滤泡性淋巴瘤（FL）是一种惰性淋巴瘤，预后通常良好。然而，组织学转化（HT）为更具侵袭性的疾病会导致明显较差的结果。本研究旨在确定 FL 初始诊断时预测 HT 的生物学差异。我们显示了随后发生 HT 的 FL 患者（随后转化的 FL，st-FL，n=20）与未发生 HT 的患者（非转化 FL，nt-FL，n=34）的诊断性肿瘤组织样本之间的差异蛋白表达通过无标记定量纳液相色谱-串联质谱 (LFQ nLC-MS/MS) 分析。 nt-FL 和 st-FL 样本的蛋白质谱可识别出患有 HT 高风险的患者。伴随着影响细胞凋亡、细胞骨架、细胞周期和免疫过程的细胞途径的紊乱。诊断性 st-FL 样品与配对转化 FL（tFL，n=20）样品之间的比较显示出差异的蛋白质谱和破坏的细胞途径，表明从诊断时间到 HT 之间存在显着的生物学差异。对凋亡蛋白 CASP3、MCL1、BAX、BCL-xL 和 BCL-rambo 进行的免疫组织化学分析证实，与 nt-FL 样本相比，st-FL 中的表达水平较高（p<0.001、p=0.015、p=0.003、p=分别为 0.025 和 p=0.057）。此外，所有五种标记均与较短的无转化生存期相关（TFS；分别为p<0.001、p=0.002、p<0.001、p=0.069 和p=0.010）。值得注意的是，将这些蛋白质的表达水平结合到风险评分中显示，随着阳性标记物数量的增加，TFS 越来越差。总之，蛋白质组学在 FL 诊断时发现了改变的蛋白质表达谱（特别是凋亡蛋白），这预测了后来的转化。这可能有助于未来改进这些患者的风险评估和个性化管理策略。版权所有 © 2023 美国血液学会。

Follicular lymphoma (FL) is an indolent lymphoma with a generally favorable prognosis. However, histological transformation (HT) to a more aggressive disease leads to markedly inferior outcomes. This study aimed to identify biological differences predictive of HT at the time of initial FL diagnosis. We show differential protein expression between diagnostic tumor-tissue samples from FL patients with subsequent HT (subsequently-transforming FL, st-FL, n=20) compared with patients without HT (non-transforming FL, nt-FL, n=34) by label-free quantification nano liquid chromatography-tandem mass spectrometry (LFQ nLC-MS/MS) analysis. Protein profiles from nt-FL and st-FL samples identified patients with high risk of HT. This was accompanied by disturbances in cellular pathways influencing apoptosis, the cytoskeleton, cell cycle, and immune processes. Comparisons between diagnostic st-FL samples and paired transformed FL (tFL, n=20) samples demonstrated differential protein profiles and disrupted cellular pathways, indicating striking biological differences from the time of diagnosis up to HT. Immunohistochemical analysis of apoptotic proteins, CASP3, MCL1, BAX, BCL-xL, and BCL-rambo, confirmed higher expression levels in st-FL compared with nt-FL samples (p<0.001, p=0.015, p=0.003, p=0.025, and p=0.057, respectively). Moreover, all five markers were associated with shorter transformation-free survival (TFS; p<0.001, p=0.002, p<0.001, p=0.069, and p=0.010, respectively). Notably, combining the expression levels of these proteins in a risk score revealed increasingly inferior TFS with an increasing number of positive markers. In conclusion, proteomics identified altered protein expression profiles (in particular apoptotic proteins) at time of FL diagnosis, that predicted later transformation. This may contribute to future improved risk assessment and personalized management strategies for these patients.Copyright © 2023 American Society of Hematology.