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Precision medicine-based therapies in advanced colorectal cancer: The University of California San Diego Molecular Tumor Board experience

Cited 8 time in Web of Science Cited 8 time in Scopus
Authors

Louie, Bryan H.; Kato, Shumei; Kim, Ki Hwan; Lim, Hyo Jeong; Lee, Suzanna; Okamura, Ryosuke; Fanta, Paul T.; Kurzrock, Razelle

Issue Date
2022-07
Publisher
Elsevier BV
Citation
Molecular Oncology, Vol.16 No.13, pp.2575-2584
Abstract
© 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.Treatment for advanced colorectal cancer is often limited by complex molecular profiles, which promote resistance to systemic agents and targeted monotherapies. Recent studies suggest that a personalized, combinatorial approach of matching drugs to tumor alterations may be more effective. We implemented a precision medicine strategy by forming a Molecular Tumor Board (MTB), a multidisciplinary team of clinicians, scientists, bioinformaticians and geneticists. The MTB integrated molecular profiling information and patient characteristics to develop N-of-One treatments for 51 patients with advanced colorectal cancer. All patients had metastatic disease and 63% had received ≥ 3 prior therapy lines. Overall, 34/51 patients (67%) were matched to ≥ 1 drug recommended by the MTB based on individual tumor characteristics, whereas 17/51 (33%) patients received unmatched therapies. Patients who received matched therapy demonstrated significantly longer progression-free survival (hazard ratio [HR], 0.41; 95% confidence interval [CI], 0.21–0.81; P = 0.01) and a trend towards higher clinical benefit rates (41% vs. 18%, P = 0.058) (all multivariate) compared to patients receiving unmatched therapy. The MTB facilitated personalized matching of drugs to tumor characteristics, which was associated with improved progression-free survival in patients with advanced colorectal cancer.
ISSN
1574-7891
URI
https://hdl.handle.net/10371/184589
DOI
https://doi.org/10.1002/1878-0261.13202
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