Testing of rapid evaporative mass spectrometry for histological tissue classification and molecular diagnostics in a multi-site study

IF 6.4 1区 医学 Q1 ONCOLOGY British Journal of Cancer Pub Date : 2024-09-18 DOI:10.1038/s41416-024-02739-y
Martin Kaufmann, Pierre-Maxence Vaysse, Adele Savage, Loes F. S. Kooreman, Natasja Janssen, Sonal Varma, Kevin Yi Mi Ren, Shaila Merchant, Cecil Jay Engel, Steven W. M. Olde Damink, Marjolein L. Smidt, Sami Shousha, Hemali Chauhan, Evdoxia Karali, Emine Kazanc, George Poulogiannis, Gabor Fichtinger, Boglárka Tauber, Daniel R. Leff, Steven D. Pringle, John F. Rudan, Ron M. A. Heeren, Tiffany Porta Siegel, Zoltán Takáts, Júlia Balog
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Abstract

While REIMS technology has successfully been demonstrated for the histological identification of ex-vivo breast tumor tissues, questions regarding the robustness of the approach and the possibility of tumor molecular diagnostics still remain unanswered. In the current study, we set out to determine whether it is possible to acquire cross-comparable REIMS datasets at multiple sites for the identification of breast tumors and subtypes. A consortium of four sites with three of them having access to fresh surgical tissue samples performed tissue analysis using identical REIMS setups and protocols. Overall, 21 breast cancer specimens containing pathology-validated tumor and adipose tissues were analyzed and results were compared using uni- and multivariate statistics on normal, WT and PIK3CA mutant ductal carcinomas. Statistical analysis of data from standards showed significant differences between sites and individual users. However, the multivariate classification models created from breast cancer data elicited 97.1% and 98.6% correct classification for leave-one-site-out and leave-one-patient-out cross validation. Molecular subtypes represented by PIK3CA mutation gave consistent results across sites. The results clearly demonstrate the feasibility of creating and using global classification models for a REIMS-based margin assessment tool, supporting the clinical translatability of the approach.

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在一项多站点研究中测试用于组织学组织分类和分子诊断的快速蒸发质谱法
背景虽然REIMS技术已成功用于体外乳腺肿瘤组织的组织学鉴定,但有关该方法的稳健性和肿瘤分子诊断可能性的问题仍未得到解答。在当前的研究中,我们试图确定是否有可能在多个研究机构获得具有交叉可比性的 REIMS 数据集,用于鉴定乳腺肿瘤和亚型。方法由四个研究机构组成的联合研究小组使用相同的 REIMS 设置和方案对组织进行了分析,其中三个研究机构可以获得新鲜的手术组织样本。结果对标准数据的统计分析显示,不同研究机构和个体用户之间存在显著差异。然而,根据乳腺癌数据创建的多变量分类模型在 "不包括一个站点 "和 "不包括一个患者 "交叉验证中的正确率分别为 97.1%和 98.6%。以 PIK3CA 基因突变为代表的分子亚型在不同研究机构的结果是一致的。结论这些结果清楚地证明了为基于 REIMS 的边缘评估工具创建和使用全局分类模型的可行性,支持了该方法的临床转化能力。
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来源期刊
British Journal of Cancer
British Journal of Cancer 医学-肿瘤学
CiteScore
15.10
自引率
1.10%
发文量
383
审稿时长
6 months
期刊介绍: The British Journal of Cancer is one of the most-cited general cancer journals, publishing significant advances in translational and clinical cancer research.It also publishes high-quality reviews and thought-provoking comment on all aspects of cancer prevention,diagnosis and treatment.
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