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Biomedicines
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Tumor Microenvironment in Cancer: Basic Science, Artificial Intelligence, and Clinical...
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Tumor Microenvironment in Cancer: Basic Science, Artificial Intelligence, and Clinical Research

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 757

Special Issue Editor

Dr. Rada Amin

E-Mail Website
Guest Editor
Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, USA
Interests: lymphoma; tumor microenvironment; immunotherapy; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The tumor microenvironment (TME) is a critical determinant of cancer progression, therapy resistance, and immune evasion, making it a key focus for innovative treatment strategies. Achieving a complete response remains challenging due to the persistence of drug-resistant clones supported by the TME and the multiple resistance mechanisms through which the TME counteracts therapy efficacy. The dynamic interactions between cancer stem cells, stromal components, immune infiltrates, and the extracellular matrix (ECM) create a highly adaptive and heterogeneous ecosystem that is difficult to predict and control. While immunotherapies, such as immune checkpoint inhibitors (ICIs), have shown promising results, the TME remains a major barrier to long-term efficacy due to its immunosuppressive nature and therapy-induced adaptations.

Therefore, innovative research is needed to unravel the complex molecular and cellular landscape of the TME and to identify novel targets to reduce relapse, overcome resistance, and prevent drug-resistant clones.

This Special Issue welcomes reviews and research articles spanning basic science to artificial intelligence approaches aimed at enhancing our understanding of the influence of TME on malignancies and improving therapeutic strategies.

Dr. Rada Amin
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. Biomedicines is an international peer-reviewed open access monthly 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 2600 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

  • tumor microenvironment
  • cancer progression
  • malignancies
  • immunotherapy
  • therapy resistance
  • immune evasion

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Published Papers (1 paper)

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Research

17 pages, 3037 KB  
Article
Programmed-Cell-Death-Related Signature Reveals Immune Microenvironment Characteristics and Predicts Therapeutic Response in Diffuse Large B Cell Lymphoma
by Donghui Xing, Kaiping Luo, Xiang He, Xin Hu, Yixin Zhai, Yanan Jiang, Wenqi Wu and Zhigang Zhao
Biomedicines 2025, 13(10), 2320; https://doi.org/10.3390/biomedicines13102320 - 23 Sep 2025
Viewed by 462
Abstract
Background/Objectives: Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous and aggressive lymphoma with a high incidence rate. Although modern therapeutic approaches have significantly improved patient survival rates, treatment relapse and drug resistance remain major clinical challenges. Programmed cell death (PCD) [...] Read more.
Background/Objectives: Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous and aggressive lymphoma with a high incidence rate. Although modern therapeutic approaches have significantly improved patient survival rates, treatment relapse and drug resistance remain major clinical challenges. Programmed cell death (PCD) promotes tumorigenesis and regulates the tumor microenvironment (TME) and drug sensitivity. Exploring the application potential of PCD in DLBCL could pave the way for new treatment strategies for this malignancy. Methods: We systematically analyzed 13 types of PCD pathways and integrated transcriptomic and clinical data from 832 DLBCL patients (GSE10846, GSE11318, and GSE87371). A PCD-based prognostic signature, termed the Programmed Cell Death Score (PCDS), was constructed using 20 key PCD-related genes. Its clinical relevance was evaluated through survival analysis, drug response profiling, and tumor immune infiltration assessment using CIBERSORT, ESTIMATE, and ssGSEA algorithms. Results: The PCDS robustly stratified patients by survival and outperformed conventional clinical indicators such as age, stage, Eastern Cooperative Oncology Group (ECOG), and lactate dehydrogenase (LDH) in prognostic prediction. High-PCDS tumors were associated with immune suppression, characterized by reduced CD8+ T cell infiltration, elevated M2 macrophages, and increased programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) expression. Drug sensitivity analysis revealed that high-PCDS patients may benefit more from agents like sorafenib and fulvestrant, while low-PCDS patients responded better to NU7441. Functional validation using DLBCL cell lines and xenografts confirmed the oncogenic role of a representative gene (CTH) within the model. Conclusions: This study presents a novel prognostic scoring system derived from multiple PCD pathways that effectively stratifies DLBCL patients by risk and therapeutic responsiveness. Notably, the PCDS is closely associated with key immunological characteristics of the TME. These findings advance personalized treatment strategies and support clinically relevant decision-making in DLBCL. Full article
(This article belongs to the Special Issue Tumor Microenvironment in Cancer: Basic Science, Artificial Intelligence, and Clinical Research)
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