Role of genomic factors beyond thymidylate synthase in the prediction of response to 5-fluorouracil

Autor: K. Smid, E. Meijer, C. J. van Groeningen, Godefridus J. Peters, Leticia G. Leon
Přispěvatelé: Medical oncology laboratory, CCA - Biomarkers, Hematology, Medical oncology
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Nucleosides, Nucleotides and Nucleic Acids, 35(10-12), 595-603. Taylor and Francis Ltd.
Peters, G J, Smid, K, Meijer, E, Van Groeningen, C J & Leon, L G 2016, ' Role of genomic factors beyond thymidylate synthase in the prediction of response to 5-fluorouracil ', Nucleosides, Nucleotides and Nucleic Acids, vol. 35, no. 10-12, pp. 595-603 . https://doi.org/10.1080/15257770.2016.1218020
ISSN: 1525-7770
Popis: 5-Fluorouracil (5FU) is still a major drug in combinations regimens for the treatment of colorectal cancer (CRC) both in the adjuvant and palliative setting. 5FU or its oral prodrug capecitabine is usually combined with irinotecan/oxaliplatin and the novel agents bevacizumab/cetuximab. Although this improved the outcome, the overall prognosis in patients with metastasized disease is still relatively poor. Although the target for 5FU, thymidylate synthase was shown to have a predictive value, this could only predict response in a subset of patients. Given the heterogeneous and complex nature of CRC, it is likely that other aberrations can affect therapeutic response. As an alternative, we investigated Copy number alterations using oligonucleotide-based high-throughput array-comparative-genomic-hybridization (aCGH) to obtain an unbiased screening of the whole genetic spectrum. Chromosomal aberrations have been identified in 85% of CRC patients and include genomic regions harboring copy number alterations in the DNA. These alterations may change the expression of many genes and might explain the differential response to therapy as shown in recent studies with several 5FU combinations. In order to clarify new predictive parameters for 5FU, we used aCGH in a historical cohort of patients, which received treatment with single agent 5FU, and an unsupervised clustering analysis showed a statistical (p0.05) difference between responding and nonresponding patients. We also find that several regions showed differences between responders/non-responders, such as losses in 12p12.3-12q15 and in 18p (where TS is located) in responding patients. Genome-wide analysis may provide an additional tool to discriminate between responders and nonresponders.
Databáze: OpenAIRE