S9, a Novel Anticancer Agent, Exerts Its Anti-Proliferative Activity by Interfering with Both PI3K-Akt-mTOR Signaling and Microtubule Cytoskeleton

BACKGROUND: Deregulation of the phosphatidylinositol 3-kinases (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway plays a central role in tumor formation and progression, providing validated targets for cancer therapy. S9, a hybrid of alpha-methylene-gamma-lactone and 2-phenyl indole compound, possessed potent activity against this pathway. METHODOLOGY/PRINCIPAL FINDINGS: Effects of S9 on PI3K-Akt-mTOR pathway were determined by Western blot, immunofluorescence staining and in vitro kinas assay. The interactions between tubulin and S9 were investigated by polymerization assay, CD, and SPR assay. The potential binding modes between S9 and PI3K, mTOR or tubulin were analyzed by molecular modeling. Anti-tumor activity of S9 was evaluated in tumor cells and in nude mice bearing human cancer xenografts. S9 abrogated EGF-activated PI3K-Akt-mTOR signaling cascade and Akt translocation to cellular membrane in human tumor cells. S9 possessed inhibitory activity against both PI3K and mTOR with little effect on other tested 30 kinases. S9 also completely impeded hyper-phosphorylation of Akt as a feedback of inhibition of mTOR by rapamycin. S9 unexpectedly arrested cells in M phase other than G1 phase, which was distinct from compounds targeting PI3K-Akt-mTOR pathway. Further study revealed that S9 inhibited tubulin polymerization via binding to colchicine-binding site of tubulin and resulted in microtubule disturbance. Molecular modeling indicated that S9 could potentially bind to the kinase domains of PI3K p110alpha subunit and mTOR, and shared similar hydrophobic interactions with colchicines in the complex with tubulin. Moreover, S9 induced rapid apoptosis in tumor cell, which might reflect a synergistic cooperation between blockade of both PI3-Akt-mTOR signaling and tubulin cytoskeleton. Finally, S9 displayed potent antiproliferative activity in a panel of tumor cells originated from different tissue types including drug-resistant cells and in nude mice bearing human tumor xenografts. CONCLUSIONS/SIGNIFICANCE: Taken together, S9 targets both PI3K-Akt-mTOR signaling and microtubule cytoskeleton, which combinatorially contributes its antitumor activity and provides new clues for anticancer drug design and development

Population Genetic Diversity and Structure of a Naturally Isolated Plant Species, Rhodiola dumulosa (Crassulaceae)

Aims: Rhodiola dumulosa (Crassulaceae) is a perennial diploid species found in high-montane areas. It is distributed in fragmented populations across northern, central and northwestern China. In this study, we aimed to (i) measure the genetic diversity of this species and that of its populations; (ii) describe the genetic structure of these populations across the entire distribution range in China; and (iii) evaluate the extent of gene flow among the naturally fragmented populations. Methods: Samples from 1089 individuals within 35 populations of R. dumulosa were collected, covering as much of the entire distribution range of this species within China as possible. Population genetic diversity and structure were analyzed using AFLP molecular markers. Gene flow among populations was estimated according to the level of population differentiation. Important Findings: The total genetic diversity of R. dumulosa was high but decreased with increasing altitude. Populationstructure analysis indicated that the most closely related populations were geographically restricted and occurred in close proximity to each other. A significant isolation-by-distance pattern, caused by the naturally fragmented population distribution, was observed. At least two distinct gene pools were found in the 35 sampled populations, one composed of populations in northern China and the other composed of populations in central and northwestern China. The calculation of Nei’s gene diversity index revealed that the genetic diversity in the northern China pool (0.1972) was lower than that in th

Differences in the Properties and Mirna Expression Profiles between Side Populations from Hepatic Cancer Cells and Normal Liver Cells

AIMS: Because hepatic cancer stem cells (HCSCs) are believed to derive from the conversion of hepatic normal stem cells (HNSCs), the identification of the differences that distinguish HCSCs from HNSCs is important. METHODS: The HCC model was established in F344 rats by DEN induction. Using FACS analysis, side population cells from HCC (SP-HCCs) were isolated from the epithelial-like cells of HCC tissues, and the side population cells from normal liver (SP-NLCs) were isolated from syngeneic normal liver cells. The expression of stem cell markers was detected in both freshly isolated and amplified subpopulations. After induction with HGF, the differentiation of each subpopulation was analyzed by detection of early and late liver markers. In vivo, the biological characteristics of SP-HCCs and SP-NLCs were analyzed by repairing injured livers or forming tumors in nude mice. In addition, the expression of miRNAs was examined in both populations by miRNA array and QRT-PCR. RESULTS: SP-NLCs and SP-HCCs were 4.30±0.011% and 2.100±0.010% of the whole population, respectively. Both SP-NLCs and SP-HCCs displayed greater expression of stem cell markers (CD133 and EpCAM) than NSP-NLCs and NSP-HCCs, respectively (P<0.01), both after fresh isolation and amplification. Upon HGF induction, SP-NLCs generated many ALB positive cells and few CK-7 positive cells, but NSP-NLCs could generate only ALB positive cells. In contrast, SP-HCCs gave rise to only AFP positive cells. As few as 5 × 10⁵ SP-NLCs were capable of repairing liver injury, while the same number of NSP-NLCs could not repair the liver. Furthermore, only 1 × 10⁴ SP-HCCs were necessary to initiate a tumor, while NSP-HCCs could not form a tumor. Compared to SP-NLCs, 68 up-regulated and 10 down-regulated miRNAs were present in SP-HCCs (P<0.01). CONCLUSION: Based on the decisive roles of some miRNAs in the genesis of HCSCs, miRNAs may contribute to the different characteristics that distinguish SP-HCCs from SP-NLCs

The muon system of the Daya Bay Reactor antineutrino experiment

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Search for a Light Sterile Neutrino at Daya Bay

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Improved Measurement of Electron Antineutrino Disappearance at Daya Bay

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Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe