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个性化医疗中前列腺癌基因组学的背景。

The context of prostate cancer genomics in personalized medicine.

作者信息

Liu Yanling

机构信息

Department of Oncology-Pathology, Karolinska Institutet, Stockholm SE-171 76, Sweden.

出版信息

Oncol Lett. 2017 May;13(5):3347-3353. doi: 10.3892/ol.2017.5911. Epub 2017 Mar 24.

Abstract

Prostate cancer is one of the most common types of cancer in males. Heterogeneous genomic aberrations may lead to prostate cancer onset, progression and metastasis. This heterogeneity also contributes to the variety in cancer risk and outcomes, different drug responses and progression, observed between individual patients. Classical prognostic factors, including prostate-specific antigen, Gleason Score and clinical tumor staging, are not sufficient to portray the complexity of a clinically relevant cancer diagnosis, risk prognosis, treatment choice and therapy monitoring. There is a requirement for novel genetic biomarkers in order to understand the oncogenic heterogeneity in a patient-personalized clinical setting and to improve the efficacy of risk prognosis and treatment choice. A number of biomarkers and gene panels have been established from patient sample cohort studies. These previous studies have provided distinct information to the investigation of heterogeneous malignancy in prostate cancer, which aids in clinical decision-making. Biomarker-guided therapies may facilitate the effective selection of drugs during early treatment; therefore, are beneficial to the individual patient. A non-invasive approach allows for convenient and repeated sampling to screen for cancer and monitor treatment response without the requirement for invasive tissue biopsies. With the current availability of numerous advanced technologies, reliable detection of the minimal tumor residues present following treatment may become clinical practice and, therefore, inform further in the field of personalized medicine.

摘要

前列腺癌是男性最常见的癌症类型之一。基因组异质性畸变可能导致前列腺癌的发生、进展和转移。这种异质性还导致了个体患者之间在癌症风险和预后、不同药物反应及进展方面的差异。包括前列腺特异性抗原、 Gleason评分和临床肿瘤分期在内的传统预后因素,不足以描绘临床相关癌症诊断、风险预后、治疗选择和治疗监测的复杂性。为了在患者个性化临床环境中理解致癌异质性,并提高风险预后和治疗选择的有效性,需要新的基因生物标志物。已经从患者样本队列研究中建立了一些生物标志物和基因组合。这些先前的研究为前列腺癌异质性恶性肿瘤的研究提供了独特的信息,有助于临床决策。生物标志物指导的治疗可能有助于在早期治疗期间有效选择药物;因此,对个体患者有益。非侵入性方法允许方便且重复地采样以筛查癌症并监测治疗反应,而无需进行侵入性组织活检。随着当前众多先进技术的可用性,治疗后存在的最小肿瘤残留的可靠检测可能会成为临床实践,从而为个性化医学领域提供更多信息。

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本文引用的文献

1
Circulating biomarkers to monitor cancer progression and treatment.
Comput Struct Biotechnol J. 2016 Jun 1;14:211-22. doi: 10.1016/j.csbj.2016.05.004. eCollection 2016.
2
Validation of Novel Biomarkers for Prostate Cancer Progression by the Combination of Bioinformatics, Clinical and Functional Studies.
PLoS One. 2016 May 19;11(5):e0155901. doi: 10.1371/journal.pone.0155901. eCollection 2016.
4
Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker-Based Risk Score.
Eur Urol. 2016 Nov;70(5):740-748. doi: 10.1016/j.eururo.2016.04.012. Epub 2016 Apr 20.
5
A Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer at Initial Biopsy.
JAMA Oncol. 2016 Jul 1;2(7):882-9. doi: 10.1001/jamaoncol.2016.0097.
6
New developments in prostate cancer biomarkers.
Curr Opin Oncol. 2016 May;28(3):248-52. doi: 10.1097/CCO.0000000000000279.
7
Cancer Drug Resistance: A Brief Overview from a Genetic Viewpoint.
Methods Mol Biol. 2016;1395:1-18. doi: 10.1007/978-1-4939-3347-1_1.
8
Haplotyping germline and cancer genomes with high-throughput linked-read sequencing.
Nat Biotechnol. 2016 Mar;34(3):303-11. doi: 10.1038/nbt.3432. Epub 2016 Feb 1.
9
Single-cell genome sequencing: current state of the science.
Nat Rev Genet. 2016 Mar;17(3):175-88. doi: 10.1038/nrg.2015.16. Epub 2016 Jan 25.
10
A Prospective Investigation of PTEN Loss and ERG Expression in Lethal Prostate Cancer.
J Natl Cancer Inst. 2015 Nov 27;108(2). doi: 10.1093/jnci/djv346. Print 2016 Feb.

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