protein frequently deregulated in cancer, emerged as another potential target related to treatment resistance in DLBCL. Immunohistochemistry evaluation of CYCLON and NPM1 revealed that their co-expression is strongly related to inferior prognosis in DLBCL. More specifically, alternative sub-cellular localizations of the proteins (extra-nucleolar CYCLON and pan-cellular NPM1) represent independent predictive factors specifically associated to R-CHOP refractory DLBCL patients, which could allow them to be orientated towards risk-adapted or novel targeted therapies. Full article
(This article belongs to the Special Issue Recent Advances in Diagnostic and Treatment Strategies in Malignant Lymphoma)
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11 pages, 9775 KiB  
Article
Deep Learning for the Classification of Non-Hodgkin Lymphoma on Histopathological Images
by Georg Steinbuss, Mark Kriegsmann, Christiane Zgorzelski, Alexander Brobeil, Benjamin Goeppert, Sascha Dietrich, Gunhild Mechtersheimer and Katharina Kriegsmann
Cancers 2021, 13(10), 2419; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13102419 - 17 May 2021
Cited by 24 | Viewed by 3623
Abstract
The diagnosis and the subtyping of non-Hodgkin lymphoma (NHL) are challenging and require expert knowledge, great experience, thorough morphological analysis, and often additional expensive immunohistological and molecular methods. As these requirements are not always available, supplemental methods supporting morphological-based decision making and potentially [...] Read more.
The diagnosis and the subtyping of non-Hodgkin lymphoma (NHL) are challenging and require expert knowledge, great experience, thorough morphological analysis, and often additional expensive immunohistological and molecular methods. As these requirements are not always available, supplemental methods supporting morphological-based decision making and potentially entity subtyping are required. Deep learning methods have been shown to classify histopathological images with high accuracy, but data on NHL subtyping are limited. After annotation of histopathological whole-slide images and image patch extraction, we trained and optimized an EfficientNet convolutional neuronal network algorithm on 84,139 image patches from 629 patients and evaluated its potential to classify tumor-free reference lymph nodes, nodal small lymphocytic lymphoma/chronic lymphocytic leukemia, and nodal diffuse large B-cell lymphoma. The optimized algorithm achieved an accuracy of 95.56% on an independent test set including 16,960 image patches from 125 patients after the application of quality controls. Automatic classification of NHL is possible with high accuracy using deep learning on histopathological images and routine diagnostic applications should be pursued. Full article
(This article belongs to the Special Issue Recent Advances in Diagnostic and Treatment Strategies in Malignant Lymphoma)
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