Preparation and Crystal Structure of a Platinum(II) Complex of [CH2N(CH2COOH)CH2CONH2]2, the Hydrolysis Product of an Anti-Tumour Bis(3,5-Dioxopiperazin-1-YL)Alkane

The synthesis and crystal and molecular structures of the platinum(II) complex Pt(HL)Cl where H2L is the diacid diamide –[CH2N(CH2COOH)CH2CONH2]2, a hydrolytic metabolite of an antitumour active bis(3,5-dioxopiperazin-1-yl)alkane are reported. The complex is square planar and contains HL– as a tridentate 2N (amino), O (carboxylate) donor. The metal to ligand bond distances are Pt-Cl 2.287(1) Å, Pt-O 2.002 (1) Å, Pt-Ntrans Cl 2.014(1) Å and Pt-Ntrans O 2.073 Å. There is extensive hydrogen bonding, each molecule of Pt(HL)Cl being intermolecularly hydrogen bonded to ten others giving a 3-dimensional network. There is also one intramolecular H-bond

The 2017 Regent Landslide, Freetown Peninsula, Sierra Leone

At 06:50 on Monday 14th August 2017, a hillslope on the Freetown Peninsula, Sierra Leone, collapsed, sending 300,000 m3 of debris into the flooded valley below. As this debris mixed with floodwater it became a sediment-laden flood which entered a drainage channel and travelled 6 km to the coastline. The event destroyed nearly 400 buildings, claimed the lives of an estimated 1,100 people and affected approximately 5,000 people. The mechanism was a two-stage rainfall-triggered landslide followed by a channelised debris-laden flood. The processes were similar to the nearby 1945 event in Charlotte, which killed at least 13 people. Geomorphological mapping has identified evidence of hundreds of other large landslides that occurred before modern records, providing an appreciation of the slope processes affecting the Freetown Peninsula. Following the 2017 Regent Landslide, rehabilitation of the affected area involved a risk reduction strategy that centred on reducing population exposure. These events are a reminder that the steep slopes and valleys across the Freetown Peninsula are highly susceptible to rainfall-triggered landslides which, given the topography have a high propensity to generate high intensity landslides and debris-laden floods. Future urbanization must consider whole-catchment management, flooding and slope engineering issues to provide lasting landslide risk reduction

Host-derived RANKL is responsible for osteolysis in a C4-2 human prostate cancer xenograft model of experimental bone metastases

<p>Abstract</p> <p>Background</p> <p>C4-2 prostate cancer (CaP) cells grown in mouse tibiae cause a mixed osteoblastic/osteolytic response with increases in osteoclast numbers and bone resorption. Administration of osteoprotegerin (OPG) blocks these increases, indicating the critical role of RANKL in osteolysis in this model. The objective of our study was to investigate whether RANKL expressed by tumor cells (human origin) directly stimulates osteolysis associated with the growth of these cells in bone or whether the increased osteolysis is caused by RANKL expressed by the host environment cells (murine origin). The relative contribution of tumor-<it>vs. </it>host-derived RANKL has been difficult to establish, even with human xenografts, because murine and human RANKL are both capable of stimulating osteolysis in mice, and the RANKL inhibitors used to date (OPG and RANK-Fc) inhibit human and murine RANKL.</p> <p>Methods</p> <p>To address this question we used a neutralizing, antibody (huRANKL MAb), which specifically neutralizes the biological activities of human RANKL and thereby the contribution of C4-2 derived RANKL in this tibial injection model of experimental bone metastases.</p> <p>Results</p> <p>Administration of huRANKL MAb did not inhibit the osteolytic response of the bone to these cells, or affect the establishment and growth of the C4-2 tumors in this environment.</p> <p>Conclusion</p> <p>In conclusion, our results suggest that in this model, murine RANKL and not the tumor-derived human RANKL is the mediator of the osteolytic reaction associated with C4-2 growth in bone. We hypothesize that C4-2 cells express other factor/s inducing host production of RANKL, thereby driving tumor-associated osteolysis.</p

Chemosensitivity profiling of osteosarcoma tumour cell lines identifies a model of BRCAness

Osteosarcoma (OS) is an aggressive sarcoma, where novel treatment approaches are required. Genomic studies suggest that a subset of OS, including OS tumour cell lines (TCLs), exhibit genomic loss of heterozygosity (LOH) patterns reminiscent of BRCA1 or BRCA2 mutant tumours. This raises the possibility that PARP inhibitors (PARPi), used to treat BRCA1/2 mutant cancers, could be used to target OS. Using high-throughput drug sensitivity screening we generated chemosensitivity profiles for 79 small molecule inhibitors, including three clinical PARPi. Drug screening was performed in 88 tumour cell lines, including 18 OS TCLs. This identified known sensitivity effects in OS TCLs, such as sensitivity to FGFR inhibitors. When compared to BRCA1/2 mutant TCLs, OS TCLs, with the exception of LM7, were PARPi resistant, including those with previously determined BRCAness LoH profiles. Post-screen validation experiments confirmed PARPi sensitivity in LM7 cells as well as a defect in the ability to form nuclear RAD51 foci in response to DNA damage. LM7 provides one OS model for the study of PARPi sensitivity through a potential defect in RAD51-mediated DNA repair. The drug sensitivity dataset we generated in 88 TCLs could also serve as a resource for the study of drug sensitivity effects in OS

Identification of highly penetrant Rb-related synthetic lethal interactions in triple negative breast cancer.

Although defects in the RB1 tumour suppressor are one of the more common driver alterations found in triple-negative breast cancer (TNBC), therapeutic approaches that exploit this have not been identified. By integrating molecular profiling data with data from multiple genetic perturbation screens, we identified candidate synthetic lethal (SL) interactions associated with RB1 defects in TNBC. We refined this analysis by identifying the highly penetrant effects, reasoning that these would be more robust in the face of molecular heterogeneity and would represent more promising therapeutic targets. A significant proportion of the highly penetrant RB1 SL effects involved proteins closely associated with RB1 function, suggesting that this might be a defining characteristic. These included nuclear pore complex components associated with the MAD2 spindle checkpoint protein, the kinase and bromodomain containing transcription factor TAF1, and multiple components of the SCFSKP Cullin F box containing complex. Small-molecule inhibition of SCFSKP elicited an increase in p27Kip levels, providing a mechanistic rationale for RB1 SL. Transcript expression of SKP2, a SCFSKP component, was elevated in RB1-defective TNBCs, suggesting that in these tumours, SKP2 activity might buffer the effects of RB1 dysfunction

Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.European Commission - Seventh Framework Programme (FP7)Health Research BoardScience Foundation IrelandWellcome TrustCancer Research UKBreast Cancer NowNational Health Servic

Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.European Commission - Seventh Framework Programme (FP7)Health Research BoardScience Foundation IrelandWellcome TrustCancer Research UKBreast Cancer NowNational Health Servic