The goal of the Biostatistics/Bioinformatics Core is to collaborate with SPORE Investigators and other Core resource scientists to enhance the quality of the research undertaken in the Michigan Prostate SPORE. The Core personnel have been chosen because of their expertise in relevant areas of Biostatistics and Bioinformatics that is specifically required for the SPORE projects to succeed. Support will be provided in all stages of the research, beginning with the formulation of the research question, through the experimental design stage and data collection stage, including genomic sequencing, data analysis, and interpretation, to the writing of reports and dissemination of results. It will be apparent from this proposal that Core personnel have played a significant role in designing the proposed experiments and planning the data analyses. The exact nature of the collaboration will depend on the specifics of the science and the needs of the project. In addition to direct support of the projects and other Cores, senior statisticians will also focus on statistical methodology development and the advancement of genomic/bioinformatic capabilities related to the needs of prostate cancer research in this SPORE. Thus, the Specific Aims of the Core are: 1) Assist Investigators in the design of clinical, laboratory, and high-throughput genomic sequencing experiments; 2) Assist Investigators in the analysis and interpretation of data from clinical and laboratory experiments, the processing and examination of high-throughput genomic datasets, and in writing of manuscripts relaying Michigan Prostate SPORE results to the scientific community; 3) Undertake translational biostatistics/bioinformatics research to develop methodology and software implementation relevant to prostate cancer including the development of algorithmic toolkits for emerging types of genomic assays and the adaptation/refinement of existing computational approaches to the needs of the Michigan Prostate SPORE; 4) To establish a center of excellence for immunogenomics in prostate cancer. The center will provide state-of-art support for interdisciplinary research at the interface of cancer immunology and genomics and facilitate the rapid clinical translation of immunogenomic findings. The Biostatistics/Bioinformatics Core will be led by Dr. Alexander Tsodikov, Ph.D., a Professor of Biostatistics at U-M. He has served as the Director of the Prostate SPORE Biostatistics Core since 2009 and has substantial experience in the development of mechanistic statistical models of prostate cancer and biostatistical methodology and software, and statistical models in cancer. Drs. Jeremy Taylor, Ph.D. (U-M), Hui Jiang, Ph.D. (U-M), Lance Heilbrun, Ph.D. (KCI), and Marcin Cieslik, Ph.D. (U-M), will serve as Co-Investigators.

Public Health Relevance

The Biostatistics/Bioinformatics Core is critical to the ongoing success of the Michigan Prostate SPORE. It has contributed to the success of the current projects and has participated in a meaningful way in the planning and design of the proposed projects. Our ultimate goal is to decrease the morbidity and mortality of prostate cancer through innovative research that is supported by rigorous biostatistical and bioinformatics support.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
2P50CA186786-06
Application #
9791697
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
6
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Wu, Yi-Mi; Cie?lik, Marcin; Lonigro, Robert J et al. (2018) Inactivation of CDK12 Delineates a Distinct Immunogenic Class of Advanced Prostate Cancer. Cell 173:1770-1782.e14
Zhang, Yajia; Pitchiaya, Sethuramasundaram; Cie?lik, Marcin et al. (2018) Analysis of the androgen receptor-regulated lncRNA landscape identifies a role for ARLNC1 in prostate cancer progression. Nat Genet 50:814-824
Hussain, Maha; Daignault-Newton, Stephanie; Twardowski, Przemyslaw W et al. (2018) Targeting Androgen Receptor and DNA Repair in Metastatic Castration-Resistant Prostate Cancer: Results From NCI 9012. J Clin Oncol 36:991-999
Salami, Simpa S; Hovelson, Daniel H; Kaplan, Jeremy B et al. (2018) Transcriptomic heterogeneity in multifocal prostate cancer. JCI Insight 3:
Zhao, Shanshan; Leonardson, Amy; Geybels, Milan S et al. (2018) A five-CpG DNA methylation score to predict metastatic-lethal outcomes in men treated with radical prostatectomy for localized prostate cancer. Prostate :
Niknafs, Yashar S; Pandian, Balaji; Gajjar, Tilak et al. (2018) MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data. Neoplasia 20:1144-1149
Xiao, Lanbo; Tien, Jean C; Vo, Josh et al. (2018) Epigenetic Reprogramming with Antisense Oligonucleotides Enhances the Effectiveness of Androgen Receptor Inhibition in Castration-Resistant Prostate Cancer. Cancer Res 78:5731-5740
Piert, Morand; Shankar, Prasad R; Montgomery, Jeffrey et al. (2018) Accuracy of tumor segmentation from multi-parametric prostate MRI and 18F-choline PET/CT for focal prostate cancer therapy applications. EJNMMI Res 8:23
Rice, John D; Tsodikov, Alex (2017) Semiparametric profile likelihood estimation for continuous outcomes with excess zeros in a random-threshold damage-resistance model. Stat Med 36:1924-1935
Shen, Rex; Luo, Lan; Jiang, Hui (2017) Identification of gene pairs through penalized regression subject to constraints. BMC Bioinformatics 18:466

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