Background: Metastasis causes the most breast cancer-related deaths in women. Here, we investigated the antitumor effect of solid lipid nanoparticles (SLN-DTX) when used in the treatment of metastatic breast tumors using 4T1-bearing BALB/c mice. Results: Solid lipid nanoparticles (SLNs) were produced using the high-energy method. Compritol 888 ATO was selected as the lipid matrix, and Pluronic F127 and Span 80 as the surfactants to stabilize nanoparticle dispersion. The particles had high stability for at least 120 days. The SLNs’ dispersion size was 128 nm, their polydispersity index (PDI) was 0.2, and they showed a negative zeta potential. SLNs had high docetaxel (DTX) entrapment efficiency (86%), 2% of drug loading and showed a controlled drug-release profile. The half-maximal inhibitory concentration (IC₅₀) of SLN-DTX against 4T1 cells was more than 100 times lower than that of free DTX after 24 h treatment. In the cellular uptake test, SLN-DTX was taken into the cells significantly more than free DTX. The accumulation in the G2-M phase was significantly higher in cells treated with SLN-DTX (73.7%) than in cells treated with free DTX (23.0%), which induced subsequent apoptosis. TEM analysis revealed that SLN-DTX internalization is mediated by endocytosis, and fluorescence microscopy showed DTX induced microtubule damage. In vivo studies showed that SLN-DTX compared to free docetaxel exhibited higher antitumor efficacy by reducing tumor volume (p < 0.0001) and also prevented spontaneous lung metastasis in 4T1 tumor-bearing mice. Histological studies of lungs confirmed that treatment with SLN-DTX was able to prevent tumor. IL-6 serum levels, ki-67 and BCL-2 expression were analyzed and showed a remarkably strong reduction when used in a combined treatment. Conclusions: These results indicate that DTX-loaded SLNs may be a promising carrier to treat breast cancer and in metastasis prevention.

Photodynamic therapy (PDT) has been clinically employed to treat mainly superficial cancer, such as basal cell carcinoma. This approach can eliminate tumors by direct cytotoxicity, tumor ischemia, or by triggering an immune response against tumor cells. Among the immune-related mechanisms of PDT, the induction of immunogenic cell death (ICD) in target cells is to be cited. ICD is an apoptosis modality distinguished by the emission of damage-associated molecular patterns (DAMP). Therefore, this study aimed to analyze the immunogenicity of CT26 and 4T1 treated with PDT mediated by aluminum-phthalocyanine in nanoemulsion (PDT-AlPc-NE). Different PDT-AlPc-NE protocols with varying doses of energy and AlPc concentrations were tested. The death mechanism and the emission of DAMPs–CRT, HSP70, HSP90, HMGB1, and IL-1β–were analyzed in cells treated in vitro with PDT. Then, the immunogenicity of these cells was assessed in an in vivo vaccination-challenge model with BALB/c mice. CT26 and 4T1 cells treated in vitro with PDT mediated by AlPc IC₅₀ and a light dose of 25 J/cm² exhibited the hallmarks of ICD, i.e., these cells died by apoptosis and exposed DAMPs. Mice injected with these IC₅₀ PDT-treated cells showed, in comparison to the control, increased resistance to the development of tumors in a subsequent challenge with viable cells. Mice injected with 4T1 and CT26 cells treated with higher or lower concentrations of photosensitizer and light doses exhibited a significantly lower resistance to tumor development than those injected with IC₅₀ PDT-treated cells. The results presented in this study suggest that both the photosensitizer concentration and light dose affect the immunogenicity of the PDT-treated cells. This event can affect the therapy outcomes in vivo.

Immunotherapy for cancer treatment has gained increased attention in recent years. Recently, our group reported the case of a patient with glioblastoma who underwent vaccination based on dendritic cells and experienced a strong Th1 immune response together with near-complete tumor remission. Here we report the results of a phase I/II prospective, non-controlled clinical trial with 37 patients harboring glioblastoma or grade 4 astrocytomas. At the time of first recurrence after surgery, patients began receiving monthly intradermal injections of allogenic DC-autologous tumor cell hybridomas. Overall survival, quality of life, and immunological profiles were assessed prospectively. Compared with patients in the Genomic Data Commons data bank, overall survival for vaccinated patients with glioblastoma was 27.6 ± 2.4 months (vs. 16.3 ± 0.7, log-rank p < 0.001, hazard ratio 0.53, 95%CI 0.36–0.78, p < 0.01), and it was 59.5 ± 15.9 for vaccinated astrocytoma grade 4 patients (vs. 19.8 ± 2.5, log-rank p < 0.05, hazard ratio 0.18, 95%CI 0.05–0.62, p < 0.01). Furthermore, seven vaccinated patients (two IDH-1-mutated and five wild type) remain alive at the time of this report (overall survival 47.9 months, SD 21.1, range: 25.4–78.6 months since diagnosis; and 34.2 months since recurrence, range: 17.8 to 40.7, SD 21.3). We believe that the data reported here can foster the improvement of treatment protocols for high-grade gliomas based on cellular immunotherapy.

Immunotherapy has brought hope to the fight against glioblastoma, but its efficacy remains unclear. We present the case of CST, a 25-year-old female patient with a large right-hemisphere glioblastoma treated with a dendritic–tumor cell fusion vaccine. CST showed a near-complete tumor response, with a marked improvement in her functional status and simultaneous increases in tumor-specific CD8+ and CD4+ T cells. Two months before recurrence, the frequency of tumor-specific T cells decreased, while that of IL-17 and CD4+ T cells increased. CST passed away 15 months after enrollment. In this illustrative case, the tumor-specific CD4+ T-cell numbers and phenotype behaved as treatment efficacy biomarkers, highlighting the key role of the latter in glioblastoma immunotherapy.

Nanoparticle delivery to tumor tissue is one of the most important applications of nanomedicine. However, the literature shows that this pharmacological event is highly-affected by several tumor biology characteristics, including tumor size and maturation. Thus, the objective of the present study is to report on the investigation of the biodistribution of a lipid nanoemulsion (NE) in a breast cancer tumor model using in vivo imaging techniques. As highlights of this study, we can indicate that the biodistribution was measured in different tumor sites (primary and metastatic tumors) and in the same experimental mice for four subsequent weeks. With this approach it is possible to observe that the NE tumor delivery is significantly altered during tumor growth and metastasis progression. Furthermore, in the present report we introduce a phenomenological mathematical model that successfully explains the delivery behavior of a hydrophobic infrared fluorescent NE marker to both primary tumor and metastatic lesions. We believe that these data, in addition to the phenomenological mathematical model, are relevant to understanding how the stage of tumor development can alter macromolecule and/or nanoparticle delivery to tumor tissues, thus improving the efficacy of the passive delivery features promoted by tumor biology.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients’ overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.