Paul Spellman, PhD
I am interested in using genetic, genomic, and proteomic data tounderstand and model the biology of cancer and to develop methods toeffectively deploy therapeutic agents in the age of molecularly guidedmedicine. Members of my lab use a combination of conventional molecularbiology, high throughput genomic and proteomic assays, and bioinformaticanalyses in their work.
Cancer Genomics: My group participates in numerous collaborations to understand the effects of genome aberrations in cancer. These efforts include development of new methodologies for identifying changes in the cancer genome, systematic integration of multiple genomic data types (copy number, expression, and mutation) to better understand the process by which cancer develops, and the application of cell line systems as models for the genetic heterogeneity within cancers. Two major thrusts are the systematic characterization of cancer genomes as part of The Genome Data Analysis Network and the development and application of methods to reconstruct tumor evolution (Durinck et al. Cancer Discover, 2011, Gerstung et al. 2018 BioRxiv <https://www.biorxiv.org/content/early/2018/09/12/161562>).
My lab also works within the Cancer Early Detection Advanced Research Center (CEDAR) to develop approaches to understand, detect, and treat early lethal cancers. In CEDAR I am one of the Co-Directors of the overall effort. Projects in CEDAR that I participate in include developing cohorts for early detection, identify populations at risk for developing cancer, and understanding the early biology of breast cancers.
Finally, my lab uses genomic technologies to monitor the return of cancer and its evolution. Using ctDNA we can track tumor specific mutations after initial treatment (Butler et al. PLoS One 2015). We are deploying these approaches in clinical trials to alter treatment
P.T. Spellman, G. Sherlock, M. Q. Zhang, V. R. Iyer, K. Anders, M. B. Eisen, P. O. Brown, D. Botstein and B. Futcher. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell 9: 3273-97, 1998.
M. B. Eisen, P.T. Spellman, P. O. Brown and D. Botstein. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences, U.S.A. 95: 14863-8, 1998.
D. T. Ross, U. Scherf, M. B. Eisen, C. M. Perou, C. Rees, P. Spellman, V. Iyer, S. S. Jeffrey, M. Van de Rijn, M. Waltham, A. Pergamenschikov, J. C. Lee, D. Lashkari, D. Shalon, T. G. Myers, J. N. Weinstein, D. Botstein and P. O. Brown. Systematic variation in gene expression patterns in human cancer cell lines. Nature Genetics 24: 227-35, 2000.
R.M. Neve, K. Chin, J. Fridlyand, J. Yeh, F.L. Baehner, T. Fevr, L. Clark, N. Bayani, J.P. Coppe JP, F. Tong, T. Speed, P.T. Spellman, S. DeVries, A. Lapuk, N.J. Wang, W.L. Kuo, J.L. Stilwell, D. Pinkel, D.G. Albertson, F.M. Waldman, F. McCormick, R.B. Dickson, M.D. Johnson, M. Lippman, S. Ethier, A. Gazdar, J.W. Gray. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 6:515-27. 2006
Y. Wang, M. Moorhead, G. Karlin-Neumann, N. Wang, J. Ireland, S. Lin, C. Chen, L.M. Heiser, K. Chin, L. Esserman, J.W. Gray, P.T. Spellman. M. Faham. Performance of Molecular Inversion Probes (MIP) in Allele Copy Number Determination. Genome Biology. 8:R246. 2007
The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008
S. Durinck, J. Bullard, P.T. Spellman, S. Dudoit. GenomeGraphs: Integrated genomic visualization with R. BMC Bioinformatics. 2009
H. Bengtsson, A. Ray, P. Spellman, T.P. Speed. A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods. Bioinformatics. 2009
L.M. Heiser, N.J. Wang, C.L. Talcott, K.R. Laderoute, M. Knapp, Y. Guan, Z. Hu, S. Ziyad, B.L. Weber, S Laquerre, J.R. Jackson, R.F. Wooster, W.L. Kuo, J.W. Gray, P.T. Spellman. Genome Biology. 2009
S. Durinck, P.T. Spellman, W. Huber. Mapping Identifiers for the Integration of Genomic Datasets with the R/Bioconductor package biomaRt. Nature Protocols. 2009
International Cancer Genome Consortium. International network of cancer genome projects. Nature. 2010.
E.A. Collisson, A. Sadanandam, P. Olson, W.J. Gibb, M. Truitt, S. Gu, J. Cooc, J. Weinkle, G.E. Kim, L. Jakkula, H.S. Feiler, A.H. Koh, A.B. Olshen, K.L. Danenberg, M.A. Tempero, P.T. Spellman, D. Hanahan, and J.W. Gray. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat. Med. 2011
TCGA Network, P.T. Spellman corresponding author. Integrative Genomic Analyses of Ovarian Carcinoma. Nature. 2011
S. Durinck, C. Ho, N.J. Wang, W. Liao, L.R. Jakkula, E.A. Collisson, J. Pons, S.W. Chan, E.T. Lam, C. Chu, K. Park, S.W. Hong, J.S. Hur, N. Huh, I.M. Neuhaus, S.S. Yu, R.T. Grekin, T.M. Mauro, J.E. Cleaver, P.Y. Kwok, P.E. LeBoit, G. Getz, K. Cibulskis, J.C. Aster, H. Huang, E. Purdom, J. Li, L. Bolund, S. Arron, J.W. Gray, P.T. Spellman*, R.J. Cho* (*corresponding authors). Temporal Dissection of Tumorigenesis in Primary Cancers. Cancer Discovery. 2011
L.M. Heiser, A. Sadanandam, W.L. Kuo, S.C. Benz, T.C. Goldstein, S. Ng, W.J. Gibb, N.J. Wang, S. Ziyad, F. Tong, N. Bayani, Z Hu, J.I. Billig, A. Dueregger, S. Lewis, L. Jakkula, J.E. Korkola, S. Durinck, F. Pepin, Y. Guan, E. Purdom, P. Neuvial, H. Bengtsson, K.W. Wood, P.G. Smith, L.T. Vassilev, B.T. Hennessy, J. Greshock, K.E. Bachman, M.A. Hardwicke, J.W. Park, L.J. Marton, D.M. Wolf, E.A. Collisson, R.M. Neve, G.B. Mills, T.P. Speed, H.S. Feiler, R.F. Wooster, D. Haussler, J.M. Stuart, J.W. Gray, P.T. Spellman. Subtype and pathway specific responses to anti-cancer compounds in breast cancer. PNAS. 2012.
Griffith OL, Pepin F, Enache OM, Heiser LM, Collisson EA, Spellman PT, Gray JW. A robust prognostic signature for hormone-positive node-negative breast cancer. Genome Med. 2013