Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology

Brendan Reardon; Nathanael D Moore; Nicholas S Moore; Eric Kofman; Saud H AlDubayan; Alexander T M Cheung; Jake Conway; Haitham Elmarakeby; Alma Imamovic; Sophia C Kamran; Tanya Keenan; Daniel Keliher; David J Konieczkowski; David Liu; Kent W Mouw; Jihye Park; Natalie I Vokes; Felix Dietlein; Eliezer M Van Allen

doi:10.1038/s43018-021-00243-3

Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology

Nat Cancer. 2021 Oct;2(10):1102-1112. doi: 10.1038/s43018-021-00243-3. Epub 2021 Sep 30.

Authors

Brendan Reardon^{1

2}, Nathanael D Moore^{1

2

3

4

5}, Nicholas S Moore^{1

2

6}, Eric Kofman^{1

2

7

8}, Saud H AlDubayan^{1

2

9

10}, Alexander T M Cheung^{1

2

11}, Jake Conway^{1

2

12}, Haitham Elmarakeby^{1

2

13}, Alma Imamovic^{2

14}, Sophia C Kamran^{2

15}, Tanya Keenan^{1

2}, Daniel Keliher^{1

2

16}, David J Konieczkowski^{2

17

18

19}, David Liu^{1

2}, Kent W Mouw^{2

6

17}, Jihye Park^{1

2}, Natalie I Vokes^{1

2

20}, Felix Dietlein^{1

2}, Eliezer M Van Allen^{21

22}

Affiliations

¹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
² Broad Institute of MIT and Harvard, Cambridge, MA, USA.
³ Indiana University School of Medicine, Indianapolis, IN, USA.
⁴ Howard Hughes Medical Institute, Chevy Chase, MD, USA.
⁵ Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA.
⁶ Harvard Medical School, Harvard University, Boston, MA, USA.
⁷ Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
⁸ Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA.
⁹ Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA.
¹⁰ College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
¹¹ Grossman School of Medicine, New York University, New York, NY, USA.
¹² Division of Medical Sciences, Harvard University, Boston, MA, USA.
¹³ Department of System and Computer Engineering, Al-Azhar University, Cairo, Egypt.
¹⁴ Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
¹⁵ Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
¹⁶ Department of Mathematics, Tufts University, Medford, MA, USA.
¹⁷ Department of Radiation Oncology, Dana-Farber Cancer Institute & Brigham and Women's Hospital, Boston, MA, USA.
¹⁸ Harvard Radiation Oncology Program, Massachusetts General Hospital, Boston, MA, USA.
¹⁹ Department of Radiation Oncology, the Ohio State University Comprehensive Cancer Center-Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, Columbus, OH, USA.
²⁰ Department of Thoracic/Head and Neck Oncology, MD Anderson Cancer Center, Houston, TX, USA.
²¹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. eliezerm_vanallen@dfci.harvard.edu.
²² Broad Institute of MIT and Harvard, Cambridge, MA, USA. eliezerm_vanallen@dfci.harvard.edu.

Abstract

Tumor molecular profiling of single gene-variant ('first-order') genomic alterations informs potential therapeutic approaches. Interactions between such first-order events and global molecular features (for example, mutational signatures) are increasingly associated with clinical outcomes, but these 'second-order' alterations are not yet accounted for in clinical interpretation algorithms and knowledge bases. We introduce the Molecular Oncology Almanac (MOAlmanac), a paired clinical interpretation algorithm and knowledge base to enable integrative interpretation of multimodal genomic data for point-of-care decision making and translational-hypothesis generation. We benchmarked MOAlmanac to a first-order interpretation method across multiple retrospective cohorts and observed an increased number of clinical hypotheses from evaluation of molecular features and profile-to-cell line matchmaking. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 47% of patients. Overall, we present an open-source computational method for integrative clinical interpretation of individualized molecular profiles.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Genomics / methods
Humans
Neoplasms* / diagnosis
Precision Medicine
Prospective Studies
Retrospective Studies

Abstract

Publication types

MeSH terms

Grants and funding