Local Interleukin-2 Immunotherapy of Breast Cancer: Benefit and Risk in a Spontaneous Mouse Model

Nanotechnology Applications in Breast Cancer Immunotherapy

Next-generation cancer treatments are expected not only to target cancer cells but also to simultaneously train immune cells to combat cancer while modulating the immune-suppressive environment of tumors and hosts to ensure a robust and lasting response. Achieving this requires carriers that can codeliver multiple therapeutics to the right cancer and/or immune cells while ensuring patient safety. Nanotechnology holds great potential for addressing these challenges. This article highlights the recent advances in nanoimmunotherapeutic development, with a focus on breast cancer. While immune checkpoint inhibitors (ICIs) have achieved remarkable success and lead to cures in some cancers, their response rate in breast cancer is low. The poor response rate in solid tumors is often associated with the low infiltration of anti-cancer T cells and an immunosuppressive tumor microenvironment (TME). To enhance anti-cancer T-cell responses, nanoparticles are employed to deliver ICIs, bispecific antibodies, cytokines, and agents that induce immunogenic cancer cell death (ICD). Additionally, nanoparticles are used to manipulate various components of the TME, such as immunosuppressive myeloid cells, macrophages, dendritic cells, and fibroblasts to improve T-cell activities. Finally, this article discusses the outlook, challenges, and future directions of nanoimmunotherapeutics.

Soluble interleukin-2 receptor as a predictive and prognostic marker for patients with familial breast cancer

The incidence of breast cancer increases annually, and it has become common within families of breast cancer patients. Interleukin-2 activates cytotoxic T lymphocytes, which are important for cancer immunity. To identify markers of increased familial breast cancer risk, soluble interleukin-2 receptor levels and immunologic factors were investigated in familial breast cancer and non-familial breast cancer patients. Of 106 untreated breast cancer patients in this study, 24 had familial breast cancer and 82 had non-familial breast cancer. The patients' soluble interleukin-2 receptor, interleukin-10, vascular endothelial growth factor, interleukin-17, regulatory T cell, myeloid-derived suppressor cell, white blood cell, and C-reactive protein levels, and their neutrophil-to-lymphocyte ratios were measured, and their prognoses were compared according to the soluble interleukin-2 receptor levels. Additionally, postoperative tissues from the patients with high soluble interleukin-2 receptor levels were stained with programmed cell death ligand 1 and cluster of differentiation 8. The soluble interleukin-2 receptor level in the familial breast cancer patients was significantly higher, and it showed significantly stronger correlations with the neutrophil-to-lymphocyte ratio and the interleukin-10, vascular endothelial growth factor, interleukin-17, regulatory T cell, myeloid-derived suppressor cell, white blood cell, and C-reactive protein levels, than in the non-familial breast cancer patients. The regulatory T cell and myeloid-derived suppressor cell levels were significantly higher in the patients with high soluble interleukin-2 receptor levels, and the overall survival and disease-free-survival rates were significantly worse for the familial breast cancer patients than for the non-familial breast cancer patients. Triple-negative breast cancer tissues from the familial breast cancer patients with high soluble interleukin-2 receptor levels stained well for programmed cell death ligand 1 and cluster of differentiation 8. Soluble interleukin-2 receptor levels can be used to predict the prognosis of familial breast cancer patients. Prospectively identifying patients who are less likely to have non-familial breast cancer is vital for improving their overall survival.

Imbalances in cellular immunological parameters in blood predetermine tumor onset in a natural mouse model of breast cancer

The development of new approaches to breast cancer (BC) early diagnosis is an important objective of modern oncology. Although the role of the immune system in cancer initiation process was experimentally well established, the prognostic value of cellular blood immunological parameters (CBIPs) for BC onset prediction was not demonstrated either in clinics or in mouse models. In this study, we focused on revealing informative CBIPs for mammary cancer (MC) onset prediction in the BLRB/BYRB mouse model with a high incidence of natural MC development. Blood samples were collected from 80 aging females of these original mouse strains, 12 basic CBIPs were estimated by flow cytometry. Then mice were followed up for 28 weeks, and the outcome of females (MC diagnosis, death without MC or MC-free survival) was registered. We estimated the patterns of changes in CBIPs with age and in accordance with the outcome. An increasing imbalance in 11 CBIPs during natural aging of females clearly resembled human immunosenescence phenomenon and several patterns corresponded to the results obtained on cancer-free members of BC-affected families. We stratified heterogeneous female population into middle-aged and old subgroups. Low NK-cell levels in middle-aged mice and low B-cell along with high T-helper levels in old mice distinguished females with developed MC from the other groups. We found a reliable correlation of several CBIPs with age at MC diagnosis and survival of cancer-bearing females. Thus, we demonstrated the predictive potential of CBIPs as a basis for the development of prognostic models for BC onset in clinics.