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同样是乳腺癌，为何生存率差别这么大？最新研究发现，这主要是由于特定基因发生突变造成的。 2016年5月10日，英国《自然·通讯》杂志在线发表了英国癌症研究基金会、剑桥大学、诺丁汉大学、伦敦国王学院、挪威奥斯陆大学、澳大利亚彼得·麦卡勒姆癌症中心、加拿大皇后大学、不列颠哥伦比亚癌症研究中心等机构的研究报告，揭示了乳腺癌如何产生、乳腺癌患者生存相关基因变化的重要基因信息。 该研究根据揭示出乳腺癌可被划分为10种不同亚型的METABRIC研究病理标本，更加深入地了解这10个亚型的基因突变。结果发现，40种发生突变的基因可导致乳腺癌发展，这些基因中只有一小部分此前被发现与乳腺癌发展存在相关性。其中，更常发生突变的PIK3CA基因与10种乳腺癌亚型中的3种亚型生存率降低有相关性。重要的是，这可能有助于解释为何靶向作用于PIK3CA的药物只对某些女性有效而对其他女性无效，有助于发现针对这些基因突变从而阻止乳腺癌发生发展的药物，也提供了协助设计乳腺癌临床研究和改善乳腺癌检测的重要信息。 该研究为2012年4月18日发表在《自然》杂志的METABRIC研究提供了更加详细的信息。METABRIC研究是一项涉及约2000例乳腺癌患者的大型研究，揭示出乳腺癌可被划分为10种亚型。这项规模最大的乳腺癌分子分析研究，旨在研究任何一种乳腺癌亚型接受治疗后如何发展。 METABRIC研究绘制出乳腺癌的基因蓝图，而新的研究结果更加详细地了解哪些基因突变可能与不同类型乳腺癌亚型如何发生发展相关。这些信息可能有助于设计乳腺癌临床研究，或者提供更多液体活检（检测血液中死亡癌细胞所释放基因物质的方法）生物标志物。 该研究再次突显癌症是如何复杂，而这些难题正在被比以前更快地成功解决。该研究提供更多关于乳腺癌如何发生、为何某些亚型比其他亚型更难治疗的重要信息，而且这些信息对全世界研究者而言是巨大的资源，利用这项成果能在未来开发出更好的乳腺癌检测和治疗方法。 Nat Commun. 2016 May 10;7:11479. The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Pereira B, Chin SF, Rueda OM, Vollan HK, Provenzano E, Bardwell HA, Pugh M, Jones L, Russell R, Sammut SJ, Tsui DW, Liu B, Dawson SJ, Abraham J, Northen H, Peden JF, Mukherjee A, Turashvili G, Green AR, McKinney S, Oloumi A, Shah S, Rosenfeld N, Murphy L, Bentley DR, Ellis IO, Purushotham A, Pinder SE, Borresen-Dale AL, Earl HM, Pharoah PD, Ross MT, Aparicio S, Caldas C. Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Robinson Way, Cambridge CB2 0RE, UK; University of Cambridge, Cambridge CB2 2QQ, UK; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Montebello, Oslo 0310, Norway; The K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0318, Norway; Cambridge Breast Unit, Addenbrooke's Hospital, Cambridge University Hospital NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre, Cambridge CB2 2QQ, UK; Cambridge Experimental Cancer Medicine Centre, Cambridge University Hospitals NHS, Hills Road, Cambridge CB2 0QQ, UK; Inivata, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK; Peter MacCallum Cancer Centre, Melbourne, Victoria 3002, Australia; Illumina, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK; Division of Cancer and Stem Cells, School of Medicine, University of Nottingham and Nottingham University Hospital NHS Trust, Nottingham NG5 1PB, UK; Department of Pathology and Molecular Medicine, Queen's University/Kingston General Hospital, 76 Stuart Street, Kingston, Ontario, Canada K7L 2V7; Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada V5Z 1L3; Research Institute in Oncology and Hematology, 675 McDermot Avenue, Winnipeg, Mannitoba, Canada R3E 0V9; NIHR Comprehensive Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and Research Oncology, Cancer Division, King's College London, London SE1 9RT, UK; Strangeways Research Laboratory, University of Cambridge, 2 Worts' Causeway, Cambridge CB1 8RN, UK. The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. PMID: 27161491 DOI: 10.1038/ncomms11479
Nature. 2012 Apr 18;486(7403):346-52. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Graf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S; METABRIC Group, Langerod A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Borresen-Dale AL, Brenton JD, Tavaré S, Caldas C, Aparicio S. Collaborators (86): Caldas C, Aparicio S, Curtis C, Shah SP, Caldas C, Aparicio S, Brenton JD, Ellis I, Huntsman D, Pinder S, Purushotham A, Murphy L, Caldas C, Aparicio S, Caldas C, Bardwell H, Chin SF, Curtis C, Ding Z, Graf S, Jones L, Liu B, Lynch AG, Papatheodorou I, Sammut SJ, Wishart G, Aparicio S, Chia S, Gelmon K, Huntsman D, McKinney S, Speers C, Turashvili G, Watson P, Ellis I, Blamey R, Green A, Macmillan D, Rakha E, Purushotham A, Gillett C, Grigoriadis A, Pinder S, de Rinaldis E, Tutt A, Murphy L, Parisien M, Troup S, Caldas C, Chin SF, Chan D, Fielding C, Maia AT, McGuire S, Osborne M, Sayalero SM, Spiteri I, Hadfield J, Aparicio S, Turashvili G, Bell L, Chow K, Gale N, Huntsman D, Kovalik M, Ng Y, Prentice L, Caldas C, Tavaré S, Curtis C, Dunning MJ, Graf S, Lynch AG, Rueda OM, Russell R, Samarajiwa S, Speed D, Markowetz F, Yuan Y, Brenton JD, Aparicio S, Shah SP, Bashashati A, Ha G, Haffari G, McKinney S. The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA-RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 'CNA-devoid' subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome. PMID: 22522925 PMCID: PMC3440846 DOI: 10.1038/nature10983 |
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