Calligaris David, Feldman Daniel R, Norton Isaiah, Brastianos Priscilla K, Dunn Ian F, Santagata Sandro, Agar Nathalie Y R
Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115.
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115.
Int J Mass Spectrom. 2015 Feb 1;377:690-698. doi: 10.1016/j.ijms.2014.06.024.
Meningiomas are the most frequent intracranial tumors. The majority is benign slow-growing tumors but they can be difficult to treat depending on their location and size. While meningiomas are well delineated on magnetic resonance imaging by their uptake of contrast, surgical limitations still present themselves from not knowing the extent of invasion of the dura matter by meningioma cells. The development of tools to characterize tumor tissue in real or near real time could prevent recurrence after tumor resection by allowing for more precise surgery, i.e. removal of tumor with preservation of healthy tissue. The development of ambient ionization mass spectrometry for molecular characterization of tissue and its implementation in the surgical decision-making workflow carry the potential to fulfill this need. Here, we present the characterization of meningioma and dura mater by desorption electrospray ionization mass spectrometry to validate the technique for the molecular assessment of surgical margins and diagnosis of meningioma from surgical tissue in real-time. Nine stereotactically resected surgical samples and three autopsy samples were analyzed by standard histopathology and mass spectrometry imaging. All samples indicated a strong correlation between results from both techniques. We then highlight the value of desorption electrospray ionization mass spectrometry for the molecular subtyping/subgrouping of meningiomas from a series of forty genetically characterized specimens. The minimal sample preparation required for desorption electrospray ionization mass spectrometry offers a distinct advantage for applications relying on real-time information such as surgical decision-making. The technology here was tested to distinguish meningioma from dura mater as an approach to precisely define surgical margins. In addition we classify meningiomas into fibroblastic and meningothelial subtypes and more notably recognize meningiomas with genetic aberrations.
脑膜瘤是最常见的颅内肿瘤。大多数是良性生长缓慢的肿瘤,但根据其位置和大小,治疗可能会很困难。虽然脑膜瘤在磁共振成像中通过其对比剂摄取情况能够清晰显示,但由于不清楚脑膜瘤细胞对硬脑膜的侵袭范围,手术仍存在局限性。开发能够实时或近实时表征肿瘤组织的工具,可以通过实现更精确的手术(即切除肿瘤并保留健康组织)来预防肿瘤切除后的复发。常压电离质谱技术用于组织的分子表征及其在手术决策流程中的应用,有潜力满足这一需求。在此,我们通过解吸电喷雾电离质谱对脑膜瘤和硬脑膜进行表征,以验证该技术用于实时评估手术切缘和诊断手术组织中的脑膜瘤的有效性。对9个立体定向切除的手术样本和3个尸检样本进行了标准组织病理学和质谱成像分析。所有样本均表明两种技术的结果具有很强的相关性。然后,我们强调了解吸电喷雾电离质谱对于从一系列40个基因特征明确的标本中对脑膜瘤进行分子亚型/亚组分类的价值。解吸电喷雾电离质谱所需的样本制备最少,这对于依赖实时信息的应用(如手术决策)具有明显优势。这里测试的技术用于区分脑膜瘤和硬脑膜,作为精确界定手术切缘的一种方法。此外,我们将脑膜瘤分为成纤维细胞型和脑膜内皮型亚型,更值得注意的是识别出具有基因异常的脑膜瘤。