Abstract
AbstractPrecision medicine has revolutionised cancer treatments; however, actionable biomarkers remain scarce. To address this, we develop the Oncology Biomarker Discovery (OncoBird) framework for analysing the molecular and biomarker landscape of randomised controlled clinical trials. OncoBird identifies biomarkers based on single genes or mutually exclusive genetic alterations in isolation or in the context of tumour subtypes, and finally, assesses predictive components by their treatment interactions. Here, we utilise the open-label, randomised phase III trial (FIRE-3, AIO KRK-0306) in metastatic colorectal carcinoma patients, who received either cetuximab or bevacizumab in combination with 5-fluorouracil, folinic acid and irinotecan (FOLFIRI). We systematically identify five biomarkers with predictive components, e.g., patients with tumours that carry chr20q amplifications or lack mutually exclusive ERK signalling mutations benefited from cetuximab compared to bevacizumab. In summary, OncoBird characterises the molecular landscape and outlines actionable biomarkers, which generalises to any molecularly characterised randomised controlled trial.
Funder
EC | Horizon 2020 Framework Programme
Merck KGaA
Pfizer
Almac Group
Roche
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary
Reference72 articles.
1. Ting, N., Cappelleri, J. C., Ho, S. & Chen, D.-G. (eds) Design and Analysis of Subgroups with Biopharmaceutical Applications (Springer, 2020).
2. European Medicines Agency. Guideline on the Investigation of Subgroups in Confirmatory Clinical Trials. Draft. European Medicines Agency/Committee for Medicinal Products for Human Use. EMA/CHMP/539146/2013 (EMA, 2014).
3. Lipkovich, I., Dmitrienko, A. & D'Agostino Sr, B. R. Tutorial in biostatistics: data-driven subgroup identification and analysis in clinical trials. Stat. Med. 36, 136–196 (2017).
4. Zhang, Z., Seibold, H., Vettore, M. V., Song, W.-J. & François, V. Subgroup identification in clinical trials: an overview of available methods and their implementations with R. Ann. Transl. Med. 6, 122 (2018).
5. Loh, W., Cao, L. & Zhou, P. Subgroup identification for precision medicine: a comparative review of 13 methods. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 9, e1326 (2019).
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献