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THE International Cancer Genome Consortium, an alliance of laboratories that is trying to produce a definitive list of the genetic mutations that cause cancer, is accumulating data at an astonishing rate. About 3,000 individual breast tumours, for example, have now had their genotypes published. But these data will not, by themselves, help patients. For that, they have to be collected in the context of a drug trial. And this is just what Matthew Ellis and his colleagues at Washington University in St Louis have done for women suffering from breast cancer. Their methods, if they prove to work for other cancers too, may revolutionise treatment.
國際癌癥基因組協作組（THE International Cancer Genome Consortium）是試圖建立一份會引起癌癥的基因突變完整清單的實驗室聯盟，它積累數據的速度讓人吃驚。例如，它已經發表了大約3000種不同的乳房腫瘤的基因型。但光憑這些數據本身無法幫助患者。要醫治病人，人們必須結合藥物試驗采集數據。而這正是在圣路易斯市的華盛頓大學（Washington University in St Louis）工作的馬修?埃利斯（Matthew Ellis）及其同事們為罹患乳腺癌的婦女們所作的工作。如果事實證明他們的方法對其他癌癥也有用的話，這可能會是癌癥治療的一次革命。
Dr Ellis and his team sequenced the whole genomes of both cancerous and normal tissue from 46 women with tumours of a type called oestrogen-receptor-positive breast cancer. They also sequenced just the gene-containing regions of the genome-about 1% of total DNA-from an additional 31 women, and parts of the sequences of 240 more. They then compared the healthy and tumorous genomes of each patient, in order to discover which genes had mutated in the cancer.
埃利斯博士及其團隊對46名身患雌激素受體陽性乳腺癌的婦女的癌組織和正常組織進行了全基因組測序。他們也對另外31名病人的基因組中含有基因的那些區域（約占整個DNA的1%）進行了測序，并對其他240名病人的這些部分做了部分測序。此后，為找出癌細胞中哪些基因發生了突變，他們比較了每個病人的健康和癌變基因組。
In this, they were following the normal protocol of the cancer genome consortium. The novelty of their approach was that the women in question had each been involved in one of two clinical trials of a drug called letrozole. These trials established letrozole as a standard treatment for people with this type of breast cancer, but not all patients benefit equally from the drug. Dr Ellis hoped to find out why.
他們在這一工作中是按癌癥基因組協作組的標準程序操作的，但其方法的新穎之處是，他們還同時進行一種名為來曲唑的藥物的臨床試驗。該試驗有兩種，每個病人都接受其中的一種。這些試驗證實來曲唑是這類乳腺癌的標準治療方法，但它對每個病人的療效并不一樣。埃利斯博士希望找出其原因。
As they report in Nature, he and his team discovered 18 genes that were often mutated. Some were the usual suspects of cancer genetics. These included p53, a gene that, when working properly, suppresses cancer by regulating DNA repair, cell division and cellular suicide, and MAP3K1 and MAP2K4, which both promote cell growth. Others, though, were a surprise. At the top of that list were five which had previously been linked to leukaemia, but were not thought to affect solid tumours.
正如他們在《自然》雜志中所報告的那樣，埃利斯和他的團隊發現了18種經常發生突變的基因，其中有些是癌癥遺傳學通常懷疑的對象。這中間包括p53，這種基因在正常工作時通過調節DNA對的修復、細胞分裂和細胞自殺來抑制癌癥；還有MAP3K1和MAP2K4，它們都能促進細胞生長。但也有些令人吃驚的其他結果。高踞名單前列的5種基因是人們過去認為與白血病有關的，沒想到它們也會影響實體瘤。
By combining their newly acquired genetic data with clinical data from the participants, Dr Ellis and his colleagues showed that those whose tumours carried mutations in p53 (16% of the total) were less likely to have responded to letrozole than women whose tumours had normal p53. Conversely, those whose tumours had changes in either MAP3K1 or MAP2K4 (another 16%) had better than average responses to the drug.
將他們新得到的基因數據與參與試驗者的臨床數據結合，埃利斯博士等人證明了，來曲唑對腫瘤中有p53基因突變的病人（占總數的16%）的療效不如對腫瘤中p53基因正常的病人那樣顯著。與此相反，這一藥物對腫瘤中MAP3K1或MAP2K4有變化的病人（也占總數的16%）的療效高于平均水平。
This sort of information has obvious implications for treatment. And the cheapness of modern gene-sequencing methods, particularly those that are looking for specific mutations suspected in advance, means that a tumour's mutational complement can be worked out easily in an appropriately equipped pathology laboratory. In the case of oestrogen-receptor-positive breast cancer, the genetic analysis has not yet gone so far as to be able to say with certainty which drug will produce the best result for a given individual, but Dr Ellis's result lays a foundation on which such an edifice might be built for breast cancer and perhaps for other types of tumour, too.
這種信息對治療的含義是明顯的。而且，現代基因測序法價格低廉，尋找預先已有懷疑的某些特別的基因突變尤為便宜；這意味著，在擁有合適裝備的病理實驗室里，人們可以很容易地找出腫瘤基因突變的補體。就雌激素受體陽性乳腺癌來說，基因分析還無法肯定地告訴我們，哪種藥物對某個病人療效最佳；但埃利斯博士的結果打下了一個基礎，或許可以在此之上為乳腺癌——甚至其他種類的癌癥——的治療建立有效的預測方法。
