The balance of regulatory and stimulatory B cell subsets in breast cancer draining lymph nodes correlates with tumor prognostic factors

Induced electric fields inhibit breast cancer growth and metastasis by modulating the immune tumor microenvironment

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.

Lymph node metastasis and tumor-educated immune tolerance: Potential therapeutic targets against distant metastasis

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.

B Cells in Breast Cancer Pathology

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.

A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology

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.

Expression of Interleukin-21 and Interleukin-21 receptor in lymphocytes derived from tumor-draining lymph nodes of breast cancer

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.

Lymph Node Immune Profiles as Predictive Biomarkers for Immune Checkpoint Inhibitor Response

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.