Suppr超能文献

用于基于基因组信息的癌症研究性治疗的决策支持框架。

A decision support framework for genomically informed investigational cancer therapy.

作者信息

Meric-Bernstam Funda, Johnson Amber, Holla Vijaykumar, Bailey Ann Marie, Brusco Lauren, Chen Ken, Routbort Mark, Patel Keyur P, Zeng Jia, Kopetz Scott, Davies Michael A, Piha-Paul Sarina A, Hong David S, Eterovic Agda Karina, Tsimberidou Apostolia M, Broaddus Russell, Bernstam Elmer V, Shaw Kenna R, Mendelsohn John, Mills Gordon B

机构信息

Sheikh Khalifa Al Nahyan Ben Zayed Institute for Personalized Cancer Therapy , the University of Texas MD Anderson Cancer Center, Houston, TX (FMB, AJ, VH, AMB, JZ, KRS, JM, GBM); Departments of Investigational Cancer Therapeutics (FMB, LB, SAPP, DSH, AMT), Surgical Oncology (FMB), Hematopathology (MR, KPP), Bioinformatics & Computational Biology (KC), GI Medical Oncology (SK), Melanoma Medical Oncology (MAD), Experimental Therapeutics (RB), Systems Biology (AKE, GBM), the University of Texas MD Anderson Cancer Center, Houston, TX; School of Biomedical Informatics, the University of Texas Health Science Center, Houston, TX (EVB).

出版信息

J Natl Cancer Inst. 2015 Apr 11;107(7). doi: 10.1093/jnci/djv098. Print 2015 Jul.

Abstract

Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient's molecular profile, including molecular characterization of the tumor and the patient's germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a "cancer gene" at the level of a specific variant in order to discriminate so-called "drivers" from "passengers." Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially "actionable." At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients.

摘要

对分子肿瘤学的快速深入理解、新兴的新型疗法以及越来越容易获得且价格合理的下一代测序技术,为提供基于基因组信息的个性化癌症治疗创造了机会。然而,要实施基于基因组信息的治疗,临床医生需要解读患者的分子特征,包括肿瘤的分子特征和患者的种系DNA。在本评论中,我们回顾了精准肿瘤学的现有数据和工具,并提出了一个框架,用于回顾关于基因组改变的治疗意义的现有生物医学文献。基因组改变,包括突变、插入/缺失、融合和拷贝数变化,需要根据它们在特定变异水平上改变“癌症基因”功能的可能性进行整理,以便区分所谓的“驱动因素”和“乘客”。可通过批准或研究性疗法直接或间接靶向的改变可能是“可操作的”。目前,在特定癌症类型的背景下,将预测性生物标志物与疗法联系起来的证据仅对少数基因组标志物有力。对于其他疾病中的这些基因组改变以及其他基因组改变,临床数据要么缺乏,要么不足以支持基于生物标志物的疗法的常规临床应用。然而,人们非常希望能让患者最佳地匹配早期临床试验。因此,我们需要可访问、全面且经常更新的知识库,以描述基因组变化及其临床意义,同时还需要对临床医生和患者进行持续教育。

相似文献

1
A decision support framework for genomically informed investigational cancer therapy.
J Natl Cancer Inst. 2015 Apr 11;107(7). doi: 10.1093/jnci/djv098. Print 2015 Jul.
2
Can a Liquid Biopsy Detect Circulating Tumor DNA With Low-passage Whole-genome Sequencing in Patients With a Sarcoma? A Pilot Evaluation.
Clin Orthop Relat Res. 2025 Jan 1;483(1):39-48. doi: 10.1097/CORR.0000000000003161. Epub 2024 Jun 21.
3
The Black Book of Psychotropic Dosing and Monitoring.
Psychopharmacol Bull. 2024 Jul 8;54(3):8-59.
4
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
Cochrane Database Syst Rev. 2020 Jan 9;1(1):CD011535. doi: 10.1002/14651858.CD011535.pub3.
6
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
Cochrane Database Syst Rev. 2021 Apr 19;4(4):CD011535. doi: 10.1002/14651858.CD011535.pub4.
7
Cost-effectiveness of using prognostic information to select women with breast cancer for adjuvant systemic therapy.
Health Technol Assess. 2006 Sep;10(34):iii-iv, ix-xi, 1-204. doi: 10.3310/hta10340.
9
EORTC guidelines for the use of erythropoietic proteins in anaemic patients with cancer: 2006 update.
Eur J Cancer. 2007 Jan;43(2):258-70. doi: 10.1016/j.ejca.2006.10.014. Epub 2006 Dec 19.
10
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
Cochrane Database Syst Rev. 2017 Dec 22;12(12):CD011535. doi: 10.1002/14651858.CD011535.pub2.

引用本文的文献

1
The present and future of precision oncology and tumor-agnostic therapeutic approaches.
Oncologist. 2025 Jun 4;30(6). doi: 10.1093/oncolo/oyaf152.
2
Clinical outcomes of tumor-agnostic targeting of BRAF, tumor mutation burden-high, and RET.
ESMO Open. 2025 Jun;10(6):105061. doi: 10.1016/j.esmoop.2025.105061. Epub 2025 Jun 2.
3
Concordance between tumor tissue and plasma DNA genotyping in the NCI-MATCH trial (EAY131).
Clin Cancer Res. 2025 May 19. doi: 10.1158/1078-0432.CCR-24-3531.
4
Agnostic Drugs: A New Paradigm in Pharmacological Therapy.
Hosp Pharm. 2025 May 8:00185787251340598. doi: 10.1177/00185787251340598.
6
Application and prospect of organoid technology in breast cancer.
Front Immunol. 2024 Aug 26;15:1413858. doi: 10.3389/fimmu.2024.1413858. eCollection 2024.
7
Criteria for assessing evidence for biomarker-targeted therapies in rare cancers-an extrapolation framework.
Ther Adv Med Oncol. 2024 Sep 2;16:17588359241273062. doi: 10.1177/17588359241273062. eCollection 2024.
8
9
The evolution of precision oncology: The ongoing impact of the Drug Rediscovery Protocol (DRUP).
Acta Oncol. 2024 May 23;63:368-372. doi: 10.2340/1651-226X.2024.34885.
10
Kinase inhibitor pulldown assay (KiP) for clinical proteomics.
Clin Proteomics. 2024 Jan 16;21(1):3. doi: 10.1186/s12014-023-09448-3.

本文引用的文献

2
NCCN Working Group report: designing clinical trials in the era of multiple biomarkers and targeted therapies.
J Natl Compr Canc Netw. 2014 Nov;12(11):1629-49. doi: 10.6004/jnccn.2014.0161.
3
Prioritizing targets for precision cancer medicine.
Ann Oncol. 2014 Dec;25(12):2295-2303. doi: 10.1093/annonc/mdu478. Epub 2014 Oct 24.
4
Prospective enterprise-level molecular genotyping of a cohort of cancer patients.
J Mol Diagn. 2014 Nov;16(6):660-72. doi: 10.1016/j.jmoldx.2014.06.004. Epub 2014 Aug 23.
6
Return of genomic results to research participants: the floor, the ceiling, and the choices in between.
Am J Hum Genet. 2014 Jun 5;94(6):818-26. doi: 10.1016/j.ajhg.2014.04.009. Epub 2014 May 8.
7
Physicians' attitudes about multiplex tumor genomic testing.
J Clin Oncol. 2014 May 1;32(13):1317-23. doi: 10.1200/JCO.2013.52.4298. Epub 2014 Mar 24.
8
Synonymous mutations frequently act as driver mutations in human cancers.
Cell. 2014 Mar 13;156(6):1324-1335. doi: 10.1016/j.cell.2014.01.051.
9
Concordance of genomic alterations between primary and recurrent breast cancer.
Mol Cancer Ther. 2014 May;13(5):1382-9. doi: 10.1158/1535-7163.MCT-13-0482. Epub 2014 Mar 7.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验