12 research outputs found

    NEFL mRNA Expression Level Is a Prognostic Factor for Early-Stage Breast Cancer Patients

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    Neurofilament, light polypeptide (NEFL) was demonstrated to be ectopically expressed in breast cancer tissues and decreased in lymph node metastases compared to the paired primary breast cancers in our previous study. Moreover, in several studies, NEFL was regarded as a tumor suppressor gene, and its loss of heterozygosity (LOH) was related to carcinogenesis and metastasis in several types of cancer. To explore the role of NEFL in the progression of breast cancer and to evaluate its clinical significance, we detected the NEFL mRNA level in normal breast tissues, primary breast cancer samples and lymph node metastases, and then analyzed the association between the NEFL expression level and several clinicopathological parameters and disease-free survival (DFS). NEFL mRNA was found to be expressed in 92.3% of breast malignancies and down-regulated in lymph node metastases compared to the paired primary tumors. NEFL mRNA level was lower in primary breast cancers with positive lymph nodes than in cancers with negative lymph nodes. Moreover, a low expression level of NEFL mRNA indicated a poor five-year DFS for early-stage breast cancer patients. Thus, NEFL mRNA is ectopically expressed in breast malignancies and could be a potential prognostic factor for early-stage breast cancer patients

    Identification of MSRA gene on chromosome 8p as a candidate metastasis suppressor for human hepatitis B virus-positive hepatocellular carcinoma

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    <p>Abstract</p> <p>Background</p> <p>The prognosis of patients with hepatocellular carcinoma (HCC) still remains very dismal, which is mainly due to metastasis. In our previous studies, we found that chromosome 8p deletions might contribute to metastasis of HCC. In this study, we aimed to identify the candidate metastatic suppressor gene on chromosome 8p.</p> <p>Methods</p> <p>Oligo-nucleotide microarrays which included 322 genes on human chromosome 8p were constructed to analyze the difference in gene expression profiles between HCC tissues with and without metastasis. The leading differentially expressed genes were identified and selected for further analysis by real-time PCR and Western blotting. Recombinant expression plasmid vectors for each target gene were constructed and transfected into HCC cells and its <it>in vitro </it>effects on proliferation and invasion of HCC cells were also investigated.</p> <p>Results</p> <p>Sixteen leading differentially expressed genes were identified from the HCC tissues with metastasis compared with those without metastasis (<it>p </it>< 0.01, <it>q </it>< 16 %). Among of the 10 significantly down-regulated genes in HCC with metastasis, methionine sulfoxide reductase A (<it>MSRA</it>) had the lowest <it>p </it>value and false discovery rate (FDR), and was considered as a potential candidate for metastasis suppressor gene. Real-time PCR and Western blotting confirmed that the mRNA and protein expression levels of <it>MSRA </it>were significantly decreased in HCC with metastasis compared with those without metastasis (<it>p </it>< 0.001), and <it>MSRA </it>mRNA level in HCCLM6 cells (with high metastatic potential) was also much lower than that of other HCC cell lines. Transfection of a recombinant expression plasmid vector and overexpression of <it>MSRA </it>gene could obviously inhibit cell colony formation (4.33 ± 2.92 vs. 9.17 ± 3.38, <it>p </it>= 0.008) and invasion (7.40 ± 1.67 vs. 17.20 ± 2.59, <it>p</it>= 0.0001) of HCCLM6 cell line.</p> <p>Conclusion</p> <p><it>MSRA </it>gene on chromosome 8p might possess metastasis suppressor activity in HCC.</p

    Perspective historique de robots humanoĂŻdes en Europe

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    International audienceFrom the very first humanoid automation designed by Leonardo da Vinci in 1495 to Pyrène – a fully force control humanoid robot – designed for research purpose in 2016, this chapter discusses the contributions of Europe in humanoid robot research and development. It is organized around the presentation of the main influential platforms, followed by thematic contributions covering collaborative robots, control, biomechanics, and neurosciences
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