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Systems Biology investigators

Michael Becich, MD, PhD
5607 Baum Boulevard
Room 521
Pittsburgh PA
Research Interests and Keywords:
  • Translational bioinformatics
  • oncology informatics
  • tissue banking and pathology informatics
  • prostate tumor cell biology
  • research resource development
  • content-based image retrieval and digital libraries
Uma Chandran, PhD, MSIS
Room 513
5607 Baum Boulevard
Pittsburgh PA
Research Interests and Keywords:
  • Bioinformatics
Adrian Lee, PhD
Magee-Womens Research Institute
204 Craft Avenue, A412
Pittsburgh PA
Phone: 412-641-7739
Research Interests and Keywords:
  • Breast cancer
  • steroid receptors
  • growth factor signaling
  • estrogen receptor
  • progesterone receptor
  • insulin-like growth factor
  • tumor heterogeneity
The goal of the Lee laboratory is translational breast cancer research. The laboratory has two main areas of focus. The first involves targeting the insulin-like growth factor pathway in breast cancer. A major emphasis is upon the downstream signaling intermediates the insulin receptor substrates (IRSs) analyzing interactions with steroid hormone receptors (ER and PR), role in normal mouse mammary gland development, mechanisms of transformation of mammary epithelial cells in vitro and in mouse models, and roles in human breast cancer. The second area of research is studies on tumor heterogeneity and molecular changes during progression, with a particular focus on DNA and RNA structural rearrangements. The laboratory participated in the first comprehensive report of structural rearrangements in a breast cancer cell line (MCF7) and reported on a novel massively parallel fosmid-based mate-pair assay for determining structural rearrangements. This work focuses on different tumor areas, or tumors from different parts of the body (obtained via rapid autopsy) to identify novel changes that may offer therapeutic insight. In addition, the University of Pittsburgh is the largest contributor of tissue to The Cancer Genome Atlas (TCGA), and many results are validated in these index cases.
George Tseng
Da Yang, MD, PhD
308 Pavilion
Pittsburgh PA
Phone: 412-383-5145
Research Interests and Keywords:
  • Drug resistance
  • genomics
  • epigenetics
  • cancer therapeutics
  • biomarkers
  • personalized cancer medicine
The research of Dr. Yang's laboratory focuses on using integrated genomic and functional studies to identify mechanisms of resistance to cancer therapeutics, and to develop novel approaches and biomarkers to enable personalized cancer medicine. Currently, ongoing work involves: 1) mechanistic studies of resistance to cancer therapeutics, especially targeted therapy for pathways with the most prevalent genomic alterations in human solid tumors; and 2) characterization of genetic and epigenetic alterations of non protein-coding components (ncRNAs) of the genome, such as miRNA and lncRNA genes in solid tumors. His approaches have proved successful in several instances, including the identification of miR-506 as a tumor suppressor that inhibits epithelial-to-mesenchymal transition (EMT) and cell cycle pathways, and the discovery of BRCA2 gene mutations that lead to genome instability and cisplatin response in ovarian cancer.
Carlos Camacho
University of Pittsburgh, Room 3077
3501 Fifth Avenue
Pittsburgh PA
Phone: 412-648-7776
Gregory Cooper
Xiaosong Wang, MD, PhD
Hillman Cancer Center, Room G.5a
5117 Centre Ave.
Pittsburgh PA
Phone: 412-623-1587
Research Interests and Keywords:
  • Cancer genomics
  • integrative bioinformatics
  • cancer genetics
  • cancer cell biology
The Cancer Genome Project Initiatives have generated a daunting amount of genomic and deep sequencing data for tens of thousands of human tumors. An overarching challenge of this post-genomic era is to identify and recognize the cancer drivers and targets from these big genomic data, especially those that can be therapeutically targeted to improve the clinical outcome. The mission of our lab is to apply a multiple disciplinary approach inclusive of integrative bioinformatics, cancer genetics, molecular cancer biology, and translational studies to identify driving genetic aberrations and appropriate cancer targets on the basis of deep sequencing and genomic profiling datasets. Our research projects are composed of both computational and laboratory components. Our dry lab researches focus on developing innovative and integrative computational technologies to discover causal genetic and epigenetic alternations, viable therapeutic targets, and predictive biomarkers in cancer. In particular, we have innovated a concept signature (ConSig) analysis that employs molecular fingerprints for high-throughput interpretation of the biological function of candidate targets in cancer (Nature biotech 2009). In addition, we have formulated a 'fusion breakpoint principle' that describes the intragenic copy number aberrations characteristic of recurrent gene fusions, thus enabling genome-wide detection of copy number breakpoints generating gene fusions. Based on these principles we further developed a powerful bioinformatics tool called 'Fusion Zoom' that identifies recurrent pathological gene fusions via integrative analyses of RNA sequencing, copy number, and gene concept datasets (Nature Commun 2014). Further, we have discovered the crucial application of ConSig analysis in revealing the primary oncogenes targeted by genomic amplifications, and developed a new integrative genomic analysis called 'ConSig-Amp' to detect viable cancer targets. Moreover we also developed an integrated computational-experimental approach called HEPA-PARSE for the genome-wide detection of clinically important tumor specific antigen (TSA) targets (Cancer Research 2012). Our wet lab researches focus on experimentally characterizing individual genetic and epigenetic aberrations in breast cancer such as recurrent gene fusions, genomic amplifications, and epimutations, as well as qualifying viable cancer targets and predictive biomarkers for the development of precision therapeutics in breast cancer. Our current disease focus is clinically intractable breast cancers, such as luminal B or basal-like tumors. In particular, by applying the FusionZoom analysis to the RNAseq and copy number data from The Cancer Genome Atlas, we have discovered a novel recurrent gene fusion involving the estrogen receptor gene in a subset of breast cancers. This fusion called ESR1-CCDC170 is preferentially present in 6-8% of luminal B tumors -- a more aggressive subtype of estrogen receptor positive breast cancer. To date, this is the first and most frequent gene fusion yet reported in this tumor entity (Nature Commun. 2014). We are now assessing the druggability of this fusion with the goal of developing effective targeted therapy against this genomic target. We expect that our new discoveries will yield novel insights into the recurring genetic abnormalities leading to breast cancer initiation, progression, and therapeutic resistance, and establish viable targets for effective intervention.