Scott Jacob G, Berglund Anders, Schell Michael J, Mihaylov Ivaylo, 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
Department of Radiation Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA; Department of Integrated Mathematical Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Department of Integrated Bioinformatics and Biostatistics, Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Lancet Oncol. 2017 Feb;18(2):202-211. doi: 10.1016/S1470-2045(16)30648-9. Epub 2016 Dec 18.
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.
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).
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).
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.
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尽管放射疗法在癌症治疗中被广泛使用，但尚未进入精准医学时代，也没有基于肿瘤之间或肿瘤内部生物学差异来调整剂量的方法。我们旨在评估患者特异性的放射敏感性分子特征是否可用于确定最佳放疗剂量。
我们使用基于基因表达的放射敏感性指数和线性二次模型来推导基因组调整放射剂量（GARD）。高GARD值预示着放疗具有高治疗效果；我们推测这与临床结果相关。利用前瞻性观察性全癌护理（TCC）方案的数据，我们针对20种疾病部位的原发性肿瘤计算GARD，每种疾病类型均采用标准放疗剂量。我们还使用多变量Cox模型评估GARD在五个临床队列中是否与临床结果独立相关：伊拉斯姆斯乳腺癌队列（n = 263）；卡罗林斯卡乳腺癌队列（n = 77）；莫菲特肺癌队列（n = 60）；莫菲特胰腺癌队列（n = 40）；以及癌症基因组图谱胶质母细胞瘤患者队列（n = 98）。
我们计算了TCC队列中8271个组织样本的GARD。尽管在疾病类型内分配了统一的放疗剂量，但TCC队列中的GARD值范围很广（范围为1·66 - 172·4）。胶质瘤和肉瘤的GARD中位数最低，宫颈癌和口咽头颈癌的GARD中位数最高。肿瘤类型组内的GARD值范围也很广。GARD可独立预测乳腺癌、肺癌、胶质母细胞瘤和胰腺癌的临床结果。在伊拉斯姆斯乳腺癌队列中，GARD值高的患者5年无远处转移生存率高于GARD值低的患者（风险比2·11，95% 置信区间1·13 - 3·94，p = 0·018）。
基于GARD的临床模型可使放疗剂量根据肿瘤放射敏感性进行个体化，并可为放射肿瘤学中设计基因组指导的临床试验提供框架。
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