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A systems approach to clinical oncology: Focus on breast cancer

机译:临床肿瘤学的系统方法:关注乳腺癌

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摘要

During the past decade, genomic microarrays have been applied with some success to the molecular profiling of breast tumours, which has resulted in a much more detailed classification scheme as well as in the identification of potential gene signature sets. These gene sets have been applied to both the prognosis and prediction of outcome to treatment and have performed better than the current clinical criteria. One of the main limitations of microarray analysis, however, is that frozen tumour samples are required for the assay. This imposes severe limitations on access to samples and precludes large scale validation studies from being conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), on the other hand, can be used with degraded RNAs derived from formalin-fixed paraffin-embedded (FFPE) tumour samples, the most important and abundant source of clinical material available. More recently, the novel DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay has been developed as a high throughput gene expression profiling system specifically designed for use with FFPE tumour tissue samples.However, we do not believe that genomics is adequate as a sole prognostic and predictive platform in breast cancer. The key proteins driving oncogenesis, for example, can undergo post-translational modifications; moreover, if we are ever to move individualization of therapy into the practical world of blood-based assays, serum proteomics becomes critical. Proteomic platforms, including tissue micro-arrays (TMA) and protein chip arrays, in conjunction with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), have been the technologies most widely applied to the characterization of tumours and serum from breast cancer patients, with still limited but encouraging results.This review will focus on these genomic and proteomic platforms, with an emphasis placed on the utilization of FFPE tumour tissue samples and serum, as they have been applied to the study of breast cancer for the discovery of gene signatures and biomarkers for the early diagnosis, prognosis and prediction of treatment outcome. The ultimate goal is to be able to apply a systems biology approach to the information gleaned from the combination of these techniques in order to select the best treatment strategy, monitor its effectiveness and make changes as rapidly as possible where needed to achieve the optimal therapeutic results for the patient.
机译:在过去的十年中,基因组微阵列已成功应用于乳腺肿瘤的分子谱分析,这导致了更为详细的分类方案以及潜在基因签名集的鉴定。这些基因集已被应用于治疗的预后和预后,并且比目前的临床标准表现更好。然而,微阵列分析的主要限制之一是测定需要冷冻的肿瘤样品。这对获取样品提出了严格的限制,并阻止了大规模验证研究的进行。另一方面,定量逆转录酶聚合酶链反应(qRT-PCR)可与源自福尔马林固定石蜡包埋(FFPE)肿瘤样品的降解RNA结合使用,FFPE是最重要和最丰富的可用临床材料。最近,已开发出一种新颖的DASL(cDNA介导的退火,选择,延伸和连接)测定法,该测定法是专门设计用于FFPE肿瘤组织样品的高通量基因表达谱分析系统,但我们认为基因组学不够充分作为乳腺癌的唯一预后和预测平台。例如,驱动肿瘤发生的关键蛋白可以进行翻译后修饰;此外,如果我们要将治疗的个体化应用到基于血液的测定的实际世界中,血清蛋白质组学就变得至关重要。蛋白质组学平台,包括组织微阵列(TMA)和蛋白质芯片阵列,以及表面增强的激光解吸电离飞行时间质谱(SELDI-TOF / MS),已成为表征中应用最广泛的技术对乳腺癌患者的肿瘤和血清进行研究,结果仍然有限,但令人鼓舞。本文将重点研究这些基因组学和蛋白质组学平台,重点是对FFPE肿瘤组织样品和血清的利用,因为它们已被用于研究用于发现基因特征和生物标志物以早期诊断,预后和预测治疗结果。最终目标是能够对从这些技术的组合中收集到的信息应用系统生物学方法,以便选择最佳的治疗策略,监控其效果并在需要时尽可能快地进行更改以实现最佳治疗效果为病人。

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