Islam Syed S, Al-Tweigeri Taher, Tulbah Asma, Najjar Saleh N, Aljohani Sarah S, Al-Harbi Layla, Gad Ahmed M, Ujjahan Shafat, Aboussekhra Abdelilah
Department of Molecular Oncology, King Faisal Specialist Hospital & Research Centre, Riyadh, Saudi Arabia.
School of Medicine, Al-Faisal University, Riyadh, Saudi Arabia.
Cell Death Discov. 2025 Sep 9;11(1):421. doi: 10.1038/s41420-025-02701-8.
Ado-trastuzumab is considered a standard treatment for patients with HER2+ metastatic breast cancer (mBC). Current clinical practices do not reliably predict therapeutic outcomes for patients who are refractory to therapy. Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and therapeutic resistance, and the use of lncRNAs as tumor biomarkers is becoming more common in other diseases. However, whether they may also be used to predict therapy response in HER2+ mBC is unclear. Using lncRNA microarray profiling, we identified 23 differentially expressed lncRNAs in the serum of HER2+ mBC patients with unique responses to trastuzumab-emtansine (T-DM1). Following RT-PCR validation and machine learning-based selection in the training cohort, four lncRNAs were selected to construct the signature panel and used for T-DM1 response prediction. This four-lncRNA signature classifies patients into high- and low-risk groups and significantly and distinctively predicts patient survival. Importantly, identical outcomes were obtained from the two validation cohorts, confirming that the signature accurately predicts the T-DM1 response of HER2+ mBC patients. Integrative analysis demonstrated that this four-lncRNA signature is primarily released by immune and tumor cells and is correlated with immune activity. Our findings indicate that the four-lncRNA signature is a potentially promising biomarker for predicting T-DM1 treatment outcome, as it may reliably predict the T-DM1 treatment response in HER2+ mBC.
ado曲妥珠单抗被认为是HER2阳性转移性乳腺癌(mBC)患者的标准治疗方法。目前的临床实践无法可靠地预测对治疗耐药患者的治疗结果。长链非编码RNA(lncRNA)正成为基因表达和治疗耐药的关键调节因子,lncRNA作为肿瘤生物标志物在其他疾病中的应用越来越普遍。然而,它们是否也可用于预测HER2阳性mBC的治疗反应尚不清楚。通过lncRNA微阵列分析,我们在对曲妥珠单抗-恩美曲妥珠单抗(T-DM1)有独特反应的HER2阳性mBC患者血清中鉴定出23种差异表达的lncRNA。在训练队列中进行RT-PCR验证和基于机器学习的筛选后,选择了4种lncRNA构建特征面板并用于T-DM1反应预测。这种4-lncRNA特征将患者分为高风险和低风险组,并显著且独特地预测患者生存。重要的是,两个验证队列获得了相同的结果,证实该特征准确预测了HER2阳性mBC患者的T-DM1反应。综合分析表明,这种4-lncRNA特征主要由免疫细胞和肿瘤细胞释放,并与免疫活性相关。我们的研究结果表明,4-lncRNA特征是预测T-DM1治疗结果的潜在有前景的生物标志物,因为它可以可靠地预测HER2阳性mBC患者的T-DM1治疗反应。