里程碑式研究：前列腺癌首次分类

　　

生物通报道：七月二十九日，在《EBioMedicine》发表的一项里程碑式的研究中，来自英国癌症研究中心的科学家们，首次确定有五种不同类型的前列腺癌，并发现了一种方法来区分它们。延伸阅读：Nature子刊：新的前列腺癌致病基因。

这项发现，能够识别更可能生长并在体内积极扩散的肿瘤，对未来医生如何治疗前列腺癌，有着重要的指导意义。

英国癌症研究中心剑桥研究所和Addenbrooke医院的研究人员，研究了250多名男性的健康的和癌变的前列腺组织。通过寻找异常染色体，并测量100个不同的疾病相关基因的活性，研究人员能够将肿瘤分为五种不同的类型，每一种类型都具有特有的遗传指纹。

与目前医生所使用的测试（包括PSA检测和Gleason得分）相比，这种分析更擅长预测哪些癌症可能是最具侵袭性的。但是，这些发现需要在具有更多受试者的临床试验中得到证实。

我想了解Lonza的原代细胞和优化培养基

本研究共同通讯作者、来自英国癌症研究中心剑桥研究所的Alastair Lamb博士说：“我们这些令人振奋的结果表明，前列腺癌可以分为五种不同的遗传类型。这些研究结果，可以帮助医生根据每名患者的肿瘤特点，决定对他们采取哪种最佳的疗程。

“下一步我们将在更大的研究中证实这些结果，并深入了解每一种特定前列腺癌类型的具体细节。通过对‘不同疾病如何表现’开展更多的研究，未来我们可以开发出更有效的方法，来治疗前列腺癌患者，挽救更多的生命。”

前列腺癌是英国男性最常见的癌症，每年确诊41,700例。英国每年有大约10,800人死于这种疾病。英国癌症研究中心的前列腺癌专家Malcolm Mason教授说：“治疗前列腺癌的挑战在于，它可以要么像一只小猫那样生长缓慢，不会在一个人的一生中引发问题，要么就像老虎那样侵袭性地扩散，需要紧急治疗。但是，目前我们没有可靠的方法来区分它们。这意味着一些人可能要接受他们并不需要的治疗，从而造成不必要的副作用，而其他人则可能会受益于更密集的治疗。”

“如果这些结果在更大规模的临床试验中得以验证，这项研究可能是划时代的，可以给我们更好的信息来指导每名患者的治疗——甚至帮助我们为侵袭性癌症患者选择疗法。最终，这可能意味着更有效的治疗，有助于挽救更多的生命，提高成千上万前列腺癌患者的生活质量。”

（生物通：王英）

生物通推荐原文摘要：
Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study
Abstract
Background
Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

Methods
In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

Findings
We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

Interpretation
For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.