RNA表达的比较分析确定了肌上皮癌中的有效靶向药物。
Comparative analysis of RNA expression identifies effective targeted drug in myoepithelial carcinoma.
作者信息
Vasquez Yvonne A, Sanders Lauren, Beale Holly C, Lyle A Geoffrey, Kephart Ellen T, Learned Katrina, Peralez Jennifer, Li Amy, Huang Min, Pyke-Grimm Kimberly A, Tan Serena Y, Salama Sofie R, Haussler David, Bjork Isabel, Vaske Olena M, Spunt Sheri L
机构信息
Department of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, CA, USA.
UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA.
出版信息
NPJ Precis Oncol. 2025 May 17;9(1):145. doi: 10.1038/s41698-025-00918-5.
Myoepithelial carcinoma is an ultra-rare pediatric solid tumor with no targeted treatments. Clinical implementation of tumor RNA sequencing (RNA-Seq) for identifying therapeutic targets is underexplored in pediatric cancer. We previously published the Comparative Analysis of RNA Expression (CARE), a framework for incorporating RNA-Seq-derived gene expression into the clinic for difficult-to-treat pediatric cancers. Here, we discuss a 4-year-old male diagnosed with myoepithelial carcinoma who was treated at Stanford Medicine Children's Health. A metastatic lung nodule from the patient underwent standard-of-care tumor DNA profiling and CARE analysis, wherein the patient's tumor RNA-Seq profile was compared to over 11,000 uniformly analyzed tumor profiles from public data repositories. DNA profiling yielded no actionable mutations. CARE identified overexpression biomarkers and nominated a treatment that produced a durable clinical response. These findings underscore the utility of data sharing and concurrent analysis of large genomic datasets for clinical benefit, particularly for rare cancers with unknown biological drivers.
肌上皮癌是一种极为罕见的儿童实体瘤,目前尚无靶向治疗方法。肿瘤RNA测序(RNA-Seq)在儿科癌症中用于识别治疗靶点的临床应用尚未得到充分探索。我们之前发表了RNA表达比较分析(CARE),这是一个将RNA-Seq衍生的基因表达纳入临床治疗难治性儿科癌症的框架。在此,我们讨论一名在斯坦福大学医学中心儿童医院接受治疗的4岁男性肌上皮癌患者。对该患者的一个转移性肺结节进行了标准的肿瘤DNA分析和CARE分析,即将患者的肿瘤RNA-Seq图谱与来自公共数据存储库的11,000多个经过统一分析的肿瘤图谱进行比较。DNA分析未发现可采取行动的突变。CARE确定了过表达生物标志物并推荐了一种产生持久临床反应的治疗方法。这些发现强调了数据共享和对大型基因组数据集进行同步分析以实现临床获益的实用性,特别是对于生物学驱动因素未知的罕见癌症。