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.
Publications
Full list of publications are also available through Google Scholar
Journal Publications
- Razi A, Afghah F, Singh S, Varadan V#, “Network-based enriched gene subnetwork identification: a game-theoretic approach,” Biomed Eng Comput Biol., 7:1-4, 2016. [PMID: 27081328] (# corresponding author)
- Venkitachalam S, Revoredo L, Varadan V, Fecteau RE, Ravi L, Lutterbaugh J, Markowitz SD, Willis JE, Gerken TA, Guda K, “Biochemical and functional characterization of glycosylation-associated mutational landscapes in colon cancer,” Scientific Reports, 6:23642, 2016. [PMID: 27004849]
- Varadan V#, Gilmore H, Miskimen KLS, Tuck D, Parsai S, Awadallal A, Krop IE, Winer EP, Bossuyt V, Somlo G, Abu-Khalaf M, Sikov W, Harris LN#, “Immune Signatures Following Single Dose Trastuzumab Predict Pathologic Response to Preoperative Trastuzumab and Chemotherapy in HER2-Positive Early Breast Cancer,” Clinical Cancer Research, 2016. [PMID: 26842237] (# corresponding author)
- Goel S, Wang Q, Watt AC, Tolaney SM, Dillon DA, Li W, Ramm S, Palmer AC, Yuzugullu H, Varadan V, Tuck D, Harris LN, Wong K, Liu S, Sicinski P, Winer EP, Krop IE & Zhao JJ. Overcoming Therapeutic Resistance in HER2-Positive Breast Cancers with CDK4/6 Inhibitors. Cancer Cell, 29(3):255-69, 2016. [PMID: 26977878].
- Varadan V†, Kamalakaran S, Gilmore H, Banerjee N, Janevski A, Miskimen KLS, Williams N, Basavanhalli A, Madabhushi A, Lezon-Geyda K, Bossuyt V, Lannin DR, Abu-Khalaf M, Sikov W, Dimitrova N, Harris LN†, “Brief-exposure to preoperative bevacizumab reveals a TGF-β signature predictive of response in HER2-negative breast cancers,” Int. Journal of Cancer, 2015. [PMID: 26284485] (†Corresponding author)
- Varadan V†, Singh S, Nosrati A, Ravi L, Lutterbaugh J, Barnholtz-Sloan JS, Markowitz SD, Willis JE, Guda K†, “ENVE: a novel computational framework characterizes copy-number mutational landscapes in colorectal cancers from African American patients.” Genome Medicine, 7(1): 69, 2015. [PMID: 26269717] (†Corresponding author)
- Guda K, Veigl ML*, Varadan V*, Nosrati A, Ravi L, Lutterbaugh J, Beard L, Willson JKV, Sedwick WD, Wang ZJ, Molyneaux N, Miron A, Adams MD, Elston RC, Markowitz SD, Willis JE, “Novel recurrently mutated genes in African American colon cancers,” Proc. Natl. Acad. Sciences, 112(4):1149-54,2015. [PMID: 25583493] (*equal contribution)
- Wrzeszczynski KO, Varadan V, Kamalakaran S, Levine DA, Dimitrova N, Lucito R, “Integrative prediction of gene function and platinum-free survival from genomic and epigenetic features in ovarian cancer,” Methods Mol. Biol., 1049:35-51, 2013. [PMID: 23769412]
- Kamalakaran S, Varadan V, Janevski A, Banerjee N, Tuck D, McCombie R, Dimitrova N, Harris LN, “Translating Next Generation Sequencing to practice: opportunities and necessary steps,” Molecular Oncology, 2013. [PMID: 23769412]
- Wang S, Wang L, Bayaxi N, Li J, Verhaegh W, Janevski A, Varadan V, et al, “A microRNA panel to discriminate carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissue”, Gut, 62(2):280-9, 2013. [PMID: 22535378]
- Tang MH, Varadan V, Kamalakaran S, Zhang MQ, Dimitrova N, Hicks J, “Major chromosomal breakpoint intervals in breast cancer co-localize with differentially methylated regions”, Frontiers in Oncology, 2:197, 2012. [PMID: 23293768]
- Janevski A, Varadan V, Kamalakaran S, et.al, “Effective normalization for copy number variation detection from whole genome sequencing”, BMC Genomics, 13 Suppl 6:S16, 2012. [PMID: 23134596]
- Varadan V, Mittal P, Vaske CJ, Benz SC, “The integration of biological pathway knowledge in cancer genomics: a review of existing computational approaches”, IEEE Signal Processing Magazine, 29(1):35-50, 2012.
- Wrzeszczynski KO, Varadan V, Byrnes J, Lum E, et al, “Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer”, PLoS One, 6(12):e28503, 2011. [PMID: 22174824]
- Kamalakaran S, Varadan V, Giercksky Russnes HE, Levy D, Kendall J, Janevski A et al. DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables, Molecular Oncology, 2011. [PMID: 21169070]
- Kim H, Watkinson J, Varadan V, Anastassiou D, “Multi-cancer computational analysis reveals invasion-associated variant of desmoplastic reaction involving INHBA, THBS2 and COL11A1”, BMC Medical Genomics, 3:51, 2010. [PMID: 21047417]
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, 2016 – A single dose of trastuzumab kick starts immune response in certain breast cancers
March 1, 2016 – Health 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