Penetration and intracellular uptake of poly(glycerol-adipate)nanoparticles into 3-dimensional brain tumour cell culture models

Nanoparticle (NP) drug delivery systems may potentially enhance the efficacy of therapeutic agents. It is difficult to characterise many important properties of NPs in vivo and therefore attempts have been made to use realistic in vitro multicellular spheroids instead. In this paper we have evaluated poly(glycerol-adipate) (PGA) NPs as a potential drug carrier for local brain cancer therapy. Various 3-dimensional (3-D) cell culture models have been used to investigate the delivery properties of PGA NPs. Tumour cells in 3-D culture showed a much higher level of endocytic uptake of NPs than a mixed normal neonatal brain cell population. Differences in endocytic uptake of NPs in 2-D and 3-D models strongly suggest that it is very important to use in vitro 3-D cell culture models for evaluating this parameter. Tumour penetration of NPs is another important parameter which could be studied in 3-D cell models. The penetration of PGA NPs through 3-D cell culture varied between models, which will therefore require further study to develop useful and realistic in vitro models. Further use of 3-D cell culture models will be of benefit in the future development of new drug delivery systems, particularly for brain cancers which are more difficult to study in vivo

Fusion of short telomeres in human cells is characterized by extensive deletion and microhomology, and can result in complex rearrangements

Telomere fusion is an important mutational event that has the potential to lead to large-scale genomic rearrangements of the types frequently observed in cancer. We have developed single-molecule approaches to detect, isolate and characterize the DNA sequence of telomere fusion events in human cells. Using these assays, we have detected complex fusion events that include fusion with interstitial loci adjacent to fragile sites, intra-molecular rearrangements, and fusion events involving the telomeres of both arms of the same chromosome consistent with ring chromosome formation. All fusion events were characterized by the deletion of at least one of the telomeres extending into the sub-telomeric DNA up to 5.6 kb; close to the limit of our assays. The deletion profile indicates that deletion may extend further into the chromosome. Short patches of DNA sequence homology with a G:C bias were observed at the fusion point in 60% of events. The distinct profile that accompanies telomere fusion may be a characteristic of the end-joining processes involved in the fusion event

Genome-Wide Gene Expression Analysis in Cancer Cells Reveals 3D Growth to Affect ECM and Processes Associated with Cell Adhesion but Not DNA Repair

Cell morphology determines cell behavior, signal transduction, protein-protein interaction, and responsiveness to external stimuli. In cancer, these functions profoundly contribute to resistance mechanisms to radio- and chemotherapy. With regard to this aspect, this study compared the genome wide gene expression in exponentially growing cell lines from different tumor entities, lung carcinoma and squamous cell carcinoma, under more physiological three-dimensional (3D) versus monolayer cell culture conditions. Whole genome cDNA microarray analysis was accomplished using the Affymetrix HG U133 Plus 2.0 gene chip. Significance analysis of microarray (SAM) and t-test analysis revealed significant changes in gene expression profiles of 3D relative to 2D cell culture conditions. These changes affected the extracellular matrix and were mainly associated with biological processes like tissue development, cell adhesion, immune system and defense response in contrast to terms related to DNA repair, which lacked significant alterations. Selected genes were verified by semi-quantitative RT-PCR and Western blotting. Additionally, we show that 3D growth mediates a significant increase in tumor cell radio- and chemoresistance relative to 2D. Our findings show significant gene expression differences between 3D and 2D cell culture systems and indicate that cellular responsiveness to external stress such as ionizing radiation and chemotherapeutics is essentially influenced by differential expression of genes involved in the regulation of integrin signaling, cell shape and cell-cell contact

Genomics and proteomics of vertebrate cholesterol ester lipase (LIPA) and cholesterol 25-hydroxylase (CH25H)

Cholesterol ester lipase (LIPA; EC 3.1.1.13) and cholesterol 25-hydroxylase (CH25H; EC 1.14.99.48) play essential role in cholesterol metabolism in the body by hydrolysing cholesteryl esters and triglycerides within lysosomes (LIPA) and catalysing the formation of 25-hydroxycholesterol from cholesterol (CH25H) which acts to repress cholesterol biosynthesis. Bioinformatic methods were used to predict the amino acid sequences, structures and genomic features of several vertebrate LIPA and CH25H genes and proteins, and to examine the phylogeny of vertebrate LIPA. Amino acid sequence alignments and predicted subunit structures enabled the identification of key sequences previously reported for human LIPA and CH25H and transmembrane structures for vertebrate CH25H sequences. Vertebrate LIPA and CH25H genes were located in tandem on all vertebrate genomes examined and showed several predicted transcription factor binding sites and CpG islands located within the 5′ regions of the human genes. Vertebrate LIPA genes contained nine coding exons, while all vertebrate CH25H genes were without introns. Phylogenetic analysis demonstrated the distinct nature of the vertebrate LIPA gene and protein family in comparison with other vertebrate acid lipases and has apparently evolved from an ancestral LIPA gene which predated the appearance of vertebrates

SNPs in DNA repair or oxidative stress genes and late subcutaneous fibrosis in patients following single shot partial breast irradiation

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to evaluate the potential association between single nucleotide polymorphisms related response to radiotherapy injury, such as genes related to DNA repair or enzymes involved in anti-oxidative activities. The paper aims to identify marker genes able to predict an increased risk of late toxicity studying our group of patients who underwent a Single Shot 3D-CRT PBI (SSPBI) after BCS (breast conserving surgery).</p> <p>Methods</p> <p>A total of 57 breast cancer patients who underwent SSPBI were genotyped for SNPs (single nucleotide polymorphisms) in XRCC1, XRCC3, GST and RAD51 by Pyrosequencing technology. Univariate analysis (ORs and 95% CI) was performed to correlate SNPs with the risk of developing ≥ G2 fibrosis or fat necrosis.</p> <p>Results</p> <p>A higher significant risk of developing ≥ G2 fibrosis or fat necrosis in patients with: polymorphic variant <it>GSTP1 </it>(Ile105Val) (OR = 2.9; 95%CI, 0.88-10.14, <it>p </it>= 0.047).</p> <p>Conclusions</p> <p>The presence of some SNPs involved in DNA repair or response to oxidative stress seem to be able to predict late toxicity.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01316328">NCT01316328</a></p

A Bioinformatics Filtering Strategy for Identifying Radiation Response Biomarker Candidates

The number of biomarker candidates is often much larger than the number of clinical patient data points available, which motivates the use of a rational candidate variable filtering methodology. The goal of this paper is to apply such a bioinformatics filtering process to isolate a modest number (<10) of key interacting genes and their associated single nucleotide polymorphisms involved in radiation response, and to ultimately serve as a basis for using clinical datasets to identify new biomarkers. In step 1, we surveyed the literature on genetic and protein correlates to radiation response, in vivo or in vitro, across cellular, animal, and human studies. In step 2, we analyzed two publicly available microarray datasets and identified genes in which mRNA expression changed in response to radiation. Combining results from Step 1 and Step 2, we identified 20 genes that were common to all three sources. As a final step, a curated database of protein interactions was used to generate the most statistically reliable protein interaction network among any subset of the 20 genes resulting from Steps 1 and 2, resulting in identification of a small, tightly interacting network with 7 out of 20 input genes. We further ranked the genes in terms of likely importance, based on their location within the network using a graph-based scoring function. The resulting core interacting network provides an attractive set of genes likely to be important to radiation response