Serum proteomic profiling by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry for cancer diagnosis: Next steps
Serum proteomic profiling by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry for cancer diagnosis: Next steps
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DOI：
10.1158/0008-5472.can-05-4503
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发表时间：
2006-06-01
期刊：
影响因子：
11.2
通讯作者：
Diamandis, Eleftherios P.
中科院分区：
文献类型：
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作者：
Diamandis, Eleftherios P.
大约4年前，Petricoin等人发表了一种通过使用表面增强激光解吸电离飞行时间质谱（SELDI-TOF-MS;参考文献1）诊断卵巢癌的新方法。这种方法的原理相对简单。据推测，由肿瘤细胞或其环境释放的蛋白质或蛋白质片段可能进入全身循环。通过使用从全血清中进行蛋白质粗提取的蛋白质芯片，可以固定蛋白质组，然后通过使用SELDI（基质辅助激光解吸电离，MALDI的衍生物）结合数学算法进行检测。从那时起，该方法已被许多研究人员用于诊断其他恶性肿瘤，如乳腺癌、前列腺癌、膀胱癌、胰腺癌、头颈癌、肺癌、黑色素瘤、肝癌、鼻咽癌、神经胶质瘤等。（二）、然而，所有这些文章都报告了令人印象深刻的诊断敏感性和特异性，在许多情况下接近100%。目前可用的血清癌症生物标志物中没有一种以这种灵敏度/特异性为特征。因此，这种方法在科学家、临床医生、公众和媒体中引起了极大的兴奋，这是很自然的。在第一份报告发表后不久，这位作者和其他人发现了方法学和生物信息学的缺陷（4-12）。该技术的优点和缺点在文献中已被广泛讨论，重复是没有道理的（13-16）。时间将是最终的裁判。但现在可以解决一些问题：这项技术如何从原理证明阶段进入验证阶段，并最终进入患者阶段？先说好消息。对SELDI-TOF检测前列腺癌的可重复性进行的多中心评估表明，在不同实验室中通过相同平台获得的模式可以令人满意地重现（17）。不过，坏消息也是铺天盖地，Petricoin等人发表在《柳叶刀》上的原始数据，再也没有被复制过。尚未鉴别出鉴别峰。此外，对原始数据的重新分析发现了可能使原始结论无效的生物信息学伪影（12，18）。最近，通过SELDI-TOF对蛋白质组学分析的样品收集和处理方法进行了仔细评估，结果显示，分析前变量（如样品处理）可能会显着影响结果（10）。另一份报告强调了偏倚对血清蛋白质组学的影响
Approximately 4 years ago, Petricoin et al. published a new approach for diagnosing ovarian cancer by using surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF-MS; ref. 1). The principle of this method is relatively straightforward. It has been hypothesized that proteins or protein fragments released by tumor cells or their environment may enter the general circulation. By using a protein chip, which performs a crude extraction of proteins from whole serum, groups of proteins may be immobilized and then detected by using SELDI (a derivative of matrix-assisted laser desorption-ionization, MALDI), in association with a mathematical algorithm. Since that time, the method has been used by numerous investigators to diagnose other malignancies such as breast, prostate, bladder, pancreatic, head and neck, lung, melanoma, liver, nasopharyngeal cancers, gliomas, etc.(2). Invariably, all these articles reported impressive diagnostic sensitivities and specificities, in many cases approaching 100%. None of the currently available serum cancer biomarkers is characterized by such sensitivity/specificity. It is thus natural that this method has created tremendous excitement among scientists, clinicians, the public, and the media (3). Soon after publication of the first report, this author, and others, identified methodologic and bioinformatic shortcomings (4–12). The merits and shortcomings of this technology have been widely debated in the literature and repetition is not warranted (13–16). Time will be the ultimate judge. But some issues could be addressed now: how can this technology move from the proofof-principle stage to validation and, eventually, the patients? The good news first. A multicenter evaluation of the reproducibility of SELDI-TOF for the detection of prostate cancer indicated that patterns obtained by the same platform in different laboratories can be satisfactorily reproduced (17). However, the bad news is rather overwhelming.The original data published by Petricoin et al. in Lancet have never been reproduced. Discriminatory peaks have not been identified. Moreover, re-analysis of the raw data identified bioinformatic artifacts which could invalidate the original conclusions (12, 18). More recently, careful evaluation of methods of sample collection and processing for proteomic analysis by SELDI-TOF revealed that preanalytic variables such as sample handling could markedly influence results (10). Another report highlighted the effect of bias in influencing serum proteomic