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Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT study


Cancer treatments have evolved from indiscriminate cytotoxic agents to selective genome- and immune-targeted drugs that have transformed the outcomes of some malignancies1. Tumor complexity and heterogeneity suggest that the ‘precision medicine’ paradigm of cancer therapy requires treatment to be personalized to the individual patient2,3,4,5,6. To date, precision oncology trials have been based on molecular matching with predetermined monotherapies7,8,9,10,11,12,13,14. Several of these trials have been hindered by very low matching rates, often in the 5–10% range15, and low response rates. Low matching rates may be due to the use of limited gene panels, restrictive molecular matching algorithms, lack of drug availability, or the deterioration and death of end-stage patients before therapy can be implemented. We hypothesized that personalized treatment with combination therapies would improve outcomes in patients with refractory malignancies. As a first test of this concept, we implemented a cross-institutional prospective study (I-PREDICT, NCT02534675) that used tumor DNA sequencing and timely recommendations for individualized treatment with combination therapies. We found that administration of customized multidrug regimens was feasible, with 49% of consented patients receiving personalized treatment. Targeting of a larger fraction of identified molecular alterations, yielding a higher ‘matching score’, was correlated with significantly improved disease control rates, as well as longer progression-free and overall survival rates, compared to targeting of fewer somatic alterations. Our findings suggest that the current clinical trial paradigm for precision oncology, which pairs one driver mutation with one drug, may be optimized by treating molecularly complex and heterogeneous cancers with combinations of customized agents.

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Fig. 1: Molecular alterations targeted by matched therapies and impact of matching score on treatment outcome.

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Supporting source data for all figures and tables are made available in Supplementary Table 1 and Supplementary Table 2.


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We thank J. Wrolstad, M. Scur, and J. Porter for their critical roles in clinical trial and data management, L. Marquez for medication acquisition, D. Sandler, C. M. Tang, H. Yoon, M. Yerba and S. Silverman for assistance with manuscript preparation, T. Reya for her critical review of the manuscript, and most importantly, the patients and their families. This work was supported in part by Foundation Medicine, Inc. (J.K.S., R.O., B.L.-J., R.K.), as well as the Joan and Irwin Jacobs Philanthropic Fund (R.K.), the Jon Schneider Memorial Cancer Research Fund (J.K.S., P.T.F.), and National Institutes of Health (NIH) grant nos. P30CA023100 (J.K.S., S.M.L., R.K.) and P30CA016672 (J.J.L.). The authors also acknowledge the support of NIH grant nos. K08CA168999 and R21CA192072, as well as Pedal the Cause, The David Foundation, and Kristen Ann Carr Fund (J.K.S.).

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Authors and Affiliations



J.K.S. contributed to the conception/design of the work, the acquisition, analysis, and interpretation of the data, and the drafting and substantive revision of the work. S.K. and R.O. contributed to the acquisition, analysis, and interpretation of the data, and the drafting and substantive revision of the work. M.S. contributed to the acquisition, analysis, and interpretation of the data, and the drafting of the work. M.E.H., C.B.W., P.D., and P.T.F. contributed to the acquisition and analysis of data. A.K. and D.E.P. contributed to the acquisition of the data. V.A.M. contributed to the design of the work, the drafting of the work, and the substantive revision of the work. J.S.R. contributed to the conception/design of the work, the acquisition, analysis, and interpretation of the data, and the drafting of the work. A.B., J.W., and P.J.S. contributed to the acquisition, analysis, and interpretation of the data. J.J.L. contributed to the design of the work, the analysis and interpretation of the data, and the drafting of the work. S.M.L. contributed to the conception/design of the work. B.L.-J. contributed to the acquisition, analysis, and interpretation of data, and the drafting of the work. R.K. contributed to the conception/design of the work, the acquisition, analysis, and interpretation of the data, and the drafting and substantive revision of the work. All authors approved the submitted version (and any substantially modified version that involves the authors’ contribution to the study). All authors have agreed to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones where the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

Corresponding authors

Correspondence to Jason K. Sicklick or Razelle Kurzrock.

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Competing interests

J.K.S. receives research funds from Foundation Medicine, Inc., Novartis Pharmaceuticals, Blueprint Medicines, and Amgen, as well as consultant fees from Loxo Oncology, Biotheranostics, and Grand Rounds. M.E.H. receives research funds from General Electric and is an equity holder in Illumina, Inc. C.W. receives research support from Takeda, TESARO, and Pfizer, as well as consultant fees from Takeda. V.A.M., J.S.R., and J.W. are employees and equity holders in Foundation Medicine, Inc. V.A.M. is also on the Board of Directors for Revolution Medicines (equity and compensation >$10,000) and has patent royalties for EGFR T790M testing issued to the Memorial Sloan Kettering Cancer Center. A.B. is formerly an employee and is an equity holder in Foundation Medicine, Inc. He is now an employee of Scipher Medicine. P.J.S. is formerly an employee and is formerly an equity holder in Foundation Medicine, Inc. He is now an employee of GRAIL, Inc. J.J.L. served on the Statistical Advisory Board of AbbVie. R.K. has research funding from Incyte, Genentech, Merck Serono, Pfizer, Sequenom, Grifols, OmniSeq, Foundation Medicine, Inc., Guardant Health, and Konica Minolta, as well as consultant fees from Loxo Oncology, Actuate Therapeutics, Roche, XBiotech, and NeoMed. She serves as an advisor to Soluventis. She receives speaker fees from Roche, and has an equity interest in IDbyDNA, CureMatch, Inc., and Soluventis. All other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Consolidated Standards of Reporting Trials (CONSORT) diagram, which includes the 149 patients that consented to I-PREDICT.

*Treated evaluable patients includes patients who received >10 d of treatment for drugs given on a daily basis (generally drugs given by mouth) or at least two doses of a drug normally given every two weeks or more frequently (the latter generally being intravenous drugs). Only patients whose treatment was reviewed and validated by data analysis lockdown are included. **One patient had inadequate tissue for NGS and declined biopsy; he was later reenrolled after he agreed to undergo biopsy. One treated patient who initially was believed to have prior therapy was found, after data lockdown analysis, to have not received the prior regimen.

Supplementary information

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Supplementary Text, Supplementary Tables 3–10, and Supplementary References

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Sicklick, J.K., Kato, S., Okamura, R. et al. Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT study. Nat Med 25, 744–750 (2019).

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