Prensner John R, Zhao Shuang, Erho Nicholas, Schipper Matthew, Iyer Matthew K, Dhanasekaran Saravana M, Magi-Galluzzi Cristina, Mehra Rohit, Sahu Anirban, Siddiqui Javed, Davicioni Elai, Den Robert B, Dicker Adam P, Karnes R Jeffrey, Wei John T, Klein Eric A, Jenkins Robert B, Chinnaiyan Arul M, Feng Felix Y
Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI, USA.
Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI, USA.
Lancet Oncol. 2014 Dec;15(13):1469-1480. doi: 10.1016/S1470-2045(14)71113-1. Epub 2014 Nov 17.
Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy.
Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene.
1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2·45, 95% CI 1·70-3·53; p<0·0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2·14, 95% CI 1·77-2·58; p<0·0001).
We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study.
Prostate Cancer Foundation, National Institutes of Health, Department of Defense, Early Detection Research Network, Doris Duke Charitable Foundation, and Howard Hughes Medical Institute.
对于局限性前列腺癌，需要改进疾病进展的临床预测指标，因为只有一部分患者在一线治疗后会出现复发或难治性疾病。因此，我们进行了一项无偏分析，以确定与前列腺切除术后转移进展相关的RNA生物标志物。
在三个学术机构接受根治性前列腺切除术的患者的前列腺癌样本，通过高密度Affymetrix基因芯片平台进行基因表达分析，该平台涵盖超过100万个基因组位点。在一个发现队列中，根据随后发生转移的肿瘤与未发生转移的肿瘤之间的表达倍数变化，对所有蛋白质编码基因和已知的长链非编码RNA进行排名。然后在另外三个独立队列中验证排名最高的基因对转移进展的预后价值。95%的基因表达检测在符合临床实验室改进修正案标准的实验室设施中进行。通过受试者操作曲线下面积分析评估所有基因预测转移进展的能力。对转移进展的主要终点进行多变量分析，变量包括 Gleason评分、术前前列腺特异性抗原浓度、精囊侵犯、手术切缘状态、包膜外扩展、淋巴结侵犯以及排名最高的基因的表达。
1008例患者纳入研究：发现队列中有545例，验证队列中有463例。长链非编码RNA SChLAP1被确定为转移进展癌症中排名最高的过表达基因。在三个独立队列中的验证证实了SChLAP1对转移进展的预后价值。在多变量模型中，SChLAP1表达（高 vs 低）独立预测10年内发生转移（比值比[OR]2.45，95%CI 1.70 - 3.53；p<0.0001）。另一个独立预测10年内发生转移的变量是Gleason评分（8 - 10 vs 5 - 7；OR 2.14，95%CI 1.77 - 2.58；p<0.0001）。
我们鉴定并验证了高SChLAP1表达对前列腺癌转移疾病进展具有显著预后意义。我们的研究结果表明，进一步开发SChLAP1作为一种潜在的生物标志物，用于强化侵袭性前列腺癌的治疗，值得未来进行研究。
前列腺癌基金会、美国国立卫生研究院、国防部、早期检测研究网络、多丽丝·杜克慈善基金会和霍华德·休斯医学研究所。
