The Biostatistics, Bioinformatics and Systems Biology (BBSB) Core 1. provides statistics and data analysis required by the Projects and Core to achieve their specific aims; 2. provides bioinformatics and systems biology expertise required for analysis of high-throughput assay data; 3. assists in the design and implementation of trials and studies arising from the ongoing research of the SPORE; 4. provides data management support for the Cores and Projects. The Core assists Project 1 with the development of high dimensional predictive models for early detection, and with the identification of further potential markers (e.g. autoantibodies) for improving panels available. The Core assists Project 2 with the design and analysis of in vitro and in vivo studies interrogating the interaction of DII4-Notch signaling, angiogenesis, and VEGF in ovarian cancer. The Core will provide assistance with the design and analysis of a Phase I clinical trial. The Core assists Project 3 with the characterization low grade tumor data from SNP arrays, expression arrays and mutation data measured on selected genes by direct sequencing. The Core assists with biomarker identification, sample size and power calculations, and with planning for a phase I clinical trial. The Core assists Project 4 with refining definitions for PISKness and BRCAness using data from several high-throughput assays, and with determining the extent to which these signatures are predictive of response in cell line and xenograft models. The Core is also providing assistance with the design of two Phase II trials involving targeted therapies. The Core assists Project 5 with the determination of the optimal dose, gene product, and combination with chemtherapy for treatment with Mesenchymal Stem Cells (MSCs). The Core will also assist with assessing effectiveness of MSC therapy and with the design of a Phase l/ll trial to identify an optimal biological dose with acceptable toxicity.
The BBSB Core provides support to the Projects and Cores of the SPORE. This support includes designing in vivo and in vitro experiments and analyzing results obtained, designing new clinical trials, assisting in the conduct of and analyzing results from ongoing trials, supplying analysis and interpretation of high-throughput assays, combining results across assays, and helping interpret results in terms of component pathways.
|SÃ¶lÃ©tormos, GyÃ¶rgy; Duffy, Michael J; Othman Abu Hassan, Suher et al. (2016) Clinical Use of Cancer Biomarkers in Epithelial Ovarian Cancer: Updated Guidelines From the European Group on Tumor Markers. Int J Gynecol Cancer 26:43-51|
|He, Ningning; Kim, Nayoung; Jeong, Euna et al. (2016) Glucose starvation induces mutation and lineage-dependent adaptive responses in a large collection of cancer cell lines. Int J Oncol 48:67-72|
|Liu, Joyce; Westin, Shannon N (2016) Rational selection of biomarker driven therapies for gynecologic cancers: The more we know, the more we know we don't know. Gynecol Oncol 141:65-71|
|Chen, Tenghui; Wang, Zixing; Zhou, Wanding et al. (2016) Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types. BMC Genomics 17 Suppl 2:394|
|Nishizuka, Satoshi S; Mills, Gordon B (2016) New era of integrated cancer biomarker discovery using reverse-phase protein arrays. Drug Metab Pharmacokinet 31:35-45|
|Zand, Behrouz; Previs, Rebecca A; Zacharias, Niki M et al. (2016) Role of Increased n-acetylaspartate Levels in Cancer. J Natl Cancer Inst 108:djv426|
|Huang, Yan; Lichtenberger, Lenard M; Taylor, Morgan et al. (2016) Antitumor and Antiangiogenic Effects of Aspirin-PC in Ovarian Cancer. Mol Cancer Ther 15:2894-2904|
|Hansen, Jean M; Coleman, Robert L; Sood, Anil K (2016) Targeting the tumour microenvironment in ovarian cancer. Eur J Cancer 56:131-43|
|Whiting, Nicholas; Hu, Jingzhe; Zacharias, Niki M et al. (2016) Developing hyperpolarized silicon particles for in vivo MRI targeting of ovarian cancer. J Med Imaging (Bellingham) 3:036001|
|Yang, Hailing; Das, Partha; Yu, Yinhua et al. (2016) NDN is an imprinted tumor suppressor gene that is downregulated in ovarian cancers through genetic and epigenetic mechanisms. Oncotarget 7:3018-32|
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