Centre for Healthcare Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, P.O. Botanic Garden, Howrah 711103, WB, India.
Department of Physics, Bose Institute, Kolkata, 93/1, Acharya Prafulla Chandra Road, Kolkata-700009, WB, India.
Analyst. 2019 Feb 21;144(4):1309-1325. doi: 10.1039/c8an02092b. Epub 2018 Dec 18.
FTIR spectroscopy and Raman spectroscopy of biological analytes are increasingly explored as screening tools for early detection of cancer. In the present study, an integrated analysis of the FTIR and Raman spectra obtained from exfoliated cells is adopted to improve discrimination of normal, pre-cancerous and cancerous conditions. Multiple spectra were obtained from 13 normal, 13 pre-cancer and 10 cancer patients in both modes. Compared to normal patients, significant differences were observed at 1550, 1580, 1640, 2370, 2330, 2950-3000 and 3650-3750 cm (FTIR) and 520, 640, 785, 827, 850, 935, 1003, 1175, 1311 cm and 1606 cm (Raman) vibrations of the other two. The increase in DNA, protein and lipid content with malignancy was more clearly elucidated by examining both spectra. Principal component analysis (PCA)-linear discriminant analysis (LDA) with 10-fold cross validation of the FTIR and Raman spectral data sets showed efficient discrimination between normal and pathological conditions while overlapping was seen between the two pathologies. The PCA-LDA model of the dual spectra yielded a classification accuracy of 98% in comparison with either FTIR (85%) or Raman (82%) in a spectrum-wise comparison. In the patient-wise approach (mean of all spectra from a patient), the overall classification efficiency was 73%, 80% and 87% for FTIR, Raman and integrated spectral approaches respectively. Moreover, the efficiency of the integrated FTIR-Raman PCA-LDA model as a prediction tool was tested to screen susceptible individuals (11 cigarette smokers) using the dual spectra acquired from these individuals. The study presents proof-of-concept for adopting a large-scale, follow-up trial of the approach for mass screening purposes.
傅里叶变换红外光谱（FTIR）和拉曼光谱分析技术作为癌症早期检测的筛查工具，其在生物分析物中的应用正日益得到探索。在本研究中，我们采用整合分析从细胞剥落物中获得的 FTIR 和拉曼光谱，以提高对正常、癌前和癌症状态的区分能力。在这两种模式下，从 13 名正常、13 名癌前和 10 名癌症患者中获得了多个光谱。与正常患者相比，在 1550、1580、1640、2370、2330、2950-3000 和 3650-3750 cm（FTIR）以及 520、640、785、827、850、935、1003、1175、1311 cm 和 1606 cm（拉曼）振动处，观察到显著差异。通过检查这两种光谱，更清楚地阐明了随着恶性程度的增加，DNA、蛋白质和脂质含量的增加。FTIR 和拉曼光谱数据集的主成分分析（PCA）-线性判别分析（LDA）与 10 倍交叉验证显示，正常和病理条件之间的区分效率很高，而两种病理条件之间存在重叠。与 FTIR（85%）或拉曼（82%）的光谱分析相比，双光谱的 PCA-LDA 模型的分类准确率为 98%。在患者层面（从每位患者的所有光谱平均值），FTIR、拉曼和综合光谱方法的整体分类效率分别为 73%、80%和 87%。此外，还测试了整合 FTIR-Raman PCA-LDA 模型作为预测工具的效率，以使用从这些个体获得的双光谱筛选易感性个体（11 名吸烟者）。该研究为采用大规模、后续试验来进行大规模筛查提供了概念验证。
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