CD133 mRNA-transfected dendritic cells induce coordinated cytotoxic and helper T cell responses against breast cancer stem cells

Modulation of the tumor microenvironment and mechanism of immunotherapy-based drug resistance in breast cancer

Breast cancer, the most frequent female malignancy, is often curable when detected at an early stage. The treatment of metastatic breast cancer is more challenging and may be unresponsive to conventional therapy. Immunotherapy is crucial for treating metastatic breast cancer, but its resistance is a major limitation. The tumor microenvironment (TME) is vital in modulating the immunotherapy response. Various tumor microenvironmental components, such as cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs), are involved in TME modulation to cause immunotherapy resistance. This review highlights the role of stromal cells in modulating the breast tumor microenvironment, including the involvement of CAF-TAM interaction, alteration of tumor metabolism leading to immunotherapy failure, and other latest strategies, including high throughput genomic screening, single-cell and spatial omics techniques for identifying tumor immune genes regulating immunotherapy response. This review emphasizes the therapeutic approach to overcome breast cancer immune resistance through CAF reprogramming, modulation of TAM polarization, tumor metabolism, and genomic alterations.

Functional Roles of CD133: More than Stemness Associated Factor Regulated by the Microenvironment

CD133 protein has been one of the most used surface markers to select and identify cancer cells with stem-like features. However, its expression is not restricted to tumoral cells; it is also expressed in differentiated cells and stem/progenitor cells in various normal tissues. CD133 participates in several cellular processes, in part orchestrating signal transduction of essential pathways that frequently are dysregulated in cancer, such as PI3K/Akt signaling and the Wnt/β-catenin pathway. CD133 expression correlates with enhanced cell self-renewal, migration, invasion, and survival under stress conditions in cancer. Aside from the intrinsic cell mechanisms that regulate CD133 expression in each cellular type, extrinsic factors from the surrounding niche can also impact CD33 levels. The enhanced CD133 expression in cells can confer adaptive advantages by amplifying the activation of a specific signaling pathway in a context-dependent manner. In this review, we do not only describe the CD133 physiological functions known so far, but importantly, we analyze how the microenvironment changes impact the regulation of CD133 functions emphasizing its value as a marker of cell adaptability beyond a cancer-stem cell marker.

Interaction of phenotypic sublines isolated from triple-negative breast cancer cell line MDA-MB-231 modulates their sensitivity to paclitaxel and doxorubicin in 2D and 3D assays

Breast cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. These result in molecular and phenotypic heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells. We aimed to analyze cell phenotypic sublines and the influence of their interaction on drug resistance, spheroid formation, and migration. Seven sublines were derived from the MDA-MB-231 breast cancer cell line using a multiple-cell suspension dilution. The growth rate, CD133 receptor expression, migration ability, and chemosensitivity of these sublines to anticancer drugs doxorubicin (DOX) and paclitaxel (PTX) were determined. Three sublines (F5, D8, H2) have been chosen to study their interaction in 2D and 3D assays. In the 2D model, the resistance of all sublines composition to DOX decreased, but in the 3D model, the resistance of all sublines except H2, increased to both PTX and DOX. In the 3D model, the combined sublines F5 and D8 had higher resistance to DOX and statistically significantly lower resistance for PTX compared to the control. The interaction between cancer stem-like cells (F5) and increased migration cells (D8) increased resistance to PTX in cell monolayer and increased resistance against both DOX and PTX in the spheroids. The interaction of DOX-resistant (H2) cells with other cell subpopulations (D8, F5, HF) decreased the resistance to DOX in cell monolayer and both DOX and PTX in spheroids.

Dendritic cell vaccines in breast cancer: Immune modulation and immunotherapy

Breast cancer (BC) is the most common cancer in women worldwide. Although substantial progress has been made in the diagnosis and treatment of breast cancer, the efficacy and side effects of traditional treatment methods are still unsatisfactory. In recent years, immunotherapy including tumor vaccine has achieved great success in the treatment of BC. Dendritic cells (DCs) are multifunctional antigen-presenting cells that play an important role in the initiation and regulation of innate and adaptive immune responses. Numerous studies have shown that DC-based treatments might have a potential effect on BC. Among them, the clinical study of DC vaccine in BC has demonstrated considerable anti-tumor effect, and some DC vaccines have entered the stage of clinical trials. In this review, we summarize the immunomodulatory effects and related mechanisms of DC vaccine in breast cancer as well as the progress of clinical trials to propose possible challenges of DC vaccines and new development directions.

The modulatory role of dendritic cell-T cell cross-talk in breast cancer: Challenges and prospects

Antigen recognition and presentation are highlighted as the first steps in developing specialized antigen responses. Dendritic cells (DCs) are outstanding professional antigen-presenting cells (APCs) responsible for priming cellular immunity in pathological states, including cancer. However, the diminished or repressed function of DCs is thought to be a substantial mechanism through which tumors escape from the immune system. In this regard, DCs obtained from breast cancer (BC) patients represent a notably weakened potency to encourage specific T-cell responses. Additionally, impaired DC-T-cell cross-talk in BC facilitates the immune evade of cancer cells and is connected with tumor advancement, immune tolerance, and adverse prognosis for patients. In this review we aim to highlight the available knowledge on DC-T-cell interactions in BC aggressiveness and show its therapeutic potential in BC treatment.

High tumor mutational burden (TMB) identifies a microsatellite stable pancreatic cancer subset with prolonged survival and strong anti-tumor immunity

AIM

Tumor mutational burden (TMB: somatic mutations per megabase, mut/Mb) predicts the efficacy of immunotherapy. Here, we link TMB levels with the activation of immune pathways and intratumoral immune responses in pancreatic adenocarcinoma (PDAC) to explore immunoarchitectural patterns associated with high TMB.

METHODS

We assessed TMB in 161 resected, microsatellite stable (MSS) PDACs, including 41 long-term survivors (LTS). Five microsatellite instable (MSI-high) cases were also assessed. Cases were classified into TMB-high (≥10 mut/Mb), TMB-intermediate (>5 < 10 mut/Mb), and TMB-low (≤5 mut/Mb) categories. Tumors additionally underwent mRNA in situ hybridization for immune pathway genes and were immunoprofiled by multiplex immunofluorescence followed by automated image analysis.

RESULTS

We detected 12 TMB-high, 28 TMB-intermediate, and 121 TMB-low cases. TMB-high tumors comprised ten LTSs (10/41; 24%) and two conventional PDACs (2/120; 1.7%). They exhibited the highest T cell density with significantly increased CD3+CD4+T helper and CD208+dendritic cell (DC) counts, compared to all other cases. CD3+CD8+cytotoxic T cells were significantly closer to tumor cells and T helper cells closer to DCs in TMB-high PDACs. Immune pathways involved in T cell activation, immune cell adhesion/migration, antigen presentation, and cytokine signaling were upregulated in most TMB-high and many TMB-intermediate tumors. ARID1A and ERBB4 alterations were more frequent in TMB-high PDACs. All MSI-high PDACs were TMB-high.

CONCLUSIONS

TMB-high cases frequently belong to specific PDAC subsets with prolonged survival such as LTSs and MSI-high PDACs. They display strong anti-tumor immune responses fueled by a T helper cell/DC-mediated priming of the cytotoxic T cells. Moreover, they frequently harbor further actionable alterations.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

One of the outstanding challenges of the mathematical modeling of cancer progression is the existence of many unknown parameters. In this work, we develop a data-driven mathematical model of breast cancer progression by deriving a system of ordinary differential equations for the interaction networks of key cell types and molecules in breast tumors. To overcome the limitations of unknown parameters, we utilize a time course data of a PyMT mice model of breast cancer and estimate parameters using an optimization method. Although the predicted dynamics of cancer and necrotic cells using the obtained values of parameters are in good agreement with the data, the predicted values for a few other variables do not match the data. This might indicate that there are some other key interactions that have not been modeled, and/or there is a noise in the data. The sensitivity and bifurcation analyses show that the most important parameters in controlling the cancer cells population are the proliferation and death rates of cancer cells and adipocytes. These results are in agreement with some biological and clinical studies of breast cancer, which have reported a link between adipocytes and breast cancer progression.