Faculty

Roger S. Day, ScD

Room 532
5607 Baum Boulevard
Pittsburgh, PA 15206
Phone Number: 
412-624-3253
Fax: 
412-624-5310
Admin Support: 

Research Interests

  • High throughput identifier mapping
  • Ethical design and execution of clinical trials
  • Applications of biostatistics in cancer research 
  • Software architecture for comprehensive modeling and validation
  • Multi-scale modeling in cancer
  • Strategies for overcoming drug resistance in cancer
  • How pharmaceutical and biological interactions should be statistically modeled

Appointments and Positions

Associate Professor of Biomedical Informatics
Associate Professor of Biostatistics
Biomedical Informatics Training Program Core Faculty

Current Research Projects and Collaborations

Statistical methods for integromics discovery

This project aims to develop statistical methods for integrating information from multiple high throughput biotechnology for inferring signal transduction systems

Gynecological Cancer Translational Center of Excellence

We hypothesize that progestins and vitamin D both target the early steps of carcinogenesis in the endometrium by clearing genetically damaged endometrial glandular cells, resulting in effective cancer prevention. In addition, we hypothesize that the combination of a progestin and vitamin D will be more effective for endometrial cancer prevention than either agent administered alone. Our goal is to develop this combination for endometrial cancer prevention. To achieve this end, we propose the following:  to elucidate the molecular mechanism(s) underlying the synergistic interaction of progestins and vitamin D in the endometrium, directly test the endometrial cancer preventive efficacy of a potent progestin, vitamin D, and the combination of a progestin and vitamin D in vivo in a prospective trial using PTEN heterozygote mice which have been shown to be prone to develop endometrial hyperplasia and cancer, to examine the impact of progestin and Vitamin D exposure, and their interaction, on endometrial cancer risk in a population based study (Nurses Health Study), and to demonstrate that progestin and vitamin D activate surrogate endpoint biomarkers relevant to chemoprevention in the endometrium in a prospective randomized trial in women undergoing hysterectomy for benign indications.

Spore in Skin Cancer

The overall goals of the University of Pittsburgh Skin Cancer SPORE are to improve the prevention and treatment of skin cancers, focusing upon melanoma and cutaneous T cell lymphoma. The SPORE program will consist of five translational research projects in skin cancer, four cores including an administrative core, a developmental research program and a career development program. The University of Pittsburgh Skin Cancer SPORE will use an interdisciplinary approach to meet its objectives by carrying out projects with co-investigators in basic, applied and clinical science. It is also organ-specific in that its approach and all projects will test hypotheses about skin cancer molecular biology and progression, tumor immunobiology and treatment. The long-term translational research projects will serve as the basis for improving the outcome of patients with lethal skin cancers

 

Recent Publications

Maxwell GL,  HoodBL, DayR, et al.  Proteomic analysis of stage I endometrial cancer tissue: Identification of proteins associated with oxidative processes  and inflammation.  Gynecol Oncol.2011. Jun 1;121(3):586-94.Epub 2011 Apr1.PMCID:PMC21458040

DayRS,McDade KK,Chandran UR, Lisovich A, ConradsTP, Hood BL,Kumar Kolli VS,KirchnerD, Litzi T, Maxwell GL. Identifier performance for integrating ranscriptomics and proteomics experimental results.  BMC Bioinformatics.2011May27;12(1):213.PMCID:PMC3124437

Lisovich,A. and Day,R.S. The IdMappingAnalysis package: critically comparing identifier maps retrieved from bioinformatics annotation resources.  R package Version 1.1.1., in Bioconductor Release 2.11, 2012.

Lisovich,A. and Day,R.S. The IdMappingRetrieval package inBioconductor: Collecting and caching identifier mappings from online sources. R package Version 1.3.1, in Bioconductor Release 2.9, 2011.

Wang M, Day RS.  Adaptive Bayesian design for phase I dose-finding trials using a joint model of response and toxicity.   2010 Jan.  J Bioppharm Stat. 20(1), 125-44.

Day R.  Failsafe automation of Phase II clinical trial interim monitoring for stopping rules. Clin Trials 2010, 7(1), 78-84.