Lancet：预测前列腺癌复发风险的新方案

　　

生物通报道：最近，前列腺研究人员开发出一种遗传检测法，来确定哪些前列腺癌患者在接受局部治疗、手术或放疗之后，具有最高的复发风险。

相关研究结果发表在2014年11月13日的《柳叶刀肿瘤学》（Lancet Oncology）。本文共同第一作者、Princess Margaret 癌症中心临床科学家Robert Bristow博士和安大略湖癌症研究所Paul Boutros博士报道称，这种基因检测可提供一种急需、快速和准确的工具，更精确地确定哪些患者接受局部治疗（手术或放疗）效果最好，哪些患者将需要额外的治疗（化疗和激素治疗），以确保癌症被完全根除。

Bristow博士说：“我们的研究结果，为解决接受治疗的侵袭性疾病患者持续很久的临床问题，奠定了基础，这类疾病在30%到50%的患者当中会复发，因为在初期治疗时，隐藏的微小肿瘤已经在前列腺之外。”

“这种基因检测通过防止前列腺癌的这种转移性扩散，能够提高中危到高危患者的治愈率。”下一步是，在三到五年内，在世界各地更多的患者身上检测这些基因标记，将这种检测方法转化成一种临床容易使用的方法，指导个性化的前列腺癌治疗。

预测性检测分析的是治疗之前的活检组织，甚至开始识别前列腺癌的异常遗传特性（异常DNA）及其氧含量。低氧或缺氧，是前列腺癌扩散的一个已知因素。总之，研究显示，在大约3天时间内，这些信息的预测准确率几乎达到80%，预测这些前列腺癌患者处于疾病复发的最大风险。

Bristow博士说：“对于成千上万的患者来说，这具有巨大的临床潜力。这完全是个性化癌症医学——根据患者独特的癌症遗传指纹，加上在癌细胞周围环境中发生了什么，为患者提供更多的靶向治疗。我们希望，能够通过降低癌症复发的机会和防止细胞扩散，提高癌症的治愈率。”

研究人员在两组患者中进行了遗传检测。在第一组当中，研究人员分析了126名男性最初诊断活检的DNA，这些患者接受影像导航（IGRT）治疗，并进行了平均7.8年的随访。在第二组当中，研究小组在150名接受肿瘤手术切除（根治性前列腺切除术）的患者中进行了检测。在这两组患者中，遗传检测产生了相似的结果，因此可以用于选择放疗或手术治疗作为初始治疗的患者。

Bristow博士说，他们还发现，当在患者中用IGRT和基因检验测试肿瘤发缺氧性时，这种结合的信息使测试变得更加准确。

研究表明，具有最好预后结果（前列腺癌的五年复发率低于7%）的男性，具有低水平的遗传变化和低缺氧。对于具有高水平遗传变化和高缺氧的男性来说，预后结果更糟——超过50%的人会复发，这些人在将来有可能要接受强化治疗，作为其个性化治疗计划的一部分。

（生物通：王英）

延伸阅读：Nature子刊：阻止前列腺癌扩散的分子突破

生物通推荐原文摘要：
Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study
Summary
Background
Clinical prognostic groupings for localised prostate cancers are imprecise, with 30—50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors.
Methods
We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment.
Findings
Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4•5 [95% CI 2•1—9•8]; p=0•00013; area under the receiver operator curve [AUC] 0•70 [95% CI 0•65—0•76]) and radical prostatectomy (4•0 [1•6—9•7]; p=0•0024; AUC 0•57 [0•52—0•61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3•8 [1•2—12]; p=0•019; AUC 0•67 [0•61—0•73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6•1 [95% CI 2•0—19]; p=0•0015; AUC 0•74 [95% CI 0•65—0•83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2•9 [95% CI 1•4—6•0]; p=0•0039; AUC 0•68 [95% CI 0•63—0•73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures.
Interpretation
This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials.