Aftimos Philippe G, Barthelemy Philippe, Awada Ahmad
Medical Oncology Clinic, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium.
Discov Med. 2014 Feb;17(92):81-91.
Biomarkers may have prognostic and/or predictive value and have relied mainly on clinico-pathological information. Prognostic biomarkers provide information on patients' outcome irrespective of treatment, whereas predictive biomarkers provide information on the likelihood of response to a specific therapy. Biomarkers in the treatment of solid tumors were determined for many decades on protein expression by immunohistochemistry. Over the last decade, microarray-based technologies and new high-throughput sequencing methods have emerged, leading to a better understanding of tumor biology. The landmark advances in tumor genomics have highlighted specific molecular abnormalities, such as copy number alterations, mutations, and rearrangements. Several new cancer drugs target those specific molecular alterations or cell signaling pathways yielding unprecedented anti-cancer activity. Gene expression signatures have been developed in order to tailor adjuvant treatment in common tumor types. The "one size fits all" approach has been replaced by a personalized approach. The advent of massive parallel sequencing is responsible of a paradigm shift in biomarker discovery and clinical trial design on the way to what is now called "biomarker-driven cancer medicine" or "precision medicine."
生物标志物可能具有预后和/或预测价值,并且主要依赖临床病理信息。预后生物标志物提供与治疗无关的患者预后信息,而预测生物标志物提供对特定治疗反应可能性的信息。几十年来,实体瘤治疗中的生物标志物都是通过免疫组织化学检测蛋白质表达来确定的。在过去十年中,基于微阵列的技术和新的高通量测序方法不断涌现,使人们对肿瘤生物学有了更好的理解。肿瘤基因组学的里程碑式进展突出了特定的分子异常,如拷贝数改变、突变和重排。几种新型抗癌药物针对这些特定的分子改变或细胞信号通路,产生了前所未有的抗癌活性。为了针对常见肿瘤类型量身定制辅助治疗,人们开发了基因表达特征。“一刀切”的方法已被个性化方法所取代。大规模平行测序的出现推动了生物标志物发现和临床试验设计的范式转变,朝着如今所谓的“生物标志物驱动的癌症医学”或“精准医学”发展。