Peter W. Laird


Director, USC Epigenome Center
Professor of Surgery
Professor of Biochemistry & Molecular Biology
Keck School of Medicine
USC / Norris Comprehensive Cancer Center

Research Topics

  • Epigenetics
  • Epigenomics
  • Computational Biology
  • Bioinformatics
  • Cancer
  • Cancer Genetics
  • Cancer Epigenetics
  • DNA Methylation
  • Gene Regulation/Transcription
  • Human/Mammalian Genetics

Research Images

Research Overview

Our goal is to develop a detailed understanding of the molecular basis of human disease, with a particular emphasis on cancer. Insight into the molecular basis of human disease will lead to improved improved treatments, earlier detection methods, and more accurate diagnoses. For the past few decades, cancer has been thought to be primarily a disease with a somatic and germline genetic origin. Our research has focused on the role of epigenetics in cancer. Epigenetics refers to stable phenotypes based on mechanisms other than primary DNA sequence. Epigenetic mechanisms include DNA methylation, histone modifications, DNA binding protein complexes, and chromatin remodeling. We have used a multi-disciplinary approach to understand the role of DNA methylation in cancer, relying on technology development, mechanistic studies in model organisms and cell culture, clinical and translational collaborations, and epidemiological studies. In recent years, our research has shifted to the generation and analysis of high-dimensional genetic and epigenetic data sets, since I became Director of the USC Epigenome Center in 2007. This includes the application of next-generation sequencing technology to single-basepair resolution whole genome DNA methylation analysis. We produce all epigenomic data for The Cancer Genome Atlas. We are currently building a bioinformatics team at the USC Epigenome Center dedicated to analyzing complex data and generating novel tools to advance this type of research. We are particularly interested in recruiting team members with interest or experience in genomic and epigenomic bioinformatics, computational biology and biostatistics.