Laboratory-Clinic InterfaceUse of molecular markers for predicting therapy response in cancer patients
Introduction
Because of biological heterogeneity, only a proportion of patients with a particular type of malignancy benefit from a specific treatment. Thus, response rates for patients with different types of advanced cancer to currently available drugs varies from about 10% to >90%.1 Many of the newer biological or so called targeted therapies, in particular, have efficacy in only a minority of patients. Clearly, an ability to prospectively identify patients likely to respond to a specific treatment would be of great clinical value.
Predictive markers are molecules that provide upfront information as to whether or not a patient is likely to benefit from a specific therapy. Predictive markers thus guide the choice of therapy.2 Patients with marker levels indicating a likely response to a specific therapy are potential candidates for undergoing treatment with that therapy. On the other hand, those patients with marker concentrations suggesting resistance could receive an alternative therapy that may be more beneficial. If an effective alternative therapy is unavailable, these patients could volunteer to participate in clinical trials evaluating new therapies or they could make an informed decision to avoid the needless costs and toxicity of likely ineffective therapy.3 As well as assessing efficacy, predictive markers may be able to identify optimum drug dose and predict toxicity. Thus, the availability of predictive markers increase efficacy and decrease toxicity, which in turn, should decrease overall health care costs and result in an enhanced quality of life for patients.4
Predictive markers should not be confused with prognostic markers. Prognostic markers, in contrast to predictive markers, allow the natural course of a specific disease to be predicted.5 They thus differentiate between patients likely to have a good vs. a poor outcome. Candidate prognostic markers for cancer are molecules involved in tumor cell proliferation, dedifferentiation, angiogenesis, invasion or metastasis. On the other hand, predictive markers are likely to be direct targets of drugs, molecules that signal downstream of the primary target, molecules involved in DNA repair or polymorphisms in genes involved in drug metabolism. Examples of predictive markers involved in these processes are listed in Table 1. The aim of this article is to critically review the most widely investigated predictive markers, especially those that are in clinical use or close to entering clinical use. While this review will primarily focus on molecular predictive markers, we would like to state that in certain situations, clinical, demographic and pathological factors may also be associated with response to oncological therapies. This applies especially to patients with non-small-cell lung cancer, see below.
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ER and PR for predicting response to hormone therapy in patients with breast cancer
The first and still one of the best therapy predictive markers in oncology is the estrogen receptor (ER), i.e., ER-alpha, which is used in selecting patients with breast cancer for endocrine hormone therapy.6 The original rationale for investigating ER as a predictive marker for hormone therapy was based on the fact that the growth of at least some breast cancers was dependent on estrogens. Since estrogens promoted tumor growth via the ER, it was hypothesised that levels of this receptor in
Cytochrome P450 2D6 in predicting benefit from tamoxifen in breast cancer
One reason why some ER-positive patients fail to respond to tamoxifen therapy may relate to inadequate conversion of the prodrug, tamoxifen to its active metabolite, endoxifen.40 In order to mediate its anti-cancer activity, tamoxifen undergoes metabolism to several metabolites that have variable anti-estrogen activity. The initial activation step involves the conversion of tamoxifen to N-desmethyl tamoxifen. N-desmethyl tamoxifen is then converted to its active form in a reaction catalysed by
HER-2 for predicting response to Trastuzumab and Lapatinib in patients with breast cancer
HER-2 which is also known as c-ErbB2, is a member of the HER (ErbB) transmembrane receptor tyrosine kinase family. Other members of this family include HER-1 (cerbB-1), HER-3 (c-erbB3) and HER-4 (c-erbB4). These 4 receptors have a similar general structure that includes an extracellular domain, a transmembrane domain and an intracellular domain.45 Overexpression of the HER-2 protein which usually results from gene amplification is found in 15–25% of newly diagnosed invasive breast cancers. This
KRAS for predicting response to anti-EGFR antibodies in patients with colorectal cancer
In colorectal cancer (CRC), the HER family member that has been most successfully targeted for treatment is EGFR.66, 67, 68 Similar to HER-2, EGFR stimulates cell growth and survival by signalling through the MAPK, PI3K and JAK/STAT pathways. Two monoclonal antibodies, cetuximab and panitumumab that bind to and inhibit EGFR signalling have been approved for the treatment of advanced chemorefractory CRC. Both these antibodies act by binding to the external domain of EGFR and competitively
EGFR and K-RAS in predicting benefit form tyrosine kinase inhibitors in patients with non-small-cell lung cancer
As in CRC, EGFR has been widely investigated as a therapeutic target in patients with non-small-cell lung cancer (NSCLC).73, 74, 75 Currently, 2 TKIs, gefitinib and erlotinib which target this receptor have been approved for second-line treatment of patients with advanced NSCLC. Results from early phase II studies showed that only about 10% of unselected patients with advanced NSCLC responded to these TKIs (reviewed in Refs. 73, 74, 75). Occasionally, these responses were dramatic, resulting in
Multigene profiles
Historically, single or small numbers of markers have been measured to address a specific clinical problem. In the future however, multi marker profiles, especially genetic profiles are likely to find increasing use. Multigene profiles have now been described for many types of malignancy, especially for breast cancer.30, 31, 32, 33, 34, 35, 92, 93 Two of the best validated gene signatures in breast cancer are the 21-gene recurrence score and the 70-gene (Amsterdam) profiles.92, 93
To-date, these
Emerging predictive markers
In addition to the markers discussed above, there are several emerging oncological therapy predictive markers. Some of these are listed in Table 4. Most of these require further validation before recommendation for clinical use. Furthermore, assays for these markers require optimisation and standardisation prior to clinical use.
Conclusion
It is clear from above that good progress has been made in identifying predictive markers in recent years. Indeed, a number of these markers are currently in everyday clinical use such as ER and PR for identifying patients with breast cancers likely to benefit from hormone therapy, HER-2 for the identification of breast cancer patients likely to benefit from trastuzumab and K-RAS mutation status for the identification of colorectal cancer patients likely to benefit from either cetuximab or
Conflict of interest statement
The authors have no conflict of interest to report.
Acknowledgement
The authors wish to thank Science Foundation Ireland, Strategic Research Cluster award (08/SRC/B1410) to Molecular Therapeutics for Cancer Ireland and the Health Research Board Clinician Scientist Award (CSA/2007/11) for funding this work.
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