Targeting the Resistant Tumor Microenvironment in Lymphoma: From Basic Science to Artificial Intelligence
A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 2044
Special Issue Editor
Interests: lymphoma; tumor microenvironment; immunotherapy; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Lymphomas are heterogeneous groups of neoplasms that originate from the aberrant proliferation of immune cells, including B lymphocytes, T lymphocytes, and natural killer (NK) cells. While tumoral initiation is associated with the accumulation of genetic mutations, the tumor microenvironment (TME) is a crucial infrastructure in lymphomagenesis, as they are strongly dependent on the TME for various steps of malignancies. The TME constitutes a dynamic ecosystem composed of immune and stromal cells, implicated from progression to metastasis. Despite recent advances in lymphoma treatment, achieving a durable response remains poor, leading to relapse and resistance to various immunotherapies.
Current challenges in reaching a complete response include the high degree of heterogeneity in the TME composition and the multitude mechanisms through which the TME can counteract the efficacy of therapy. The high pressure exerted by treatments results in the modulation of TME response prompting necessary signals for the development of resistant clones against therapeutic regimens.
Therefore, further research is necessary to explore the complex molecular and cellular ecosystem of lymphoma disease and reveal innovative microenvironmental targets that can reduce the high incidence of relapse and resistance and minimize the development of drug-resistant clones.
This Special Issue welcomes reviews and innovative research articles spanning from basic science to artificial intelligence approaches on the TME-lymphoma crosstalk. The aim is to enhance our understanding of the influence of TME on malignancies and improve therapy effectiveness.
Dr. Rada Amin
Guest Editor
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Keywords
- lymphoma
- tumor microenvironment
- tumor–immune cell interaction
- immunotherapy
- machine learning
- bioimaging
- artificial intelligence
- immunology
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