FlyTitle: Oncology

The most comprehensive genetic map of cancers ever made shows how hard they will be to crack

迄今最全面的癌症基因图谱表明,要攻克癌症困难重重

经济学人双语版-肿瘤测绘 The topography of tumours

PERHAPS MORE than any other, cancer is seen as a disease of genes gone wrong. So, as genetic-sequencing technology has become cheaper and faster, cancer scientists are using it to check which changes to genes cause tumours to spread.

相较于其他疾病,癌症或许更多地被认为是因基因出错而引发。因此,随着基因测序技术成本下降和操作更加快捷,肿瘤学家正在利用这项技术来核查是哪些基因变化导致了肿瘤扩散。

The latest insights from one group, the international Pan-Cancer Analysis of Whole Genomes (PCAWG), are revealed last month in Nature. In an analysis of the full genomes of 2,658 samples of 38 types of tumour taken from the bladder to the brain, the researchers give a blow-by-blow account of how a series of genetic mutations can turn normal cells into runaway clones. It provides the most comprehensive analysis yet of where to find this damaging disruption to DNA and, by unpicking the genetics of what makes cancer tick, just how hard it will be to tame.

其中一个科研团队上个月在《自然》杂志上发表了他们最新的研究成果。“泛癌症全基因组分析”(PCAWG)国际团队分析了包括膀胱癌和脑癌在内的38种肿瘤的2658个样本的全部基因组,极为详尽地描述了一系列基因突变如何令正常细胞变成恶性增殖的癌细胞的过程。它为从何处寻找DNA受到的这种损害性扰乱提供了迄今为止最全面的分析,并且,通过揭示癌症发病的遗传学机制,告诉人们要攻克癌症困难重重。

For each of the cancer samples, the team produced a read-out of the tumour genome—the 3bn or so individual DNA letters—and compared it with the genome sequences of healthy cells taken from the same patients. In this way they could look for the genetic signatures of the cancer cells, where specific mutations had warped the genetic information.

该团队对每一份癌症样本都进行了肿瘤基因组测序,即分析其约30亿个独立DNA碱基的序列,然后与同一病人健康细胞的基因组序列做比对。通过这种方法,他们得以寻找癌细胞的遗传标志,也就是那些因特定突变导致遗传信息发生变异的位置。

Most mutations in the genome are harmless. But driver mutations, where genetic changes cause a cell to multiply more easily and faster than other cells, can trigger tumour growth. Many driver mutations have been found over the past decade and a handful have been translated into new medicines. In a fifth of breast cancers (pictured), for example, a driver mutation in the gene HER2 makes cells produce more of a protein on their surface that encourages them to grow and divide out of control. A series of drugs, including Herceptin, target this protein, and lead to significantly improved survival rates. The same HER2 mutation also appears in some lung cancers, raising hopes that similar therapies could work against that disease.

基因组中大多数的突变都是无害的。但发生“驱动突变”时,基因变化会导致突变细胞比其他细胞更容易并更快速地繁殖,可能触发肿瘤生长。过去十年中, 人类已经找到了不少驱动突变,并基于其中的几个研制出了新药。例如,在五分之一的乳腺癌中(见图),HER2基因发生的驱动突变使细胞表面产生更多的蛋白质,导致细胞的生长和分裂失控。包括赫赛汀(Herceptin)在内的一系列靶向药物就是针对这种蛋白质,显著提高了存活率。部分肺癌中也出现了同样的HER2突变,因此类似的疗法也有望用于治疗肺癌。

The problem is that most cancers have multiple driver mutations. Indeed, the PCAWG work found that on average each cancer genome carried four or five. And with some clever genetic archaeology they also found that some driver mutations can occur years before symptoms appear.

问题是大多数癌症存在多重驱动突变。实际上,PCAWG的研究发现每个癌症基因组平均携带四到五个驱动突变。通过一些巧妙的基因溯源手段,研究还发现有些驱动突变可能在出现症状数年之前就已发生。

To discover this, researchers used a new concept called “molecular time” to reconstruct the cellular evolution of tumour cells. By comparing the DNA of cells within tumours, the researchers could place mutations in chronological order based on how many cells they appeared in. Earlier mutations occur more frequently. For example, driver mutations in a gene called TP53 were found to have originated at least 15 years before diagnosis in types of ovarian cancer, and at least five years before in types of colorectal and pancreatic cancer. Driver mutations in a gene called CDKN2A were found to have occurred in some lung cancers more than five years before diagnosis. In theory, that provides a window in which to find people at risk of developing these diseases, and perhaps prevent the cancer ever appearing.

为验证这一发现,研究人员采用了被称为“分子时间”的新概念来重现癌细胞的演化过程。通过比较肿瘤内细胞的DNA,他们可以根据发生突变的细胞数量来按时间顺序排列突变。较早发生的突变发生的次数也更多。例如,TP53基因的驱动突变在各类卵巢癌被确诊的至少15年前开始发生,在各类结直肠癌和胰腺癌被确诊的至少五年前开始发生。CDKN2A基因也是在部分肺癌被确诊的至少五年前就已发生驱动突变。从理论上讲,这提供了窗口期来找出可能发展成癌症的人,从而可能遏制癌症的发生。

The new study closes down talk that significant numbers of unknown driver mutations could lurk in the relatively unexplored regions of the human genome. One such driver mutation in non-coding DNA was found in 2013—a mutation in the TERT gene across many different cancer types. To check for more like this, the consortium sequenced and analysed all the DNA letters of these non-coding regions (which account for 98% of human DNA) for the first time. They found that non-TERT driver mutations occurred at a rate of less than one per 100 tumours in these regions.

这项新研究让一种说法偃旗息鼓——有些人认为还有大量未知的驱动突变可能潜伏在人类基因组中相对未被探索的区域。2013年,在非编码DNA中发现了这样一种驱动突变,即出现在许多不同癌症中的TERT基因突变。为检测更多这样的突变,PCAWG研究团队首次对这些非编码区域(占人类DNA的98%)的所有DNA碱基做了测序和分析,发现在这些区域,肿瘤中存在非TERT驱动突变的比率低于1%。

Peter Campbell of the Wellcome Sanger Institute in Cambridge, Britain, and a member of the PCAWG consortium, says an important contribution of the study is that by sequencing so many tumours it has raised the number of patients in whom a genetic contribution to their cancer can be identified from less than 70% to 95%. The goal, he says, is for genome sequencing of tumours to become routine. Efforts to introduce this are under way in some countries, including Britain, the Netherlands and South Korea, he adds.

研究团队成员、英国剑桥的威康桑格研究所(Wellcome Sanger Institute)的彼得·坎贝尔(Peter Campbell)指出,这项研究的一大贡献在于,通过对这么多肿瘤测序,把可以识别出其所患癌症的遗传因素的病患比率从不到70%升至95%。他表示,研究的目标是将肿瘤基因组测序常态化。他补充道,包括英国、荷兰和韩国在内的一些国家正在努力推行这一做法。

Results, results, results

实效,实效,出实效

Insights are all very well, but what about cold, hard clinical progress? Turning genome sequences into meaningful predictors of cancer will require comparisons between samples from tens of thousands of patients, say the researchers, along with data on their treatments and survival rates. Processing this would be beyond the reach of any single organisation. Instead, a follow-up project is planned that includes national funding agencies, charities and corporate partners from more than a dozen countries around the world. It aims to link full sequences of 200,000 cancer patients to their clinical data by 2025.■

这样的研究成果固然很好,但是否能促成切实可靠的临床进展呢?PCAWG的研究人员表示,要将基因组序列转化为有效的癌症预测指标,需要比对数万名癌症患者的样本,还需要他们的治疗和存活率数据。单靠任何一个机构都无法做到这些。因此,研究人员规划了一个后续项目,参与者包括全球十多个国家的全国性赞助机构、慈善机构和企业合作伙伴,希望在2025年前将20万名癌症患者的全基因序列与其临床治疗数据对接起来。