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本文引用的文献

1
Analysis of gene expression using gene sets discriminates cancer patients with and without late radiation toxicity.使用基因集进行基因表达分析可区分有和没有晚期放射毒性的癌症患者。
PLoS Med. 2006 Oct;3(10):e422. doi: 10.1371/journal.pmed.0030422.
2
Preventing or reducing late side effects of radiation therapy: radiobiology meets molecular pathology.预防或减轻放射治疗的晚期副作用:放射生物学与分子病理学的结合
Nat Rev Cancer. 2006 Sep;6(9):702-13. doi: 10.1038/nrc1950.
3
Gene expression changes in peripheral blood cells provide insight into the biological mechanisms associated with regimen-related toxicities in patients being treated for head and neck cancers.外周血细胞中的基因表达变化有助于深入了解头颈部癌患者与治疗方案相关毒性有关的生物学机制。
Oral Oncol. 2007 Mar;43(3):289-300. doi: 10.1016/j.oraloncology.2006.03.014. Epub 2006 Aug 22.
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Distinct effects of ionizing radiation on in vivo murine kidney and brain normal tissue gene expression.
Clin Cancer Res. 2006 Jun 15;12(12):3823-30. doi: 10.1158/1078-0432.CCR-05-2418.
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Early gene expression profile in mouse brain after exposure to ionizing radiation.暴露于电离辐射后小鼠大脑中的早期基因表达谱
Radiat Res. 2006 Feb;165(2):142-54. doi: 10.1667/rr3485.1.
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The Gene Ontology (GO) project in 2006.2006年的基因本体论(GO)项目。
Nucleic Acids Res. 2006 Jan 1;34(Database issue):D322-6. doi: 10.1093/nar/gkj021.
7
Reliability and reproducibility issues in DNA microarray measurements.DNA微阵列测量中的可靠性和可重复性问题。
Trends Genet. 2006 Feb;22(2):101-9. doi: 10.1016/j.tig.2005.12.005. Epub 2005 Dec 27.
8
Can risk of radiotherapy-induced normal tissue complications be predicted from genetic profiles?能否根据基因图谱预测放疗引起的正常组织并发症风险?
Acta Oncol. 2005;44(8):801-15. doi: 10.1080/02841860500374513.
9
Microarray analysis of the transcriptional response to single or multiple doses of ionizing radiation in human subcutaneous fibroblasts.人皮下成纤维细胞对单剂量或多剂量电离辐射转录反应的微阵列分析。
Radiother Oncol. 2005 Dec;77(3):231-40. doi: 10.1016/j.radonc.2005.09.020. Epub 2005 Nov 17.
10
Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.基因集富集分析:一种基于知识的方法用于解读全基因组表达谱。
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基因表达阵列作为揭示正常组织辐射损伤机制和预测反应的工具。

Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response.

作者信息

Kruse Jacqueline J C M, Stewart Fiona A

机构信息

The Netherlands Cancer Institute, Department of Experimental Therapy (H6), Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.

出版信息

World J Gastroenterol. 2007 May 21;13(19):2669-74. doi: 10.3748/wjg.v13.i19.2669.

DOI:10.3748/wjg.v13.i19.2669
PMID:17569134
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4147114/
Abstract

Over the past 5 years there has been a rapid increase in the use of microarray technology in the field of cancer research. The majority of studies use microarray analysis of tumor biopsies for profiling of molecular characteristics in an attempt to produce robust classifiers for prognosis. There are now several published gene sets that have been shown to predict for aggressive forms of breast cancer, where patients are most likely to benefit from adjuvant chemotherapy and tumors most likely to develop distant metastases, or be resistant to treatment. The number of publications relating to the use of microarrays for analysis of normal tissue damage, after cancer treatment or genotoxic exposure, is much more limited. A PubMed literature search was conducted using the following keywords and combination of terms: radiation, normal tissue, microarray, gene expression profiling, prediction. With respect to normal tissue radiation injury, microarrays have been used in three ways: (1) to generate gene signatures to identify sensitive and resistant populations (prognosis); (2) to identify sets of biomarker genes for estimating radiation exposure, either accidental or as a result of terrorist attack (diagnosis); (3) to identify genes and pathways involved in tissue response to injury (mechanistic). In this article we will review all (relevant) papers that covered our literature search criteria on microarray technology as it has been applied to normal tissue radiation biology and discuss how successful this has been in defining predisposition markers for radiation sensitivity or how it has helped us to unravel molecular mechanisms leading to acute and late tissue toxicity. We also discuss some of the problems and limitations in application and interpretation of such data.

摘要

在过去5年里,微阵列技术在癌症研究领域的应用迅速增加。大多数研究使用肿瘤活检的微阵列分析来描绘分子特征,试图生成用于预后的可靠分类器。目前已有几种已发表的基因集被证明可预测侵袭性乳腺癌,这类患者最有可能从辅助化疗中获益,其肿瘤最有可能发生远处转移或对治疗产生耐药性。关于使用微阵列分析癌症治疗或基因毒性暴露后正常组织损伤的出版物数量则要少得多。我们使用以下关键词和术语组合在PubMed上进行了文献检索:辐射、正常组织、微阵列、基因表达谱分析、预测。关于正常组织辐射损伤,微阵列有三种应用方式:(1)生成基因特征以识别敏感和抗性群体(预后);(2)识别用于估计意外或恐怖袭击导致的辐射暴露的生物标志物基因集(诊断);(3)识别参与组织损伤反应的基因和通路(机制)。在本文中,我们将回顾所有符合我们文献检索标准的(相关)论文,这些论文涉及微阵列技术应用于正常组织辐射生物学的研究,并讨论其在定义辐射敏感性易感性标志物方面的成功程度,以及它如何帮助我们揭示导致急性和晚期组织毒性的分子机制。我们还将讨论此类数据在应用和解释方面的一些问题和局限性。