1
|
Charan M, Jones TH, Ahirwar DK, Acharya N, Subramaniam VV, Ganju RK, Song JW. Induced electric fields inhibit breast cancer growth and metastasis by modulating the immune tumor microenvironment. bioRxiv 2024:2024.04.14.589256. [PMID: 38659909 PMCID: PMC11042207 DOI: 10.1101/2024.04.14.589256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Despite tremendous advances in oncology, metastatic triple-negative breast cancer remains difficult to treat and manage with established therapies. Here, we show in mice with orthotopic triple-negative breast tumors that alternating (100 kHz), and low intensity (<1 mV/cm) induced electric fields (iEFs) significantly reduced primary tumor growth and distant lung metastases. Non-contact iEF treatment can be delivered safely and non-invasively in vivo via a hollow, rectangular solenoid coil. We discovered that iEF treatment enhances anti-tumor immune responses at both the primary breast and secondary lung sites. In addition, iEF reduces immunosuppressive TME by reducing effector CD8+ T cell exhaustion and the infiltration of immunosuppressive immune cells. Furthermore, iEF treatment reduced lung metastasis by increasing CD8+ T cells and reducing immunosuppressive Gr1+ neutrophils in the lung microenvironment. We also observed that iEFs reduced the metastatic potential of cancer cells by inhibiting epithelial-to-mesenchymal transition. By introducing a non-invasive and non-toxic electrotherapeutic for inhibiting metastatic outgrowth and enhancing anti-tumor immune response in vivo, treatment with iEF technology could add to a paradigm-shifting strategy for cancer therapy.
Collapse
|
2
|
Peng JM, Su YL. Lymph node metastasis and tumor-educated immune tolerance: Potential therapeutic targets against distant metastasis. Biochem Pharmacol 2023; 215:115731. [PMID: 37541450 DOI: 10.1016/j.bcp.2023.115731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/30/2023] [Accepted: 08/01/2023] [Indexed: 08/06/2023]
Abstract
Lymph node metastasis has been shown to positively associated with the prognosis of many cancers. However, in clinical treatment, lymphadenectomy is not always successful, suggesting that immune cells in the tumor and sentinel lymph nodes still play a pivotal role in tumor immunosuppression. Recent studies had shown that tumors can tolerate immune cells through multiple strategies, including tumor-induced macrophage reprogramming, T cells inactivation, production of B cells pathogenic antibodies and activation of regulatory T cells to promote tumor colonization, growth, and metastasis in lymph nodes. We reviewed the bidirectional effect of immune cells on anti-tumor or promotion of cancer cell metastasis during lymph node metastasis, and the mechanisms by which malignant cancer cells modify immune cells to create a more favorable environment for the growth and survival of cancer cells. Research and treatment strategies focusing on the immune system in lymph nodes and potential immune targets in lymph node metastasis were also be discussed.
Collapse
Affiliation(s)
- Jei-Ming Peng
- Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, No. 123, Dapi Rd., Niaosong Dist., Kaohsiung, 83301, Taiwan.
| | - Yu-Li Su
- Division of Hematology Oncology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University, College of Medicine, No. 123, Dapi Rd., Niaosong Dist., Kaohsiung, 83301, Taiwan.
| |
Collapse
|
3
|
Li M, Quintana A, Alberts E, Hung MS, Boulat V, Ripoll MM, Grigoriadis A. B Cells in Breast Cancer Pathology. Cancers (Basel) 2023; 15:1517. [PMID: 36900307 PMCID: PMC10000926 DOI: 10.3390/cancers15051517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/13/2023] [Accepted: 02/20/2023] [Indexed: 03/06/2023] Open
Abstract
B cells have recently become a focus in breast cancer pathology due to their influence on tumour regression, prognosis, and response to treatment, besides their contribution to antigen presentation, immunoglobulin production, and regulation of adaptive responses. As our understanding of diverse B cell subsets in eliciting both pro- and anti-inflammatory responses in breast cancer patients increases, it has become pertinent to address the molecular and clinical relevance of these immune cell populations within the tumour microenvironment (TME). At the primary tumour site, B cells are either found spatially dispersed or aggregated in so-called tertiary lymphoid structures (TLS). In axillary lymph nodes (LNs), B cell populations, amongst a plethora of activities, undergo germinal centre reactions to ensure humoral immunity. With the recent approval for the addition of immunotherapeutic drugs as a treatment option in the early and metastatic settings for triple-negative breast cancer (TNBC) patients, B cell populations or TLS may resemble valuable biomarkers for immunotherapy responses in certain breast cancer subgroups. New technologies such as spatially defined sequencing techniques, multiplex imaging, and digital technologies have further deciphered the diversity of B cells and the morphological structures in which they appear in the tumour and LNs. Thus, in this review, we comprehensively summarise the current knowledge of B cells in breast cancer. In addition, we provide a user-friendly single-cell RNA-sequencing platform, called "B singLe cEll rna-Seq browSer" (BLESS) platform, with a focus on the B cells in breast cancer patients to interrogate the latest publicly available single-cell RNA-sequencing data collected from diverse breast cancer studies. Finally, we explore their clinical relevance as biomarkers or molecular targets for future interventions.
Collapse
Affiliation(s)
- Mengyuan Li
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
| | | | - Elena Alberts
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- Immunity and Cancer Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Miu Shing Hung
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
| | - Victoire Boulat
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- Immunity and Cancer Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Mercè Martí Ripoll
- Immunology Unit, Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
- Biosensing and Bioanalysis Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Anita Grigoriadis
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
- Breast Cancer Now Unit, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK
| |
Collapse
|
4
|
Zhang Y, Shi W, Sun Y. A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology. BMC Genomics 2023; 24:76. [PMID: 36797662 PMCID: PMC9936134 DOI: 10.1186/s12864-023-09157-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/31/2023] [Indexed: 02/18/2023] Open
Abstract
Since genes do not function individually, the gene module is considered an important tool for interpreting gene expression profiles. In order to consider both functional similarity and expression similarity in module identification, GMIGAGO, a functional Gene Module Identification algorithm based on Genetic Algorithm and Gene Ontology, was proposed in this work. GMIGAGO is an overlapping gene module identification algorithm, which mainly includes two stages: In the first stage (initial identification of gene modules), Improved Partitioning Around Medoids Based on Genetic Algorithm (PAM-GA) is used for the initial clustering on gene expression profiling, and traditional gene co-expression modules can be obtained. Only similarity of expression levels is considered at this stage. In the second stage (optimization of functional similarity within gene modules), Genetic Algorithm for Functional Similarity Optimization (FSO-GA) is used to optimize gene modules based on gene ontology, and functional similarity within gene modules can be improved. Without loss of generality, we compared GMIGAGO with state-of-the-art gene module identification methods on six gene expression datasets, and GMIGAGO identified the gene modules with the highest functional similarity (much higher than state-of-the-art algorithms). GMIGAGO was applied in BRCA, THCA, HNSC, COVID-19, Stem, and Radiation datasets, and it identified some interesting modules which performed important biological functions. The hub genes in these modules could be used as potential targets for diseases or radiation protection. In summary, GMIGAGO has excellent performance in mining molecular mechanisms, and it can also identify potential biomarkers for individual precision therapy.
Collapse
Affiliation(s)
- Yan Zhang
- grid.440686.80000 0001 0543 8253College of Environmental Science and Engineering, Dalian Maritime University, 116026 Dalian, Liaoning China
| | - Weiyu Shi
- grid.440686.80000 0001 0543 8253College of Maritime Economics & Management, Dalian Maritime University, 116026 Dalian, Liaoning China
| | - Yeqing Sun
- College of Environmental Science and Engineering, Dalian Maritime University, 116026, Dalian, Liaoning, China.
| |
Collapse
|
5
|
Balouchi-Anaraki S, Mohammadsadeghi S, Norouzian M, Rasolmali R, Talei AR, Mehdipour F, Ghaderi A. Expression of Interleukin-21 and Interleukin-21 receptor in lymphocytes derived from tumor-draining lymph nodes of breast cancer. Breast Dis 2022; 41:373-382. [PMID: 36189580 DOI: 10.3233/bd-220013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Interleukin-21 (IL-21) is produced by various cell types inducing positive and negative effects in immunity against tumors. OBJECTIVE To investigate the expression of IL-21 by CD4+T and IL-21 receptor (IL-21R) by B lymphocytes isolated from breast-tumor draining lymph nodes (TDLNs). METHODS Fresh lymph node samples were obtained from 45 patients with breast cancer. To assess IL-21 expression, mononuclear cells were briefly stimulated whereas IL-21R expression was assessed in unstimulated B cells. Cells were stained with antibodies for CD4, IL-21, CD19 and IL-21R and acquired by flow cytometry. RESULTS The frequency of IL-21+CD4+T cells did not show significant association with disease parameters. However, the geometric mean fluorescence intensity (gMFI) of IL-21 in CD4+T cells was significantly lower in patients with grade III tumor than grade I + II (P = 0.042). In non-involved LNs, the intensity of IL-21 was significantly higher in patients with stage II compared with stage III (P = 0.038) and correlated negatively with the number of involved LNs. The frequency of IL-21R+CD19+B cells was significantly higher in grade III than grade I + II (P = 0.037). CONCLUSION The higher intensity of IL-21 in CD4+T cells showed association with good prognosticators in breast cancer and warrants further investigation of the role played by IL-21 in immunity against breast cancer.
Collapse
Affiliation(s)
- Sima Balouchi-Anaraki
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sara Mohammadsadeghi
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Marzieh Norouzian
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.,Department of Laboratory Sciences, School of Allied Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Reza Rasolmali
- Department of Pathology, Shiraz Central Hospital, Shiraz, Iran
| | - Abdol-Rasoul Talei
- Breast Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Fereshteh Mehdipour
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Abbas Ghaderi
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.,Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| |
Collapse
|
6
|
Goode EF, Roussos Torres ET, Irshad S. Lymph Node Immune Profiles as Predictive Biomarkers for Immune Checkpoint Inhibitor Response. Front Mol Biosci 2021; 8:674558. [PMID: 34141724 PMCID: PMC8205515 DOI: 10.3389/fmolb.2021.674558] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/22/2021] [Indexed: 01/22/2023] Open
Abstract
The need for predictive biomarkers that can accurately predict patients who will respond to immune checkpoint inhibitor (ICI) immunotherapies remains a clinically unmet need. The majority of research efforts have focused on expression of immune-related markers on the tumour and its associated tumour microenvironment (TME). However, immune response to tumour neoantigens starts at the regional lymph nodes, where antigen presentation takes place and is regulated by multiple cell types and mechanisms. Knowledge of the immunological responses in bystander lymphoid organs following ICI therapies and their association with changes in the TME, could prove to be a valuable component in understanding the treatment response to these agents. Here, we review the emerging data on assessment of immunological responses within regional lymph nodes as predictive biomarkers for immunotherapies.
Collapse
Affiliation(s)
- Emily F. Goode
- Institute of Cancer Research, London, United Kingdom
- Cancer Research UK (CRUK) Clinical Fellow, London, United Kingdom
| | - Evanthia T. Roussos Torres
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sheeba Irshad
- School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom
- Cancer Research UK (CRUK) Clinician Scientist, London, United Kingdom
| |
Collapse
|