Liu Xuan, Ge Zhongqi, Yang Fei, Contreras Alejandro, Lee Sanghoon, White Jason B, Lu Yiling, Labrie Marilyne, Arun Banu K, Moulder Stacy L, Mills Gordon B, Piwnica-Worms Helen, Litton Jennifer K, Chang Jeffrey T
Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX, USA.
Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
NPJ Breast Cancer. 2022 May 10;8(1):64. doi: 10.1038/s41523-022-00427-9.
Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.
约2%-7%的乳腺癌患者存在BRCA1或BRCA2种系突变,这使得PARP抑制剂在晚期乳腺癌治疗中获得批准。我们之前报道了一项针对种系BRCA致病性变异患者的单药他拉唑帕利新辅助II期试验,病理完全缓解(pCR)率为53%。由于近一半接受治疗的患者未达到pCR,因此需要更好的策略来克服治疗耐药性。为此,我们对13例接受单药新辅助他拉唑帕利治疗的初治乳腺癌肿瘤进行了多组学分析。我们寻找了治疗6个月后预测反应(通过残余癌负荷评估)的生物标志物。我们发现,所有耐药肿瘤均表现为SHLD2缺失、缺氧特征表达或干细胞特征表达。这些结果表明,对治疗前肿瘤的深入分析可以识别预测他拉唑帕利及其他PARP抑制剂反应的生物标志物,并提供一个框架,有助于更好地选择治疗患者,以及为开发预防耐药性出现的新型联合疗法提供路线图。