Feasibility of Large-Scale Genomic Testing to Facilitate Enrollment Onto Genomically Matched Clinical Trials
Open accessAbstract
Purpose: We report the experience with 2,000 consecutive patients with advanced cancer who underwent testing on a genomic testing protocol, including the frequency of actionable alterations across tumor types, subsequent enrollment onto clinical trials, and the challenges for trial enrollment. Patients and Methods: Standardized hotspot mutation analysis was performed in 2,000 patients, using either an 11-gene (251 patients) or a 46- or 50-gene (1,749 patients) multiplex platform. Thirty-five genes were considered potentially actionable based on their potential to be targeted with approved or investigational therapies. Results: Seven hundred eighty-nine patients (39%) had at least one mutation in potentially actionable genes. Eighty-three patients (11%) with potentially actionable mutations went on genotype-matched trials targeting these alterations. Of 230 patients with PIK3CA/AKT1/PTEN/BRAF mutations that returned for therapy, 116 (50%) received a genotype-matched drug. Forty patients (17%) were treated on a genotype-selected trial requiring a mutation for eligibility, 16 (7%) were treated on a genotype-relevant trial targeting a genomic alteration without biomarker selection, and 40 (17%) received a genotype-relevant drug off trial. Challenges to trial accrual included patient preference of noninvestigational treatment or local treatment, poor performance status or other reasons for trial ineligibility, lack of trials/slots, and insurance denial. Conclusion: Broad implementation of multiplex hotspot testing is feasible; however, only a small portion of patients with actionable alterations were actually enrolled onto genotype-matched trials. Increased awareness of therapeutic implications and access to novel therapeutics are needed to optimally leverage results from broad-based genomic testing.
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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 [162]
The Results (page not provided) report potentially actionable mutations in 39% of the 2,000 patients tested, not approximately 10–20%. The Enrollment Onto Clinical Trials section reports that 11% of patients with potentially actionable alterations entered genotype-matched trials. That supports the point that relatively few received a matched intervention, but 11% is not the proportion of all patients who had an actionable alteration. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe SHIVA trial showed that strategies based on tumor sequencing do not outperform conventional physician's choice.
“In addition, the SHIVA trial has shown how this strategies based on tumor sequencing do not outperform better than the conventional physician’s choice161,162.”
From Organoids (2022) · cites this paper as [162]
The Results section reports enrollment onto genomically matched trials, and the discussion describes this study as observational. Searches for “SHIVA trial” and a comparison with physician’s choice found no passage reporting SHIVA’s outcome or that comparison in our copy. (LLM, conf=0.76)
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Cites
Frampton, G. M., Fichtenholtz, A., Otto, G. A., Wang, K., Downing, S. R., He, J., Schnall-Levin, M., White, J., Sanford, E. M., An, P., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2696 · Cited by 2,157 · cited 1× · see citing works
“Such larger panels may demonstrate potentially actionable alterations in many more patients.(3-6) We noted several challenges in linking genomic testing to genomically matched trials.”
BackgroundUsing Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs
Kris, M. G., Johnson, B. E., Berry, L. D., Kwiatkowski, D. J., Iafrate, A. J., Wistuba, I. I., Varella-Garcia, M., Franklin, W. A., Aronson, S. L., Su, P.-F., et al. (2014) · JAMA · doi:10.1001/jama.2014.3741 · Cited by 1,724 · see citing works
André, F., Bachelot, T., Commo, F., Campone, M., Arnedos, M., Dieras, V. C., Lacroix‐Triki, M., Lacroix, L., Cohen, P. A., Gentien, D., et al. (2014) · The Lancet Oncology · doi:10.1016/s1470-2045(13)70611-9 · Cited by 403 · see citing works
Singh, R. R., Patel, K. P., Routbort, M. J., Reddy, N. G., Barkoh, B. A., Handal, B. A., Kanagal‐Shamanna, R., Greaves, W. O., Medeiros, L. J., Aldape, K., et al. (2013) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2013.05.003 · Cited by 315 · see citing works
Self-citationPhysicians' Attitudes About Multiplex Tumor Genomic Testing
Gray, S. W., Hicks-Courant, K., Cronin, A. M., Rollins, B. J., & Weeks, J. C. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.52.4298 · Cited by 241 · see citing works
Clinical next‐generation sequencing in patients with non–small cell lung cancer
Hagemann, I. S., Devarakonda, S. H. K., Lockwood, C. M., Spencer, D. H., Guebert, K., Bredemeyer, A. J., Al‐Kateb, H., Nguyen, T. T., Duncavage, E. J., Cottrell, C. E., et al. (2014) · Cancer · doi:10.1002/cncr.29089 · Cited by 232 · see citing works
Lovly, C. M., Dahlman, K. B., Fohn, L. E., Su, Z., Dias-Santagata, D. C., Hicks, D. J., Hucks, D., Berry, E., Terry, C. R., Duke, M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035309 · Cited by 203 · see citing works
Concordance of Genomic Alterations between Primary and Recurrent Breast Cancer
Meric‐Bernstam, F., Frampton, G. M., Ferrer-Lozano, J., Yelensky, R., Fidalgo, J. A. P., Wang, Y., Palmer, G. A., Ross, J. S., Miller, V. A., Su, X., et al. (2014) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-13-0482 · Cited by 116 · see citing works
Self-citationJohnson, D. B., Dahlman, K. H., Knol, J., Gilbert, J., Puzanov, I., Means-Powell, J., Balko, J., Lovly, C., Murphy, B., Goff, L., et al. (2014) · The Oncologist · doi:10.1634/theoncologist.2014-0011 · Cited by 110 · see citing works
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Zehir, A., Benayed, R., Shah, R. H., Syed, A., Middha, S., Kim, H. R., Srinivasan, P., Gao, J., Chakravarty, D., Devlin, S. M., et al. (2017) · Nature Medicine · doi:10.1038/nm.4333 · Cited by 3,380 · see citing works
Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs
Kris, M. G., Johnson, B. E., Berry, L. D., Kwiatkowski, D. J., Iafrate, A. J., Wistuba, I. I., Varella-Garcia, M., Franklin, W. A., Aronson, S. L., Su, P.-F., et al. (2014) · JAMA · doi:10.1001/jama.2014.3741 · Cited by 1,724 · see citing works
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Skoulidis, F., Goldberg, M. E., Greenawalt, D. M., Hellmann, M. D., Awad, M. M., Gainor, J. F., Schrock, A. B., Hartmaier, R. J., Trabucco, S. E., Gay, L., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-0099 · Cited by 1,641 · see citing works
Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens
Behan, F. M., Iorio, F., Picco, G., Gonçalves, E., Beaver, C. M., Migliardi, G., Santos, R., Rao, Y., Sassi, F., Pinnelli, M., et al. (2019) · Nature · doi:10.1038/s41586-019-1103-9 · Cited by 1,338 · see citing works
Zhao, Z., Chen, X., Dowbaj, A. M., Sljukic, A., Bratlie, K., Lin, L., Fong, E. L. S., Balachander, G. M., Chen, Z., Soragni, A., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00174-y · Cited by 1,001 · see citing works
Griffith, M., Spies, N. C., Krysiak, K., McMichael, J. F., Coffman, A. C., Danos, A. M., Ainscough, B. J., Ramirez, C. A., Rieke, D. T., Kujan, L., et al. (2017) · Nature Genetics · doi:10.1038/ng.3774 · Cited by 628 · see citing works
Jordan, E. J., Kim, H. R., Arcila, M. E., Barron, D., Chakravarty, D., Gao, J., Chang, M. T., Ni, A., Kundra, R., Jonsson, P., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-1337 · Cited by 643 · see citing works
Institutional implementation of clinical tumor profiling on an unselected cancer population
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., et al. (2016) · JCI Insight · doi:10.1172/jci.insight.87062 · Cited by 450 · see citing works
Clinical actionability of molecular targets in endometrial cancer
Urick, M. E., & Bell, D. W. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0177-x · Cited by 405 · see citing works
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Letai, A. (2017) · Nature Medicine · doi:10.1038/nm.4389 · Cited by 366 · see citing works
Patient-derived organoids as a predictive biomarker for treatment response in cancer patients
Wensink, G. E., Elias, S. G., Mullenders, J., Koopman, M., Boj, S. F., Kranenburg, O. W., & Roodhart, J. M. L. (2021) · npj Precision Oncology · doi:10.1038/s41698-021-00168-1 · Cited by 323 · see citing works
Hamamoto, R., Suvarna, K., Yamada, M., Kobayashi, K., Shinkai, N., Miyake, M., Takahashi, M., Jinnai, S., Shimoyama, R., Sakai, A., et al. (2020) · Cancers · doi:10.3390/cancers12123532 · Cited by 207 · see citing works
Aisner, D. L., Sholl, L. M., Berry, L. D., Rossi, M. R., Chen, H., Fujimoto, J., Moreira, A. L., Ramalingam, S. S., Villaruz, L. C., Otterson, G. A., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-2289 · Cited by 206 · see citing works
Biopsy-free circulating tumor DNA assay identifies actionable mutations in lung cancer
Villaflor, V., Won, B., Nagy, R., Banks, K., Lanman, R. B., Talasaz, A., & Salgia, R. (2016) · Oncotarget · doi:10.18632/oncotarget.11801 · Cited by 75 · see citing works
Mundi, P. S., Dela Cruz, F. S., Grunn, A., Diolaiti, D., Mauguen, A., Rainey, A. R., Guillan, K. C., Siddiquee, A., You, D., Realubit, R., et al. (2021) · doi:10.1101/2021.10.03.462951 · Cited by 51 · see citing works
Loree, J. M., Wang, Y., Syed, M. A., Sorokin, A. V., Coker, O., Xiu, J., Weinberg, B. A., Vanderwalde, A. M., Tesfaye, A., Raymond, V. M., et al. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-0180 · Cited by 43 · see citing works
Self-citationRedefining Colorectal Cancer by Tumor Biology
Salem, M. E., Puccini, A., & Tie, J. (2020) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk_279867 · Cited by 14 · see citing works
- Authors
- Meric-Bernstam, F., Brusco, L., Shaw, K., Horombe, C., Kopetz, S., Davies, M. A., Routbort, M., Piha-Paul, S. A., Janku, F., Ueno, N., Hong, D., De Groot, J., Ravi, V., Li, Y., Luthra, R., Patel, K., Broaddus, R., Mendelsohn, J., & Mills, G. B.
- Affiliations
- All authors: The University of Texas MD Anderson Cancer Center, Houston, TX.
- The University of Texas MD Anderson Cancer Center (US)
- ORCID
- Venue
- Journal of Clinical Oncology
- Published
- 2015-09-01
- Volume
- 33
- Issue
- 25
- Pages
- 2753-2762
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- PMC
- PMC4550690
- OpenAlex
- W2106410630
- Cited by
- 424
- References
- 9
- Citations by year
- 2026: 12 · 2025: 17 · 2024: 14 · 2023: 25 · 2022: 36 · 2021: 47 · 2020: 33 · 2019: 57 · 2018: 44 · 2017: 78 · 2016: 46 · 2015: 13 · 2014: 1 · 2012: 1
- FWCI
- 20.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Oncology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Cancer Prevention and Research Institute of Texas (P30CA016672, UL1TR000371, CA016672, RP110584)
- National Institutes of Health (UL1TR000371, CA- 016672, TR000371)
- University of Texas MD Anderson Cancer Center ((CA016672), P30-CA-016672, UL1 TR000371)
- National Cancer Institute (U01CA180964, CA 016672, R21CA159270, P50CA083639, P30CA016672)
- National Center for Advancing Translational Sciences (TR000371)
- Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy (UL1 TR000371, P30 CA016672)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
- Keywords
- genomic testing, advanced cancer, clinical trial recruitment, actionable mutations, multiplexed sequencing, PIK3CA, BRAF, PTEN, AKT1, targeted therapy, insurance denials
- MeSH terms
- Adult, Aged, Clinical Trials as Topic, Feasibility Studies, Female, Genetic Testing, Genotype, Humans, Male, Middle Aged, Mutation, Neoplasms, Biomarkers, Tumor, Patient Selection, Phosphatidylinositol 3-Kinases, Genomics, Proto-Oncogene Proteins B-raf, Proto-Oncogene Proteins c-akt, PTEN Phosphohydrolase, Class I Phosphatidylinositol 3-Kinases
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