57 research outputs found
Microarray Probe Expression Measures, Data Normalization and Statistical Validation
DNA microarray technology is a high-throughput method for gaining information on gene function. Microarray technology is based on deposition/synthesis, in an ordered
manner, on a solid surface, of thousands of EST sequences/genes/oligonucleotides.
Due to the high number of generated datapoints, computational tools are essential in
microarray data analysis and mining to grasp knowledge from experimental results.
In this review, we will focus on some of the methodologies actually available to define
gene expression intensity measures, microarray data normalization, and statistical
validation of differential expression
Aurora Kinase A expression is associated with lung cancer histological-subtypes and with tumor de-differentiation
<p>Abstract</p> <p>Background</p> <p>Aurora kinase A (<it>AURKA</it>) is a member of serine/threonine kinase family. Several kinases belonging to this family are activated in the G2/M phase of the cell cycle being involved in mitotic chromosomal segregation. <it>AURKA </it>overexpression is significantly associated with neoplastic transformation in several tumors and deregulated <it>Aurora Kinases </it>expression leads to chromosome instability, thus contributing to cancer progression. The purpose of the present study was to investigate the expression of <it>AURKA </it>in non small cell lung cancer (NSCLC) specimens and to correlate its mRNA or protein expression with patients' clinico-pathological features.</p> <p>Materials and methods</p> <p>Quantitative real-time PCR and immunohistochemistry analysis on matched cancer and corresponding normal tissues from surgically resected non-small cell lung cancers (NSCLC) have been performed aiming to explore the expression levels of <it>AURKA </it>gene.</p> <p>Results</p> <p><it>AURKA </it>expression was significantly up-modulated in tumor samples compared to matched lung tissue (p < 0.01, mean log2(FC) = 1.5). Moreover, <it>AURKA </it>was principally up-modulated in moderately and poorly differentiated lung cancers (p < 0.01), as well as in squamous and adenocarcinomas compared to the non-invasive bronchioloalveolar histotype (p = 0.029). No correlation with survival was observed.</p> <p>Conclusion</p> <p>These results indicate that in NSCLC <it>AURKA </it>over-expression is restricted to specific subtypes and poorly differentiated tumors.</p
Differential expression of DNA repair machinery genes in normal bronchial tissue and non-small cell lung cancer (NSCLC)
Effects of Src kinase inhibition induced by dasatinib in non-small cell lung cancer cell lines treated with cisplatin
Persistent DNA damage-induced premature senescence alters the functional features of human bone marrow mesenchymal stem cells
Human mesenchymal stem cells (hMSCs) are adult multipotent stem cells located in various tissues, including the bone marrow. In contrast to terminally differentiated somatic cells, adult stem cells must persist and function throughout life to ensure tissue homeostasis and repair. For this reason, they must be equipped with DNA damage responses able to maintain genomic integrity while ensuring their lifelong persistence. Evaluation of hMSC response to genotoxic insults is of great interest considering both their therapeutic potential and their physiological functions. This study aimed to investigate the response of human bone marrow MSCs to the genotoxic agent Actinomycin D (ActD), a well-known anti-tumour drug. We report that hMSCs react by undergoing premature senescence driven by a persistent DNA damage response activation, as hallmarked by inhibition of DNA synthesis, p21 and p16 protein expression, marked Senescent Associated β-galactosidase activity and enlarged γH2AX foci co-localizing with 53BP1 protein. Senescent hMSCs overexpress several senescence-associated secretory phenotype (SASP) genes and promote motility of lung tumour and osteosarcoma cell lines in vitro. Our findings disclose a multifaceted consequence of ActD treatment on hMSCs that on the one hand helps to preserve this stem cell pool and prevents damaged cells from undergoing neoplastic transformation, and on the other hand alters their functional effects on the surrounding tissue microenvironment in a way that might worsen their tumour-promoting behaviour
Human mesenchymal stem cells labelled with dye-loaded amorphous silica nanoparticles: long-term biosafety, stemness preservation and traceability in the beating heart
Treatment of myocardial infarction with mesenchymal stem cells (MSCs) has proven beneficial effects in both animal and clinical studies. Engineered silica nanoparticles (SiO2-NPs) have been extensively used as contrast agents in regenerative medicine, due to their resistance to degradation and ease of functionalization. However, there are still controversies on their effective biosafety on cellular systems. In this perspective, the aims of the present study are: 1) to deeply investigate the impact of amorphous 50 nm SiO2-NPs on viability and function of human bone marrow-derived MSCs (hMSCs); 2) to optimize a protocol of harmless hMSCs labelling and test its feasibility in a beating heart model. Optimal cell labelling is obtained after 16 h exposure of hMSCs to fluorescent 50 nm SiO2-NPs (50 µg mL(-1)); interestingly, lysosomal activation consequent to NPs storage is not associated to oxidative stress. During prolonged culture hMSCs do not undergo cyto- or genotoxicity, preserve their proliferative potential and their stemness/differentiation properties. Finally, the bright fluorescence emitted by internalized SiO2-NPs allows both clear visualization of hMSCs in normal and infarcted rat hearts and ultrastructural analysis of cell engraftment inside myocardial tissue. Overall, 50 nm SiO2-NPs display elevated compatibility with hMSCs in terms of lack of cyto- and genotoxicity and maintenance of important features of these cells. The demonstrated biosafety, combined with proper cell labelling and visualization in histological sections, make these SiO2-NPs optimal candidates for the purpose of stem cell tracking inside heart tissue
Early gene expression profiling through a macro-array approach on non-apoptotic human monocytes fed with hemozoin (malarial pigment)
Selection of suitable reference genes for accurate normalization of gene expression profile studies in non-small cell lung cancer
BACKGROUND: In real-time RT quantitative PCR (qPCR) the accuracy of normalized data is highly dependent on the reliability of the reference genes (RGs). Failure to use an appropriate control gene for normalization of qPCR data may result in biased gene expression profiles, as well as low precision, so that only gross changes in expression level are declared statistically significant or patterns of expression are erroneously characterized. Therefore, it is essential to determine whether potential RGs are appropriate for specific experimental purposes. Aim of this study was to identify and validate RGs for use in the differentiation of normal and tumor lung expression profiles. METHODS: A meta-analysis of lung cancer transcription profiles generated with the GeneChip technology was used to identify five putative RGs. Their consistency and that of seven commonly used RGs was tested by using Taqman probes on 18 paired normal-tumor lung snap-frozen specimens obtained from non-small-cell lung cancer (NSCLC) patients during primary curative resection. RESULTS: The 12 RGs displayed showed a wide range of Ct values: except for rRNA18S (mean 9.8), the mean values of all the commercial RGs and ESD ranged from 19 to 26, whereas those of the microarray-selected RGs (BTF-3, YAP1, HIST1H2BC, RPL30) exceeded 26. RG expression stability within sample populations and under the experimental conditions (tumour versus normal lung specimens) was evaluated by: (1) descriptive statistic; (2) equivalence test; (3) GeNorm applet. All these approaches indicated that the most stable RGs were POLR2A, rRNA18S, YAP1 and ESD. CONCLUSION: These data suggest that POLR2A, rRNA18S, YAP1 and ESD are the most suitable RGs for gene expression profile studies in NSCLC. Furthermore, they highlight the limitations of commercial RGs and indicate that meta-data analysis of genome-wide transcription profiling studies may identify new RGs
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