Fordbernstein2107

There has been accumulating evidence suggesting nitric oxide donors as such targeting agents and considering their pleiotropic antitumor activities, including both the reversal of chemo and immuno-resistance of various unresponsive resistant cancers. The in vitro and in vivo preclinical findings corroborate the sensitizing antitumor activities of nitric oxide donors. In addition, a few clinical findings with NO donors that have been applied in patients have corroborated their antitumor and sensitizing activities in combination with standard therapies. In this review, the role and underlying mechanisms by which nitric oxide donors sensitize cancer resistant cells to both chemotherapy and immunotherapy are briefly described. Transcriptional coactivators p300 and CBP catalyze the acetylation of lysine residues in histone proteins. Upregulation of p300 and CBP has been associated with lung, colorectal and hepatocellular cancer, indicating an important role of p300 and CBP in tumorigenesis. Recently, the novel p300 and CBP-selective inhibitor A485 became available, which was shown to inhibit proliferation of 124 different cancer cell lines. Here, we found that downregulation of EP300 or CREBBP enhances apoptosis upon TRAIL stimulation in non-small-cell lung cancer (NSCLC) cells. A485 upregulates pro- and anti- apoptotic genes at the mRNA level, implying an apoptosis-modulating effect in NSCLC cells. VX-661 molecular weight However, A485 alone does not induce apoptosis. Interestingly, we observed that the number of apoptotic cells increases upon combined treatment with A485 and TRAIL. Therefore, A485, as a TRAIL-sensitizer, was used in combination with TRAIL in wild type of NSCLC cell lines (HCC827and H1650) and cells with acquired erlotinib resistance (HCC827-ER and H1650-ER). Our results show that the combination of A485 and TRAIL synergistically increases cell death and inhibits long-term cell proliferation. Furthermore, this combination inhibits the growth of 3D spheroids of EGFR-TKI-resistant cells. Taken together, we demonstrate a successful combination of A485 and TRAIL in EGFR-TKI-sensitive and resistant NSCLC cells. PURPOSE The purpose of this in vitro study was to determine the precision evaluation of blue light scanning of abutment teeth impressions and dental stone casts according to different 3D superimposition methods. METHODS Impressions and dental stone casts of the maxillary canine, 1st premolar, and 1st molar were fixed; they were repeatedly scanned 11 times, (6 types, total n = 66). Stereolithography (STL) files were superimposed one by one, and used to obtain 10 root mean square (RMS) values with the 2 superimposition methods (best-fit-alignment, no control). Statistical analysis included the independent t test and one-way ANOVA with Tukey honest significant differences (α = 0.05). RESULTS RMS ± Standard Deviation (SD) values for the best-fit-alignment method of the abutment teeth impressions of the maxillary canine, 1st premolar, and 1st molar was 8.07 ± 0.76, 5.03 ± 0.23, and 6.59 ± 0.24, respectively, and those of the no control method were 9.36 ± 0.82, 7.10 ± 1.14, and 8.17 ± 0.36 respectively. RMS ± SD values for the best-fit-alignment method for the dental stone casts were 4.07 ± 0.27, 3.39 ± 0.07, and 3.29 ± 0.07, respectively, and those for the no control method were 6.26 ± 2.50, 4.98 ± 1.16, and 4.55± 0.74, respectively. CONCLUSIONS Using different 3D superimposition methods, blue light scanning of abutment teeth impressions and dental stone casts shows high precision. The no control method showed lower precision best-fit-alignment. However, the results may help advance the digital dental CAD/CAM research and the clinical field of Prosthodontics. Mantle Cell lymphoma (MCL) is a tumor with poor prognosis. A few studies have examined the molecular landscape by next generation sequencing and provided valuable insights into recurrent lesions driving this heterogeneous cancer. However, none have attempted to cross-link the individual genomic and transcriptomic profile in sorted MCL cells in order to perform individual molecular characterizations of the lymphomas. Such approaches are relevant as MCL is heterogenous by nature, and thorough molecular diagnostics may potentially benefit the patient with more focused treatment options. Here, we use sorted lymphoma cells from four patients at diagnosis and relapse by intersecting the coding DNA and mRNA. In spite of only few patients included, this method enabled us to pinpoint a specific set of expressed somatic mutations and to present an overall expression profile different from the normal B cell counterparts, and to track molecular aberrations from diagnosis to relapse. Changes of single nucleotide coding variants, subtle clonal changes in large copy number alterations, subclonal involvement and changes in expression levels in the clinical course provided detailed information on each of the individual malignancies. In addition to mutations in known genes (e.g. TP53, CCND1, NOTCH1, ATM), we identified others, not linked to MCL, such as a nonsense mutation in SPEN and MYD88 missense mutation in one patient, which along with copy number alterations showed molecular resemblance towards splenic marginal zone lymphoma. The detailed exonic and transcriptomic portrait of the individual MCL patients by the methodology presented here could help in diagnostics, surveillance and a potentially more precise usage of therapeutic drugs by efficient screen of biomarkers. BACKGROUND We investigated the association between synchronous metastases (SMs), histologic subtype (HS), tumor size (TS), and tumor grade (TG) in surgically treated stage T2 renal cell carcinoma (RCC). MATERIALS AND METHODS Within the Surveillance, Epidemiology, and End Results database (2005-2015), 8344 patients with T2 RCC who had undergone radical nephrectomy were identified. The SM rates were tabulated according to the HS, TG, and TS and tested in multivariable logistic regression models. RESULTS According to the HS, the average SM rates were 0%, 1.4%, 4.6%, 6.4%, 12.7%, 20.0%, and 32.7% for multilocular cystic, chromophobe, papillary, TG 1-2 clear cell, TG 3-4 clear cell, collecting duct, and sarcomatoid dedifferentiation RCC, respectively. In multivariable logistic regression models predicting for SMs, HS represented the strongest predictor, followed by TG, TS, and race. When combined, HS, TG, TS, and race predicted for SMs with 70.2% accuracy compared with 62.5% with HS, 60.2% with TG, 57.8% with TS, and 53.