據(jù)7月15日刊JAMA上的一則研究披露,，在一個(gè)變異基因網(wǎng)絡(luò)之間的相互作用看來在腦腫瘤的發(fā)生與進(jìn)展上扮演著一種重要的角色,。
惡性膠質(zhì)瘤（腦腫瘤）與不成比例的高發(fā)病率和死亡率有關(guān)，它們屬于最具毀滅性的腫瘤之一,。特殊的基因組變化是其形成及惡性發(fā)展的基礎(chǔ),。文章的作者寫道：“染色體的改變被人們假定會(huì)通過修飾獨(dú)特基因的表達(dá)或功能而施加其促進(jìn)膠質(zhì)細(xì)胞生長的作用,，它們也可通過解除對生長因子的信號(hào)傳播途徑和存活途徑的調(diào)節(jié)而促進(jìn)膠質(zhì)細(xì)胞的生長。”
對腦腫瘤的腫瘤發(fā)生學(xué)的研究一直聚焦于個(gè)別染色體內(nèi)的標(biāo)靶基因的變化所帶來的腫瘤促進(jìn)或腫瘤抑制的功能上,。然而,，這些基因的改變并非以孤立的方式存在，人們也無法用單個(gè)基因的變異來解釋膠質(zhì)細(xì)胞瘤的發(fā)生,。相反,，根據(jù)文章的背景資料，可能存在著同時(shí)發(fā)生的基因變異等在機(jī)制上的聯(lián)系,。
Northwestern University Feinberg School of Medicine, Chicago之Northwestern Brain Tumor Institute的Markus Bredel, M.D., Ph.D.及其同僚對膠質(zhì)瘤中的促進(jìn)腫瘤發(fā)生的基因之間的關(guān)系進(jìn)行了調(diào)查,。該研究包括了采自美國和The Cancer Genome Atlas Pilot Project (TCGA) 的多個(gè)學(xué)術(shù)中心的罹患膠質(zhì)瘤的501名患者的基因組和臨床形態(tài)特征（有45個(gè)腫瘤病例屬于初始發(fā)現(xiàn)的數(shù)據(jù)組，它們的數(shù)據(jù)是在2001年至2004年之間采集的,；有456個(gè)腫瘤病例屬于確診數(shù)據(jù)組,，它們在2006年至2008年之間對外公開）。此項(xiàng)分析包括辨識(shí)帶有同時(shí)發(fā)生的基因變化的基因,、相關(guān)的基因劑量（以某種分析方法所決定的某一特別基因的拷貝數(shù)目）與基因表達(dá)和多重功能性相互作用,；以及這些基因與患者生存率之間的相關(guān)性。
研究人員發(fā)現(xiàn)：“膠質(zhì)瘤中的因反復(fù)發(fā)生的染色體畸變所導(dǎo)致的多重網(wǎng)絡(luò)狀聯(lián)系的基因變化會(huì)通過多重性的且相互合作的機(jī)制解除對關(guān)鍵性信號(hào)通路的調(diào)節(jié),。這些在膠質(zhì)細(xì)胞瘤發(fā)生過程中的基因變異可能是因?yàn)閷σ粋€(gè)獨(dú)特基因形貌 [ 即一種一致性的染色體變異模式 ] 的非隨機(jī)性選擇而造成的,，這些基因變異與患者的預(yù)后有關(guān)。”
文章的作者補(bǔ)充說,，在膠質(zhì)瘤中發(fā)現(xiàn)的這些基因變異可促使人們將這些變異當(dāng)作可能的治療標(biāo)靶進(jìn)行評估,。 “一種基因的網(wǎng)絡(luò)背景可能會(huì)影響以其編碼的蛋白作為標(biāo)靶的治療方法的功效。我們的基因形貌模型的復(fù)雜性可幫助人們解釋為什么以單個(gè)基因產(chǎn)物作為標(biāo)靶的治療策略缺乏功效,。”（生物谷Bioon.com）
生物谷推薦原始出處：
JAMA. 2009;302(3):261-275.
A Network Model of a Cooperative Genetic Landscape in Brain Tumors
Markus Bredel, MD, PhD; Denise M. Scholtens, PhD; Griffith R. Harsh, MD; Claudia Bredel, PhD; James P. Chandler, MD; Jaclyn J. Renfrow, MA; Ajay K. Yadav, PhD; Hannes Vogel, MD, PhD; Adrienne C. Scheck, PhD; Robert Tibshirani, PhD; Branimir I. Sikic, MD
Context Gliomas, particularly glioblastomas, are among the deadliest of human tumors. Gliomas emerge through the accumulation of recurrent chromosomal alterations, some of which target yet-to-be-discovered cancer genes. A persistent question concerns the biological basis for the coselection of these alterations during gliomagenesis.
Objectives To describe a network model of a cooperative genetic landscape in gliomas and to evaluate its clinical relevance.
Design, Setting, and Patients Multidimensional genomic profiles and clinical profiles of 501 patients with gliomas (45 tumors in an initial discovery set collected between 2001 and 2004 and 456 tumors in validation sets made public between 2006 and 2008) from multiple academic centers in the United States and The Cancer Genome Atlas Pilot Project (TCGA).
Main Outcome Measures Identification of genes with coincident genetic alterations, correlated gene dosage and gene expression, and multiple functional interactions; association between those genes and patient survival.
Results Gliomas select for a nonrandom genetic landscape—a consistent pattern of chromosomal alterations—that involves altered regions ("territories") on chromosomes 1p, 7, 8q, 9p, 10, 12q, 13q, 19q, 20, and 22q (false-discovery rate–corrected P<.05). A network model shows that these territories harbor genes with putative synergistic, tumor-promoting relationships. The coalteration of the most interactive of these genes in glioblastoma is associated with unfavorable patient survival. A multigene risk scoring model based on 7 landscape genes (POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7, and PDCD4) is associated with the duration of overall survival in 189 glioblastoma samples from TCGA (global log-rank P = .02 comparing 3 survival curves for patients with 0-2, 3-4, and 5-7 dosage-altered genes). Groups of patients with 0 to 2 (low-risk group) and 5 to 7 (high-risk group) dosage-altered genes experienced 49.24 and 79.56 deaths per 100 person-years (hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.10-2.40; Cox regression model P = .02), respectively. These associations with survival are validated using gene expression data in 3 independent glioma studies, comprising 76 (global log-rank P = .003; 47.89 vs 15.13 deaths per 100 person-years for high risk vs low risk; Cox model HR, 3.04; 95% CI, 1.49-6.20; P = .002) and 70 (global log-rank P = .008; 83.43 vs 16.14 deaths per 100 person-years for high risk vs low risk; HR, 3.86; 95% CI, 1.59-9.35; P = .003) high-grade gliomas and 191 glioblastomas (global log-rank P = .002; 83.23 vs 34.16 deaths per 100 person-years for high risk vs low risk; HR, 2.27; 95% CI, 1.44-3.58; P<.001).
Conclusions The alteration of multiple networking genes by recurrent chromosomal aberrations in gliomas deregulates critical signaling pathways through multiple, cooperative mechanisms. These mutations, which are likely due to nonrandom selection of a distinct genetic landscape during gliomagenesis, are associated with patient prognosis.
Author Affiliations: Department of Neurological Surgery, Northwestern Brain Tumor Institute, Lurie Center for Cancer Genetics Research and Center for Genetic Medicine (Drs M. Bredel, Chandler, and Yadav and Ms Renfrow), and Department of Preventive Medicine (Dr Scholtens), Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Neurosurgery (Drs M. Bredel and Harsh), Oncology Division, and Departments of Medicine (Drs C. Bredel and Sikic), Pathology (Dr Vogel), and Health Research and Policy and Statistics (Dr Tibshirani), Stanford University School of Medicine, Stanford, California; Department of General Neurosurgery, Neurocenter and Comprehensive Cancer Center Freiburg, University of Freiburg, Freiburg, Germany (Drs M. Bredel and C. Bredel); and Ina Levine Brain Tumor Center, Neuro-Oncology and Neurosurgery Research, Barrow Neurological Institute of St Joseph's Medical Center, Phoenix, Arizona (Dr Scheck).
