研究對象：
分析檢測平臺：GC-TOF／MS和UHPLC-QqQ-MS（BIOTREE）
期刊：Tumor Biology
影響因子：2.926
發表時間：2016
摘要：
Abstract Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. Our study was to construct a tissue-targeted metabolomics analysis method based on untargeted and targeted metabolic multi-platforms to identify a comprehensive PTC metabolic network in clinical samples. We applied untargeted gas chromatography-time of-flight mass spectrometry (GC-TOF-MS) for preliminary screening of potential biomarkers. With diagnostic models constructed using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), 45 differentially abundant metabolites with a variable importance in the projection (VIP) value greater than 1 and a P value less than 0.05 were identified, and we show that our approach was able to discriminate PTC tissues from healthy tissues. We then performed validation experiments based on targeted GCTOF-MS combined with ultra-high-performance liquid chromatography-triple-quadrupole mass spectrometry (UHPLC-q-MS) through constructing linear standard curves of analytes. Ultimately, galactinol, melibiose, and melatonin were validated as significantly altered metabolites (p <0.05). These three metabolites were defined as a combinatorial biomarker to assist needle biopsy for PTC diagnosis as demonstrated by receiver operating characteristic (ROC) curve analysis, which revealed an area under the ROC curve
(AUC) value of 0.96. Based on the metabolite enrichment analysis results, the galactose metabolism pathway was regarded as an important factor influencing PTC development by affecting energy metabolism. Alpha-galactosidase (GLA) was considered to be a potential target for PTC therapy.
一、研究背景：
甲狀腺腫瘤的發病率逐年升高，通過早期的診斷和治療可有效降低其復發率和致死率。目前甲狀腺腫瘤主要通過超聲和超聲介導的穿刺活體切片（FNAB）進行診斷，但其特異性等仍有待提高。腫瘤生物標志物可與FNAB方法結合使用，以更準確地進行惡性腫瘤診斷。乳突狀甲狀腺腫瘤（PTC）是常見的惡性甲狀腺腫瘤的亞型之一。如整合目前代謝組學研究中的非靶向（GC-TOF-MS）和靶向（UHPLC--MS）兩種研究平臺可更加高效和可靠地進行潛在生物標志物的篩選。
二、方法流程：
三、研究結果與討論：
1 不同組織代謝指紋圖譜：
1）檢測到686個內源性代謝物峰
2）腫瘤組織和正常組織代謝物出現明顯區別
3）通過OPLS-DA模型篩選得到45個標志性差異物
4）半乳糖代謝途徑在腫瘤組織中發生顯著改變
圖1非靶標實驗結果
2 通過靶標代謝組學對潛在生物標志物的驗證
1）通過UHPLC-Q-MS對前期篩到的潛在標志物通過標準曲線進行精確定量，其中11個可測定；
2）精確定量物質中，3個在前列腺腫瘤（PTC）中濃度高，8個在PTC中濃度低；
3）半乳糖代謝途徑上的代謝物經過T檢驗表現出統計學顯著性差異
4）結合靶標、非靶標實驗確定的生物標志物：肌醇半乳糖苷、蜜二糖、褪黑激素
圖2 靶標實驗獲得標志性物質獲得的ROC曲線3 PTC中代謝途徑的特征1） 乳糖代謝途徑減弱與PTC癌變過程可能有關2） PTC中褪黑激素含量降低，該物質可能具有抑制腫瘤作用3） 不飽和脂肪酸合成途徑減弱可能與PTC發病相關
圖3結合非靶標和靶標代謝組學信息獲得的PTC可能相關途徑四、亮點和展望l 非靶標代謝組學實驗之后用靶標實驗對標志性差異物進行精確定量，為建立生物標志物提供了更加堅實的基礎；
通過靶標實驗更精確地定位癌細胞中發生變化的代謝通路，為后續研究提供更可靠的線索
l 展望：針對精確定量得到的生物標志物可通過大樣本進行驗證和推進
l 展望：針對乳糖代謝途徑進行多角度研究，研究其細致的調節機制
