Tze-Kiong Er , Luis Bujanda , Maximiliano Rodrigo , Marta Herreros-Villanueva
{"title":"Pharmacogenomic biomarkers for colorectal cancer treatment","authors":"Tze-Kiong Er , Luis Bujanda , Maximiliano Rodrigo , Marta Herreros-Villanueva","doi":"10.1016/j.ctrc.2015.08.003","DOIUrl":null,"url":null,"abstract":"<div><p>An important part of personalized medicine in colorectal cancer (CRC) relies on using the most effective treatment based on molecular biomarkers, which define groups of patients according to specific tumor alterations. Therefore, anti-tumoral drugs are administered selectively to a subgroup of patients whose genetic alterations in the tumors indicate that they have an increased probability of recurrence without treatment or to those patients who will most likely respond to the treatment.</p><p>Currently, pharmaceutical companies use targeted drugs with biomarkers during the early stages of drug development. Then, the companion diagnostics that are developed based on response-specific biomarkers allow for the administration of the right drug to the right patient. Because CRC has become one of the most common neoplasias, personalized medicine has changed the oncologists' and pathologists' daily routines. In fact, <em>KRAS</em> mutations represented a revolution in targeted therapies and had clinical relevance for patients, clinicians and pharmaceutical companies. However, the new biomarkers, including microsatellite instability (MSI) and both <em>NRAS</em> and <em>BRAF</em> mutations, are well established molecular markers that determine CRC subgroups and should be considered separately when debating treatment options. However, despite the scientific evidence, these biomarkers have not yet been incorporated into practice. More clinical facts and cost-effectiveness analysis may be needed for their uniform implementation.</p></div>","PeriodicalId":90461,"journal":{"name":"Cancer treatment communications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ctrc.2015.08.003","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer treatment communications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213089615300062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
An important part of personalized medicine in colorectal cancer (CRC) relies on using the most effective treatment based on molecular biomarkers, which define groups of patients according to specific tumor alterations. Therefore, anti-tumoral drugs are administered selectively to a subgroup of patients whose genetic alterations in the tumors indicate that they have an increased probability of recurrence without treatment or to those patients who will most likely respond to the treatment.
Currently, pharmaceutical companies use targeted drugs with biomarkers during the early stages of drug development. Then, the companion diagnostics that are developed based on response-specific biomarkers allow for the administration of the right drug to the right patient. Because CRC has become one of the most common neoplasias, personalized medicine has changed the oncologists' and pathologists' daily routines. In fact, KRAS mutations represented a revolution in targeted therapies and had clinical relevance for patients, clinicians and pharmaceutical companies. However, the new biomarkers, including microsatellite instability (MSI) and both NRAS and BRAF mutations, are well established molecular markers that determine CRC subgroups and should be considered separately when debating treatment options. However, despite the scientific evidence, these biomarkers have not yet been incorporated into practice. More clinical facts and cost-effectiveness analysis may be needed for their uniform implementation.