Lazaro-Pacheco Daniela, Shaaban Abeer M, Titiloye Nicholas Akinwale, Rehman Shazza, Rehman Ihtesham Ur
Department of Engineering, University of Exeter, Exeter, UK.
Department of Cellular Pathology, Queen Elizabeth Hospital Birmingham, and University of Birmingham, Birmingham, UK.
EXCLI J. 2021 Jul 2;20:1118-1132. doi: 10.17179/excli2021-3962. eCollection 2021.
The current gold standard for breast cancer (BC) diagnosis is the histopathological assessment of biopsy samples. However, this approach limits the understanding of the disease in terms of biochemical changes. Raman spectroscopy has demonstrated its potential to provide diagnostic information and facilitate the prediction of the biochemical progression for different diseases in a rapid non-destructive manner. Raman micro-spectroscopy was used to characterize and differentiate breast cancer and normal breast samples. In this study, tissue microarrays of breast cancer biopsy samples (n=499) and normal breast (n=79) were analyzed using Raman micro-spectroscopy, and principal component analysis (PCA) was used for feature extraction. Linear discriminant analysis (LDA) was used for feature validation. Normal breast and breast cancer were successfully differentiated with a sensitivity of 90 % and specificity of 78 %. Dominance of lipids, specifically fatty acids, was identified in the normal tissue whereas proteins dominated the malignant spectra. Higher intensities of carotenoids, β-carotenoids, and cholesterol were identified in the normal breast while ceramide related peaks were mostly visible in the BC spectra. The biochemical characterization achieved with Raman micro-spectroscopy showed that this technique is a powerful and reliable tool for the monitoring and diagnosis of BC, regardless of the cohort heterogeneity. Raman spectroscopy also provided a powerful insight into the biochemical changes associated with the BC progression and evolution.
目前乳腺癌（BC）诊断的金标准是对活检样本进行组织病理学评估。然而，这种方法在生化变化方面限制了对该疾病的理解。拉曼光谱已显示出其以快速无损方式提供诊断信息并促进预测不同疾病生化进展的潜力。拉曼显微光谱用于表征和区分乳腺癌和正常乳腺样本。在本研究中，使用拉曼显微光谱分析了乳腺癌活检样本（n = 499）和正常乳腺（n = 79）的组织微阵列，并使用主成分分析（PCA）进行特征提取。线性判别分析（LDA）用于特征验证。正常乳腺和乳腺癌成功区分，灵敏度为90%，特异性为78%。在正常组织中鉴定出脂质占主导，特别是脂肪酸，而蛋白质在恶性光谱中占主导。在正常乳腺中鉴定出类胡萝卜素、β-胡萝卜素和胆固醇的强度较高，而神经酰胺相关峰在乳腺癌光谱中大多可见。拉曼显微光谱实现的生化表征表明，该技术是监测和诊断乳腺癌的强大而可靠的工具，无论队列的异质性如何。拉曼光谱还为与乳腺癌进展和演变相关的生化变化提供了有力的见解。
