A genome-based model for adjusting radiotherapy dose (GARD)

a retrospective, cohort-based study

Jacob G. Scott, Anders Berglund, Michael J. Schell, Ivaylo B Mihaylov, William J. Fulp, Binglin Yue, Eric Welsh, Jimmy J. Caudell, Kamran Ahmed, Tobin S. Strom, Eric Mellon, Puja Venkat, Peter Johnstone, John Foekens, Jae Lee, Eduardo Moros, William S. Dalton, Steven A. Eschrich, Howard McLeod, Louis B. Harrison & 1 others Javier F. Torres-Roca

Research output: Contribution to journalArticle

97 Citations (Scopus)

Abstract

Background Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose. Methods We used the gene-expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98). Findings We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66–172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13–3·94, p=0·018). Interpretation A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology. Funding None.

Original languageEnglish (US)
Pages (from-to)202-211
Number of pages10
JournalThe Lancet Oncology
Volume18
Issue number2
DOIs
StatePublished - Feb 1 2017

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Cohort Studies
Radiotherapy
Genome
Neoplasms
Radiation Tolerance
Breast Neoplasms
Lung Neoplasms
Glioblastoma
Head and Neck Neoplasms
Pancreatic Neoplasms
Oropharyngeal Neoplasms
Precision Medicine
Radiation Oncology
Atlases
Therapeutic Uses
Glioma
Uterine Cervical Neoplasms
Sarcoma
Linear Models
Clinical Trials

ASJC Scopus subject areas

  • Oncology

Cite this

A genome-based model for adjusting radiotherapy dose (GARD) : a retrospective, cohort-based study. / Scott, Jacob G.; Berglund, Anders; Schell, Michael J.; Mihaylov, Ivaylo B; Fulp, William J.; Yue, Binglin; Welsh, Eric; Caudell, Jimmy J.; Ahmed, Kamran; Strom, Tobin S.; Mellon, Eric; Venkat, Puja; Johnstone, Peter; Foekens, John; Lee, Jae; Moros, Eduardo; Dalton, William S.; Eschrich, Steven A.; McLeod, Howard; Harrison, Louis B.; Torres-Roca, Javier F.

In: The Lancet Oncology, Vol. 18, No. 2, 01.02.2017, p. 202-211.

Research output: Contribution to journalArticle

Scott, JG, Berglund, A, Schell, MJ, Mihaylov, IB, Fulp, WJ, Yue, B, Welsh, E, Caudell, JJ, Ahmed, K, Strom, TS, Mellon, E, Venkat, P, Johnstone, P, Foekens, J, Lee, J, Moros, E, Dalton, WS, Eschrich, SA, McLeod, H, Harrison, LB & Torres-Roca, JF 2017, 'A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study', The Lancet Oncology, vol. 18, no. 2, pp. 202-211. https://doi.org/10.1016/S1470-2045(16)30648-9
Scott, Jacob G. ; Berglund, Anders ; Schell, Michael J. ; Mihaylov, Ivaylo B ; Fulp, William J. ; Yue, Binglin ; Welsh, Eric ; Caudell, Jimmy J. ; Ahmed, Kamran ; Strom, Tobin S. ; Mellon, Eric ; Venkat, Puja ; Johnstone, Peter ; Foekens, John ; Lee, Jae ; Moros, Eduardo ; Dalton, William S. ; Eschrich, Steven A. ; McLeod, Howard ; Harrison, Louis B. ; Torres-Roca, Javier F. / A genome-based model for adjusting radiotherapy dose (GARD) : a retrospective, cohort-based study. In: The Lancet Oncology. 2017 ; Vol. 18, No. 2. pp. 202-211.
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T2 - a retrospective, cohort-based study

AU - Scott, Jacob G.

AU - Berglund, Anders

AU - Schell, Michael J.

AU - Mihaylov, Ivaylo B

AU - Fulp, William J.

AU - Yue, Binglin

AU - Welsh, Eric

AU - Caudell, Jimmy J.

AU - Ahmed, Kamran

AU - Strom, Tobin S.

AU - Mellon, Eric

AU - Venkat, Puja

AU - Johnstone, Peter

AU - Foekens, John

AU - Lee, Jae

AU - Moros, Eduardo

AU - Dalton, William S.

AU - Eschrich, Steven A.

AU - McLeod, Howard

AU - Harrison, Louis B.

AU - Torres-Roca, Javier F.

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N2 - Background Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose. Methods We used the gene-expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98). Findings We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66–172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13–3·94, p=0·018). Interpretation A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology. Funding None.

AB - Background Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose. Methods We used the gene-expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98). Findings We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66–172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13–3·94, p=0·018). Interpretation A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology. Funding None.

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