Targeting triple-negative breast cancer cells with a ß1-integrin binding aptamer.

Targeted therapies have increased the treatment options for triple-negative breast cancer patients. However, the paucity of targetable biomarkers and tumor heterogeneity have limited the ability of precision-guided interventions to live up to their full potential. As affinity-targeting ligands, aptamers show high selectivity toward target molecules. Compared with antibodies, aptamers have lower molecular weight, increased stability during transportation, reduced immunogenicity, and increased tissue uptake. Recently, we reported discovery of the GreenB1 aptamer, which is internalized in cultured triple-negative MDA-MB-231 human breast cancer cells. We show that the GreenB1 aptamer specifically targets ß1-integrin, a protein linked previously to breast cancer cell invasiveness and migration. Aptamer binds to ß1-integrin with low nanomolar affinity. Our findings suggest potential applications for GreenB1-guided precision agents for diagnosis and therapy of cancers overexpressing ß1-integrin.

Integrative Gene Expression and Metabolic Analysis Tool IgemRNA.

Genome-scale metabolic modeling is widely used to study the impact of metabolism on the phenotype of different organisms. While substrate modeling reflects the potential distribution of carbon and other chemical elements within the model, the additional use of omics data, e.g., transcriptome, has implications when researching the genotype-phenotype responses to environmental changes. Several algorithms for transcriptome analysis using genome-scale metabolic modeling have been proposed. Still, they are restricted to specific objectives and conditions and lack flexibility, have software compatibility issues, and require advanced user skills. We classified previously published algorithms, summarized transcriptome pre-processing, integration, and analysis methods, and implemented them in the newly developed transcriptome analysis tool IgemRNA, which (1) has a user-friendly graphical interface, (2) tackles compatibility issues by combining previous data input and pre-processing algorithms in MATLAB, and (3) introduces novel algorithms for the automatic comparison of different transcriptome datasets with or without Cobra Toolbox 3.0 optimization algorithms. We used publicly available transcriptome datasets from Saccharomyces cerevisiae BY4741 and H4-S47D strains for validation. We found that IgemRNA provides a means for transcriptome and environmental data validation on biochemical network topology since the biomass function varies for different phenotypes. Our tool can detect problematic reaction constraints.

New Tools for Streamlined In Vivo Homing Peptide Identification.

In vivo peptide-phage display is an unbiased technique for mapping of the vascular diversity and identification of homing peptides. This chapter is intended to serve as a structured practical guide to execute in vivo T7 phage biopanning and data analysis experiments. We discuss experimental designs and protocols with emphasis on application of high-throughput sequencing-based technologies for streamlined in vivo biopanning and validation of homing peptides.

In vivo phage display: identification of organ-specific peptides using deep sequencing and differential profiling across tissues.

In vivo phage display is widely used for identification of organ- or disease-specific homing peptides. However, the current in vivo phage biopanning approaches fail to assess biodistribution of specific peptide phages across tissues during the screen, thus necessitating laborious and time-consuming post-screening validation studies on individual peptide phages. Here, we adopted bioinformatics tools used for RNA sequencing for analysis of high-throughput sequencing (HTS) data to estimate the representation of individual peptides during biopanning in vivo. The data from in vivo phage screen were analyzed using differential binding-relative representation of each peptide in the target organ versus in a panel of control organs. Application of this approach in a model study using low-diversity peptide T7 phage library with spiked-in brain homing phage demonstrated brain-specific differential binding of brain homing phage and resulted in identification of novel lung- and brain-specific homing peptides. Our study provides a broadly applicable approach to streamline in vivo peptide phage biopanning and to increase its reproducibility and success rate.

Purine Auxotrophic Starvation Evokes Phenotype Similar to Stationary Phase Cells in Budding Yeast.

Purine auxotrophy is an abundant trait among eukaryotic parasites and a typical marker for many budding yeast strains. Supplementation with an additional purine source (such as adenine) is necessary to cultivate these strains. If not supplied in adequate amounts, purine starvation sets in. We explored purine starvation effects in a model organism, a budding yeast Saccharomyces cerevisiae ade8 knockout, at the level of cellular morphology, central carbon metabolism, and global transcriptome. We observed that purine-starved cells stopped their cycle in G1/G0 state and accumulated trehalose, and the intracellular concentration of AXP decreased, but adenylate charge remained stable. Cells became tolerant to severe environmental stresses. Intracellular RNA concentration decreased, and massive downregulation of ribosomal biosynthesis genes occurred. We proved that the expression of new proteins during purine starvation is critical for cells to attain stress tolerance phenotype Msn2/4p targets are upregulated in purine-starved cells when compared to cells cultivated in purine-rich media. The overall transcriptomic response to purine starvation resembles that of stationary phase cells. Our results demonstrate that the induction of a strong stress resistance phenotype in budding yeast can be caused not only by natural starvation, but also starvation for metabolic intermediates, such as purines.

Differential binding cell-SELEX method to identify cell-specific aptamers using high-throughput sequencing.

Aptamers have in recent years emerged as a viable alternative to antibodies. High-throughput sequencing (HTS) has revolutionized aptamer research by increasing the number of reads from a few (using Sanger sequencing) to millions (using an HTS approach). Despite the availability and advantages of HTS compared to Sanger sequencing, there are only 50 aptamer HTS sequencing samples available on public databases. HTS data in aptamer research are primarily used to compare sequence enrichment between subsequent selection cycles. This approach does not take full advantage of HTS because the enrichment of sequences during selection can be due to inefficient negative selection when using live cells. Here, we present a differential binding cell-SELEX (systematic evolution of ligands by exponential enrichment) workflow that adapts the FASTAptamer toolbox and bioinformatics tool edgeR, which are primarily used for functional genomics, to achieve more informative metrics about the selection process. We propose a fast and practical high-throughput aptamer identification method to be used with the cell-SELEX technique to increase the aptamer selection rate against live cells. The feasibility of our approach is demonstrated by performing aptamer selection against a clear cell renal cell carcinoma (ccRCC) RCC-MF cell line using the RC-124 cell line from healthy kidney tissue for negative selection.

Effect of colorectal cancer-derived extracellular vesicles on the immunophenotype and cytokine secretion profile of monocytes and macrophages.

BACKGROUND: Macrophages are one of the most important players in the tumor microenvironment. The polarization status of tumor associated macrophages into a pro-inflammatory type M1 or anti-inflammatory type M2 may influence cancer progression and patient survival. Extracellular vesicles (EVs) are membrane-bound vesicles containing different biomolecules that are involved in cell to cell signal transfer. Accumulating evidence suggests that cancer-derived EVs are taken up by macrophages and modulate their phenotype and cytokine profile. However, the interactions of cancer-derived EVs with monocytes and macrophages at various differentiation and polarization states are poorly understood. In the current study, we have analyzed the uptake and functional effects of primary (SW480) and metastatic (SW620) isogenic colorectal cancer (CRC) cell line-derived EVs on monocytes (M), inactive macrophages (M0) and M1 and M2 polarized macrophages. METHODS: THP-1 monocytes were differentiated into M0 macrophages by addition of phorbol-12-myristate-13-acetate. Then M0 macrophages were further polarized into M1 and M2 macrophages in the presence of LPS, IFN- γ, IL-4, and IL-13 respectively. Internalization of SW480 and SW620-derived EVs was analyzed by flow cytometry and fluorescence microscopy. Changes in monocyte and macrophage immunophenotype and secretory profile upon EV exposure were analyzed by flow cytometry, quantitative PCR and Luminex assays. RESULTS: THP-1 monocytes and M0 macrophages efficiently take up SW480 and SW620-derived EVs, and our results indicate that dynamin-dependent endocytic pathways may be implicated. Interestingly, SW480 and SW620-derived EVs increased CD14 expression in M0 macrophages whereas SW480-derived EVs decreased HLA-DR expression in M1 and M2 polarized macrophages. Moreover, SW480-derived EVs significantly increased CXCL10 expression in monocytes and M0 macrophages. In contrast, SW620-derived EVs induced secretion of IL-6, CXCL10, IL-23 and IL-10 in M0 macrophages. However, addition of CRC cell line-derived EVs together with LPS, IFN- γ (M1) and IL-4, IL-13 (M2) stimuli during macrophage polarization had no additional effect on cytokine expression in M1 and M2 macrophages. CONCLUSION: Our results suggest that CRC cell line-derived EVs are internalized and reprogram the immunophenotype and secretory profile in monocytes and inactive macrophages inducing mixed M1 and M2 cytokine response. Although CRC EVs decreased HLA-DR expression in M1, M2 polarized macrophages, their effect on the secretory profile of M1 and M2 polarized macrophages was negligible.

Nanoparticle delivery to metastatic breast cancer cells by nanoengineered mesenchymal stem cells.

We created a 3D cell co-culture model by combining nanoengineered mesenchymal stem cells (MSCs) with the metastatic breast cancer cell line MDA-MD-231 and primary breast cancer cell line MCF7 to explore the transfer of quantum dots (QDs) to cancer cells. First, the optimal conditions for high-content QD loading in MSCs were established. Then, QD uptake in breast cancer cells was assessed after 24 h in a 3D co-culture with nanoengineered MSCs. We found that incubation of MSCs with QDs in a serum-free medium provided the best accumulation results. It was found that 24 h post-labelling QDs were eliminated from MSCs. Our results demonstrate that breast cancer cells efficiently uptake QDs that are released from nanoengineered MSCs in a 3D co-culture. Moreover, the uptake is considerably enhanced in metastatic MDA-MB-231 cells compared with MCF7 primary breast cancer cells. Our findings suggest that nanoengineered MSCs could serve as a vehicle for targeted drug delivery to metastatic cancer.

Nano-engineered skin mesenchymal stem cells: potential vehicles for tumour-targeted quantum-dot delivery.

Nanotechnology-based drug design offers new possibilities for the use of nanoparticles in imaging and targeted therapy of tumours. Due to their tumour-homing ability, nano-engineered mesenchymal stem cells (MSCs) could be utilized as vectors to deliver diagnostic and therapeutic nanoparticles into a tumour. In the present study, uptake and functional effects of carboxyl-coated quantum dots QD655 were studied in human skin MSCs. The effect of QD on MSCs was examined using a cell viability assay, Ki67 expression analysis, and tri-lineage differentiation assay. The optimal conditions for QD uptake in MSCs were determined using flow cytometry. The QD uptake route in MSCs was examined via fluorescence imaging using endocytosis inhibitors for the micropinocytosis, phagocytosis, lipid-raft, clathrin- and caveolin-dependent endocytosis pathways. These data showed that QDs were efficiently accumulated in the cytoplasm of MSCs after incubation for 6 h. The main uptake route of QDs in skin MSCs was clathrin-mediated endocytosis. QDs were mainly localized in early endosomes after 6 h as well as in late endosomes and lysosomes after 24 h. QDs in concentrations ranging from 0.5 to 64 nM had no effect on cell viability and proliferation. The expression of MSC markers, CD73 and CD90, and hematopoietic markers, CD34 and CD45, as well as the ability to differentiate into adipocytes, chondrocytes, and osteocytes, were not altered in the presence of QDs. We observed a decrease in the QD signal from labelled MSCs over time that could partly reflect QD excretion. Altogether, these data suggest that QD-labelled MSCs could be used for targeted drug delivery studies.