1
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Mundi PS, Dela Cruz FS, Grunn A, Diolaiti D, Mauguen A, Rainey AR, Guillan K, Siddiquee A, You D, Realubit R, Karan C, Ortiz MV, Douglass EF, Accordino M, Mistretta S, Brogan F, Bruce JN, Caescu CI, Carvajal RD, Crew KD, Decastro G, Heaney M, Henick BS, Hershman DL, Hou JY, Iwamoto FM, Jurcic JG, Kiran RP, Kluger MD, Kreisl T, Lamanna N, Lassman AB, Lim EA, Manji GA, McKhann GM, McKiernan JM, Neugut AI, Olive KP, Rosenblat T, Schwartz GK, Shu CA, Sisti MB, Tergas A, Vattakalam RM, Welch M, Wenske S, Wright JD, Hibshoosh H, Kalinsky K, Aburi M, Sims PA, Alvarez MJ, Kung AL, Califano A. A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies. Cancer Discov 2023; 13:1386-1407. [PMID: 37061969 PMCID: PMC10239356 DOI: 10.1158/2159-8290.cd-22-1020] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 01/14/2023] [Accepted: 03/14/2023] [Indexed: 04/17/2023]
Abstract
Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study. SIGNIFICANCE Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.
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Affiliation(s)
- Prabhjot S. Mundi
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Filemon S. Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Adina Grunn
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Daniel Diolaiti
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Audrey Mauguen
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Allison R. Rainey
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Kristina Guillan
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Armaan Siddiquee
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Daoqi You
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Ronald Realubit
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Charles Karan
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Michael V. Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Eugene F. Douglass
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Melissa Accordino
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Suzanne Mistretta
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Frances Brogan
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Jeffrey N. Bruce
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurological Surgery, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
| | - Cristina I. Caescu
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Richard D. Carvajal
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Katherine D Crew
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Guarionex Decastro
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Urology, Columbia University Irving Medical Center, 160 Fort Washington Ave, New York, NY USA 10032
| | - Mark Heaney
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Brian S Henick
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Dawn L Hershman
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
- Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th St. NY, NY 10032
| | - June Y. Hou
- Department of Obstetrics & Gynecology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Fabio M. Iwamoto
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurology, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
| | - Joseph G. Jurcic
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Ravi P. Kiran
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Surgery, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Michael D Kluger
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Surgery, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Teri Kreisl
- Novartis Five Cambridge, MA 02142, United States
| | - Nicole Lamanna
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Andrew B. Lassman
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurology, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
| | - Emerson A. Lim
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Gulam A. Manji
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Guy M McKhann
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurological Surgery, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
| | - James M. McKiernan
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Urology, Columbia University Irving Medical Center, 160 Fort Washington Ave, New York, NY USA 10032
| | - Alfred I Neugut
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
- Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th St. NY, NY 10032
| | - Kenneth P. Olive
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Todd Rosenblat
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Gary K. Schwartz
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Catherine A Shu
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Michael B. Sisti
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurological Surgery, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
- Department of Otolaryngology Head and Neck Surgery, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
- Department of Radiation Oncology, Columbia University Irving Medical Center, 161 Fort Washington Avenue, New York, NY 10032, United States
| | - Ana Tergas
- Department of Obstetrics & Gynecology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Reena M Vattakalam
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Obstetrics & Gynecology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Mary Welch
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Neurology, Columbia University Irving Medical Center, 710 W 168th Street, New York, NY USA 10032
| | - Sven Wenske
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Urology, Columbia University Irving Medical Center, 160 Fort Washington Ave, New York, NY USA 10032
| | - Jason D. Wright
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Obstetrics & Gynecology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
| | - Hanina Hibshoosh
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
| | - Kevin Kalinsky
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Winship Cancer Institute of Emory University and Department of Hematology and Medical Oncology, Emory University School of Medicine, 1365-C Clifton Road NE, Atlanta, GA 30322, United States
| | - Mahalaxmi Aburi
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
| | - Peter A. Sims
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, 701 W 168th Street, New York, NY USA 10032
| | - Mariano J. Alvarez
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- DarwinHealth Inc. New York
| | - Andrew L. Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY USA 10065
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave, New York, NY USA 10032
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY USA 10032
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, 701 W 168th Street, New York, NY USA 10032
- Department of Biomedical Informatics, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY USA 10032
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2
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Hughes EA, Zieliński R, Ray AE, Priebe W, Douglass EF. Development of a Novel Tool to Demystify Drug Distribution at Tissue-Blood Barriers. Chembiochem 2023:e202200804. [PMID: 36951632 DOI: 10.1002/cbic.202200804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 03/24/2023]
Abstract
Tissue endothelial cells express ABC-transporter enzymes that change the concentration of small molecule within different tissue-compartments. These "blood-tissue barriers" have been shown to directly affect the efficacy and toxicity of anti-cancer, anti-microbial, psychiatric, and anti-epileptic drugs. Currently this phenomenon is best studied for the blood-brain barrier but remains enigmatic for most other tissues. In addition, canonical pharmacokinetic theory specifically assumes an equal concentration of free drug within all tissue compartments. Inspired by Lipinski's "rule of 5," we here clarify current knowledge on drug-tissue distribution by: (1) curating the in vivo literature on 73 drugs across 23 tissues and (2) developing two graphical web-based applications to visually describe and interpret data. This curated in vivo dataset and visualization tools enabled us to achieve new insights into the logic of the barrier-tissues organization and showed remarkable correspondence to whole-body imaging of radiolabeled molecules.
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Affiliation(s)
- Elizabeth A Hughes
- University of Georgia College of Pharmacy, Pharmaceutical and Biomedical Sciences, 240 West Green Street, 30602-0001, Athens, UNITED STATES
| | - Rafał Zieliński
- The University of Texas MD Anderson Cancer Center, Department of Experimental Therapeutics, 1901 East Rd., 77054, Houston, UNITED STATES
| | - Ashley E Ray
- University of Georgia College of Pharmacy, Pharmaceutical and Biomedical Sciences, 240 W Green St, 30602, Athens, UNITED STATES
| | - Waldemar Priebe
- The University of Texas MD Anderson Cancer Center, Department of Experimental Therapeutics, 1901 East Rd., 77054, Houston, UNITED STATES
| | - Eugene F Douglass
- University of Georgia College of Pharmacy, Pharmaceutical and Biomedical Sciences, 240 W Green St, 30602, Athens, UNITED STATES
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3
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Vasciaveo A, Arriaga JM, de Almeida FN, Zou M, Douglass EF, Picech F, Shibata M, Rodriguez-Calero A, de Brot S, Mitrofanova A, Chua CW, Karan C, Realubit R, Pampou S, Kim JY, Afari SN, Mukhammadov T, Zanella L, Corey E, Alvarez MJ, Rubin MA, Shen MM, Califano A, Abate-Shen C. OncoLoop: A Network-Based Precision Cancer Medicine Framework. Cancer Discov 2023; 13:386-409. [PMID: 36374194 PMCID: PMC9905319 DOI: 10.1158/2159-8290.cd-22-0342] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 08/22/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022]
Abstract
Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide. SIGNIFICANCE OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.
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Affiliation(s)
- Alessandro Vasciaveo
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
| | - Juan Martín Arriaga
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Francisca Nunes de Almeida
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Min Zou
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Eugene F. Douglass
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
| | - Florencia Picech
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Maho Shibata
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Genetics and Development, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Department of Urology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Antonio Rodriguez-Calero
- Department for Biomedical Research, University of Bern, Bern, Switzerland 3008
- Institute of Pathology, University of Bern and Inselspital, Bern, Switzerland 3008
| | - Simone de Brot
- COMPATH, Institute of Animal Pathology, University of Bern, Switzerland 3012
| | - Antonina Mitrofanova
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
| | - Chee Wai Chua
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Genetics and Development, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Department of Urology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Charles Karan
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Ronald Realubit
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Sergey Pampou
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Jaime Y. Kim
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Stephanie N. Afari
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Timur Mukhammadov
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
| | - Luca Zanella
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
| | - Eva Corey
- Department of Urology, University of Washington, Seattle, WA USA 98195
| | - Mariano J. Alvarez
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- DarwinHealth Inc, New York, NY
| | - Mark A. Rubin
- Department for Biomedical Research, University of Bern, Bern, Switzerland 3008
- Bern Center for Precision Medicine (BCPM) Bern, Switzerland 3008
| | - Michael M. Shen
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Genetics and Development, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Department of Urology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, USA 10032
| | - Andrea Califano
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, USA 10032
- Department of Biochemistry & Molecular Biophysics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
| | - Cory Abate-Shen
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, USA 10032
- Department of Urology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, USA 10032
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY USA 10032
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4
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Vasciaveo A, Zou M, Arriaga JM, de Almeida FN, Douglass EF, Shen M, Califano A, Abate-Shen C. Abstract 1905: Accelerating clinically-translatable discoveries using a network- and RNA-based precision-oncology framework. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-1905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Despite recent advances, prioritizing therapy at the individual patient level remains challenging. In fact, inter-patient tumor heterogeneity remains one of the major challenges in cancer therapy, making it difficult to optimize available treatments on an individual patient basis. Likewise, the systematic prediction of drug sensitivity in vivo is still a major challenge in translational research, where targeted therapeutics are currently selected based on the presence of either actionable oncogene dependencies or aberrant cellular mechanisms. A further challenge is the limited availability of models that faithfully recapitulate the biology, complexity, and heterogeneity of human tumors, including their interaction with a conserved microenvironment and a competent immune system.
To address these challenges, we introduce OncoLoop, a highly-generalizable, network-based precision medicine framework to triangulate between available mouse models, human tumors, and large-scale drug perturbational assays with in vivo validation to predict personalized treatment. OncoLoop requires only transcriptomic data (i.e., RNA-seq profiles) and leverages regulatory network analysis to (a) identify cognate models based on conservation of patient-specific Master Regulator (MR) proteins and (b) prioritize drugs based on their ability to invert the activity of MR proteins (MR-inverters), using drug perturbation profiles in cognate cell lines. As proof-of-concept, we applied OncoLoop to prostate cancer using a series of genetically engineered mouse models (GEMMs) that capture a broad range of phenotypes, including metastatic, castration-resistant and neuroendocrine disease. Indeed, >70% of patients in published cohorts had at least one high-fidelity matched GEMM. Drugs targeting shared Master Regulator dependencies of a patient and its cognate GEMM(s) were predicted using perturbational profiles of >300 drugs in MR-matched cell lines, resulting in an 80% validation rate in GEMM allografts and human xenografts. This network-based approach is highly generalized and can be applied to both cancer and non-cancer-related contexts.
Citation Format: Alessandro Vasciaveo, Min Zou, Juan M. Arriaga, Francisca Nunes de Almeida, Eugene F. Douglass, Michael Shen, Andrea Califano, Cory Abate-Shen. Accelerating clinically-translatable discoveries using a network- and RNA-based precision-oncology framework [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1905.
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Affiliation(s)
| | - Min Zou
- 1Columbia University, New York, NY
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5
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Douglass EF, Allaway RJ, Szalai B, Wang W, Tian T, Fernández-Torras A, Realubit R, Karan C, Zheng S, Pessia A, Tanoli Z, Jafari M, Wan F, Li S, Xiong Y, Duran-Frigola M, Bertoni M, Badia-i-Mompel P, Mateo L, Guitart-Pla O, Chung V, Tang J, Zeng J, Aloy P, Saez-Rodriguez J, Guinney J, Gerhard DS, Califano A. A community challenge for a pancancer drug mechanism of action inference from perturbational profile data. Cell Rep Med 2022; 3:100492. [PMID: 35106508 PMCID: PMC8784774 DOI: 10.1016/j.xcrm.2021.100492] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 08/08/2021] [Accepted: 12/15/2021] [Indexed: 12/14/2022]
Abstract
The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among ∼1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessments of drug mechanisms of action. Drug-perturbed RNA sequencing data can be used to identify drug targets Technology-based drug-target definitions often subsume literature definitions Literature and screening datasets provide complementary information on drug mechanisms
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Affiliation(s)
- Eugene F. Douglass
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave., New York, NY 10032, USA
- Pharmaceutical and Biomedical Sciences, University of Georgia, 250 W. Green Street, Athens, GA 30602, USA
| | - Robert J. Allaway
- Computational Oncology Group, Sage Bionetworks, 2901 Third Ave., Ste 330, Seattle, WA 98121, USA
| | - Bence Szalai
- Semmelweis University, Faculty of Medicine, Department of Physiology, Budapest, Hungary
| | - Wenyu Wang
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Tingzhong Tian
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China
| | - Adrià Fernández-Torras
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Ron Realubit
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave., New York, NY 10032, USA
| | - Charles Karan
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave., New York, NY 10032, USA
| | - Shuyu Zheng
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Alberto Pessia
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ziaurrehman Tanoli
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Mohieddin Jafari
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Fangping Wan
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China
| | - Shuya Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China
| | - Yuanpeng Xiong
- Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
| | - Miquel Duran-Frigola
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Martino Bertoni
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Pau Badia-i-Mompel
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Lídia Mateo
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Oriol Guitart-Pla
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Verena Chung
- Computational Oncology Group, Sage Bionetworks, 2901 Third Ave., Ste 330, Seattle, WA 98121, USA
| | | | - Jing Tang
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing 100084, China
| | - Patrick Aloy
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
| | - Julio Saez-Rodriguez
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Justin Guinney
- Computational Oncology Group, Sage Bionetworks, 2901 Third Ave., Ste 330, Seattle, WA 98121, USA
| | - Daniela S. Gerhard
- Office of Cancer Genomics, National Cancer Institute, NIH, Bethesda, MD 20892, USA
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave., New York, NY 10032, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, 1130 Saint Nicholas Ave., New York, NY 10032, USA
- Department of Medicine, Columbia University Irving Medical Center, 630 W 168th Street, New York, NY 10032, USA
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, 701 W 168th Street, New York, NY 10032, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY 10032, USA
- Corresponding author
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6
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Paull EO, Aytes A, Jones SJ, Subramaniam PS, Giorgi FM, Douglass EF, Tagore S, Chu B, Vasciaveo A, Zheng S, Verhaak R, Abate-Shen C, Alvarez MJ, Califano A. A modular master regulator landscape controls cancer transcriptional identity. Cell 2021; 184:334-351.e20. [PMID: 33434495 PMCID: PMC8103356 DOI: 10.1016/j.cell.2020.11.045] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 08/06/2020] [Accepted: 11/25/2020] [Indexed: 02/06/2023]
Abstract
Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.
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Affiliation(s)
- Evan O Paull
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alvaro Aytes
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Bellvitge Institute for Biomedical Research, L'Hospitalet de Llobregat, Barcelona 08908, Spain; Program Against Cancer Therapeutics Resistance (ProCURE), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, L'Hospitalet de Llobregat, Barcelona 08908, Spain
| | - Sunny J Jones
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Prem S Subramaniam
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Federico M Giorgi
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna 40126, Italy
| | - Eugene F Douglass
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Somnath Tagore
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Brennan Chu
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alessandro Vasciaveo
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Siyuan Zheng
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Roel Verhaak
- Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Cory Abate-Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Molecular Pharmacology and Therapeutics, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Urology, Columbia University Irving Medical Center, New York, NY 10032, USA.
| | - Mariano J Alvarez
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; DarwinHealth, Inc. New York, NY 10018, USA.
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; DarwinHealth, Inc. New York, NY 10018, USA; Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA.
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7
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Douglass EF. Bridging “Big Data” and Mechanistic Insight To Enable Precision Medicine. Chembiochem 2020; 21:3047-3050. [DOI: 10.1002/cbic.202000494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/07/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Eugene F. Douglass
- Department of Systems Biology Columbia University 1130 St Nicholas Ave New York, NY 10032 USA
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8
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Laise P, Bosker G, Sun X, Shen Y, Douglass EF, Karan C, Realubit RB, Pampou S, Califano A, Alvarez MJ. The Host Cell ViroCheckpoint: Identification and Pharmacologic Targeting of Novel Mechanistic Determinants of Coronavirus-Mediated Hijacked Cell States. bioRxiv 2020:2020.05.12.091256. [PMID: 32511361 PMCID: PMC7263489 DOI: 10.1101/2020.05.12.091256] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Most antiviral agents are designed to target virus-specific proteins and mechanisms rather than the host cell proteins that are critically dysregulated following virus-mediated reprogramming of the host cell transcriptional state. To overcome these limitations, we propose that elucidation and pharmacologic targeting of host cell Master Regulator proteins-whose aberrant activities govern the reprogramed state of coronavirus-infected cells-presents unique opportunities to develop novel mechanism-based therapeutic approaches to antiviral therapy, either as monotherapy or as a complement to established treatments. Specifically, we propose that a small module of host cell Master Regulator proteins (ViroCheckpoint) is hijacked by the virus to support its efficient replication and release. Conventional methodologies are not well suited to elucidate these potentially targetable proteins. By using the VIPER network-based algorithm, we successfully interrogated 12h, 24h, and 48h signatures from Calu-3 lung adenocarcinoma cells infected with SARS-CoV, to elucidate the time-dependent reprogramming of host cells and associated Master Regulator proteins. We used the NYS CLIA-certified Darwin OncoTreat algorithm, with an existing database of RNASeq profiles following cell perturbation with 133 FDA-approved and 195 late-stage experimental compounds, to identify drugs capable of virtually abrogating the virus-induced Master Regulator signature. This approach to drug prioritization and repurposing can be trivially extended to other viral pathogens, including SARS-CoV-2, as soon as the relevant infection signature becomes available.
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Affiliation(s)
- Pasquale Laise
- DarwinHealth Inc, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | | | | | - Yao Shen
- DarwinHealth Inc, New York, NY, USA
| | - Eugene F Douglass
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Charles Karan
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Ronald B Realubit
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sergey Pampou
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Mariano J Alvarez
- DarwinHealth Inc, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
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9
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Ding H, Douglass EF, Sonabend AM, Mela A, Bose S, Gonzalez C, Canoll PD, Sims PA, Alvarez MJ, Califano A. Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm. Nat Commun 2018; 9:1471. [PMID: 29662057 PMCID: PMC5902599 DOI: 10.1038/s41467-018-03843-3] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 03/13/2018] [Indexed: 12/30/2022] Open
Abstract
We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack molecular profiles necessary for interactome inference (orphan tissues), or, as for single cells isolated from heterogeneous samples, their tissue context may be undetermined. To address this problem, we introduce metaVIPER, an algorithm designed to assess protein activity in tissue-independent fashion by integrative analysis of multiple, non-tissue-matched interactomes. This assumes that transcriptional targets of each protein will be recapitulated by one or more available interactomes. We confirm the algorithm's value in assessing protein dysregulation induced by somatic mutations, as well as in assessing protein activity in orphan tissues and, most critically, in single cells, thus allowing transformation of noisy and potentially biased RNA-Seq signatures into reproducible protein-activity signatures.
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Affiliation(s)
- Hongxu Ding
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biological Sciences, Columbia University, New York, NY, 10027, USA
| | - Eugene F Douglass
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Adam M Sonabend
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Angeliki Mela
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Sayantan Bose
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- GlaxoSmithKline, King of Prussia, PA, 19406, USA
| | - Christian Gonzalez
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Amsterdam Neuroscience, Amsterdam, 1081, The Netherlands
| | - Peter D Canoll
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Peter A Sims
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Mariano J Alvarez
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA.
- DarwinHealth Inc, New York, NY, 10032, USA.
| | - Andrea Califano
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA.
- DarwinHealth Inc, New York, NY, 10032, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA.
- J.P. Sulzberger Columbia Genome Center, Columbia University, New York, NY, 10032, USA.
- Department of Biomedical Informatics, Columbia University, New York, NY, 10032, USA.
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA.
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10
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Douglass EF, Avci H, Boy R, Rojas OJ, Kotek R. A Review of Cellulose and Cellulose Blends for Preparation of Bio-derived and Conventional Membranes, Nanostructured Thin Films, and Composites. POLYM REV 2017. [DOI: 10.1080/15583724.2016.1269124] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Eugene F. Douglass
- Textile Engineering, Chemistry and Science Department, College of Textiles, NCSU, Raleigh, North Carolina
| | - Huseyin Avci
- Metallurgical and Materials Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey
| | - Ramiz Boy
- Textile Engineering, Chemistry and Science Department, College of Textiles, NCSU, Raleigh, North Carolina
| | - Orlando J. Rojas
- Department of Forest Products Technology, Aalto University, Espoo, Finland
- Department of Forest Biomaterials, NCSU, Raleigh, North Carolina
| | - Richard Kotek
- Textile Engineering, Chemistry and Science Department, College of Textiles, NCSU, Raleigh, North Carolina
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11
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Santori FR, Huang P, van de Pavert SA, Douglass EF, Leaver DJ, Haubrich BA, Keber R, Lorbek G, Konijn T, Rosales BN, Rozman D, Horvat S, Rahier A, Mebius RE, Rastinejad F, Nes WD, Littman DR. Identification of natural RORγ ligands that regulate the development of lymphoid cells. Cell Metab 2015; 21:286-298. [PMID: 25651181 PMCID: PMC4317570 DOI: 10.1016/j.cmet.2015.01.004] [Citation(s) in RCA: 172] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 12/16/2014] [Accepted: 01/12/2015] [Indexed: 12/11/2022]
Abstract
Mice deficient in the nuclear hormone receptor RORγt have defective development of thymocytes, lymphoid organs, Th17 cells, and type 3 innate lymphoid cells. RORγt binds to oxysterols derived from cholesterol catabolism, but it is not clear whether these are its natural ligands. Here, we show that sterol lipids are necessary and sufficient to drive RORγt-dependent transcription. We combined overexpression, RNAi, and genetic deletion of metabolic enzymes to study RORγ-dependent transcription. Our results are consistent with the RORγt ligand(s) being a cholesterol biosynthetic intermediate (CBI) downstream of lanosterol and upstream of zymosterol. Analysis of lipids bound to RORγ identified molecules with molecular weights consistent with CBIs. Furthermore, CBIs stabilized the RORγ ligand-binding domain and induced coactivator recruitment. Genetic deletion of metabolic enzymes upstream of the RORγt-ligand(s) affected the development of lymph nodes and Th17 cells. Our data suggest that CBIs play a role in lymphocyte development potentially through regulation of RORγt.
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Affiliation(s)
- Fabio R Santori
- The Kimmel Center for Biology and Medicine of the Skirball Institute, New York University School of Medicine, New York, NY 10016, USA.
| | - Pengxiang Huang
- Metabolic Disease Program, Sanford-Burnham Medical Research Institute, 6400 Sanger Road, Orlando, FL 32827, USA
| | - Serge A van de Pavert
- VU University Medical Center, Department of Molecular Cell Biology and Immunology, van der Boechorststraat 7, 1081BT Amsterdam, the Netherlands
| | - Eugene F Douglass
- The Kimmel Center for Biology and Medicine of the Skirball Institute, New York University School of Medicine, New York, NY 10016, USA
| | - David J Leaver
- Center for Chemical Biology and Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX 79409, USA
| | - Brad A Haubrich
- Center for Chemical Biology and Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX 79409, USA
| | - Rok Keber
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1230 Domzale, Slovenia
| | - Gregor Lorbek
- Institute of Biochemistry, Center for Functional Genomics and Bio-chips, Faculty of Medicine, University of Ljubljana, Zaloska 4, 1000 Ljubljana, Slovenia
| | - Tanja Konijn
- VU University Medical Center, Department of Molecular Cell Biology and Immunology, van der Boechorststraat 7, 1081BT Amsterdam, the Netherlands
| | - Brittany N Rosales
- Center for Chemical Biology and Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX 79409, USA
| | - Damjana Rozman
- Institute of Biochemistry, Center for Functional Genomics and Bio-chips, Faculty of Medicine, University of Ljubljana, Zaloska 4, 1000 Ljubljana, Slovenia
| | - Simon Horvat
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1230 Domzale, Slovenia; National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
| | - Alain Rahier
- Institut de Biologie Moleculaire des Plantes (IBMP), CNRS-UPR2357, 67083 Strasbourg, France
| | - Reina E Mebius
- VU University Medical Center, Department of Molecular Cell Biology and Immunology, van der Boechorststraat 7, 1081BT Amsterdam, the Netherlands
| | - Fraydoon Rastinejad
- Metabolic Disease Program, Sanford-Burnham Medical Research Institute, 6400 Sanger Road, Orlando, FL 32827, USA
| | - W David Nes
- Center for Chemical Biology and Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX 79409, USA
| | - Dan R Littman
- The Kimmel Center for Biology and Medicine of the Skirball Institute, New York University School of Medicine, New York, NY 10016, USA; Howard Hughes Medical Institute, New York University School of Medicine, New York, NY 10016, USA
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12
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McEnaney PJ, Fitzgerald KJ, Zhang AX, Douglass EF, Shan W, Balog A, Kolesnikova MD, Spiegel DA. Chemically synthesized molecules with the targeting and effector functions of antibodies. J Am Chem Soc 2014; 136:18034-43. [PMID: 25514603 PMCID: PMC4291750 DOI: 10.1021/ja509513c] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Indexed: 12/21/2022]
Abstract
This article reports the design, synthesis, and evaluation of a novel class of molecules of intermediate size (approximately 7000 Da), which possess both the targeting and effector functions of antibodies. These compounds—called synthetic antibody mimics targeting prostate cancer (SyAM-Ps)—bind simultaneously to prostate-specific membrane antigen and Fc gamma receptor I, thus eliciting highly selective cancer cell phagocytosis. SyAMs have the potential to combine the advantages of both small-molecule and biologic therapies, and may address many drawbacks associated with available treatments for cancer and other diseases.
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Affiliation(s)
- Patrick J McEnaney
- Department of Chemistry, Yale University , 225 Prospect Street, New Haven, Connecticut 06511, United States
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13
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Parker CG, Dahlgren MK, Tao RN, Li DT, Douglass EF, Shoda T, Jawanda N, Spasov KA, Lee S, Zhou N, Domaoal RA, Sutton RE, Anderson KS, Jorgensen WL, Krystal M, Spiegel DA. Illuminating HIV gp120-Ligand Recognition through Computationally-Driven Optimization of Antibody-Recruiting Molecules. Chem Sci 2014; 5:2311-2317. [PMID: 25379167 PMCID: PMC4217211 DOI: 10.1039/c4sc00484a] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Here we report on the structure-based optimization of antibody-recruiting molecules targeting HIV gp120 (ARM-H). These studies have leveraged a combination of medicinal chemistry, biochemical and cellular assay analysis, and computation. Our findings have afforded an optimized analog of ARM-H, which is ~1000 fold more potent in gp120-binding and MT-2 antiviral assays than our previously reported derivative. Furthermore, computational analysis, taken together with experimental data, provides evidence that azaindole- and indole-based attachment inhibitors bind gp120 at an accessory hydrophobic pocket beneath the CD4-binding site and can also adopt multiple unique binding modes in interacting with gp120. These results are likely to prove highly enabling in the development of novel HIV attachment inhibitors, and more broadly, they suggest novel applications for ARMs as probes of conformationally flexible systems.
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Affiliation(s)
| | - Markus K Dahlgren
- Department of Chemistry, Yale University, New Haven, Connecticut 06520
| | - Ran N Tao
- Department of Chemistry, Yale University, New Haven, Connecticut 06520
| | - Don T Li
- Department of Chemistry, Yale University, New Haven, Connecticut 06520
| | - Eugene F Douglass
- Department of Chemistry, Yale University, New Haven, Connecticut 06520
| | - Takuji Shoda
- Department of Chemistry, Yale University, New Haven, Connecticut 06520
| | - Navneet Jawanda
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut 06520
| | - Krasimir A Spasov
- Department of Pharmacology, Yale School of Medicine, New Haven, Connecticut 06510
| | - Sangil Lee
- Bristol-Myers Squibb, Research and Development, Wallingford, CT 06492
| | - Nannan Zhou
- Bristol-Myers Squibb, Research and Development, Wallingford, CT 06492
| | - Robert A Domaoal
- Department of Pharmacology, Yale School of Medicine, New Haven, Connecticut 06510
| | - Richard E Sutton
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut 06520
| | - Karen S Anderson
- Department of Pharmacology, Yale School of Medicine, New Haven, Connecticut 06510 ; Department of Molecular Biophysics and Biochemistry, Yale School of Medicine, New Haven, Connecticut 06510
| | | | - Mark Krystal
- Bristol-Myers Squibb, Research and Development, Wallingford, CT 06492
| | - David A Spiegel
- Department of Chemistry, Yale University, New Haven, Connecticut 06520 ; Department of Pharmacology, Yale School of Medicine, New Haven, Connecticut 06510
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14
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Jakobsche CE, Parker CG, Tao RN, Kolesnikova MD, Douglass EF, Spiegel DA. Exploring binding and effector functions of natural human antibodies using synthetic immunomodulators. ACS Chem Biol 2013; 8:2404-11. [PMID: 24053626 DOI: 10.1021/cb4004942] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The ability to profile the prevalence and functional activity of endogenous antibodies is of vast clinical and diagnostic importance. Serum antibodies are an important class of biomarkers and are also crucial elements of immune responses elicited by natural disease-causing agents as well as vaccines. In particular, materials for manipulating and/or enhancing immune responses toward disease-causing cells or viruses have exhibited significant promise for therapeutic applications. Antibody-recruiting molecules (ARMs), bifunctional organic molecules that redirect endogenous antibodies to pathological targets, thereby increasing their recognition and clearance by the immune system, have proven particularly interesting. Notably, although ARMs capable of hijacking antibodies against oligosaccharides and electron-poor aromatics have proven efficacious, systematic comparisons of the prevalence and effectiveness of natural anti-hapten antibody populations have not appeared in the literature. Herein we report head-to-head comparisons of three chemically simple antigens, which are known ligands for endogenous antibodies. Thus, we have chemically synthesized bifunctional molecules containing 2,4-dinitrophenyl (DNP), phosphorylcholine (PC), and rhamnose. We have then used a combination of ELISA, flow cytometry, and cell-viability assays to compare these antigens in terms of their abilities both to recruit natural antibody from human serum and also to direct serum-dependent cytotoxicity against target cells. These studies have revealed rhamnose to be the most efficacious of the synthetic antigens examined. Furthermore, analysis of 122 individual serum samples has afforded comprehensive insights into population-wide prevalence and isotype distributions of distinct anti-hapten antibody populations. In addition to providing a general platform for comparing and studying anti-hapten antibodies, these studies serve as a useful starting point for the optimization of antibody-recruiting molecules and other synthetic strategies for modulating human immunity.
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Affiliation(s)
- Charles E. Jakobsche
- Carlson
School of Chemistry and Biochemistry, Clark University, 950 Main
Street, Worcester, Massachusetts 01610, United States
| | - Christopher G. Parker
- The
Skaggs Institute for Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Ran N. Tao
- Department
of Chemistry, Yale University, 225 Prospect Street, P.O. Box 208107, New Haven, Connecticut 06520, United States
| | | | - Eugene F. Douglass
- Department
of Chemistry, Yale University, 225 Prospect Street, P.O. Box 208107, New Haven, Connecticut 06520, United States
| | - David A. Spiegel
- Department
of Chemistry, Yale University, 225 Prospect Street, P.O. Box 208107, New Haven, Connecticut 06520, United States
- Department
of Pharmacology, Yale University School of Medicine, 333 Cedar
Street, New Haven, Connecticut 06510, United States
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15
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Abstract
Methylglyoxal (MGO), a dicarbonyl metabolite produced by all living cells, has been associated with a number of human diseases. However, studies of the role(s) MGO plays biologically have been handicapped by a lack of direct methods for its monitoring and detection. To address this limitation, we have developed a fluorescent sensor (methyl diaminobenzene-BODIPY, or "MBo") that can detect MGO under physiological conditions. We show that MBo is selective for MGO over other biologically relevant dicarbonyls and is suitable for detecting MGO in complex environments, including that of living cells. In addition, we demonstrate MBo's utility in estimating plasma concentrations of MGO. The results reported herein have the potential to advance both clinical and basic science research and practice.
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Affiliation(s)
- Tina Wang
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, Connecticut 06511, USA
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16
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Abstract
Three-component systems are often more complex than their two-component counterparts. Although the reversible association of three components in solution is critical for a vast array of chemical and biological processes, no general physical picture of such systems has emerged. Here we have developed a general, comprehensive framework for understanding ternary complex equilibria, which relates directly to familiar concepts such as EC50 and IC50 from simpler (binary complex) equilibria. Importantly, application of our model to data from the published literature has enabled us to achieve new insights into complex systems ranging from coagulation to therapeutic dosing regimens for monoclonal antibodies. We also provide an Excel spreadsheet to assist readers in both conceptualizing and applying our models. Overall, our analysis has the potential to render complex three-component systems--which have previously been characterized as "analytically intractable"--readily comprehensible to theoreticians and experimentalists alike.
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Affiliation(s)
- Eugene F Douglass
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
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17
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Driscoll PF, Douglass EF, Phewluangdee M, Soto ER, Cooper CGF, Macdonald JC, Lambert CR, McGimpsey WG. Photocurrent generation in noncovalently assembled multilayered thin films. Langmuir 2008; 24:5140-5145. [PMID: 18393555 DOI: 10.1021/la703586e] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Multilayered photocurrent generating thin films were fabricated by templated noncovalent assembly via stepwise assembly of molecular components. Each of films I-IV contained an underlying self-assembled monolayer (SAM) consisting of an alkanethiol linked covalently to a 2,6-dicarboxypyridine ligand that served as a binding site for attaching additional molecular components. The SAM subsequently was functionalized by sequential deposition of Cu(II), Co(II), or Fe(III) ions followed by a variety of substituted 2,6-dicarboxypyridine ligands as a means to incorporate one or more layers of pyrene chromophores into the film. The films were characterized by contact angle measurements, ellipsometry, grazing incidence IR, cyclic voltammetry, and impedance spectroscopy after deposition of each layer, confirming the formation of ordered, stable layers. Following incorporation into a three-electrode system, photoexcitation resulted in the generation of a cathodic photocurrent in the presence of methyl viologen and an anodic photocurrent in the presence of triethanolamine. Using this strategy, systems were fabricated that produced up to 89 nA/cm(2) of reproducible photocurrent.
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Affiliation(s)
- Peter F Driscoll
- Department of Chemistry and Biochemistry, Worcester Polytechnic Institute, Worcester, Massachusetts 01609, USA
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