背景:间变性淋巴瘤激酶-酪氨酸激酶抑制剂(ALK-TKIs)在ALK阳性的非小细胞肺癌(NSCLC)患者中显示出显著的治疗效果。识别预后生物标志物可以增强复发或难治性患者的临床疗效。
方法:我们使用独立于数据的采集-质谱(DIA-MS)分析了63例ALK阳性NSCLC患者的159例治疗前和治疗中血浆样品中的737种血浆蛋白。一致性聚类算法用于识别具有不同生物学特征的亚型。使用LASSO-Cox方法构建基于血浆的预后模型。我们进行了Mfuzz分析以对治疗期间血浆蛋白的纵向变化模式进行分类。收集来自另一个独立ALK-TKI治疗组群的52个基线血浆样品以使用ELISA验证潜在的预后标志物。
结果:我们确定了三种具有不同生物学特征和临床疗效的ALK阳性NSCLC亚型。第1亚组患者表现出激活的体液免疫和炎症反应,阳性急性期反应蛋白的表达增加,和最坏的预后。然后,我们构建并验证了一个预后模型,该模型使用五种血浆蛋白(SERPINA4,ATRN,APOA4,TF,和MYOC)在基线。接下来,我们研究了治疗期间血浆蛋白表达的纵向变化,并确定了4种不同的变化模式(1-4簇).治疗过程中急性期蛋白的纵向变化可以反映患者的治疗状态和肿瘤进展。最后,我们验证了基线血浆CRP的预后功效,SAA1,AHSG,另一个接受ALK-TKI治疗的独立NSCLC队列中的SERPINA4和TF。
结论:本研究有助于寻找血浆样本中ALK-TKI治疗的预后和耐药生物标志物,并为耐药机制和后续治疗选择提供新的见解。
Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients.
We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA.
We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment.
This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.