浸润性乳腺癌的预后因素:新的分子技术/谱分析是否显著增加了传统的组织学因素?

Mangesh A. Thorat, Sunil Badve
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引用次数: 3

摘要

提高对筛查的认识和使用导致“早期”乳腺癌的比例增加。传统的预后因素,如肿瘤大小和淋巴结状态对这些肿瘤的作用有限,因为它们大多数是淋巴结阴性和小的。在为这些低风险患者选择合适的治疗方法时,不仅需要预后因素,还需要预测治疗反应的因素,特别是避免对不太可能获得显着益处的患者进行毒性治疗。这导致了新的分子预后因素的出现,基因表达特征是最新的。虽然这些新的预后因素中没有多少被证明具有临床实用性,但最近的研究报告了使用基因表达特征作为预后和预测因素的显着结果。这些结果虽然很有希望,但仅与肿瘤分级等简单参数和广泛的实践指南进行了比较。更多的研究证明基因标记优于现有的预后算法,如诺丁汉预后指数和佐剂!在它们广泛的日常使用之前,在线是必要的。目前,基因标记最好用于随机临床试验,如MINDACT和TAILORx。在本文中,我们讨论了包括基因表达特征在内的传统和分子预后因素的生物学基础、科学证据和临床应用。
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Prognostic factors in invasive breast carcinoma: Do new molecular techniques/profiling add significantly to traditional histological factors?

Greater awareness and use of screening has led to an increase in the proportion of ‘early’ breast cancers. Conventional prognostic factors such as tumour size and nodal status are of limited use with these tumours, because most of them are node negative and small. There is a need for factors that are not only prognostic, but also predict response to therapy, in the selection of appropriate therapy for these low-risk patients, especially to avoid the administration of toxic therapies to patients who are unlikely to gain significant benefit. This has led to the emergence of newer molecular prognostic factors, gene-expression signatures being the latest. Although not many of these newer prognostic factors have proved clinical utility, recent studies report remarkable results with the use of gene-expression signatures as prognostic and predictive factors. These results, though promising, have been compared only with simple parameters such as tumour grade and with broad practice guidelines. Additional studies documenting superiority of gene signatures over existing prognostic algorithms such as the Nottingham prognostic index and Adjuvant! Online are necessary before their widespread routine use. Currently, gene signatures are best used as a part of randomized clinical trials such as MINDACT and TAILORx. In this review, we discuss the biological basis, scientific evidence and clinical application of conventional and molecular prognostic factors, including gene-expression signatures.

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