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基于基因表达谱的滤泡性淋巴瘤患者预后预测评分:三队列回顾性训练和验证分析。

A gene-expression profiling score for prediction of outcome in patients with follicular lymphoma: a retrospective training and validation analysis in three international cohorts.

机构信息

Cancer Research Center of Lyon, INSERM U1052 UMR CNRS 5286, Lyon, France; Laboratoire d'Hématologie, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre-Bénite, France.

Institut Carnot CALYM, Lyon, France.

出版信息

Lancet Oncol. 2018 Apr;19(4):549-561. doi: 10.1016/S1470-2045(18)30102-5. Epub 2018 Feb 20.

Abstract

BACKGROUND

Patients with follicular lymphoma have heterogeneous outcomes. Predictor models to distinguish, at diagnosis, between patients at high and low risk of progression are needed. The objective of this study was to use gene-expression profiling data to build and validate a predictive model of outcome for patients treated in the rituximab era.

METHODS

A training set of fresh-frozen tumour biopsies was prospectively obtained from 160 untreated patients with high-tumour-burden follicular lymphoma enrolled in the phase 3 randomised PRIMA trial, in which rituximab maintenance was evaluated after rituximab plus chemotherapy induction (median follow-up 6·6 years [IQR 6·0-7·0]). RNA of sufficient quality was obtained for 149 of 160 cases, and Affymetrix U133 Plus 2.0 microarrays were used for gene-expression profiling. We did a multivariate Cox regression analysis to identify genes with expression levels associated with progression-free survival independently of maintenance treatment in a subgroup of 134 randomised patients. Expression levels from 95 curated genes were then determined by digital expression profiling (NanoString technology) in 53 formalin-fixed paraffin-embedded samples of the training set to compare the technical reproducibility of expression levels for each gene between technologies. Genes with high correlation (>0·75) were included in an L2-penalised Cox model adjusted on rituximab maintenance to build a predictive score for progression-free survival. The model was validated using NanoString technology to digitally quantify gene expression in 488 formalin-fixed, paraffin-embedded samples from three independent international patient cohorts from the PRIMA trial (n=178; distinct from the training cohort), the University of Iowa/Mayo Clinic Lymphoma SPORE project (n=201), and the Barcelona Hospital Clinic (n=109). All tissue samples consisted of pretreatment diagnostic biopsies and were confirmed as follicular lymphoma grade 1-3a. The patients were all treated with regimens containing rituximab and chemotherapy, possibly followed by either rituximab maintenance or ibritumomab-tiuxetan consolidation. We determined an optimum threshold on the score to predict patients at low risk and high risk of progression. The model, including the multigene score and the threshold, was initially evaluated in the three validation cohorts separately. The sensitivity and specificity of the score for the prediction of the risk of lymphoma progression at 2 years were assessed on the combined validation cohorts.

FINDINGS

In the training cohort, the expression levels of 395 genes were associated with a risk of progression. 23 genes reflecting both B-cell biology and tumour microenvironment with correlation coefficients greater than 0·75 between the two technologies and sample types were retained to build a predictive model that identified a population at an increased risk of progression (p<0·0001). In a multivariate Cox model for progression-free survival adjusted on rituximab maintenance treatment and Follicular Lymphoma International Prognostic Index 1 (FLIPI-1) score, this predictor independently predicted progression (adjusted hazard ratio [aHR] of the high-risk group compared with the low-risk group 3·68, 95% CI 2·19-6·17 [p<0·0001]). The 5-year progression-free survival was 26% (95% CI 16-43) in the high-risk group and 73% (64-83) in the low-risk group. The predictor performances were confirmed in each of the individual validation cohorts (aHR comparing high-risk to low-risk groups 2·57 [95% CI 1·65-4·01] in cohort 1; 2·12 [1·32-3·39] in cohort 2; and 2·11 [1·01-4·41] in cohort 3). In the combined validation cohort, the median progression-free survival was 3·1 years (95% CI 2·4-4·8) in the high-risk group and 10·8 years (10·1-not reached) in the low-risk group (p<0·0001). The risk of lymphoma progression at 2 years was 38% (95% CI 29-46) in the high-risk group and 19% (15-24) in the low-risk group. In a multivariate analysis, the score predicted progression-free survival independently of anti-CD20 maintenance treatment and of the FLIPI score (aHR for the combined cohort 2·30, 95% CI 1·72-3·07).

INTERPRETATION

We developed and validated a robust 23-gene expression-based predictor of progression-free survival that is applicable to routinely available formalin-fixed, paraffin-embedded tumour biopsies from patients with follicular lymphoma at time of diagnosis. Applying this score could allow individualised therapy for patients according to their risk category.

FUNDING

Roche, SIRIC Lyric, LYSARC, National Institutes of Health, the Henry J Predolin Foundation, and the Spanish Plan Nacional de Investigacion.

摘要

背景

滤泡性淋巴瘤患者的结局存在异质性。需要建立预测模型,以便在诊断时区分高风险和低风险进展的患者。本研究旨在使用基因表达谱数据构建和验证利妥昔单抗时代滤泡性淋巴瘤患者结局的预测模型。

方法

前瞻性纳入 PRIMA 试验中 160 例高肿瘤负荷滤泡性淋巴瘤初治患者的新鲜冷冻肿瘤活检组织作为训练集,其中评估了利妥昔单抗联合化疗诱导后利妥昔单抗维持治疗(中位随访 6.6 年[IQR 6.0-7.0])。160 例患者中有 149 例获得了足够质量的 RNA,使用 Affymetrix U133 Plus 2.0 微阵列进行基因表达谱分析。我们对 134 例随机患者的亚组进行了多变量 Cox 回归分析,以确定独立于维持治疗的与无进展生存相关的表达水平的基因。在训练集中的 53 例福尔马林固定石蜡包埋样本中,使用数字表达谱分析(NanoString 技术)来确定 95 个经精心挑选的基因的表达水平,以比较两种技术之间每个基因表达水平的技术重现性。相关性大于 0.75 的基因被纳入 L2 惩罚 Cox 模型中,以调整利妥昔单抗维持治疗,构建无进展生存预测评分。该模型使用 NanoString 技术对来自 PRIMA 试验的三个独立国际患者队列(n=178;与训练队列不同)、爱荷华大学/Mayo 诊所淋巴瘤 SPORE 项目(n=201)和巴塞罗那医院(n=109)的 488 例福尔马林固定、石蜡包埋样本进行了验证。所有组织样本均为治疗前的诊断性活检,均确认为滤泡性淋巴瘤 1-3a 级。所有患者均接受了包含利妥昔单抗和化疗的治疗方案,可能随后接受利妥昔单抗维持治疗或替伊莫单抗-奥法木单抗巩固治疗。我们确定了一个最佳阈值来预测低风险和高风险进展的患者。该模型包括多基因评分和阈值,最初在三个验证队列中分别进行评估。在合并的验证队列中评估了该评分在预测 2 年内淋巴瘤进展风险的敏感性和特异性。

结果

在训练队列中,395 个基因的表达水平与进展风险相关。保留了 23 个反映 B 细胞生物学和肿瘤微环境的基因,它们在两种技术和样本类型之间的相关系数大于 0.75,以构建预测模型,该模型确定了一个进展风险增加的人群(p<0.0001)。在调整利妥昔单抗维持治疗和滤泡性淋巴瘤国际预后指数 1(FLIPI-1)评分的无进展生存多变量 Cox 模型中,该预测因子独立预测了进展(高风险组与低风险组的调整后危险比[aHR]为 3.68,95%CI 2.19-6.17 [p<0.0001])。高风险组的 5 年无进展生存率为 26%(95%CI 16-43),低风险组为 73%(64-83)。在每个单独的验证队列中都证实了该预测因子的性能(高风险组与低风险组的 aHR 比较分别为队列 1 中的 2.57 [95%CI 1.65-4.01];队列 2 中的 2.12 [1.32-3.39];以及队列 3 中的 2.11 [1.01-4.41])。在合并的验证队列中,高风险组的中位无进展生存率为 3.1 年(95%CI 2.4-4.8),低风险组为 10.8 年(10.1-未达到)(p<0.0001)。高风险组 2 年内淋巴瘤进展的风险为 38%(95%CI 29-46),低风险组为 19%(15-24)。在多变量分析中,该评分独立于抗 CD20 维持治疗和 FLIPI 评分预测无进展生存(联合队列的 aHR 为 2.30,95%CI 1.72-3.07)。

结论

我们开发并验证了一种稳健的基于 23 个基因表达的无进展生存预测模型,适用于滤泡性淋巴瘤患者诊断时获得的常规福尔马林固定、石蜡包埋肿瘤活检。应用该评分可根据患者的风险类别进行个体化治疗。

资助

罗氏、SIRIC Lyric、LYSARC、美国国立卫生研究院、Henry J Predolin 基金会和西班牙国家研究计划。

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