根據行政院衛生署統計資料顯示，口腔癌的死亡率在台灣男性族群中高居第四位。癌症病灶發現的早晚以及分類分期，對臨床上開發新的治療對策有很大的幫助。物質因分子化學鍵結之振盪而具有特異性之紅外光源吸收。經由同步輻射光源結合傅立葉轉換紅外顯微鏡提供亮度與品質更高的紅外光源使細胞成分中化學性質之分析無論在空間與光譜解析度上均遠超過傳統方法。本研究以此設備檢測口腔上皮細胞從正常轉型至已轉移的口腔癌細胞過程中之紅外光譜生物標記，藉以判斷在癌化過程中之生物性階段以與光譜訊號之關聯性，並探索未來臨床之應用。
為了建立癌化細胞紅外光譜特徵資料，我們選擇一系列於癌化過程不同階段之細胞，包含正常口腔上皮角質細胞 (hNOK)、亂生癌前細胞 (DOK)、未轉移癌化細胞 (SCC-15, OEC-M1, OC-2) 及轉移癌化細胞 (HSC-3)。經光譜分析結果顯示正常口腔上皮角質及癌細胞之細胞核具有脂質(3000－2800 cm-1) 及氨基 (1760－1480 cm-1) 區域的顯著的光譜訊號差異。在分類方面，使用線性判別區分法 (Linear Discriminant Analysis) 分析正常及癌細胞之紅外吸收光譜的關聯性，同樣可發現不同分布區域多具有口腔癌化過程的趨勢性分布差異呈現。在3600－3000 cm-1的光譜區域，亂生癌前細胞具有光譜轉移 (shift) 的現象，此特異性訊號可做為癌前的生物標記。除此之外，在脂質吸收區域 (3000－2800 cm-1)，具有明顯的正常口腔上皮角質細胞和其他癌化細胞的區分。在此區域包含了功能性的碳氫基吸收訊號，通常來自於細胞的脂質、蛋白質及其他成分。由於此區域的訊號貢獻主要來自於脂質，所以我們利用萃取脂質的方式，去掉細胞的脂質成分來偵測此區域性的差異訊號。去除脂質後我們發現吸收訊號的顯著降低，並觀察到相似於未處理前之癌化細胞光譜吸收訊號。此觀察支持在此區域的差異性光譜吸收訊號多貢獻自脂質。我們藉由脂質訊號的差異，可明顯區分出正常口腔表皮細胞及亂生癌前細胞和不正常細胞。
經由上述的差異性，我們分別使用相似於細胞脂質結構，不同極性的兩種有機蠟，對細胞進行物理吸附，藉由觀察有機蠟殘留在細胞上的情形，比對細胞癌化的相關聯性。從紅外影像及線性判別區分法的結果顯示，蜜蠟具有癌化細胞的專一性吸收，而對正常口腔角質細胞則不具有吸收效果。藉由此專一性的選擇吸收效果，有機蠟的檢測未來可應用於臨床檢體上，做為快速的癌化篩檢方式。
以上結果顯示同步輻射紅外光譜儀具有發展非侵入性快速癌症篩選工具之潛力。並藉由結合有機蠟吸附動力學的檢測，做為有力的癌症篩選技術。

Oral cancer is the fourth leading cause of cancer death in Taiwanese male population. Early detection and staging of oral cancer and precancer lesions provide valuable information for the development of more effective preventive and therapeutic strategies of this malignant disease. Infrared absorption spectroscopy has been developed to identify the optical signature of specific chemical bonds. Fourier transform Infrared microspectroscopy using synchrotron radiation as the light source provides unsurpassed spatial and spectral resolution for the profiling of biochemical events occurred during disease progression. The present study aimed to analyze biochemical spectral changes accompanying carcinogenesis progression in cultured cells by employing SR-FTIR and FTIR to explore their potential clinical applications. We used primary cultured normal oral keratinocyte (hNOK), oral dysplasia precancer line (DOK), primary oral cancer line (SCC-15, OEC-M1, OC-2) and metastatic oral cancer line (HSC-3) as progression of oral cancer models. For each type of oral cells, there were recorded for their nuclear and cytoplasmic FT-IR spectrum in the spectral range between 3600 and 900 cm-1. Following the analogy, we discovered the average profile of absorbance at nucleus and cytoplasm during oral carcinogenesis progression states showed distinct spectra. Moreover, Linear Discriminant Analysis (LDA) for classification and dimensionality reduction was applied to cluster and rank the unique spectral features that discriminate normal cells from pre-cancer and cancer cells. The results indicate segregated tolerance region for hNOK from other cancer cells in lipid region (3000－2800 cm-1) and amide region (1760－1480 cm-1). In the bands of amide region (3600－3000 cm-1), it was a blue shift in dysplasia cell respectively, suggest there were potential value as precancer markers for diagnosis. In addition, there were distinct alterations in specific absorbed spectra of hNOK compared with precancer and other cancer cells in the spectral region 3000－2800 cm-1. The spectral region was assigned to anti-symmetric and symmetric vibration of CH functional group contributed mainly from lipid and protein of cells. We removed the major composition of lipid in cells to detected spectral signal. The overall absorbance had conversed from strong to weak after this process. We proposed that the level of lipid could be utilized to differentiate normal cells from cancer cells. Therefore, we employed organic waxes being different polarity, which are structurally similar to lipid structure of cell membrane to perform the physisorption for diagnosing oral cavity cancer. The infrared kinetic result of normal keratinocyte cells and cancer cells showed a strong capability of physisorption for paraffin and beeswax, respectively.
These results support the potential for using SR-FTIR and FTIR as a label-free method for early screening of oral cancer and precancerous lesions to further discover the underlying contributing molecular events.

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