Vinay Varadan, PhD

Assistant Professor
Case Comprehensive Cancer Center
Member
GI Cancer Genetics Program
Case Comprehensive Cancer Center

BETRNet Roles: Project 1 Co-Investigator, Project 3 Co-Investigator

Research Information

Research Interests

  • Systems biology
  • Integrative Genomics
  • Bioinformatics
  • Machine Learning
  • Breast Cancer
  • Gastrointestinal Cancers
  • Ovarian Cancer

Research Projects

The overarching theme of my lab is the development and application of multi-scale systems biology approaches to delineate mechanisms of disease progression and to discover novel biomarkers of therapy response in cancer. As such, my role within the BETRNet is to employ robust systems biology approaches and large-scale multi-omics data integration to delineate druggable signaling networks driving Barrett’s Esophagus and Esophageal Adenocarcinoma.

The specific areas of our research focus are:

Systems Biology of Cancer

We are developing multidimensional frameworks that delineate complex cellular processes underlying disease progression through the integration of transcriptomic, genomic and/or epigenomic profiles for any given biological sample. Our goal is to develop computational methods based on information theory, Bayesian inference and deep learning to robustly infer genomic aberrations and network-level deregulations in cancer tissues. These methods are being applied to genomic profiles derived from primary cancer samples, single-cell sequencing data and genome-scale functional genomic screens.

Development of novel biomarkers of therapy response in breast cancer

We recently identified novel transcriptional signatures predictive of preoperative therapy response using large-scale RNA sequencing of HER2-negative breast tumor biopsies.  Ongoing studies are focused on integrative analysis of DNA and RNA sequencing profiles to discover signaling pathways and immune mechanisms underlying therapy response in HER2-positive breast cancers.

Integrative genomics to discover disease mechanisms in GI malignancies

Our ongoing collaboration with members of the Case GI SPORE has already resulted in the characterization of genome-wide mutation and copy-number landscapes in African American colon cancers. Current efforts involve applying our systems biology approach to discover molecular drivers of tumorigenesis in distinct pathologic subtypes of gastrointestinal cancers.

Varadan Lab Link

Publications

View All Publications

Full list of publications are also available through Google Scholar

Journal Publications

Full-length Peer-reviewed Conference Publications

  • Razi A, Banerjee N, Dimitrova N, Varadan V, "Non-Linear Bayesian Framework to Detect Functional Aberrations Driving Inconsistencies in Gene Regulatory Networks", IEEE Engg. in Medicine & Biology (EMBC), Italy, 2015.
  • Razi A, Afghah F, Varadan V, "Identifying Gene Subnetworks Associated with Clinical Outcome in Ovarian Cancer Using Network Based Coalition Game", IEEE Engg. in Medicine & Biology (EMBC), Italy, 2015.
  • Varadan V, Agrawal V, Harris L, Dimitrova N, "Identification and characterization of gene fusions in breast cancer - A non-trivial pursuit," IEEE Global Conf. on Signal and Information Processing (GlobalSIP), 3-5 Dec. 2013.
  • Varadan V, Janevski A, Kamalakaran S, Banerjee, N, Dimitrova, N, Harris LN, "Statistical assessment of gene fusion detection algorithms using RNA Sequencing Data," IEEE Stat. Sig. Proc. Workshop (SSP), 5-8 Aug. 2012.
  • Janevski A, Varadan V, Kamalakaran S, Banerjee N, Dimitrova N, "Comparative copy number variation from whole genome sequencing," 2011 IEEE Intl. Workshop on Genomic Sig. Proc. and Stat. (GENSIPS), 4-6 Dec. 2011.
  • Tang ME, Varadan V, Kamalakaran S, Zhang MQ, Dimitrova, N, Hicks J, "A method for finding novel associations between genome-wide copy number and DNA methylation patterns," 2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 4-6 Dec. 2011.
  • Banerjee N, Janevski A, Kamalakaran S, Varadan V, Lucito R, Dimitrova N, "Pathway and network analysis probing epigenetic influences on chemosensitivity in ovarian cancer," 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS),10-12 Nov. 2010.

Invited Talks and Podium Presentations

  • Varadan V, Miskimen K, Parsai S, Krop IE, Winer EP, Bossuyt V, Abu-Khalaf M, Sikov W, Harris L., “A discovery and validation set of breast cancer preoperative trials show an increase in Immune Score upon brief-exposure to trastuzumab and the HER2-enriched subtype predict response to combination chemotherapy and trastuzumab,” AACR Annual Meeting 2015 Minisymposium on Clinical Research, Philadelphia, PA, April 2015 (Oral presentation).
  • Varadan V, “Clinical Grade Gene Expression Signature Development using RNA-seq”, 2nd Annual The Clinical Genome Conference, San Francisco, June 2013 (Invited Talk).
  • Varadan V, Miskimen K, Kamalakaran S, Janevski A, Banerjee N, Williams N, Abu-Khalaf M, Sikov W, Dimitrova N, Harris L, “RNA-seq identifies a TGF-β signature that predicts response to preoperative bevacizumab in breast cancer”, AACR Annual Meeting 2013 Minisymposium on Novel Biomarkers of Drug Response, Washington DC, April 2013 (Oral presentation). 

Additional Information

In the News:

March 1, 2016A single dose of trastuzumab kick starts immune response in certain breast cancers

March 1, 2016Health Buzz: Single Dose of Trastuzumab Attacks Breast Cancer Tumors

September 17, 2015 - Biomarker may predict which HER2-negative breast cancer patients will benefit from targeted therapy

July 23, 2015 - Novel algorithm identifies DNA copy-number landscapes in African American colon cancers

January 12, 2015 - Researchers Identify New Gene Mutations Linked to Colorectal Cancer in African American Patients

Collaborations:

  • CCCC translational research groups for the identification of critical modulators of disease progression and therapy resistance
  • Computational Imaging CWRU’s Biomedical Engineering department to discover integrated imaging and genomic predictive of therapy response
  • Bioinformatics research group within Philips Healthcare focusing on integrative analysis of genomic and radiologic data for clinical decision support