Department of Medical Oncology, Lymphoma Research Group, Hospital Universitario Puerta de Hierro-Majadahonda, IDIPHISA, Madrid, Spain.
Department of Medical Oncology, Lymphoma Research Group, Hospital Universitario Puerta de Hierro-Majadahonda, IDIPHISA, Madrid, Spain; CoE Data Intelligence, Fujitsu Technology Solutions S.A., Pozuelo de Alarcón, Madrid, Spain.
Mod Pathol. 2024 Jul;37(7):100516. doi: 10.1016/j.modpat.2024.100516. Epub 2024 May 17.
Follicular lymphoma (FL) is the most frequent indolent lymphoma. Some patients (10%-15%) experience histologic transformation (HT) to a more aggressive lymphoma, usually diffuse large B-cell lymphoma (DLBCL). This study aimed to validate and improve a genetic risk model to predict HT at diagnosis.We collected mutational data from diagnosis biopsies of 64 FL patients. We combined them with the data from a previously published cohort (total n = 104; 62 from nontransformed and 42 from patients who did transform to DLBCL). This combined cohort was used to develop a nomogram to estimate the risk of HT. Prognostic mutated genes and clinical variables were assessed using Cox regression analysis to generate a risk model. The model was internally validated by bootstrapping and externally validated in an independent cohort. Its performance was evaluated using a concordance index and a calibration curve. The clinicogenetic nomogram included the mutational status of 3 genes (HIST1HE1, KMT2D, and TNFSR14) and high-risk Follicular Lymphoma International Prognostic Index and predicted HT with a concordance index of 0.746. Patients were classified as being at low or high risk of transformation. The probability HT function at 24 months was 0.90 in the low-risk group vs 0.51 in the high-risk group and, at 60 months, 0.71 vs 0.15, respectively. In the external validation cohort, the probability HT function in the low-risk group was 0.86 vs 0.54 in the high-risk group at 24 months, and 0.71 vs 0.32 at 60 months. The concordance index in the external cohort was 0.552. In conclusion, we propose a clinicogenetic risk model to predict FL HT to DLBLC, combining genetic alterations in HIST1H1E, KMT2D, and TNFRSF14 genes and clinical features (Follicular Lymphoma International Prognostic Index) at diagnosis. This model could improve the management of FL patients and allow treatment strategies that would prevent or delay transformation.
滤泡性淋巴瘤 (FL) 是最常见的惰性淋巴瘤。一些患者（10%-15%）会发生组织学转化（HT），转化为侵袭性更强的淋巴瘤，通常为弥漫性大 B 细胞淋巴瘤（DLBCL）。本研究旨在验证和改进一种遗传风险模型，以预测诊断时的 HT。我们收集了 64 例 FL 患者诊断活检的突变数据。我们将其与之前发表的队列数据（共 n=104；62 例来自未转化的患者，42 例来自转化为 DLBCL 的患者）相结合。该联合队列用于开发一个列线图来估计 HT 的风险。使用 Cox 回归分析评估预后突变基因和临床变量，以生成风险模型。通过 bootstrap 对模型进行内部验证，并在独立队列中进行外部验证。使用一致性指数和校准曲线评估其性能。临床遗传列线图包括 3 个基因（HIST1HE1、KMT2D 和 TNFSR14）的突变状态和高风险滤泡性淋巴瘤国际预后指数，并以 0.746 的一致性指数预测 HT。患者被分为低危或高危转化组。低危组 24 个月 HT 概率为 0.90，高危组为 0.51；60 个月时，低危组为 0.71，高危组为 0.15。在外部验证队列中，低危组 24 个月 HT 概率为 0.86，高危组为 0.54；60 个月时，低危组为 0.71，高危组为 0.32。外部队列的一致性指数为 0.552。总之，我们提出了一种临床遗传风险模型，以预测 FL 向 DLBLC 的 HT，该模型结合了 HIST1H1E、KMT2D 和 TNFRSF14 基因的遗传改变和诊断时的临床特征（滤泡性淋巴瘤国际预后指数）。该模型可以改善 FL 患者的管理，并允许采取预防或延迟转化的治疗策略。
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