CHICAGO – Duke University School of Medicine researchers have improved the performance of a model for determining metastatic castrate-resistant prostate cancer (mCRPC) patients' overall survival prognosis by adding circulating-tumor DNA pathogenic genetic alterations to clinical factors.

芝加哥-杜克大学医学院的研究人员通过将循环肿瘤DNA致病性遗传改变添加到临床因素中，改进了确定转移性去势抵抗性前列腺癌（mCRPC）患者总体生存预后的模型的性能。

Presenting at the American Society of Clinical Oncology's annual meeting on Saturday, Susan Halabi, a professor of biostatistics and bioinformatics at Duke, reported that the researchers built on a previously developed model that used clinical factors to determine overall survival in patients with mCRPC who had been treated with androgen receptor inhibitors.

在周六的美国临床肿瘤学会年会上，杜克大学生物统计学和生物信息学教授苏珊·哈拉比（SusanHalabi）报告说，研究人员建立在先前开发的模型基础上，该模型使用临床因素来确定接受雄激素受体抑制剂治疗的mCRPC患者的总体生存率。

The model originally factored in performance status, disease site, opioid analgesic use, and the presence of lactate dehydrogenase, albumin, hemoglobin, prostate specific antigen, and alkaline phosphatase, Halabi noted. .

哈拉比指出，该模型最初考虑了性能状态，疾病部位，阿片类镇痛药的使用以及乳酸脱氢酶，白蛋白，血红蛋白，前列腺特异性抗原和碱性磷酸酶的存在。。

Researchers sought to update this model with pathogenic genetic alterations identified in ctDNA in 776 mCRPC patients' samples from the previously conducted Alliance A031201Phase III trial. This study tested the activity of Pfizer and Astellas' Xtandi (enzalutamide) with or without Xtandi and Janssen's Biotech's Zytiga (abiraterone) and prednisone..

研究人员试图用先前进行的联盟A031201201III期试验的776名mCRPC患者样本中ctDNA中鉴定出的致病性遗传改变来更新该模型。这项研究测试了辉瑞（Pfizer）和Astellas的Xtandi（enzalutamide）在有或没有Xtandi和Janssen的Biotech的Zytiga（阿比特龙）和泼尼松的情况下的活性。。

The original model using only clinical factors had an area under the receiver operating characteristic curve of .72, while the model with combined clinical and genetic factors had an area under the receiver operating characteristic curve of .77 – a 'statistically significant' increase in accuracy, Halabi added. .

哈拉比补充道，仅使用临床因素的原始模型在受试者工作特征曲线下的面积为0.72，而结合临床和遗传因素的模型在受试者工作特征曲线下的面积为0.77，这在准确性上“具有统计学意义”。。

To determine which genetic factors would be included in the updated model, Halabi said the team used the 69-gene AR ctDetect assay, which utilized cell-free DNA isolated from up to 3 milliliters of plasma. The University of Minnesota Genomics Center performed DNA sequencing library preparation and custom targeted panel sequencing, and the researchers developed a custom bioinformatics pipeline to identify ctDNA aneuploidy fraction, copy number gains or losses of target panel genes, pathogenic single nucleotide variants in target panel genes, and AR gene structural rearrangements.

哈拉比说，为了确定更新后的模型中会包含哪些遗传因素，该团队使用了69基因AR ctDetect检测方法，该方法利用从多达3毫升血浆中分离出的无细胞DNA。明尼苏达大学基因组学中心进行了DNA测序文库制备和定制靶向面板测序，研究人员开发了定制的生物信息学管道，以鉴定ctDNA非整倍体分数，靶面板基因的拷贝数增减，靶面板基因中的致病性单核苷酸变异，以及AR基因结构重排。

.

.

In building the model, Halabi's team used a machine learning-based approach to first identify the genetic variables that were associated with survival in mCRPC patients. They cross-validated the model by randomly splitting the data 100 times to check its performance and found that the variables 'were very much robust,' Halabi said.

在建立模型时，Halabi的团队使用基于机器学习的方法，首先确定与mCRPC患者生存相关的遗传变量。哈拉比说，他们通过将数据随机分割100次来交叉验证模型，以检查其性能，发现变量“非常稳健”。

.

.

The researchers incorporated the clinical variables, ctDNA aneuploidy fraction, and BRCA2 loss into the model and determined the time-dependent area under the receiver operating characteristic curve to assess the model's predictive accuracy, Halabi added.

哈拉比补充说，研究人员将临床变量、ctDNA非整倍体分数和BRCA2丢失纳入模型，并确定受试者工作特征曲线下的时间依赖面积，以评估模型的预测准确性。

In the updated model, the genetic features that were included were AR enhancer gain, hemoglobin, MYC gain, RSPO2 gain, and alkaline phosphatase, she noted.

她指出，在更新的模型中，包括AR增强子增益，血红蛋白，MYC增益，RSPO2增益和碱性磷酸酶的遗传特征。

Finally, the researchers used the predictive risk score generated by the updated model to categorize patients in the Alliance A031201 trial into prognostic risk groups. For example, when researchers use the model to stratify patients into four prognostic risk groups — low, low intermediate, intermediate poor, and poor —  those in the poor risk group had a median overall survival of 16.3 months while some patients in the low risk group were still alive when the trial ended.

最后，研究人员使用更新模型产生的预测风险评分将联盟A031201试验中的患者分为预后风险组。例如，当研究人员使用该模型将患者分为四个预后风险组-低，低，中，中，差-低风险组的患者中位总生存期为16.3个月，而低风险组的一些患者在试验结束时仍然活着。

When they stratified patients into a three-prognostic risk group (low, intermediate, and poor), the poor risk group had a median overall survival of 17.9 months, while  some in the low risk group were still alive.  .

当他们将患者分为三个预后风险组（低，中，差）时，低风险组的中位总生存期为17.9个月，而低风险组中的一些仍然活着。。

The model 'could be used not only for counseling patients, but it could be used in the design of randomized studies for selecting patients for an enriched design or as a stratification variable ... in the randomization,' Halabi said.

该模型不仅可用于咨询患者，还可用于随机研究的设计，以选择患者进行丰富设计或作为分层变量。。。哈拉比说。

She highlighted that this genetic analysis was possible using a small amount of plasma garnered from noninvasive testing but added that the model needs to be externally validated, particularly 'in the context of other therapies.'

她强调，这种基因分析可以使用从非侵入性测试中获得的少量血浆，但补充说，该模型需要进行外部验证，特别是“在其他疗法的背景下”