首页> 外文期刊>The journal of histochemistry and cytochemistry >Imaging Mass Spectrometry Is an Accurate Tool in Differentiating Clear Cell Renal Cell Carcinoma and Chromophobe Renal Cell Carcinoma: A Proof-of-concept Study
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Imaging Mass Spectrometry Is an Accurate Tool in Differentiating Clear Cell Renal Cell Carcinoma and Chromophobe Renal Cell Carcinoma: A Proof-of-concept Study

机译:成像质谱是分化透明细胞肾细胞癌和致染色体肾细胞癌的准确工具:概念验证研究

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Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) are relatively common tumors that can have significant risk for mortality. Treatment and prognostication in renal cell carcinoma (RCC) are dependent upon correct histologic typing. ccRCC and chRCC are generally straightforward to diagnose based on histomorphology alone. However, high-grade ccRCC and chRCC can sometimes resemble each other morphologically, particularly in small biopsies. Multiple immunostains and/or colloidal iron stain are sometimes required to differentiate the two. Imaging mass spectrometry (IMS) allows simultaneous spatial mapping of thousands of biomarkers, using formalin-fixed paraffin-embedded tissue sections. In this study, we evaluate the ability of IMS to differentiate between World Health Organization/International Society for Urological Pathology grade 3 ccRCC and chRCC. IMS spectra from a training set of 14 ccRCC and 13 chRCC were evaluated via support vector machine algorithm with a linear kernel for machine learning, building a classification model. The classification model was applied to a separate validation set of 6 ccRCC and 6 chRCC, with 19 to 20, 150-μm diameter tumor foci in each case sampled by IMS. Most evaluated tumor foci were classified correctly as ccRCC versus chRCC (99% accuracy, kappa=0.98), demonstrating that IMS is an accurate tool in differentiating high-grade ccRCC and chRCC.
机译:透明细胞肾细胞癌(CCRCC)和致染色细胞肾细胞癌(CHRCC)是相对常见的肿瘤,可具有显着的死亡风险。肾细胞癌(RCC)中的治疗和预测依赖于正确的组织学类型。 CCRCC和CHRCC通常仅基于单独的组织术诊断。然而,高级CCRCC和CHRCC有时可以形态地相互作用,特别是在小活组织检查中。有时需要多种免疫抑制和/或胶体铁染色来区分两者。成像质谱(IMS)允许使用福尔马林固定的石蜡包埋的组织切片同时存在成千上万的生物标志物。在这项研究中,我们评估了IMS区分世界卫生组织/国际泌尿理性学会3级CCRCC和CHRCC的能力。来自14个CCRCC和13个CHRCC训练组的IMS光谱通过支持向量机算法进行了用于机器学习的线性核,构建分类模型。分类模型应用于6个CCRCC和6CHCC的单独验证组,在每种情况下,19至20,150μm直径的肿瘤灶,在每种情况下被IMS采样。大多数评估的肿瘤焦点被正确分类为CCRCC与CHRCC(99%的精度,Kappa = 0.98),表明IMS是差异化高档CCRCC和CHRCC的准确工具。

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