Tumor immunity is a cycle that begins with the release of antigens from tumor cells and ends with the destruction of tumor cells. High mobility group box 1 (HMGB1) is a nonhistone protein widely present in the nucleus of mammalian cells and can be released by immune cells or tumor cells. As a proinflammatory mediator or alarm protein, the activity and function of HMGB1 are determined by the environment, binding receptors, redox status and posttranslational modifications (PTMs), and HMGB1 plays a key role in inflammation and tumor immune processes. In this review, we summarize in detail the current studies on the dual role of HMGB1 in tumor immunity, focusing mainly on immunosuppressive effects, such as regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs), as well as antitumor immunoenhancement effects, such as immunogenic cell death (ICD). Finally, we discuss the potential and challenges of HMGB1 in antitumor immunotherapy.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.31083/j.fbl2810260 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Characterization of Hospital Admissions During Immune Checkpoint Inhibitor Therapy: Insights From the ICOG Study.
Cancer Med
February 2025
Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.
Introduction: Immune checkpoint inhibitors (ICI) have improved the therapeutic arsenal in outpatient oncology care; however, data on necessity of hospitalizations associated with immune-related adverse events (irAEs) are scarce. Here, we characterized hospitalizations of patients undergoing ICI, from the prospective cohort study of the immune cooperative oncology group (ICOG) Hannover.
Methods: Between 12/2019 and 06/2022, 237 patients were included.
Clinico-Pathological Significance of Tumor Infiltrating Immune Cells in Oral Squamous Cell Carcinoma-Hope or Hype?
Head Neck
January 2025
Department of Pathology, All India Institute of Medical Sciences, Rishikesh, India.
Background: To correlate between immunohistochemical expression of tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and natural killer (NK) cells with the AJCC 8th edition TNM staging system and other disease-modifying clinico-pathological variables.
Methods: The representative histology sections of tumor invasive margin (IM) and tumor core (TC) were selected according to the International Immuno-Oncology Biomarker Working Group and were subjected to immunohistochemistry with antibodies for TILs (CD3, CD8, FOXP3), NK Cells (CD57), TAMs (CD68, CD163) and pan-leukocyte marker (CD45). Histo-immuno-density-intensity (HIDI) scoring was calculated as a product of the proportion and intensity of staining.
Elevated LIF and JAK-STAT activation drive severe COVID-19 in myeloma patients receiving the BCMA-CD3 bispecific antibody Elranatamab.
J Transl Med
January 2025
Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Beijing, 100730, China.
Background: Immunotherapy is a significant risk factor for severe COVID-19 in multiple myeloma (MM) patients. Understanding how immunotherapies lead to severe COVID-19 is crucial for improving patient outcomes.
Methods: Human protein microarrays were used to examine the expression of 440 protein molecules in MM patients treated with bispecific T-cell engagers (BiTe) (n = 9), anti-CD38 monoclonal antibodies (mAbs) (n = 10), and proteasome inhibitor (PI)-based regimens (n = 10).
Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics.
Nat Commun
January 2025
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs). Here, we present Celina, a statistical method for systematically detecting cell type-specific SVGs (ct-SVGs)-a subset of SVGs exhibiting distinct spatial expression patterns within specific cell types. Celina utilizes a spatially varying coefficient model to accurately capture each gene's spatial expression pattern in relation to the distribution of cell types across tissue locations, ensuring effective type I error control and high power.
View Article and Find Full Text PDFIntegrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning.
Sci Rep
January 2025
Departments of Breast Surgery, First Affiliated Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, People's Republic of China.
The impact of mitochondrial and lysosomal co-dysfunction on breast cancer patient outcomes is unclear. The objective of this study is to develop a predictive machine learning (ML) model utilizing mitochondrial and lysosomal co-regulators in order to provide a foundation for future studies focused on breast cancer (BC) patients' stratification and personalized interventions. Firstly, Differences and correlations of mitochondrial and lysosome related genes were screened and validated by differential analysis, copy number variation (CNV), single nucleotide polymorphism (SNPs) and correlation analysis.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!