Talantov Dimitri, Baden Jonathan, Jatkoe Tim, Hahn Kristina, Yu Jack, Rajpurohit Yashoda, Jiang Yiqiu, Choi Chang, Ross Jeffrey S, Atkins David, Wang Yixin, Mazumder Abhijit
Veridex LLC, 33 Technology Dr., Warren, NJ 07059, USA.
J Mol Diagn. 2006 Jul;8(3):320-9. doi: 10.2353/jmoldx.2006.050136.
Identifying the primary site in patients with metastatic carcinoma of unknown primary origin can enable more specific therapeutic regimens and may prolong survival. Twenty-three putative tissue-specific markers for lung, colon, pancreatic, breast, prostate, and ovarian carcinomas were nominated by querying a gene expression profile database and by performing a literature search. Ten of these marker candidates were then selected based on validation by reverse transcriptase-polymerase chain reaction (RT-PCR) on 205 formalin-fixed, paraffin-embedded metastatic carcinoma specimens originating from these six and from other cancer types. Next, we optimized the RNA isolation and quantitative RT-PCR methods for these 10 markers and applied the quantitative RT-PCR assay to a set of 260 metastatic tumors. We then built a gene-based algorithm that predicted the tissue of origin of metastatic carcinomas with an overall leave-one-out cross-validation accuracy of 78%. Lastly, our assay demonstrated an accuracy of 76% when tested on an independent set of 48 metastatic samples, 37 of which were either a known primary or initially presented as carcinoma of unknown primary but were subsequently resolved.
确定原发性不明的转移性癌患者的原发部位，可采用更具针对性的治疗方案，并可能延长生存期。通过查询基因表达谱数据库并进行文献检索，提名了23种用于肺癌、结肠癌、胰腺癌、乳腺癌、前列腺癌和卵巢癌的假定组织特异性标志物。然后，基于对来自这六种癌症类型以及其他癌症类型的205份福尔马林固定、石蜡包埋的转移癌标本进行逆转录聚合酶链反应（RT-PCR）验证，从这些标志物候选物中选择了10种。接下来，我们针对这10种标志物优化了RNA分离和定量RT-PCR方法，并将定量RT-PCR检测应用于一组260个转移瘤。然后，我们构建了一种基于基因的算法，该算法预测转移癌原发组织的总体留一法交叉验证准确率为78%。最后，当在一组独立的48个转移样本上进行测试时，我们的检测方法显示准确率为76%，其中37个样本要么是已知原发灶，要么最初表现为原发性不明的癌，但随后得到了解决。
