Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy. However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In our study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal tumor pairs was analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross-validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94 and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.

中文翻译：

---

使用质谱成像鉴定透明细胞肾细胞癌的诊断代谢特征。


透明细胞肾细胞癌（ccRCC）是肾癌最常见和致命的亚型。术中冰冻切片 (IFS) 分析用于在肾部分切除术期间确认诊断。然而，使用 IFS 分析进行手术切缘评估既耗时又不可靠，导致利用率相对较低。在我们的研究中，我们展示了使用解吸电喷雾电离质谱成像 (DESI-MSI) 作为 ccRCC 的分子诊断和预后工具。对 23 个新鲜冷冻的 ccRCC 正常肿瘤配对肾切除标本进行 DESI-MSI。对 17 个正常肿瘤对的独立验证队列进行了分析。 DESI-MSI 提供组织的二维分子图像，以及代表小代谢物、脂肪酸和脂质的质谱。对这些组织进行组织病理学评估。通过执行最小绝对收缩和选择算子 (Lasso) 和对数比 Lasso 分析，鉴定了一组区分 ccRCC 和正常肾脏的代谢物。采用留一患者交叉验证的套索分析从使用 ccRCC 和正常组织的 DESI-MSI 获得的 37,608 个像素的 27,000 多个代谢特征中选择了 57 个峰值。代谢物的基线 Lasso 预测每个组织的类别为正常组织或癌组织，准确度分别为 94% 和 76%。将基线 Lasso 与葡萄糖与花生四烯酸的比率相结合可能会减少扫描时间并提高识别正常 (82%) 和 ccRCC (88%) 组织的准确性。 DESI-MSI 可以高精度地快速检测与正常和 ccRCC 相关的代谢物。随着这项技术的进步，它可用于术中快速评估手术切缘状态。