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首页> 外文期刊>Biotechnology Progress >Segregation of Ovarian Cancer Stage Exploiting Spectral Biomarkers Derived from Blood Plasma or Serum Analysis: ATR-FTIR Spectroscopy Coupled with Variable Selection Methods
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Segregation of Ovarian Cancer Stage Exploiting Spectral Biomarkers Derived from Blood Plasma or Serum Analysis: ATR-FTIR Spectroscopy Coupled with Variable Selection Methods

机译：血浆和血清分析衍生的卵巢癌分期利用光谱生物标志物的分离：ATR-FTIR光谱结合可变选择方法

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Ovarian cancer is a solid tumor and a leading cause of mortality. Diagnostic tools for the detection of early stage (stage I) ovarian cancer are urgently needed. For this purpose, attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) coupled with variable selection methods, successive projection algorithm or genetic algorithm (GA) combined with linear discriminant analysis (LDA), were employed to identify spectral biomarkers in blood plasma or serum samples for accurate diagnosis of different stages of ovarian cancer, histological type and segregation based on age. Three spectral datasets (stage I vs. stage II-IV; serous vs. non-serous carcinoma; and, <= 60 years vs. > 60 years) were processed: sensitivity and specificity required for real-world diagnosis of ovarian cancer was achieved. Toward segregating stage I vs. stage II-IV, sensitivity and specificity (plasma blood) of 100% was achieved using a GA-LDA model with 33 wavenumbers. For serous vs. non-serous category (plasma blood), the sensitivity and specificity levels, using 29 wavenumbers by GA-LDA, were remarkable (up to 94%). For <= 60 years and > 60 years categories (plasma blood), the sensitivity and specificity, using 42 wavenumbers by GA-LDA, gave complete accuracy (100%). For serum samples, sensitivity and specificity results gave relatively high accuracy (up to 91.6% stage I vs. stage II-IV; up to 93.0% serous vs. nonserous; and, up to 96.0% <= 60 years vs. > 60 years) using several wavenumbers. These findings justify a prospective population-based assessment of biomarkers signatures using ATR-FTIR spectroscopy as a screening tool for stage of ovarian cancer. (C) 2015 American Institute of Chemical Engineers
机译：卵巢癌是实体瘤，并且是死亡的主要原因。迫切需要用于检测早期（I期）卵巢癌的诊断工具。为此，采用衰减全反射傅立叶变换红外光谱（ATR-FTIR）结合变量选择方法，连续投影算法或遗传算法（GA）结合线性判别分析（LDA）来识别血浆中的光谱生物标志物或血清样本，可根据年龄准确诊断卵巢癌的不同阶段，组织学类型和分离。处理了三个光谱数据集（I期vs II-IV期;浆液性vs.非浆液性癌;以及<= 60年vs.> 60年）：实现了在现实世界中诊断卵巢癌所需的敏感性和特异性。对于第I阶段与第II-IV阶段，使用具有33个波数的GA-LDA模型可实现100％的敏感性和特异性（血浆血液）。对于浆液与非浆液类别（血浆血液），使用GA-LDA的29个波数，其灵敏度和特异性水平非常高（高达94％）。对于<= 60年和> 60年的类别（血浆血液），使用GA-LDA的42个波数，灵敏度和特异性得到了完全的准确性（100％）。对于血清样品，敏感性和特异性结果具有相对较高的准确度（I期相对于II-IV期最高可达91.6％;浆液比非浆液最高可达93.0％; 60岁以下≥60年最高可达96.0％ ）使用多个波数。这些发现证明了使用ATR-FTIR光谱作为卵巢癌分期的筛查工具对生物标志物进行基于人群的前瞻性评估。 （C）2015美国化学工程师学会

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