Personalized cancer therapy coming of age: clinical highlights in 2009 and future directions.

Abstract

Personalized MedicineVol. 7, No. 2 EditorialFree AccessPersonalized cancer therapy coming of age: clinical highlights in 2009 and future directionsBrigette BY Ma and Herbert LoongBrigette BY Ma† Author for correspondenceLKS Specialist Clinic, Department of Clinical Oncology, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China and State Key Laboratory in Oncology in South China, Hong Kong SAR, China and Sir YK Pao Centre for Cancer, Hong Kong SAR, China and Hong Kong Cancer Institute, Hong Kong SAR, China and Chinese University of Hong Kong, Hong Kong SAR, China. Search for more papers by this authorEmail the corresponding author at brigette@clo.cuhk.edu.hk and Herbert LoongPrince of Wales Hospital, Hong Kong SAR, ChinaSearch for more papers by this authorPublished Online:16 Mar 2010https://doi.org/10.2217/pme.10.11AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit Relevance of personalized drug therapy in oncologyIn the systemic treatment of cancer, therapeutic decisions are made by weighing the benefits against the risks of a drug therapy for a particular individual. Traditionally, this risk:benefit ratio is estimated via extrapolations from the results of clinical trials of that drug conducted in larger populations who share similar clinicopathological characteristics with that individual, such as histopathology and disease stage. This traditional approach is limited by the fact that it does not adequately account for the variability in drug response between individuals and populations. As a result, some patients who are biologically less likely to respond may be overtreated, while patients who are more susceptible to drug toxicity may be subjected to increased risks if they are given ‘standard’ dosages of a drug therapy. For example, most patients with stage II colon cancer have a low risk of recurrence after surgery, except for a high-risk subgroup which may benefit from adjuvant chemotherapy. However, the magnitude of benefit from chemotherapy is modest, such that up to 30 patients would have to be treated in order to prevent one cancer-related death, while drug-related toxicities can strike one in six patients and have a mortality rate of one in every 200 patients [1].Predictive biomarkers of drug response in oncology: recent developmentsThe use of predictive biomarkers for selecting drug therapy is not a new strategy in oncology. For over two decades, expression of hormonal receptors in breast cancer has been used for selecting patients for hormonal therapy. Recent technological advances in molecular biology have helped to unravel the molecular mechanisms of carcinogenesis and have led to the development of new molecularly targeted drugs. Despite the promising preclinical result of many such target-based drugs, only a few of them that were tested in clinical trials in the early 1990s have successfully obtained regulatory approval. A key lesson learnt from these early years of development is the importance of using predictive biomarkers to enrich trial populations, thereby increasing the likelihood of enrolling patients whose tumors are biologically more likely to respond to the new drug. Biomarkers that have a significant impact on the contemporary treatment of some solid tumors include: ▪ Activating mutations of the kinase-encoding genes (e.g., EGFR, HER2, KRAS and KIT) in predicting response to kinase inhibitors;▪ Germline mutations of BRCA1 and -2 genes in predicting response to poly(adenosine diphosphate-ribose) polymerase inhibitors;▪ Microarray-based gene signatures of prognosis in breast cancer for predicting benefits from adjuvant chemotherapy;▪ Genetic variants of drug-metabolizing and DNA-repair enzymes for the prediction of drug toxicity;▪ Promoter methylation of DNA-repair gene in predicting response to alkylating chemotherapy.This editorial will examine the impact of these biomarkers on current clinical practice and future development of new drug evaluations in oncology.Activating mutations in predicting drug responseInhibitors against the EGF receptor (EGFR) and human EGFR (HER)2 proteins have been demonstrated to improve survival in clinical trials and are now commercially available for the treatment of advanced lung [2–4], breast [5–7] and colorectal cancer [8,9]. The historical development of predictive biomarkers for EGFR inhibitors has undergone a more challenging course than for the HER2 inhibitors. In breast cancer, studies have demonstrated a clear association between the level of HER2 protein overexpression or gene amplification and clinical benefit to HER2 inhibitors [10]. Therefore, it is now mandatory to determine the HER2 status of a breast tumor before starting treatment with or enrolling subjects into clinical trials of anti-HER2 therapies [10].By contrast, EGFR protein overexpression or gene amplification do not consistently predict clinical benefits to anti-EGFR agents in lung [3] and colorectal cancer [11]. For example, the development of gefitinib in lung cancer illustrates the importance of biomarker-driven subject selection for the successful development of target-based drugs. Gefitinib was the first oral EGFR tyrosine kinase (TK) inhibitor to obtain fast-track approval from the US FDA in 2003 for the treatment of chemotherapy-refractory lung cancer, based on the surrogate end point of response rate in a Phase II trial [12]. Despite the initial promise, subsequent attempts to evaluate the impact of gefitinib on survival in the first-line treatment of lung cancer failed in Phase III trials [13,14], resulting in its partial withdrawal from the US market. By performing retrospective gene sequencing of tumor biopsies from responders to gefitinib, it was later discovered that some activating mutations of EGFR-TK could predict marked sensitivity to gefitinib [15]. These mutations are found in 10–15% of all lung cancers, but can be detected in over 50% of certain histologic subtypes (e.g., adenocarcinoma) and patient subgroups (e.g., Asian females or nonsmokers) [16]. Rather than enrolling unselected subjects, recent clinical trials of EGFR-TK inhibitors have incorporated EGFR-TK mutation status as a criteria for assigning treatment. A recently reported Phase III study has confirmed that EGFR-TK mutations are powerful predictors of clinical outcome following gefitinib therapy, such that patients with EGFR-mutant tumors have an impressive 72% response rate to gefitinib compared with just 1% in those with wild-type tumors [3]. Moreover, patients with EGFR-mutant tumors are more likely to derive survival benefit from gefitinib than from platinum-based chemotherapy – the current ‘standard’ in the first-line treatment of advanced lung cancer [3]. Since EGFR-TK inhibitors are more expensive and less toxic than chemotherapy, determination of EGFR-TK mutation status should be made mandatory before starting EGFR-TK inhibitors in the first-line treatment of lung cancer. Activating mutations of other signaling kinases have also significantly contributed to personalized therapy in other cancers, such as KIT mutations in predicting response to imatinib (a multitargeted kinase inhibitor) in gastrointestinal stromal tumor [17]. Based on the experience with kinase inhibitors, there is now a growing trend toward ‘personalized’ early-phase clinical trials, where new target-based drugs are evaluated in highly selected populations who express specific molecular markers. The impressive Phase I study result of a new poly(adenosine diphosphate-ribose) polymerase inhibitor in breast cancer patients who were carriers of germline mutations of BRCA1 and BRCA2[18], illustrates the dominant role that predictive biomarkers now play in the contemporary development of new anticancer drugs.Somatic mutations in predicting primary resistance to kinase inhibitorsAnti-EGFR antibodies have been commercially available for the treatment of advanced colorectal cancer for over 5 years; however, the discovery of KRAS mutations as powerful predictors of primary resistance to these drugs has only been reported recently in retrospective studies [19]. KRAS mutations can be found in approximately 40% of colorectal cancers, and Phase III studies have confirmed that only patients with KRAS wild-type tumors will benefit from anti-EGFR antibody therapies [20,21]. There is even some unsubstantiated evidence to suggest that treatment with these agents maybe harmful to patients with KRAS mutant tumors [22,23]. This discovery has led to the revision of marketing labels for these drugs (e.g., cetuximab and panitumumab) and practice guidelines from the National Comprehensive Cancer Network (PA, USA) and the American Association of Clinical Oncology (VA, USA). It is now mandatory to determine KRAS status before starting treatment with these antibodies.Other important clinical highlightsSeveral biomarkers are of major academic interests but their ability to predict drug response is not as strong as the kinase mutations mentioned above. For example, patients with glioblastoma multiforme that harbor promoter methylation in the DNA repair gene, MGMT, can derive a larger benefit from temozolomide therapy than those without MGMT methylation [24]. However, the difference in clinical outcome between patients with and without MGMT methylation is not as striking as that observed with EGFR and KRAS mutations in lung and colorectal cancer, as discussed before. In the pivotal study which led to the approval for the concomitant use of temozolomide with radiotherapy in the primary treatment of glioblastoma multiforme, a subgroup analysis has demonstrated that patients would still benefit from receiving temozolomide regardless of the MGMT methylation status of their tumors; therefore, this factor should not be used solely to select patients for temozolomide therapy [25].Several DNA array-based gene signatures have been developed for the stratification of patients with node-negative breast cancer, based on their risk of developing postoperative recurrence. Of these signatures, the Amsterdam signature (Mammaprint™ [Agendia; Amsterdam, The Netherlands], 70-gene signature) and the Recurrence Score (Oncotype™ [Genomic Health; CA, USA], 21-gene signature) are now FDA approved. The main application of these tools is to help identify patients with node-negative breast cancer who are at higher risk of developing postoperative recurrence for adjuvant chemotherapy, and these predictive tools are making a gradual impact on clinical practice in some US centers [26]. However, according to an advisory group established by the US CDC – the Evaluation of Genomic Applications in Practice and Prevention working group – it remains controversial whether these gene signatures provide added value to conventional prognostic criteria based on pathological and clinical determinants [27].Besides gene signatures, certain genetic variants of drug-metabolizing enzymes may contribute to personalized anticancer therapies in other cancers. Variants of the UGT1A1 gene are associated with an increase risk of severe irinotecan-related toxicity in patients with colorectal cancer. However, these variants could only explain 50% of all cases of severe toxicities and recent studies have revealed many other genetic variants of drug-transporter and metabolizing enzymes that have comparable predictive importance [28]. Furthermore, the predictive utility of UGT1A1 variants is only relevant when higher dosages of irinotecan are used [29]. In breast cancer, variants of the CYP2D6 gene could predict reduced benefit from tamoxifen therapy and may be helpful in identifying patients who might benefit from alternatives, such as aromatase inhibitors [30]. Although the FDA has approved inclusion of the above information in the marketing label for irinotecan and tamoxifen, the Evaluation of Genomic Applications in Practice and Prevention group does not recommend that patients undergo routine genotyping for these variants before receiving these drugs [31].Conclusion & future perspectiveSignificant progress has been made in recent years in the development of molecular markers that can predict response to anticancer drug therapy, and these tools are being applied in the ever-expanding clinical and research settings. The successful clinical application of the EGFR-TK mutation in lung cancer and the KRAS mutation in colorectal cancer illustrate some important characteristics of a good predictive biomarker. These include the ability to clearly distinguish drug responders from nonresponders, to demonstrate relative abundance in tumor expression, and their method of detection should be accurate, reproducible and widely available. More importantly, the ability of these biomarkers to improve cancer-related survival should be prospectively validated in population-based clinical trials. Additional evaluations are needed to better define the clinical utility of gene signatures, and pharmacogenomic and epigenomic biomarkers, as discussed in this editorial. Future studies should focus on how these molecular tools can enhance the predictive utility of existing clinical criteria of drug selection, on defining which patient subgroups would benefit most from undergoing these tests, and on devising practical guidelines on how to adjust therapeutic decisions based on test results.Financial & competing interests disclosureBrigette Ma has received honoraria for consultancy for Astra Zeneca Inc. 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The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download