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A novel metal–organic framework (MOF) containing Cu(II) ions with the chemical formula of {[Cu(L)2(H2O)2](DMF)3}n (1) was successfully prepared by solvothermal reaction method using metal Cu2+ ions as nodes and bifunctional ligand 3-(1H-tetrazol-5-yl)pyridine as organic linker. The activated MOF 1 (1a) could be utilized as catalyst for solvent-free heterogeneous catalytic cyanosilylation reaction because of its open Cu(II) metal positions, and its large amount of nitrogen atoms could be applied as Lewis basic positions. Thus, its catalytic mechanism was also investigated in detail. The specific mechanism was discussed, and its inhibition of the viability of MGC-803 gastric cancer cells was assessed. First, cell counting kit-8 assay was performed to determine the anti-cancer effect of compound 1a against the viability of MGC-803 cells. Then, Annexin V-fluorescein isothiocyanate/propidium iodide method was implemented to determine the percentage of apoptotic MGC-803 cells. Finally, the accumulation of reactive oxygen species in MGC-803 cells treated with the compound was determined via dichloro-dihydro-fluorescein diacetate assay. [ABSTRACT FROM AUTHOR]

The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer. [ABSTRACT FROM AUTHOR]