William Barry

 

William Barry

Nancy and Morris John Lurie Investigator
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Research

My general interests are statistical topics related to clinical and translational research in cancer, and methods for investigating molecular data derived from high-throughput biotechnologies. 

This has included the development of the statistical methodology and software, Significance Analysis of Function and Expression (SAFE), that defined several resampling-based approaches, and more recently analytical approximations to empirical tests, for the analysis of pathways in gene expression and other high dimensional genomic datasets.   By accounting for gene-gene correlation, statistical inferences are unbiased, in relation to other methods known to be grossly anti-conservative for transcriptomic data (see Gatti 2010).  SAFE has been implemented as a R package distributed through the Bioconductor repository, as a suite of analytical and graphic functions.  An on-going research project of mine is to extend the methodological framework of SAFE from exploratory investigations of gene-sets, to the evaluation of gene-signatures, as they are being developed and potentially translated into molecular biomarkers of disease.

As a Faculty Statistician of the Alliance for Clinical Trials in Oncology (formerly CALGB), I have lead the development, monitoring and analysis of multiple phase III clinical trials in the Breast Cancer Committee and retrospective/prospective biomarker validations in the Breast Correlative Science Committee. This includes CALGB 40502, Randomized Phase III Trial of Weekly Paclitaxel compared to Weekly Nanoparticle Albumin Bound Nab-Paclitaxel or Ixabepilone +/- Bevacizumab as First-Line Therapy for Locally Recurrent or Metastatic Breast Cancer where the primary clinical findings were recently presented at the 2012 ASCO Annual Meeting. 

As a methodological clinical research topic, I have developed Bayesian hierarchical models for the inclusion of integral biomarkers into randomized phase II studies. Under the Bayesian paradigm, prior selection allows one to control a gradual and seamless transition from randomized-blocks to marker-enrichment during the trial.  Compared to traditional staged designs within biomarker sub-populations, adaptation with a Bayesian hierarchical model is more robust against misspeci cation of marker prevalence, and has improved performance in identifying the sub-population where therapeutics are effective, which would better inform the target population of a subsequent phase III study.

 

Biography

Dr. Barry received a PhD in Biostatistics from the University of North Carolina School of Public Health in 2006, and a BS in Biology and BA in Physics from Duke University in 1996.  He joined DFCI in 2012 as the Nancy and Morris John Lurie Investigator at Dana-Faber Cancer Institute.  Dr. Barry has served since 2007 as Faculty Statistician of the Alliance for Clinical Trials in Oncology (formerly CALGB), a national clinical research group sponsored by the National Cancer Institute. From 2007 to 2012 Dr Barry was an Assistant Professor at Duke University, and during that time served as the Co-Director of the Duke SPORE in Breast Cancer, and as the Director of Bioinformatics Shared Resource to the Duke Cancer Institute.

 

Recent Publications

Hill KE, Kelly AD, Kuijjer ML, Barry W, Rattani A, Garbutt CC, Kissick H,
Janeway K, Perez-Atayde A, Goldsmith J, Gebhardt MC, Arredouani MS, Cote G, Hornicek F, Choy E, Duan Z, Quackenbush J, Haibe-Kains B, Spentzos D. An imprinted non-coding genomic cluster at 14q32 defines clinically relevant molecular subtypes in osteosarcoma across multiple independent datasets. J Hematol Oncol. 2017 May 15;10(1):107.

 

Wong SM, King T, Boileau JF, Barry WT, Golshan M. Population-Based Analysis of Breast Cancer Incidence and Survival Outcomes in Women Diagnosed with Lobular Carcinoma In Situ. Ann Surg Oncol. 2017 Apr 28. doi: 10.1245/s10434-017-5867-6.

 

Mandelblatt JS, Cai L, Luta G, Kimmick G, Clapp J, Isaacs C, Pitcher B, Barry W, Winer E, Sugarman S, Hudis C, Muss H, Cohen HJ, Hurria A. Frailty and long-term mortality of older breast cancer patients: CALGB 369901 (Alliance). Breast Cancer Res Treat. 2017 Mar 31.

 

Di Meglio A, Lin NU, Freedman RA, Barry WT, Winer EP, Vaz-Luis I. Patterns of Utilization of Imaging Studies and Serum Tumor Markers Among Patients With De Novo Metastatic Breast Cancer. J Natl Compr Canc Netw. 2017 Mar;15(3):316-324.

 

Vaz-Luis I, Lin NU, Keating NL, Barry WT, Winer EP, Freedman RA. Factors
Associated with Early Mortality Among Patients with De Novo Metastatic Breast Cancer: A Population-Based Study. Oncologist. 2017 Apr;22(4):386-393. 

 

Ventz S, Barry WT, Parmigiani G, Trippa L. Bayesian response-adaptive designs for basket trials. Biometrics. 2017 Feb 17.

 

Wong SM, Freedman RA, Sagara Y, Aydogan F, Barry WT, Golshan M. Growing Use of Contralateral Prophylactic Mastectomy Despite no Improvement in Long-term Survival for Invasive Breast Cancer. Ann Surg. 2017 Mar;265(3):581-589.

 

Kelley MJ, Jha G, Shoemaker D, Herndon JE 2nd, Gu L, Barry WT, Crawford J, Ready N. Phase II Study of Dasatinib in Previously Treated Patients with Advanced Non-Small Cell Lung Cancer. Cancer Invest. 2017 Jan 2;35(1):32-35.

 

Masko EM, Alfaqih MA, Solomon KR, Barry WT, Newgard CB, Muehlbauer MJ, Valilis NA, Phillips TE, Poulton SH, Freedland AR, Sun S, Dambal SK, Sanders SE, Macias E, Freeman MR, Dewhirst MW, Pizzo SV, Freedland SJ. Evidence for Feedback Regulation Following Cholesterol Lowering Therapy in a Prostate Cancer Xenograft Model. Prostate. 2017 Apr;77(5):446-457.

 

Jeselsohn R, Barry WT, Migliaccio I, Biagioni C, Zhao J, De Tribolet-Hardy J,
Guarducci C, Bonechi M, Laing N, Winer EP, Brown M, Leo AD, Malorni L.
TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor-Positive Breast Cancer. Clin Cancer Res. 2016 Dec 1;22(23):5755-5764.

 

Related Links

Alliance for Clinical Trials in Oncology 

 

Significance Analysis of Function and Expression

 

Keywords

clinical and translational cancer research, high-throughput biotechnologies