一個由美國、英國,、以色列等國組成的研究團隊建立了一種染色體不穩(wěn)定的小鼠模型，這種模型與人類的癌癥發(fā)生有很多相似之處。
達那-法伯癌癥研究所（the Dana-Farber Cancer Institute）的科學家開發(fā)了一種更接近人類癌癥的老鼠模型（mouse model）,，此模型將協(xié)助研究人員更容易找到致癌基因，并能改善實驗室中癌癥藥物試驗的預測值,。此研究由Ronald A. Depinhho醫(yī)師主導,，并結合了Lynda Chin醫(yī)師的高解析CGH矩陣，這是一種基因組掃瞄技術能找出基因組中異常的DNA,，此研究發(fā)表于5月21日的Nature期刊網絡版,。
DePinho醫(yī)師表示：“在老鼠與人類腫瘤中找到相同的異常基因樣式（patterns）,，顯示這兩個物種在癌癥機制可能極為類似,，可通過老鼠模型找出可能的癌癥基因，了解這些基因在形成腫瘤時所扮演的角色,，并找到可能的治療方法,。”傳統(tǒng)上，癌癥研究的老鼠模型是將致癌基因送入老鼠胚胎,，讓老鼠經由人工的方法得到癌癥,，并不是自然產生癌癥。這種老鼠的腫瘤缺乏人類腫瘤的關鍵的特異性,，例如：基因組的不穩(wěn)定性（genomic instability）,，包括染色體斷裂或重組等,，都會導致基因的異常或遺失,，有些甚至會造成基因的重復復制進而產生腫瘤,。
此研究中，研究人員利用基因敲除（knockout）的方法,，使老鼠細胞內缺乏一些重要的分子,，造成老鼠基因組產生不穩(wěn)定的現(xiàn)象，結果老鼠便產生T細胞急性淋巴癌（T-cell acute lymphoblastic leukemia/lymphoma,，T-ALL）,，可發(fā)現(xiàn)許多復合性的突變樣式，包括：染色體重組,、基因擴大（gene amplifications）以及基因被刪除等現(xiàn)象,。目前研究人員已在T-ALL老鼠模型中鑒定出兩個基因，F(xiàn)BXW7以及PTEN,，是在人類癌癥中最常被突變或被刪除的基因,。
Chin實驗室的研究成員在過去數(shù)年來，已經將老鼠染色體的變異與人類腫瘤樣本進行比對,，至少超過400多種癌癥,，包括：黑色素瘤、肺癌,、結腸癌,、胰臟癌以及多種骨髓癌等。比對中顯示：老鼠癌細胞中基因的不穩(wěn)定性,，在很多情況下都會造成DNA改變,，且情況類似于人類的腫瘤細胞。因此,，研究人員建議這個新的老鼠模型可用于人類癌癥的研究,。（生物谷援引生命經緯）
原始出處:
Nature advance online publication 21 May 2007 | doi:10.1038/nature05886; Received 26 March 2007; Accepted 30 April 2007; Published online 21 May 2007
Chromosomally unstable mouse tumours have genomic alterations similar to diverse human cancers
Richard S. Maser1,14, Bhudipa Choudhury4,14, Peter J. Campbell4,14, Bin Feng2,14, Kwok-Kin Wong1, Alexei Protopopov2, Jennifer O'Neil3, Alejandro Gutierrez3,5, Elena Ivanova2, Ilana Perna2, Eric Lin6, Vidya Mani1, Shan Jiang1, Kate McNamara1, Sara Zaghlul1, Sarah Edkins4, Claire Stevens4, Cameron Brennan7, Eric S. Martin1, Ruprecht Wiedemeyer1, Omar Kabbarah1, Cristina Nogueira1, Gavin Histen8, Jon Aster8, Marc Mansour11, Veronique Duke11, Letizia Foroni11, Adele K. Fielding11, Anthony H. Goldstone12, Jacob M. Rowe13, Yaoqi A. Wang1,2, A. Thomas Look3, Michael R. Stratton4, Lynda Chin1,2,9, P. Andrew Futreal4 & Ronald A. DePinho1,2,10
Department of Medical Oncology,
Center for Applied Cancer Science of the Belfer Institute for Innovative Cancer Science,
Department of Pediatric Oncology Dana Farber Cancer Institute, Boston, Massachusetts 02115, USA
Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
Division of Hematology, Children's Hospital, Boston, Massachusetts 02115, USA
Agilent Technologies, Palo Alto, California 94304, USA
Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, New York 10021, USA
Department of Pathology,
Department of Dermatology,
Department of Genetics and Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
Royal Free and University College Medical School, London NW3 2PF, UK
University College London Hospitals, London NW1 2BU, UK
Rambam Medical Center and Technion, Haifa 31096, Israel
These authors contributed equally to this work.
Correspondence to: Ronald A. DePinho1,2,10 Correspondence and requests for materials should be addressed to R.A.D. (Email: [email protected]).
Abstract
Highly rearranged and mutated cancer genomes present major challenges in the identification of pathogenetic events driving the neoplastic transformation process. Here we engineered lymphoma-prone mice with chromosomal instability to assess the usefulness of mouse models in cancer gene discovery and the extent of cross-species overlap in cancer-associated copy number aberrations. Along with targeted re-sequencing, our comparative oncogenomic studies identified FBXW7 and PTEN to be commonly deleted both in murine lymphomas and in human T-cell acute lymphoblastic leukaemia/lymphoma (T-ALL). The murine cancers acquire widespread recurrent amplifications and deletions targeting loci syntenic to those not only in human T-ALL but also in diverse human haematopoietic, mesenchymal and epithelial tumours. These results indicate that murine and human tumours experience common biological processes driven by orthologous genetic events in their malignant evolution. The highly concordant nature of genomic events encourages the use of genomically unstable murine cancer models in the discovery of biological driver events in the human oncogenome.
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