Clin Chem：开发出诊断前列腺癌的新型液体活检技术

  一篇刊登于国际杂志Clinical Chemistry的研究论文中，来自范德堡大学的研究人员揭示了一种新型方法，其可以检测血液中无细胞的肿瘤DNA，研究者认为这种新方法或可有效改善癌症的诊断，对预测疗法的治疗效果及检测病人对疗法的反应都非常有帮助。

  在对大量血液样本的研究数据进行回顾性分析后，研究人员表明，这种名为“液体活检”的技术可以在并不知道肿瘤遗传特性的情况下从众多细胞中区分出前列腺癌细胞，而且其敏感性是当前PSA（前列腺特异抗原检测）技术的三倍。研究者Mitchell说道，基于此前的研究数据及当前的工作进展，我认为这种液体活检的技术是癌症诊断领域的革命性突破。研究中，我们搜集了200多份前列腺癌病人及200多名对照个体的血清，随后研究人员对这些样本进行了PAS检测及格里森评分（Gleason score）。

  而这种新型的液体活检技术区分正常细胞和前列腺癌细胞的准确率高达84%，区分良性增生组织和前列腺炎的准确率高达91%。长期以来研究人员一直知道死亡细胞，包括肿瘤细胞都会使得其DNA暴露于血液中，但近来仅有一种名为“新一代的测序技术”可以通过鉴别出血液中存在的DNA片段从而准确鉴别出特殊的癌症DNA。

  前列腺癌研究中研究人员鉴别出了染色体不稳定性的20个“热点区域”，这些区域中DDNA的增加或减少都在0.5%之内，随后研究人员利用基因组学的技术鉴别出了热点区域中基因组的非编码区域，其或许在前列腺癌中可以产生未被识别的染色体控制片段。而其它19个热点区域均富含参与复制的基因以及和癌症高度相关的细胞控制过程。

  由于无细胞的DNA在循环过程中的半衰期较短，因此在疗法后对其进行测序或许可以用于检测实体瘤中的微小残留病灶，最后研究者指出，本文研究或可利用液体活检的技术来定量测定肿瘤对疗法的即刻反应。（转化医学网360zhyx.com）

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转化医学网推荐的原文摘要：

Chromosomal Instability in Cell-Free DNA Is a Serum Biomarker for Prostate Cancer
Clinical Chemistry doi: 10.1373/clinchem.2014.226571
Ekkehard Schütz1, Mohammad R. Akbari2,5, Julia Beck1, Howard Urnovitz1, William W. Zhang3, Kirsten Bornemann-Kolatzki1, William M. Mitchell4,*, Robert K. Nam3 and Steven A. Narod2,5
BACKGROUND: Genomic instability resulting in copy number variation is a hallmark of malignant transformation and may be identified through massive parallel sequencing. Tumor-specific cell free DNA (cfDNA) present in serum and plasma provides a real-time, easily accessible surrogate.

METHODS: DNA was extracted from serum of 204 patients with prostate cancer (Gleason score 2–10), 207 male controls, and patients with benign hyperplasia (n = 10) and prostatitis (n = 10). DNA was amplified by use of random primers, tagged with molecular identifiers, sequenced on a SOLID system, and aligned to the human genome. We evaluated the number of sequence reads of cfDNA in sliding 100-kbp intervals for variation from controls. We used chromosomal regions with significant variations in alignment hits for their ability to segregate patients and matched controls.

RESULTS: Using ROC curves to assess diagnostic performance, we evaluated the number of regions in a first subset (n = 177), with variations in alignment hits alone, provided an area under the curve (AUC) of 0.81 (95% CI 0.7–0.9, P < 0.001). Using 5 rounds of 10-fold cross-validation with the full data set, we established a final model that discriminated prostate cancer from controls with an AUC of 0.92 (0.87–0.95), reaching a diagnostic accuracy of 83%. Both benign prostatic hypertrophy and prostatitis could be distinguished from prostate cancer by use of cfDNA, with an accuracy of 90%.

CONCLUSIONS: Assessment of a limited number of chromosomal structural instabilities by use of massive parallel sequencing of cfDNA was sufficient to distinguish between prostate cancer and controls. This large cohort demonstrates the utility of cfDNA in prostate cancer recently established in other malignant neoplasms.