Key Points

• The genomic-adjusted radiation dose (GARD) is the first opportunity to use genomic information to optimize radiotherapy doses.
• GARD was significantly associated with survival and recurrence, whereas the physical radiation dose was not.

Using the predicted radiation dose effect derived from an individual patient's genomic profile may result in a better outcome according to a new study appearing in Lancet Oncology (2021;22:1221-1229. doi:10.1016/S1470-2045(21)00347-8). The study focused on a novel algorithm that a team of researchers developed on the basis of a personalized GARD model using individual tumor genomic parameters rather than the commonly administered “one-size-fits-all” dosages based on the cancer diagnosis. The researchers of this new study noted an incentive for the study: “Patients we treat uniformly do not have a uniform response.”

The development of GARD was spurred by an understanding that the researchers had uncovered from previous large-scale classification studies showing that the clinical heterogeneity of radiation response was influenced by individual-level differences in genetic variables in the tumors themselves. Using a gene expression–based radiosensitivity index that the study authors had developed earlier, they followed with the GARD model, which combined the radiosensitivity index and radiation dosages to pinpoint the biological effect on specific patients.

Study Details

In this study, researchers from the Cleveland Clinic, Case Western Reserve University, and the Moffitt Cancer Center conducted a pooled analysis of data from 11 previously published clinical cohorts of patients with varying outcomes for 7 different types of cancer: breast cancer (including triple-negative breast cancer), head and neck cancer, non–small cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. They used tumor genomic data from these studies and the clinical information about each patient's treatment to calculate individualized GARD values, and they performed a stratified Cox regression analysis to test for associations of GARD and physical radiation dose with 2 clinical outcomes: time to first recurrence and overall survival. Finally, the researchers estimated the impact that varying GARD would have on 3-year survival for each of the 7 cancer types.

With the exception of 3 cohorts, both time to first recurrence (local, regional, and distant metastasis) and overall survival were calculated from the end of treatment. These patients' outcomes were calculated from the date of pathological diagnosis for the glioma and endometrial cancer cohorts and from the date of randomization for the head and neck cancer cohort.

There were 1615 patients included overall. Among those patients evaluated for time to first recurrence, 982 received radiotherapy, and 316 did not receive radiotherapy. Among those patients evaluated for overall survival, 424 received radiotherapy, and 253 did not.

Study Results

The researchers found that although the range of physical radiation doses in the cohorts was limited to values near those of the standard of care and the doses were delivered in standard fraction sizes, the GARD values showed a wide range of predicted biological effects.

In analyses of the 7 cancer types combined, the researchers found that GARD was associated with time to first recurrence (hazard ratio [HR] per unit change in GARD, 0.98; 95% CI, 0.97-0.99; P = .0017) and overall survival (HR, 0.97; 95% CI, 0.95-0.99; P = .0007). Although the effects per unit change in GARD were small, patients who had similar or identical physical radiation doses often had GARD values differing by 20 or more units, so differences of this magnitude had clinically meaningful implications for patient outcomes.

The GARD values for patients who did not receive radiotherapy (designated as “sham-GARD”) were calculated on the basis of usual doses of physical radiation and were intended as controls. These sham-GARD values were not significantly associated with either time to first recurrence (HR, 1.00; 95% CI, 0.97-1.03) or overall survival (HR, 1.00; 95% CI, 0.98-1.02), and this supports the conclusion that the association of GARD with clinical outcomes is truly related to patients having received radiotherapy.

“We believe our study suggests that GARD is a new unit of measure—and it is the unit we should be using to dose patients.”—Jacob Scott, MD, DPhil

Patients' physical doses of radiation were not significantly associated with either outcome, with HRs of 0.99 (95% CI, 0.97-1.01) and 1.00 (95% CI, 0.96-1.04) for time to first recurrence and overall survival, respectively.

In analyses of all cancers together that included cancer type as a covariate, associations of GARD and 3-year survival were statistically and clinically significant, even though patients with each type of cancer received similar physical radiation doses.

Study Interpretation

“We think our study breaks new ground,” says study author Javier F. Torres-Roca, MD, senior member in the Department of Radiation Oncology at the Moffitt Cancer Center in Tampa, Florida. He adds that GARD is the first opportunity to use genomic information to optimize radiotherapy doses. “It tells you more about the outcome of a patient than the actual RT dose delivered. Importantly, we demonstrate that GARD is not associated with outcome in patients treated without RT and we show that the interaction between GARD and RT is significant, showing that it predicts RT treatment benefit.”

Lead study author Jacob Scott, MD, DPhil, associate professor and staff physician-scientist at Cleveland Clinic and Case Western Reserve University School of Medicine, adds, “We believe our study suggests that GARD is a new unit of measure—and it is the unit we should be using to dose patients.”

Three experts in the field wrote an accompanying comment article in Lancet Oncology (2021;22:1200-1201. doi:10.1016/S1470-2045(21)00411-3): Orit Kaidar-Person, MD, PhD (Sheba Medical Center, Ramat Gan, Israel); Philip Poortmans, MD, PhD (Iridium Network and University of Antwerp, Antwerp, Belgium); and Roberto Salgado, MD, PhD (Department of Pathology, GZA-ZNA Hospitals, Antwerp, Belgium). They wrote that the efforts of Dr. Scott and his colleagues need to be applauded worldwide “because radiotherapy is considerably lagging compared with the enormous progress done in the field of personalized medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents.”

They did have lingering questions about the research. Among their questions is gaining an understanding of the biological basis of GARD. In response, Dr. Scott says that this is largely a phenomenological signature. “Other academics always want to look at the list of genes and see ones that they know about, and then be able to say something about the biology,” he says. “This is human nature. However, due to the network-based method used, that approach doesn't work here.”

Dr. Scott says, “It isn't so much that the genes themselves need to be mechanically causative, but instead what this signature is capturing is a signal from the larger network—each of these genes is more like a canary in the coal mine rather than a specific, causative thing. As a physicist, I'm fine with this. It's just a list of genes that pick up signals that can be used to predict the state of a complex thing.”

The comment authors wrote that although the “clinical utility of genomic assays in daily practice remains to be demonstrated,” they agree with the researchers that a GARD-based framework for radiotherapy should be adopted as the new paradigm for trial design. They recommended that the assay be developed and integrated into clinical trials according to a set of criteria set forth by the National Cancer Institute. “By supporting such projects, including those aiming to identify genetic variants associated with susceptibility to radiotoxicity, we can move toward a more personalized radiotherapy approach for our patients,” they wrote.

中文翻译：

---

基因组衍生的辐射剂量提高了对结果的预测

关键点

• 基因组调整辐射剂量 (GARD) 是使用基因组信息优化放射治疗剂量的第一个机会。
• GARD 与生存和复发显着相关，而物理辐射剂量则没有。

根据Lancet Oncology (2021;22:1221-1229.doi:10.1016/S1470-2045(21)00347-8 ）。该研究侧重于一种新算法，该算法是一组研究人员在个性化 GARD 模型的基础上开发的，该模型使用个体肿瘤基因组参数，而不是基于癌症诊断的常用“一刀切”剂量。这项新研究的研究人员指出了该研究的动机：“我们统一治疗的患者没有统一的反应。”

研究人员从之前的大规模分类研究中发现，放射反应的临床异质性受到肿瘤本身遗传变量的个体水平差异的影响，从而推动了 GARD 的发展。使用研究作者较早开发的基于基因表达的放射敏感性指数，他们采用了 GARD 模型，该模型将放射敏感性指数和放射剂量相结合，以确定对特定患者的生物学效应。

学习详情

在这项研究中，来自克利夫兰诊所、凯斯西储大学和莫菲特癌症中心的研究人员对来自 11 个先前发表的临床队列的数据进行了汇总分析，这些患者对 7 种不同类型的癌症具有不同的结果：乳腺癌（包括三联阴性乳腺癌）、头颈癌、非小细胞肺癌、胰腺癌、子宫内膜癌、黑色素瘤和神经胶质瘤。他们使用来自这些研究的肿瘤基因组数据和每位患者治疗的临床信息来计算个体化的 GARD 值，并进行分层 Cox 回归分析以测试 GARD 和物理辐射剂量与 2 个临床结果的关联：首次复发时间和总生存期。最后，

除 3 个队列外，首次复发时间（局部、区域和远处转移）和总生存期均从治疗结束时计算。这些患者的结果是从胶质瘤和子宫内膜癌队列的病理诊断日期以及头颈癌队列的随机分组日期计算的。

总共包括1615名患者。在评估首次复发时间的患者中，982 人接受了放疗，316 人未接受放疗。在评估总生存期的患者中，424 人接受了放疗，253 人未接受放疗。

研究结果

研究人员发现，尽管队列中的物理辐射剂量范围仅限于接近护理标准的值，并且剂量以标准分数大小提供，但 GARD 值显示出广泛的预测生物效应。

在对 7 种癌症类型的综合分析中，研究人员发现 GARD 与首次复发时间相关（每单位 GARD 变化的风险比 [HR]，0.98；95% CI，0.97-0.99；P = .0017）和总体存活率（HR，0.97；95% CI，0.95-0.99；P = .0007）。尽管 GARD 每单位变化的影响很小，但具有相似或相同物理辐射剂量的患者的 GARD 值通常相差 20 或更多单位，因此这种幅度的差异对患者预后具有临床意义。

未接受放射治疗的患者（称为“sham-GARD”）的 GARD 值是根据物理辐射的常用剂量计算的，并用作对照。这些 sham-GARD 值与首次复发时间（HR，1.00；95% CI，0.97-1.03）或总生存期（HR，1.00；95% CI，0.98-1.02）均无显着相关性，这支持了结论GARD 与临床结果的关联确实与接受放射治疗的患者有关。

“我们相信我们的研究表明 GARD 是一种新的计量单位——它是我们应该用来给患者服用剂量的单位。”——Jacob Scott，医学博士，哲学博士

患者的物理辐射剂量与这两种结果均无显着相关性，首次复发时间和总生存期的 HR 分别为 0.99（95% CI，0.97-1.01）和 1.00（95% CI，0.96-1.04）。

在包括癌症类型作为协变量在内的所有癌症的分析中，GARD 与 3 年生存率的关联具有统计学和临床​​意义，即使患有每种癌症的患者接受了相似的物理辐射剂量。

学习解释

“我们认为我们的研究开辟了新天地，”研究作者、佛罗里达州坦帕市莫菲特癌症中心放射肿瘤学系高级成员、医学博士 Javier F. Torres-Roca 说。他补充说，GARD 是使用基因组信息优化放射治疗剂量的第一个机会。“它告诉你更多关于患者结果的信息，而不是实际提供的 RT 剂量。重要的是，我们证明 GARD 与未接受放疗的患者的结果无关，我们表明 GARD 和放疗之间的相互作用是显着的，表明它可以预测放疗治疗的益处。”

首席研究作者 Jacob Scott 医学博士、哲学博士、克利夫兰诊所和凯斯西储大学医学院副教授兼专职医师科学家补充说：“我们相信我们的研究表明 GARD 是一种新的计量单位，它是我们应该用来给病人给药的单位。”

该领域的三位专家在《柳叶刀肿瘤学》 (2021;22:1200-1201.doi:10.1016/S1470-2045(21)00411-3) 上发表了评论文章：Orit Kaidar-Person, MD, PhD (Sheba Medical Center,以色列拉马特甘）；Philip Poortmans，医学博士，博士（Iridium Network 和安特卫普大学，比利时安特卫普）；和 Roberto Salgado，医学博士，博士（比利时安特卫普 GZA-ZNA 医院病理学系）。他们写道，斯科特博士和他的同事们的努力需要得到全世界的称赞，“因为与目前主要用于决定使用全身治疗或靶向药物的个性化医疗领域取得的巨大进展相比，放射治疗明显滞后。 。”

他们确实对这项研究有挥之不去的疑问。他们的问题之一是了解 GARD 的生物学基础。作为回应，斯科特博士说这在很大程度上是一个现象学特征。“其他学者总是想查看基因列表，看看他们知道的基因，然后能够对生物学发表一些看法，”他说。“这是人的本性。但是，由于使用了基于网络的方法，这种方法在这里行不通。”

斯科特博士说，“与其说基因本身需要机械地致病，不如说这个特征捕捉到的是来自更大网络的信号——这些基因中的每一个都更像是煤矿中的金丝雀而不是一个具体的、因果的事物。作为物理学家，我对此很满意。它只是一个接收信号的基因列表，可用于预测复杂事物的状态。”

评论作者写道，尽管“基因组分析在日常实践中的临床效用仍有待证明”，但他们同意研究人员的观点，即应采用基于 GARD 的放射治疗框架作为试验设计的新范式。他们建议根据美国国家癌症研究所制定的一套标准开发并整合到临床试验中。他们写道：“通过支持此类项目，包括那些旨在识别与放射毒性易感性相关的遗传变异的项目，我们可以为我们的患者采用更加个性化的放射治疗方法。”