背景:原发性肾肿瘤的正确肿瘤分型对日常治疗决策至关重要。大多数肿瘤可以单独基于形态学进行分类。然而,有些诊断是困难的,和进一步的研究需要正确的肿瘤亚型。除了组织化学研究,高质量分辨率的基质辅助激光解吸/电离质谱成像(MALDI-MSI)可以检测新的诊断生物标志物,从而改善诊断。
方法:来自透明细胞肾细胞癌的福尔马林固定石蜡包埋组织标本(ccRCC,n=552),乳头状肾细胞癌(pRCC,n=122),嫌色细胞肾细胞癌(chRCC,n=108),和肾嗜酸细胞瘤(rO,n=71)通过高质量分辨率MALDI傅立叶变换离子回旋共振(FT-ICR)MSI分析。执行SPACiAL管道用于组织学和分子特征的自动共配准。进行通路富集和通路拓扑分析以确定RCC亚型之间的显著差异。
结果:我们区分了四种组织学亚型(ccRCC,pRCC,chRCC,和rO),并建立了亚型特异性途径和代谢谱。rO显示戊糖磷酸盐的富集,牛磺酸和次牛磺酸,甘油磷脂,氨基糖和核苷酸糖,果糖和甘露糖,甘氨酸,丝氨酸,和苏氨酸通路。ChRCC由富集途径定义,包括氨基糖和核苷酸糖,果糖和甘露糖,甘油磷脂,牛磺酸和次牛磺酸,甘氨酸,丝氨酸,和苏氨酸通路。嘧啶,氨基糖和核苷酸糖,甘油磷脂,和谷胱甘肽途径在ccRCC中富集。此外,我们检测到pRCC中富含磷脂酰肌醇和甘油磷脂途径。
结论:总之,我们进行了一个分类系统,肿瘤辨别的平均准确率为85.13%.此外,我们通过MALDI-MSI检测了四种最常见的原发性肾肿瘤的肿瘤特异性生物标志物.该方法是鉴别诊断和生物标志物检测的有用工具。
BACKGROUND: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic.
METHODS: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes.
RESULTS: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC.
CONCLUSIONS: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection.