Chin Khew-Voon, Alabanza Leah, Fujii Kazuyuki, Kudoh Kazuya, Kita Tsunekazu, Kikuchi Yoshihiro, Selvanayagam Zachariah E, Wong Yick Fu, Lin Yong, Shih Wei Chung
Department of Medicine, Medical University of Ohio at Toledo, Toledo, Ohio 43614-5809, USA.
Ann N Y Acad Sci. 2005 Nov;1058:186-95. doi: 10.1196/annals.1359.025.
During tumor progression, multiple genetic changes in the genome vastly alter the transcriptomes of cancers. Some of these changes, including the mutations of various growth regulatory genes as well as alterations in the transcription of a large number of genes, may lead to resistance to treatment. Therefore, capturing such genomic information of the tumors would enable a physician to decide on the course of treatment options clinically available. Currently, it is still not feasible to identify all the genetic mutations that have occurred in a patient's cancer genome. However, the advent of DNA microarray coupled with the completion of the human genome sequence and the identification of all its genes, have made possible genome-wide gene expression profiling of the cancer genome. In this review, we will focus on the application of expression genomics for identifying signature gene expression profiles in primary cancers to predict response to either radio- or chemotherapy. We envision that transcription profiling of the cancer genomes ultimately will not only reveal how altered gene expression results in resistance to treatment, but also be exploited for predicting and personalizing cancer therapy.
在肿瘤进展过程中，基因组中的多种基因变化极大地改变了癌症的转录组。其中一些变化，包括各种生长调节基因的突变以及大量基因转录的改变，可能导致治疗耐药性。因此，获取肿瘤的此类基因组信息将使医生能够临床确定可用的治疗方案。目前，识别患者癌症基因组中发生的所有基因突变仍然不可行。然而，DNA微阵列的出现，加上人类基因组序列的完成及其所有基因的鉴定，使得对癌症基因组进行全基因组基因表达谱分析成为可能。在本综述中，我们将重点关注表达基因组学在识别原发性癌症中的标志性基因表达谱以预测放疗或化疗反应方面的应用。我们设想，癌症基因组的转录谱分析最终不仅将揭示基因表达改变如何导致治疗耐药性，还将用于预测和个性化癌症治疗。
