Iron-Doping of Copper Oxide Nanoparticles Lowers Their Toxic Potential on C6 Glioma Cells

CD81-guided heterologous EVs present heterogeneous interactions with breast cancer cells

BACKGROUND

Extracellular vesicles (EVs) are cell-secreted particles conceived as natural vehicles for intercellular communication. The capacity to entrap heterogeneous molecular cargoes and target specific cell populations through EV functionalization promises advancements in biomedical applications. However, the efficiency of the obtained EVs, the contribution of cell-exposed receptors to EV interactions, and the predictability of functional cargo release with potential sharing of high molecular weight recombinant mRNAs are crucial for advancing heterologous EVs in targeted therapy applications.

METHODS

In this work, we selected the popular EV marker CD81 as a transmembrane guide for fusion proteins with a C-terminal GFP reporter encompassing or not Trastuzumab light chains targeting the HER2 receptor. We performed high-content imaging analyses to track EV-cell interactions, including isogenic breast cancer cells with manipulated HER2 expression. We validated the functional cargo delivery of recombinant EVs carrying doxorubicin upon EV-donor cell treatment. Then, we performed an in vivo study using JIMT-1 cells commonly used as HER2-refractory, trastuzumab-resistant model to detect a more than 2000 nt length recombinant mRNA in engrafted tumors.

RESULTS

Fusion proteins participated in vesicular trafficking dynamics and accumulated on secreted EVs according to their expression levels in HEK293T cells. Despite the presence of GFP, secreted EV populations retained a HER2 receptor-binding capacity and were used to track EV-cell interactions. In time-frames where the global EV distribution did not change between HER2-positive (SK-BR-3) or -negative (MDA-MB-231) breast cancer cell lines, the HER2 exposure in isogenic cells remarkably affected the tropism of heterologous EVs, demonstrating the specificity of antiHER2 EVs representing about 20% of secreted bulk vesicles. The specific interaction strongly correlated with improved cell-killing activity of doxorubicin-EVs in MDA-MB-231 ectopically expressing HER2 and reduced toxicity in SK-BR-3 with a knocked-out HER2 receptor, overcoming the effects of the free drug. Interestingly, the fusion protein-corresponding transcripts present as full-length mRNAs in recombinant EVs could reach orthotopic breast tumors in JIMT-1-xenografted mice, improving our sensitivity in detecting penetrant cargoes in tissue biopsies.

CONCLUSIONS

This study highlights the quantitative aspects underlying the creation of a platform for secreted heterologous EVs and shows the limits of single receptor-ligand interactions behind EV-cell engagement mechanisms, which now become the pivotal step to predict functional tropism and design new generations of EV-based nanovehicles.

Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study

The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the custom-designed 1-10% Fe-doped CuO NM library. Effects were assessed using the soil ecotoxicology model Enchytraeus crypticus (Oligochaeta) in the standard 21 days plus its extension (49 days). Results showed that 10%Fe-CuO was the most toxic (21 days reproduction EC50 = 650 mg NM/kg soil) and Fe3O4 NM was the least toxic (no effects up to 3200 mg NM/kg soil). All other NMs caused similar effects to E. crypticus (21 days reproduction EC50 ranging from 875 to 1923 mg NM/kg soil, with overlapping confidence intervals). Aiming to identify the key NM characteristics responsible for the toxicity, machine learning (ML) modeling was used to analyze the large data set [9 NMs, 68 descriptors, 6 concentrations, 2 exposure times (21 and 49 days), 2 endpoints (survival and reproduction)]. ML allowed us to separate experimental related parameters (e.g., zeta potential) from particle-specific descriptors (e.g., force vectors) for the best identification of important descriptors. We observed that concentration-dependent descriptors (environmental parameters, e.g., zeta potential) were the most important under standard test duration (21 day) but not for longer exposure (closer representation of real-world conditions). In the longer exposure (49 days), the particle-specific descriptors were more important than the concentration-dependent parameters. The longer-term exposure showed that the steepness of the concentration-response decreased with an increased Fe content in the NMs. Longer-term exposure should be a requirement in the hazard assessment of NMs in addition to the standard in OECD guidelines for chemicals. The progress toward ML analysis is desirable given its need for such large data sets and significant power to link NM descriptors to effects in animals. This is beyond the current univariate and concentration-response modeling analysis.

Evolving approaches in glioma treatment: harnessing the potential of copper metabolism modulation

The key properties and high versatility of metal nanoparticles have shed new perspectives on cancer therapy, with copper nanoparticles gaining great interest because of the ability to couple the intrinsic properties of metal nanoparticles with the biological activities of copper ions in cancer cells. Copper, indeed, is a cofactor involved in different metabolic pathways of many physiological and pathological processes. Literature data report on the use of copper in preclinical protocols for cancer treatment based on chemo-, photothermal-, or copper chelating-therapies. Copper nanoparticles exhibit anticancer activity via multiple routes, mainly involving the targeting of mitochondria, the modulation of oxidative stress, the induction of apoptosis and autophagy, and the modulation of immune response. Moreover, compared to other metal nanoparticles (e.g. gold, silver, palladium, and platinum), copper nanoparticles are rapidly cleared from organs with low systemic toxicity and benefit from the copper's low cost and wide availability. Within this review, we aim to explore the impact of copper in cancer research, focusing on glioma, the most common primary brain tumour. Glioma accounts for about 80% of all malignant brain tumours and shows a poor prognosis with the five-year survival rate being less than 5%. After introducing the glioma pathogenesis and the limitation of current therapeutic strategies, we will discuss the potential impact of copper therapy and present the key results of the most relevant literature to establish a reliable foundation for future development of copper-based approaches.

Nano-CuO causes cell damage through activation of dose-dependent autophagy and mitochondrial lncCyt b-AS/ND5-AS/ND6-AS in SH-SY5Y cells

Metal copper oxide nanoparticles (nano-CuO) are under mass production and have been widely utilized in many fields including catalysis, gas sensors, semiconductor materials, etc. The broad applications of nano-CuO have increased the possibility of risk to incidental exposure to the environment, and therefore, an in-depth investigation of their effects on live cells is required. This study investigated the impact of the nano-CuO on SH-SY5Y cells, and findings showed that the ratio of LC3-II/LC3-I was significantly increased in SH-SY5Y cells when the cells were treated with nano-CuO. However, if the autophagy inhibitor Bafilomycin A1 (Baf A1) was co-treated, the ratio of LC3-II/LC3-I was further improved. These outcomes might indicate that autophagy flux was permanently elevated by adding nano-CuO. Further results found highly activated levels of long noncoding RNAs (lncRNAs) under nano-CuO treatment. The data illustrate a mechanism that nano-CuO can promote autophagy and activate lncCyt b-AS/ND5-AS/ND6-AS in SH-SY5Y cells and have critical implications for nanoparticle biomedical applications.

Role of inorganic nanoparticle degradation in cancer therapy

Nanomaterials are currently widely exploited for their potential in the development of novel cancer therapies, and so far, mainly nanoparticles (NPs) consisting of liposomes and polymers have made their way into the clinic. However, major bottlenecks for the clinical translation of other types of NPs (i.e. inorganic) are the lack of knowledge concerning their long-term distribution in vivo and their potential toxicity. To counter this, various research groups have worked on soluble NPs, such as zinc oxide (ZnO), copper oxide (CuO), and silver (Ag), which tend to dissolve spontaneously into their ionic form, releasing toxic metal ions and leading to reactive oxygen species (ROS) generation when exposed to cellular environments. By fine-tuning the dissolution kinetics of these NPs, it is possible to control the level of ROS production and thus cytotoxicity to selectively destroy tumor tissue. Specifically, cancer cells tend to exhibit a higher basal level of oxidative stress compared to normal cells due to their higher metabolic rates, and therefore, by engineering NPs that generate sufficient ROS that barely exceed toxic thresholds in cancer cells, normal cells will only experience reversible transient damage. This review focuses on the use of these soluble inorganic NPs for selective cancer therapy and on the various in vitro and in vivo studies that have aimed to control the dissolution kinetics of these NPs, either through particle doping or surface modifications.