转化医学:天文观星技术帮助诊断侵略性肿瘤
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旨在帮助找到遥远星系的技术已经被用在寻找模糊生物印记上。英国癌症研究中心剑桥研究所的科学家们利用自动化系统检测癌症肿瘤。该系统最初用于寻找夜空中的遥远物体,而现在被用于测量两千多个乳腺肿瘤样本中特定三种蛋白质的含量。
传统而言,医生们通过给细胞上色寻找特定蛋白质的方法来鉴定恶性肿瘤,这个过程毫无疑问会使用显微镜。现在,新技术将致使由来已久的通过显... |
旨在帮助找到遥远星系的技术已经被用在寻找模糊生物印记上。英国癌症研究中心剑桥研究所的科学家们利用自动化系统检测癌症肿瘤。该系统最初用于寻找夜空中的遥远物体,而现在被用于测量两千多个乳腺肿瘤样本中特定三种蛋白质的含量。
传统而言,医生们通过给细胞上色寻找特定蛋白质的方法来鉴定恶性肿瘤,这个过程毫无疑问会使用显微镜。现在,新技术将致使由来已久的通过显微镜寻找致命癌症迹象的方法被计算机代替。
新方法利用了一个最初被用于在夜空中寻找遥远物体的自动化系统。在实验中,该技术被用于测量两千多个乳腺肿瘤样本中特定三种蛋白质的含量。研究人员对人工评估结果的准确性和电脑评估结果的准确性进行了对比。他们发现自动系统最差都和人工评估一般准确,但多数情况下速度更快。
科学家利用了天文学家分析太空图片技术和显微镜观察恶性肿瘤微妙差异两者的相似性。新的自动化方法有着可与耗时的人工分析图片比拟的准确性。
现代技术让研究人员能够进一步观察对“预测不同癌症治疗方法成功还是失败”有着重要作用的关键基因和蛋白质。但在这个方法被应用到临床诊断前,其有效性还需要通过上百或者上千个肿瘤样本来证实。
原文链接:
Astronomical algorithms for automated analysis of tissue protein expression in breast cancer
British Journal of Cancer, 19 February 2013 | doi:10.1038/bjc.2012.558
Background: High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress.
Methods: We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists.
Results: All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to 'positive' or 'negative' categories with agreement rates of up to 96%.
Conclusion: The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology.
来源:生物360
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