130,710 research outputs found
Hypoxia and human genome stability: Downregulation of BRCA2 expression in breast cancer cell lines
No full textPreviously, it has been reported that hypoxia causes increased mutagenesis and alteration in DNA repair mechanisms. In 2005, an interesting study showed that hypoxia-induced decreases in BRCA1 expression and the consequent suppression of homologous recombination may lead to genetic instability. However, nothing is yet known about the involvement of BRCA2 in hypoxic conditions in breast cancer. Initially, a cell proliferation assay allowed us to hypothesize that hypoxia could negatively regulate the breast cancer cell growth in short term in vitro studies. Subsequently, we analyzed gene expression in breast cancer cell lines exposed to hypoxic condition by microarray analysis. Interestingly, genes involved in DNA damage repair pathways such as mismatch repair, nucleotide excision repair, nonhomologous end-joining and homologous recombination repair were downregulated. In particular, we focused on the BRCA2 downregulation which was confirmed at mRNA and protein level. In addition, breast cancer cells were treated with dimethyloxalylglycine (DMOG), a cell-permeable inhibitor of both proline and asparaginyl hydroxylases able to induce HIF-1α stabilization in normoxia, providing results comparable to those previously described. These findings may provide new insights into the mechanisms underlying genetic instability mediated by hypoxia and BRCA involvement in sporadic breast cancers. © 2013 Daniele Fanale et al
Involvement of non-coding RNAs in chemo- and radioresistance of colorectal cancer
No full textDespite recent progress in understanding the cancer signaling pathways and in developing new therapeutic strategies, however, the resistance of colorectal cancer (CRC) cells to chemo- and radiotherapy represents the main hurdle to the successful treatment, leading to tumor recurrence and, consequently, a poor prognosis. Therefore, overcoming drug and radiation resistance, enhancing drug and radiation sensitivity of CRC cells, and improving the effi cacy of chemo- and radiotherapy have an important signifi cance in the treatment of CRC. The identifi cation of new molecular biomarkers which can predict therapy response and prognosis is one of the most signifi cant aims in pharmacogenomics and cancer research. Recent studies showed that non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), may play important roles in the regulation of chemo- and radioresistance of CRC, by controlling several signaling pathways, including cell cycle, proliferation, apoptosis and DNA damage repair. Recent data have demonstrated that selective modulation of the ncRNA activity can improve the response to chemo- and radiotherapy, providing an innovative anti- tumor approach based on a ncRNA-related gene therapy. Therefore, ncRNAs could not only be useful as predictive and prognostic biomarkers but also serve as targets for the development of novel therapeutic strategies to overcome drug and radiation resistance in CRC. In this chapter, we discuss the involvement of ncRNAs in chemo- and radiotherapy resistance of CRC, highlighting the impact of these molecules in prediction of the treatment response and modifi cation of the therapy, and describing possible intracellular pathways involved in these processes
Analisi del comportamento sismico di Palazzo Camponeschi: modelli rappresentativi dello scenario di danno
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MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Non-coding RNAs functioning in colorectal cancer stem cells
No full textIn recent years, the hypothesis of the presence of tumor-initiating cancer stem cells (CSCs) has received a considerable support. This model suggested the existence of CSCs which, thanks to their self-renewal properties, are able to drive the expansion and the maintenance of malignant cell populations with invasive and metastatic potential in cancer. Increasing evidence showed the ability of such cells to acquire self-renewal, multipotency, angiogenic potential, immune evasion, symmetrical and asymmetrical divisions which, along with the presence of several DNA repair mechanisms, further enhance their oncogenic potential making them highly resistant to common anticancer treatments. The main signaling pathways involved in the homeostasis of colorectal (CRC) stem cells are the Wnt, Notch, Sonic Hedgehog, and Bone Morfogenic Protein (BMP) pathways, which are mostly responsible for all the features that have been widely referred to stem cells. The same pathways have been identifi ed in colorectal cancer stem cells (CRCSCs), conferring a more aggressive phenotype compared to non-stem CRC cells. Recently, several evidences suggested that non-coding RNAs (ncRNAs) may play a crucial role in the regulation of different biological mechanisms in CRC, by modulating the expression of critical stem cell transcription factors that have been found active in CSCs. In this chapter, we will discuss the involvement of ncRNAs, especially microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in stemness acquisition and maintenance by CRCSCs, through the regulation of pathways modulating the CSC phenotype and growth, carcinogenesis, differentiation, and epithelial to mesenchymal transition (EMT)
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