Institutional implementation of clinical tumor profiling on an unselected cancer population
Open accessAbstract
BACKGROUND. Comprehensive genomic profiling of a patient’s cancer can be used to diagnose, monitor, and recommend treatment. Clinical implementation of tumor profiling in an enterprise-wide, unselected cancer patient population has yet to be reported. METHODS. We deployed a hybrid-capture and massively parallel sequencing assay (OncoPanel) for all adult and pediatric patients at our combined cancer centers. Results were categorized by pathologists based on actionability. We report the results for the first 3,727 patients tested. RESULTS. Our cohort consists of cancer patients unrestricted by disease site or stage. Across all consented patients, half had sufficient and available (>20% tumor) material for profiling; once specimens were received in the laboratory for pathology review, 73% were scored as adequate for genomic testing. When sufficient DNA was obtained, OncoPanel yielded a result in 96% of cases. 73% of patients harbored an actionable or informative alteration; only 19% of these represented a current standard of care for therapeutic stratification. The findings recapitulate those of previous studies of common cancers but also identify alterations, including in AXL and EGFR , associated with response to targeted therapies. In rare cancers, potentially actionable alterations suggest the utility of a “cancer-agnostic” approach in genomic profiling. Retrospective analyses uncovered contextual genomic features that may inform therapeutic response and examples where diagnoses revised by genomic profiling markedly changed clinical management. CONCLUSIONS. Broad sequencing-based testing deployed across an unselected cancer cohort is feasible. Genomic results may alter management in diverse scenarios; however, additional barriers must be overcome to enable precision cancer medicine on a large scale. FUNDING. This work was supported by DFCI, BWH, and the National Cancer Institute (5R33CA155554 and 5K23CA157631).
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Only a small proportion of patients, approximately 10-20%, have an actionable alteration that can be coupled to a specific intervention.
“However, as shown in several clinical trials161–165, only a small proportion of patients (approx. 10–20%) have an actionable alteration that can be coupled to a specific intervention161.”
From Organoids (2022) · cites this paper as [163]
The pan-cancer results report that 19% of alterations could inform standard-of-care therapeutic decisions, consistent with the claim’s approximate range for that narrower category. But they also report that 73% of the cohort had a clinically actionable or informative alteration, including alterations that could guide trial enrollment. The claim does not make that distinction and understates the broader proportion. (LLM, conf=0.88)
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Sherman, M. A., Yaari, A. U., Priebe, O., Dietlein, F., Loh, P.-R., & Berger, B. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01353-8 · Cited by 80 · see citing works
Natural Language Processing to Ascertain Cancer Outcomes from Medical Oncologist Notes
Kehl, K. L., Xu, W., Lepisto, E., Elmarakeby, H., Hassett, M. J., Van Allen, E. M., Johnson, B. E., & Schrag, D. (2020) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00020 · Cited by 90 · see citing works
Self-citationMadanat-Harjuoja, L. M., Renfro, L. A., Klega, K., Tornwall, B., Thorner, A. R., Nag, A., Dix, D., Dome, J. S., Diller, L. R., Fernandez, C. V., et al. (2022) · Journal of Clinical Oncology · doi:10.1200/jco.22.00098 · Cited by 41 · see citing works
Self-citation
- Authors
- Sholl, L. M., Do, K., Shivdasani, P., Cerami, E., Dubuc, A. M., Kuo, F. C., Garcia, E. P., Jia, Y., Davineni, P., Abo, R. P., Pugh, T. J., van Hummelen, P., Thorner, A. R., Ducar, M., Berger, A. H., Nishino, M., Janeway, K. A., Church, A., Harris, M., Ritterhouse, L. L., Campbell, J. D., Rojas-Rudilla, V., Ligon, A. H., Ramkissoon, S., Cleary, J. M., Matulonis, U., Oxnard, G. R., Chao, R., Tassell, V., Christensen, J., Hahn, W. C., Kantoff, P. W., Kwiatkowski, D. J., Johnson, B. E., Meyerson, M., Garraway, L. A., Shapiro, G. I., Rollins, B. J., Lindeman, N. I., & MacConaill, L. E.
- Affiliations
- Brigham and Women's Hospital (US)
- Department of Biostatistics and Computational Biology, and
- University Health Network (CA)
- Dana-Farber/Harvard Cancer Center (US)
- Broad Institute (US)
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center (US)
- Boston Children's Hospital (US)
- Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA.
- Mirati Therapeutics (United States) (US)
- Lank Center for Genitourinary Oncology and
- Corresponding author
- MacConaill, Laura E.
- ORCID
- Sholl, Lynette M.
- Do, Khanh
- Cerami, Ethan
- Dubuc, Adrian M.
- Kuo, Frank C.
- Garcia, Elizabeth P.
- Davineni, Phani
- Pugh, Trevor J.
- Thorner, Aaron R.
- Ducar, Matthew
- Berger, Alice H.
- Nishino, Mizuki
- Janeway, Katherine A.
- Church, Alanna
- Harris, Marian
- Ritterhouse, Lauren L.
- Campbell, Joshua D.
- Ligon, Azra H.
- Cleary, James M.
- Matulonis, Ursula
- Oxnard, Geoffrey R.
- Chao, Richard
- Christensen, James
- Hahn, William C.
- Kantoff, Philip W.
- Kwiatkowski, David J.
- Johnson, Bruce E.
- Meyerson, Matthew
- Garraway, Levi A.
- Shapiro, Geoffrey I.
- Rollins, Barrett J.
- Lindeman, Neal I.
- MacConaill, Laura E.
- Venue
- JCI Insight
- Published
- 2016-11-17
- Volume
- 1
- Issue
- 19
- Pages
- e87062-e87062
- ISSN
- 2379-3708 (ISSN-L)
- PMC
- PMC5111542
- OpenAlex
- W2551013093
- Cited by
- 450
- References
- 54
- Citations by year
- 2026: 20 · 2025: 36 · 2024: 27 · 2023: 63 · 2022: 44 · 2021: 58 · 2020: 63 · 2019: 53 · 2018: 56 · 2017: 29
- FWCI
- 19.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- JCI Insight (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- American Association for Cancer Research
- Dana-Farber Cancer Institute
- National Institutes of Health (5k23ca157631-02)
- National Cancer Institute (K23-CA157631, R33CA155554, 5K23CA157631, P30CA008748)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
- Keywords
- comprehensive genomic profiling, clinical implementation, actionable alterations, hybrid capture sequencing, OncoPanel, precision oncology, AXL, EGFR, rare tumor, treatment stratification, diagnostic revision, targeted therapy response
- MeSH terms
- DNA Mutational Analysis, Humans, Mutation, Neoplasms, Retrospective Studies, Genomics, Precision Medicine, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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