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利用功能突变分析对 SHIVA01 试验队列进行重新分析,成功预测了治疗结果。

Revisited analysis of a SHIVA01 trial cohort using functional mutational analyses successfully predicted treatment outcome.

机构信息

Department of Drug Development and Innovation, Institut Curie, Paris & Saint-Cloud, France.

NovellusDx, Jerusalem, Israel.

出版信息

Mol Oncol. 2018 May;12(5):594-601. doi: 10.1002/1878-0261.12180. Epub 2018 Mar 30.

Abstract

It still remains to be demonstrated that using molecular profiling to guide therapy improves patient outcome in oncology. Classification of somatic variants is not straightforward, rendering treatment decisions based on variants with unknown significance (VUS) hard to implement. The oncogenic activity of VUS and mutations identified in 12 patients treated with molecularly targeted agents (MTAs) in the frame of SHIVA01 trial was assessed using Functional Annotation for Cancer Treatment (FACT). MTA response prediction was measured in vitro, blinded to the actual clinical trial results, and survival predictions according to FACT were correlated with the actual PFS of SHIVA01 patients. Patients with positive prediction had a median PFS of 5.8 months versus 1.7 months in patients with negative prediction (P < 0.05). Our results highlight the role of the functional interpretation of molecular profiles to predict MTA response.

摘要

利用分子谱分析来指导肿瘤治疗是否能改善患者预后仍有待证实。体细胞变异的分类并不简单,因此很难根据具有未知意义的变异(VUS)做出治疗决策。在 SHIVA01 试验中,使用癌症治疗功能注释(FACT)评估了 12 名接受分子靶向药物(MTA)治疗的患者的 VUS 和突变的致癌活性。MTA 反应预测是在体外进行的,对实际临床试验结果进行了盲法,根据 FACT 的生存预测与 SHIVA01 患者的实际 PFS 相关。阳性预测的患者中位 PFS 为 5.8 个月,而阴性预测的患者为 1.7 个月(P < 0.05)。我们的结果强调了对分子谱进行功能解释以预测 MTA 反应的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9753/5928387/24a3f8ece7c0/MOL2-12-594-g001.jpg

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