Department of Hematology, Aalborg University Hospital, Sdr. Skovvej 15, DK-9000, Aalborg, Denmark.
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
BMC Cancer. 2020 Mar 20;20(1):237. doi: 10.1186/s12885-020-6643-8.
Treatment resistance is a major clinical challenge of diffuse large B-cell lymphoma (DLBCL) where approximately 40% of the patients have refractory disease or relapse. Since DLBCL is characterized by great clinical and molecular heterogeneity, the purpose of the present study was to investigate whether miRNAs associated to single drug components of R-CHOP can improve robustness of individual markers and serve as a prognostic classifier.
Fifteen DLBCL cell lines were tested for sensitivity towards single drug compounds of the standard treatment R-CHOP: rituximab (R), cyclophosphamide (C), doxorubicin (H), and vincristine (O). For each drug, cell lines were ranked using the area under the dose-response curve and grouped as either sensitive, intermediate or resistant. Baseline miRNA expression data were obtained for each cell line in untreated condition, and differential miRNA expression analysis between sensitive and resistant cell lines identified 43 miRNAs associated to growth response after exposure towards single drugs of R-CHOP. Using the Affymetrix HG-U133 platform, expression levels of miRNA precursors were assessed in 701 diagnostic DLBCL biopsies, and miRNA-panel classifiers predicting disease progression were build using multiple Cox regression or random survival forest. Classifiers were validated and ranked by repeated cross-validation.
Prognostic accuracies were assessed by Brier Scores and time-varying area under the ROC curves, which revealed better performance of multivariate Cox models compared to random survival forest models. The Cox model including miR-146a, miR-155, miR-21, miR-34a, and miR-23amiR-27amiR-24-2 cluster performed the best and successfully stratified GCB-DLBCL patients into high- and low-risk of disease progression. In addition, combination of the Cox miRNA-panel and IPI substantially increased prognostic performance in GCB classified patients.
As a proof of concept, we found that expression data of drug associated miRNAs display prognostic utility and adding these to IPI improves prognostic stratification of GCB-DLBCL patients treated with R-CHOP.
治疗抵抗是弥漫性大 B 细胞淋巴瘤 (DLBCL) 的主要临床挑战,约 40%的患者患有难治性疾病或复发。由于 DLBCL 具有很大的临床和分子异质性,本研究的目的是研究与 R-CHOP 单一药物成分相关的 miRNAs 是否可以提高单个标志物的稳健性,并作为预后分类器。
对 15 种 DLBCL 细胞系进行了针对标准治疗 R-CHOP(利妥昔单抗 [R]、环磷酰胺 [C]、多柔比星 [H] 和长春新碱 [O])中单一药物化合物的敏感性测试。对于每种药物,均使用剂量反应曲线下的面积对细胞系进行排序,并分为敏感、中间或耐药。在未经处理的情况下,为每个细胞系获得基线 miRNA 表达数据,并对敏感和耐药细胞系之间的差异 miRNA 表达进行分析,鉴定出与 R-CHOP 单一药物暴露后生长反应相关的 43 个 miRNAs。使用 Affymetrix HG-U133 平台,评估了 701 例诊断性 DLBCL 活检中的 miRNA 前体表达水平,并使用多 Cox 回归或随机生存森林构建了预测疾病进展的 miRNA 面板分类器。通过重复交叉验证验证和排序分类器。
通过 Brier 分数和时间变化的 ROC 曲线下面积评估预后准确性,这表明多变量 Cox 模型的性能优于随机生存森林模型。包含 miR-146a、miR-155、miR-21、miR-34a 和 miR-23amiR-27amiR-24-2 簇的 Cox 模型表现最好,并成功将 GCB-DLBCL 患者分为疾病进展高风险和低风险组。此外,Cox miRNA 面板与 IPI 的组合大大提高了 GCB 分类患者的预后分层。
作为概念验证,我们发现与药物相关的 miRNA 的表达数据具有预后作用,并且将这些与 IPI 结合使用可以改善接受 R-CHOP 治疗的 GCB-DLBCL 患者的预后分层。