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Clinical interpretation of integrative molecular profiles to guide precision cancer medicine

View ORCID ProfileBrendan Reardon, Nathaniel D Moore, Nicholas Moore, Eric Kofman, Saud Aldubayan, Alexander Cheung, Jake Conway, Haitham Elmarakeby, Alma Imamovic, Sophia C. Kamran, Tanya Keenan, Daniel Keliher, David J Konieczkowski, David Liu, Kent Mouw, Jihye Park, Natalie Vokes, Felix Dietlein, View ORCID ProfileEliezer M Van Allen
doi: https://doi.org/10.1101/2020.09.22.308833
Brendan Reardon
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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  • ORCID record for Brendan Reardon
Nathaniel D Moore
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
3Indiana University School of Medicine, Indianapolis, IN, USA
4Howard Hughes Medical Institute, Chevy Chase, MD, USA
5Department of Internal Medicine, University of Cincinnati, Cincinnati, Ohio, USA
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Nicholas Moore
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
6Harvard Medical School, Harvard University, Boston, MA, USA
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Eric Kofman
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
7Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
8Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
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Saud Aldubayan
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
9Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA
10College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
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Alexander Cheung
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
11Grossman School of Medicine, New York University, New York, NY, USA
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Jake Conway
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
12Division of Medical Sciences, Harvard University, Boston, MA, USA
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Haitham Elmarakeby
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
13Department of System and Computer Engineering, Al-Azhar University, Cairo, Egypt
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Alma Imamovic
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
14Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
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Sophia C. Kamran
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
15Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Tanya Keenan
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Daniel Keliher
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
16Department of Mathematics, Tufts University, Medford, MA, USA
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David J Konieczkowski
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
17Department of Radiation Oncology, Dana-Farber Cancer Institute & Brigham and Women’s Hospital, Boston, MA
18Harvard Radiation Oncology Program, Massachusetts General Hospital, Boston, MA, USA
19Department of Radiation Oncology, The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J Solove Research Institute, Columbus, OH, USA
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David Liu
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Kent Mouw
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
6Harvard Medical School, Harvard University, Boston, MA, USA
17Department of Radiation Oncology, Dana-Farber Cancer Institute & Brigham and Women’s Hospital, Boston, MA
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Jihye Park
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Natalie Vokes
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
20Department of Thoracic / Head and Neck Oncology, MD Anderson Cancer Center, Houston, TX, USA
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Felix Dietlein
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Eliezer M Van Allen
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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  • ORCID record for Eliezer M Van Allen
  • For correspondence: EliezerM_VanAllen@dfci.harvard.edu
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ABSTRACT

Individual tumor molecular profiling is routinely used to detect single gene-variant (“first-order”) genomic alterations that may inform therapeutic actions -- for instance, a tumor with a BRAF p.V600E variant might be considered for RAF/MEK inhibitor therapy. Interactions between such first-order events (e.g., somatic-germline) and global molecular features (e.g. mutational signatures) are increasingly associated with clinical outcomes, but these “second order” alterations are not yet generally accounted for in clinical interpretation algorithms and knowledge bases. Here, we introduce the Molecular Oncology Almanac (MOAlmanac), a clinical interpretation algorithm paired with a novel underlying knowledge base to enable integrative interpretation of genomic and transcriptional cancer data for point-of-care treatment decision-making and translational hypothesis generation. We compared MOAlmanac to first-order interpretation methodology in multiple retrospective patient cohorts and observed that the inclusion of preclinical and inferential evidence as well as second-order molecular features increased the number of nominated clinical hypotheses. MOAlmanac also performed matchmaking between patient molecular profiles and cancer cell lines to further expand individualized clinical actionability. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 46% of patient profiles. Overall, we present a novel computational method to perform integrative clinical interpretation of individualized molecular profiles. MOAlmanc increases clinical actionability over conventional approaches by considering second-order molecular features and additional evidence sources, and is available as an open-source framework.

Competing Interest Statement

E.M.V.A. holds consulting roles with Tango Therapeutics, Genome Medical, Invitae, Enara Bio, Janssen, Manifold Bio, Monte Rosa. E.M.V.A. has received research support from Novartis, BMS. E.M.V.A. owns equity in Tango Therapeutics, Genome Medical, Syapse, Enara Bio, Manifold Bio, Microsoft, and Monte Rosa and has received travel reimbursement from Roche/Genentech. E.M.V.A., B.R., and N.D.M. have institutional patents filed on methods for clinical interpretation.

Footnotes

  • https://github.com/vanallenlab/moalmanac-paper

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Clinical interpretation of integrative molecular profiles to guide precision cancer medicine
Brendan Reardon, Nathaniel D Moore, Nicholas Moore, Eric Kofman, Saud Aldubayan, Alexander Cheung, Jake Conway, Haitham Elmarakeby, Alma Imamovic, Sophia C. Kamran, Tanya Keenan, Daniel Keliher, David J Konieczkowski, David Liu, Kent Mouw, Jihye Park, Natalie Vokes, Felix Dietlein, Eliezer M Van Allen
bioRxiv 2020.09.22.308833; doi: https://doi.org/10.1101/2020.09.22.308833
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Clinical interpretation of integrative molecular profiles to guide precision cancer medicine
Brendan Reardon, Nathaniel D Moore, Nicholas Moore, Eric Kofman, Saud Aldubayan, Alexander Cheung, Jake Conway, Haitham Elmarakeby, Alma Imamovic, Sophia C. Kamran, Tanya Keenan, Daniel Keliher, David J Konieczkowski, David Liu, Kent Mouw, Jihye Park, Natalie Vokes, Felix Dietlein, Eliezer M Van Allen
bioRxiv 2020.09.22.308833; doi: https://doi.org/10.1101/2020.09.22.308833

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