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Non-invasive diagnostic test for lung cancer using biospectroscopy and variable selection techniques in saliva samples
Analyst ( IF 3.6 ) Pub Date : 2024-08-01 , DOI: 10.1039/d4an00726c Camilo L M Morais 1, 2 , Kássio M G Lima 1 , Andrew W Dickinson 3 , Tarek Saba 3 , Thomas Bongers 3 , Maneesh N Singh 4, 5 , Francis L Martin 3, 4 , Danielle Bury 3
Analyst ( IF 3.6 ) Pub Date : 2024-08-01 , DOI: 10.1039/d4an00726c Camilo L M Morais 1, 2 , Kássio M G Lima 1 , Andrew W Dickinson 3 , Tarek Saba 3 , Thomas Bongers 3 , Maneesh N Singh 4, 5 , Francis L Martin 3, 4 , Danielle Bury 3
Affiliation
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Lung cancer is one of the most commonly occurring malignant tumours worldwide. Although some reference methods such as X-ray, computed tomography or bronchoscope are widely used for clinical diagnosis of lung cancer, there is still a need to develop new methods for early detection of lung cancer. Especially needed are approaches that might be non-invasive and fast with high analytical precision and statistically reliable. Herein, we developed a swab “dip” test in saliva whereby swabs were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy harnessed to principal component analysis–quadratic discriminant analysis (QDA) and variable selection techniques employing successive projections algorithm (SPA) and genetic algorithm (GA) for feature selection/extraction combined with QDA. A total of 1944 saliva samples (56 designated as lung-cancer positive and 1888 designed as controls) were obtained in a lung cancer-screening programme being undertaken in North-West England. GA-QDA models achieved, for the test set, sensitivity and specificity values of 100.0% and 99.1%, respectively. Three wavenumbers (1422 cm−1, 1546 cm−1 and 1578 cm−1) were identified using the GA-QDA model to distinguish between lung cancer and controls, including ring C–C stretching, C![[double bond, length as m-dash]](https://www.rsc.org/images/entities/char_e001.gif)
N adenine, Amide II [δ(NH), ν(CN)] and νs(COO−) (polysaccharides, pectin). These findings highlight the potential of using biospectroscopy associated with multivariate classification algorithms to discriminate between benign saliva samples and those with underlying lung cancer.
中文翻译：
使用唾液样本中的生物光谱学和变量选择技术对肺癌进行无创诊断测试
肺癌是全世界最常见的恶性肿瘤之一。尽管X射线、计算机断层扫描或支气管镜等一些参考方法广泛用于肺癌的临床诊断，但仍需要开发新的肺癌早期检测方法。特别需要的是非侵入性、快速、分析精度高且统计可靠的方法。在此，我们开发了唾液中的拭子“浸入”测试，其中使用衰减全反射傅里叶变换红外（ATR-FTIR）光谱分析拭子，该光谱利用主成分分析-二次判别分析（QDA）和采用连续投影算法的变量选择技术(SPA) 和遗传算法 (GA) 与 QDA 相结合进行特征选择/提取。在英格兰西北部进行的一项肺癌筛查项目中，总共获得了 1944 份唾液样本（56 份被指定为肺癌阳性样本，1888 份被设计为对照）。 GA-QDA 模型在测试集上的灵敏度和特异性值分别为 100.0% 和 99.1%。使用GA-QDA模型识别了三个波数（1422 cm -1 、1546 cm -1和1578 cm -1 ）来区分肺癌和对照，包括环C-C拉伸、C N 腺嘌呤、酰胺 II [ δ (NH)、 ν (CN)] 和ν s (COO - )（多糖、果胶）。 这些发现凸显了使用生物光谱学与多变量分类算法相关的潜力来区分良性唾液样本和患有潜在肺癌的唾液样本。
更新日期：2024-08-06
N adenine, Amide II [δ(NH), ν(CN)] and νs(COO−) (polysaccharides, pectin). These findings highlight the potential of using biospectroscopy associated with multivariate classification algorithms to discriminate between benign saliva samples and those with underlying lung cancer.
中文翻译：
使用唾液样本中的生物光谱学和变量选择技术对肺癌进行无创诊断测试
肺癌是全世界最常见的恶性肿瘤之一。尽管X射线、计算机断层扫描或支气管镜等一些参考方法广泛用于肺癌的临床诊断，但仍需要开发新的肺癌早期检测方法。特别需要的是非侵入性、快速、分析精度高且统计可靠的方法。在此，我们开发了唾液中的拭子“浸入”测试，其中使用衰减全反射傅里叶变换红外（ATR-FTIR）光谱分析拭子，该光谱利用主成分分析-二次判别分析（QDA）和采用连续投影算法的变量选择技术(SPA) 和遗传算法 (GA) 与 QDA 相结合进行特征选择/提取。在英格兰西北部进行的一项肺癌筛查项目中，总共获得了 1944 份唾液样本（56 份被指定为肺癌阳性样本，1888 份被设计为对照）。 GA-QDA 模型在测试集上的灵敏度和特异性值分别为 100.0% 和 99.1%。使用GA-QDA模型识别了三个波数（1422 cm -1 、1546 cm -1和1578 cm -1 ）来区分肺癌和对照，包括环C-C拉伸、C
N 腺嘌呤、酰胺 II [ δ (NH)、 ν (CN)] 和ν s (COO - )（多糖、果胶）。 这些发现凸显了使用生物光谱学与多变量分类算法相关的潜力来区分良性唾液样本和患有潜在肺癌的唾液样本。
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