Stefano Monti, Ph.D.

Associate Professor

Education:2009_06_01_BroadPhotoID

Postdoc, Robotics Institute, Carnegie Mellon
Ph.D., Intelligent Systems Program, University of Pittsburgh
M.S., Intelligent Systems Program, University of Pittsburgh
B.S., Computer Science, University of Udine, Italy

General field of research:

Computational Biology & Genomics

Affiliations other than medicine:

Affiliate Faculty, Bioinformatics Program
Affiliate Member, Broad Institute of MIT & Harvard
Affiliate Member, Hariri Institute for Computing and Computational Science & Engineering

Contact information:

Office
72 East Concord St, E-613B

Office Phone
617-414-7031

Lab Phone
617-414-6960

Fax
617-414-6947

Email
smonti@bu.edu

Keywords:

Cancer, Translational Medicine, Bioinformatics, Machine Learning, Statistics

Summary of academic interest:

Monti’s research centers on the development and application of computational approaches for the dissection and characterization of the molecular machinery of human malignancies and their response to environmental insults. This multidisciplinary effort relies on the generation, analysis, and integration of high-throughput genomic data, and it is aimed at the identification of novel therapeutic targets and the development of diagnostic and prognostic markers.

Monti’s lab is involved in several projects, with collaborators in the School of Medicine, the School of Public Health, Harvard Medical School, and the Broad Institute. These projects include:

• Development of gene expression-based clinical classifiers for prognosis and clinical trial patient stratification.
• Molecular characterization of lymphoma malignancies: genome, transcriptome, epi-genome, and their cross-talk.
• Molecular characterization of the transcriptional program in lung cancer based on high-throughput RNA-sequencing.
• Computational genomic models of environmental and chemical carcinogenesis.

Recent publications:

Chiarle R, Zhang Y, Frock RL, Lewis SM, Molinie B, Ho Y, Myers DR, Choi VW, Compagno M, Malkin DJ, Neuberg D, Monti S, Giallourakis CC, Gostissa M, and Alt FW. Genome-Wide Translocation Sequencing Reveals Mechanisms of Chromosome Breaks and Rearrangements in B Cells. Cell, 147(1):107-119, 2011. PMCID: PMC3186939.

Green M, Monti S, et al., Signatures of murine B-cell development implicate Yy1 as a regulator of the germinal center-specific program. PNAS, 108(7), 2873-78, 2011. PMCID: PMC3041080.

Green M, Monti S, et al. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular Sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood, 116(17): 3268-3277, 2010.

The Cancer Genome Atlas (TCGA) Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 455(7216):1061-8, 2008.

Takeyama K, Monti S (co-first author), et al., Integrative Analysis Reveals 53BP1 Copy Loss and Decreased Expression in a Subset of Human Diffuse Large B-cell Lymphomas. Oncogene, 27(3): 318-322, 2008. PMID: 17637749.

Polo JM, Juszczynski P, Monti S, et al. A transcriptional signature with differential expression of BCL6 target genes accurately identifies BCL6-dependent diffuse large B-cell lymphomas. PNAS, 104(9): 3207-3212, 2007. PMCID: PMC1805543.

Monti, S., Savage, K.J., et al., Molecular profiling of diffuse large B-cell lymphoma identifies robust subtypes including one characterized by host inflammatory response. Blood, 2005. 105(5): p. 1851-1861. PMID: 15550490.

Monti, S., et al., Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data. Machine Learning, 2003. 52(1-2): p. 91-118.

Hartley SW, Monti S, Liu CT, Steinberg MH, and Sebastiani P (2012), Bayesian methods for multivariate modeling of pleiotropic SNP associations and genetic risk prediction, Frontiers in Genetics, 3:176.

Monti S, Chapuy B, Takeyama K, Rodig SJ, Yeda KT, Inguilizian H, Mermel C, Curie T, Dogan A, Kutok J, Beroukim R, Neuberg D, Habermann T, Getz G, Kung AL, Golub TR, and Shipp MA (2012) Integrative Analysis Reveals an Outcome-associated and Targetable Pattern of p53 and Cell Cycle Deregulation in Diffuse Large B-cell Lymphoma. Cancer Cell, 22(3):359-372.

Caro P, Kishan AU, Norberg E, Stanley I, Chapuy B, Ficarro SB, Polak K, Tondera D, Gounarides J, Hong Y, Zhou F, Green MR, Chen L, Monti S, Marto JA, Shipp MA, and Danial NN (2012), Metabolic Signatures Uncover Distinct Targets in Molecular Subsets of Diffuse Large B-Cell Lymphoma. Cancer Cell, In Press.

Chiarle R, Zhang Y, Frock RL, Lewis SM, Molinie B, Ho Y, Myers DR, Choi VW, Compagno M, Malkin DJ, Neuberg D, Monti S, Giallourakis CC, Gostissa M, and Alt FW (2011), Genome-Wide Translocation Sequencing Reveals Mechanisms of Chromosome Breaks and Rearrangements in B Cells. Cell, 147(1):107-119.

Green MR, Monti S, Dalla-Favera R, Pasqualucci L, Walsh NC, Schmidt-Supprian M, Kutok JL, et al. (2011). Signatures of murine B-cell development implicate Yy1 as a regulator of the germinal center-specific program. PNAS, 108(7), 2873–2878.

Green MR, Monti S, Rodig SJ, Juszczynski P, Currie T, O’Donnell E, Chapuy B, et al. (2010). Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood, 116(17), 3268–3277.

The Cancer Genome Atlas (TCGA) Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 455(7216):1061-8, 2008.

Polo JM, Juszczynski P, Monti S, Cerchietti L, Ye K, Greally JM, Shipp MA, et al. (2007). Transcriptional signature with differential expression of BCL6 target genes accurately identifies BCL6-dependent diffuse large B cell lymphomas. PNAS, 104(9), 3207–3212.

Monti S, Savage KJ, Kutok JL, Feuerhake F, Kurtin P, Mihm M, Wu B, et al. (2005). Molecular profiling of diffuse large B-cell lymphoma identifies robust subtypes including one characterized by host inflammatory response. Blood, 105(5), 1851–1861.

Monti S, Tamayo P, Mesirov J, & Golub T (2003). Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data. Machine Learning, 52(1 – 2), 91–118.