The emergence of multidimensional datasets characterizing genetic, epigenetic, and functional properties of large normal and tumor-related samples is creating unique opportunities for the systems-level dissection of mechanisms associated with malignant phenotypes. Coupled with novel high-throughput technologies and computational methodologies for the dissection, interrogation, and perturbation of genome-wide regulatory pathways, this will lead to highly efficient approaches for the rapid identification and validation of therapeutic targets, their small molecule inhibitors, and associated biomarkers. Columbia University investigators have pioneered systems-biology-based approaches for the dissection of regulatory networks in human malignancies and for their interrogation, using computational, RNAi, and small-molecule approaches, to identify molecular targets for therapeutic intervention. The goal of this project is the use and build upon a successful pipeline between the investigators labs for the discovery and validation of master regulator modules that implement functional bottlenecks that integrate aberrant signals from multiple genetic and epigenetic alterations, and thus, constitute natural dependencies (i.e., Achille's heel) for the tumor subtype. These will be characterized in terms of their synergistic behavior, driver genetic alterations, and druggable modulators. This pipeline will allow processing of a novel tumor phenotype every 18 to 24 months, yielding validated individual and synergistic targets that constitute either oncogene or non-oncogene dependencies of the tumor or that increase sensitivity to existing FDA approved or late-stage development compounds. Relevance: The identification of targets that abrogate tumorigenesis in the patient, are extensively biochemically characterized, chemically tractable, and highly penetrant constitutes one of the greatest challenges of cancer research. The goal of this proposal is to leverage an integrative computational and experimental pipeline for the systematic identification of novel potential targets that may inspire future development of therapeutic applications.

Public Health Relevance

The identification of targets that abrogate tumorigenesis in the patient, are extensively biochemically characterized, chemically tractable, and highly penetrant constitutes one of the greatest challenges of cancer research. By interrogating multidimensional datasets characterizing genetic, epigenetic, and functional properties of large normal and tumor-related samples, it is the aim of this proposal to leverage an integrative computational and experimental pipeline for the systematic identification of novel targets that may inspire future development of therapeutic applications.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA168426-02
Application #
8471675
Study Section
Special Emphasis Panel (ZCA1-SRLB-V (J1))
Program Officer
Gerhard, Daniela
Project Start
2012-06-01
Project End
2017-04-30
Budget Start
2013-05-01
Budget End
2014-04-30
Support Year
2
Fiscal Year
2013
Total Cost
$1,107,785
Indirect Cost
$383,333
Name
Columbia University (N.Y.)
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Rajbhandari, Presha; Lopez, Gonzalo; Capdevila, Claudia et al. (2018) Cross-Cohort Analysis Identifies a TEAD4-MYCN Positive Feedback Loop as the Core Regulatory Element of High-Risk Neuroblastoma. Cancer Discov 8:582-599
Aksoy, Bülent Arman; Dancík, Vlado; Smith, Kenneth et al. (2017) CTD2 Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network. Database (Oxford) 2017:
Sanchez-Martin, Marta; Ambesi-Impiombato, Alberto; Qin, Yue et al. (2017) Synergistic antileukemic therapies in NOTCH1-induced T-ALL. Proc Natl Acad Sci U S A 114:2006-2011
Walsh, Logan A; Alvarez, Mariano J; Sabio, Erich Y et al. (2017) An Integrated Systems Biology Approach Identifies TRIM25 as a Key Determinant of Breast Cancer Metastasis. Cell Rep 20:1623-1640
Califano, Andrea; Alvarez, Mariano J (2017) The recurrent architecture of tumour initiation, progression and drug sensitivity. Nat Rev Cancer 17:116-130
Dela Cruz, Filemon S; Diolaiti, Daniel; Turk, Andrew T et al. (2016) A case study of an integrative genomic and experimental therapeutic approach for rare tumors: identification of vulnerabilities in a pediatric poorly differentiated carcinoma. Genome Med 8:116
Alvarez, Mariano J; Shen, Yao; Giorgi, Federico M et al. (2016) Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nat Genet 48:838-47
Cancer Target Discovery and Development Network (2016) Transforming Big Data into Cancer-Relevant Insight: An Initial, Multi-Tier Approach to Assess Reproducibility and Relevance. Mol Cancer Res 14:675-82
Lachmann, Alexander; Giorgi, Federico M; Lopez, Gonzalo et al. (2016) ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information. Bioinformatics 32:2233-5
Yu, Jiyang; Silva, Jose; Califano, Andrea (2016) ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling. Bioinformatics 32:260-7

Showing the most recent 10 out of 25 publications