Background/Objectives: Salivary gland tumors (SGTs) are a rare and histologically heterogeneous group of neoplasms that are challenging to diagnose due to phenotypic heterogeneity and overlapping histomorphological markers. Accurate diagnosis is required for clinical management, particularly in unusual subtypes. The objective of this study was to ascertain whether attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, in combination with enzymatic deglycosylation, would be useful in SGT classification by detecting glycosylation-related metabolic variations. Methods: 155 tissue sections, consisting of 80 SGTs and 75 controls, were analyzed. ATR-FTIR spectroscopy was used to record the mid-infrared (MIR) spectra (4000–400 cm−1) of enzymatically untreated and deglycosylated samples. Spectral data were preprocessed and analyzed by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Enzymatic deglycosylation focused on sialic acid and fucose residues with α2-3,6,8 neuraminidase, α1-2,4,6 fucosidase O, and α1-3,4 fucosidase. Results: Tumor and control samples were discriminated with an OPLS-DA model, achieving an accuracy of 81.9% (78.7% for controls and 85.0% for tumors), especially in the glycosylation-relevant spectral range (850–1250 cm−1). Classification between benign and malignant tumors was more challenging, with an accuracy of 70.0% (72.5% for benign and 67.5% for malignant cases). Enzymatic deglycosylation resulted in detectable changes in the MIR spectra, confirming the contribution of glycosylation to tumor-specific signatures. Benign vs. malignant tumor discrimination was still poor and was not much enhanced in the sense of incorporating glycosylation-specific regions. Conclusions: ATR-FTIR spectroscopy coupled with enzymatic deglycosylation can distinguish tumor and control tissues based on glycan-associated spectral differences. Application of the technique to benign/malignant SGT discrimination is hampered by spectral overlap and tumor heterogeneity. Further research will be necessary to explore other clustering algorithms and larger and more homogeneous datasets for improved diagnostic accuracy.
背景/目的：唾液腺肿瘤是一类罕见且组织学异质性的肿瘤，由于其表型异质性和组织形态学标志物重叠，诊断具有挑战性。临床管理需要准确诊断，尤其对于非典型亚型。本研究旨在探讨衰减全反射-傅里叶变换红外光谱结合酶解脱糖基化技术，是否可通过检测糖基化相关代谢差异来辅助唾液腺肿瘤分类。方法：分析155份组织切片（80例唾液腺肿瘤和75例对照样本）。使用ATR-FTIR光谱记录未经酶处理与脱糖基化样本的中红外光谱（4000–400 cm−1）。通过主成分分析和正交偏最小二乘判别分析对预处理后的光谱数据进行分析。酶解脱糖基化主要针对唾液酸和岩藻糖残基，使用α2-3,6,8神经氨酸酶、α1-2,4,6岩藻糖苷酶O和α1-3,4岩藻糖苷酶。结果：通过OPLS-DA模型可区分肿瘤与对照样本，准确率达81.9%（对照样本78.7%，肿瘤样本85.0%），尤其在糖基化相关光谱区间（850–1250 cm−1）区分效果显著。良恶性肿瘤的分类更具挑战性，准确率为70.0%（良性72.5%，恶性67.5%）。酶解脱糖基化引起中红外光谱的显著变化，证实了糖基化对肿瘤特征信号的贡献。但良恶性肿瘤的区分效果仍不理想，结合糖基化特征区域后改善有限。结论：ATR-FTIR光谱结合酶解脱糖基化技术可通过糖链相关光谱差异区分肿瘤与正常组织。但由于光谱重叠和肿瘤异质性，该技术在良恶性唾液腺肿瘤鉴别中的应用仍受限。未来需进一步研究其他聚类算法，并采用更庞大、更同质化的数据集以提高诊断准确性。
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