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Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis.

التفاصيل البيبلوغرافية
العنوان: Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis.
المؤلفون: Scott JG; Translational Hematology and Oncology Research, Radiation Oncology Department, Cleveland Clinic, Cleveland, OH, USA; Systems Biology and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA., Sedor G; School of Medicine, Case Western Reserve University, Cleveland, OH, USA., Ellsworth P; School of Medicine, Case Western Reserve University, Cleveland, OH, USA., Scarborough JA; Translational Hematology and Oncology Research, Radiation Oncology Department, Cleveland Clinic, Cleveland, OH, USA; Systems Biology and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA., Ahmed KA; Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA., Oliver DE; Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA., Eschrich SA; Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA., Kattan MW; Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA., Torres-Roca JF; Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA. Electronic address: Javier.torresroca@moffitt.org.
المصدر: The Lancet. Oncology [Lancet Oncol] 2021 Sep; Vol. 22 (9), pp. 1221-1229. Date of Electronic Publication: 2021 Aug 04.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Lancet Pub. Group Country of Publication: England NLM ID: 100957246 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1474-5488 (Electronic) Linking ISSN: 14702045 NLM ISO Abbreviation: Lancet Oncol Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : Lancet Pub. Group, c2000-
مواضيع طبية MeSH: Radiotherapy Dosage*, Neoplasms/*radiotherapy , Radiation Genomics/*methods, Databases, Factual ; Humans ; Neoplasms/genetics ; Neoplasms/mortality ; Precision Medicine ; Recurrence ; Survival Rate
مستخلص: Background: Despite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. We hypothesise that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared with physical dose of radiotherapy alone. We aimed to test this hypothesis and investigate the GARD-based radiotherapy dosing paradigm.
Methods: We did a pooled, pan-cancer analysis of 11 previously published clinical cohorts of unique patients with seven different types of cancer, which are all available cohorts with the data required to calculate GARD, together with clinical outcome. The included cancers were breast cancer, head and neck cancer, non-small-cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. Our dataset comprised 1615 unique patients, of whom 1298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 patients (424 with radiotherapy and 253 without radiotherapy) were assessed for overall survival. We analysed two clinical outcomes of interest: time to first recurrence and overall survival. We used Cox regression, stratified by cohort, to test the association between GARD and outcome with separate models using dose of radiation and sham-GARD (ie, patients treated without radiotherapy, but modelled as having a standard-of-care dose of radiotherapy) for comparison. We did interaction tests between GARD and treatment (with or without radiotherapy) using the Wald statistic.
Findings: Pooled analysis of all available data showed that GARD as a continuous variable is associated with time to first recurrence (hazard ratio [HR] 0·98 [95% CI 0·97-0·99]; p=0·0017) and overall survival (0·97 [0·95-0·99]; p=0·0007). The interaction test showed the effect of GARD on overall survival depends on whether or not that patient received radiotherapy (Wald statistic p=0·011). The interaction test for GARD and radiotherapy was not significant for time to first recurrence (Wald statistic p=0·22). The HR for physical dose of radiation was 0·99 (95% CI 0·97-1·01; p=0·53) for time to first recurrence and 1·00 (0·96-1·04; p=0·95) for overall survival. The HR for sham-GARD was 1·00 (0·97-1·03; p=1·00) for time to first recurrence and 1·00 (0·98-1·02; p=0·87) for overall survival.
Interpretation: The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose.
Funding: None. VIDEO ABSTRACT.
Competing Interests: Declaration of interests JGS, SAE, and JFT-R hold intellectual property on RSI, GARD, and prescription dose base on RSI (known as RxRSI), in addition to equity in Cvergenx, a company that seeks to commercialise these methods. Patents held by Moffitt Cancer Center are as follows: RSI (awarded) patent number 7 879 545; 8 655 598; 8 660 801, and 9 846 762; GARD (awarded) patent number 10 697 023; and Cvergenx (RxRSI [pending] application number 16/658 961). SAE and JFT-R are cofounders and board members of Cvergenx. All other authors declare no competing interests.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)
التعليقات: Comment in: Lancet Oncol. 2021 Sep;22(9):1200-1201. (PMID: 34363760)
Comment in: Lancet Oncol. 2021 Nov;22(11):e468. (PMID: 34735810)
Comment in: Lancet Oncol. 2021 Nov;22(11):e469. (PMID: 34735811)
Comment in: Lancet Oncol. 2021 Nov;22(11):e470-e471. (PMID: 34735812)
Comment in: CA Cancer J Clin. 2022 Jan;72(1):5-6. (PMID: 34874554)
تواريخ الأحداث: Date Created: 20210807 Date Completed: 20210921 Latest Revision: 20220215
رمز التحديث: 20240628
DOI: 10.1016/S1470-2045(21)00347-8
PMID: 34363761
قاعدة البيانات: MEDLINE
الوصف
تدمد:1474-5488
DOI:10.1016/S1470-2045(21)00347-8