Precision treatment for cancer: role of prognostic and predictive markers.

http://informahealthcare.com/lab ISSN: 1040-8363 (print), 1549-781X (electronic) Crit Rev Clin Lab Sci, 2014; 51(1): 30–45 ! 2014 Informa Healthcare USA, Inc. DOI: 10.3109/10408363.2013.865700

Precision treatment for cancer: Role of prognostic and predictive markers Michael J. Duffy1,3 and John Crown2,3 1

Clinical Research Centre, 2Department of Medical Oncology, St Vincent’s University Hospital, Dublin, Ireland, and 3UCD School of Medicine and Medical Science, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland Abstract

Keywords

Precision or personalized treatment can be defined as using the biological characteristics of a patient’s disease in order to administer the most effective therapy at the optimum dose. The aim of this article is to discuss the use of prognostic and predictive markers to aid precision treatment in patients with cancer. Prognostic markers help to differentiate between indolent and life-threatening disease and thereby identify who should or should not receive adjuvant systemic therapy following surgical removal of a primary tumor. Predictive markers, on the other hand, help to identify upfront those patients who are likely to be responsive or resistant to a specific therapy. The use of prognostic and predictive markers can thus help to match each patient to the most effective and least toxic therapy and as a result avoid preventable toxicity and unnecessary costs.

Personalized treatment, precision treatment, predictive, prognostic, tumor biomarkers

Abbreviations: 3D-CRT, 3D conformation radiation therapy; ADCC, antibody-dependent cellular cytotoxicity; AFP, alpha-fetoprotein; ASCO, American Society of Clinical Oncology; BRAF, v-raf murine sarcoma viral oncogene homolog B1; CI, confidence interval; CMF, cyclophosphamide-methotrexate-5-fluorouracil; CRC, colorectal cancer; EGFR, epidermal growth factor receptor; ELISA, enzyme-linked imunosorbent assay; ER, estrogen receptor; ESMO, European Society of Medical Oncology; FFPE, formalin-fixed paraffin-embedded; GCT, germ cell tumor; HCG, human gonadotropic hormone; HER2, human epidermal growth factor receptor 2; HR, hazard ratio; IMRT, 3D intensity modulated radiation therapy; KRAS, v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog; LDH, lactate dehydrogenase; MAPK, mitogenactivated protein kinase; MMR, mismatch repair; MS, microsatellite; MSI, microsatellite instability; NCCN, National Comprehensive Cancer Network; NSCLC, non-small cell lung cancer; NSGCT, non-seminomatous germ cell tumor; PAI-1, plasminogen activator inhibitor 1; PD-1, programmed cell death protein 1; PI3K, phosphatidylinositol 3-kinase; PPV, positive predictive value; PR, progesterone receptor; PSA, prostate specific antigen; PSADT, PSA doubling time, time required for PSA levels to double their concentration; PSAV, PSA velocity, change in PSA concentration over time; RS, recurrence score; T-DM1, ado-trastuzumab emtansine; TKI, tyrosine kinase inhibitor; UICC, Union Internationale Contre le Cancer; uPA, urokinase plasminogen activator; VEGF, vascular endothelial growth factor

Introduction The traditional approach to treating patients with cancer is often referred to as ‘‘trial and error’’ or ‘‘one size fits all’’1. This arbitrary practice is inefficient and costly, and frequently results in the administration of an inappropriate therapy1,2.

Referee Dr. Neil O’Brien, Division of Hematology-Oncology, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA Address for correspondence: Professor M. J. Duffy, Clinical Research Centre, St. Vincent’s University Hospital, Elm Park, Dublin 4, Ireland. E-mail: [email protected]

History Received 19 August 2013 Revised 21 October 2013 Accepted 11 November 2013 Published online 9 January 2014

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REVIEW ARTICLE

The consequences of this approach for patients may include overtreatment in some situations, under-treatment in other situations, low response rates and unnecessary toxicity. In contrast to the traditional approach, precision or personalized treatment, i.e. giving the most appropriate drug or combination of drugs at the optimum dose to every patient, has the potential to increase efficacy, decrease toxicity, and ultimately, result in more cost-effective patient management. In order to progress to precision/personalized treatment, several different types of markers are required. These include prognostic markers for differentiating between indolent and aggressive disease, predictive markers to identify the therapy most likely to be efficacious, markers for upfront prediction

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of serious adverse reactions and markers for identifying the optimal drug dose3. This article will discuss the use of prognostic and therapy predictive markers for individualizing cancer treatment. The focus will mostly be on single markers rather than multi-analyte (multigene) tests.


Role of prognostic markers in guiding precision treatment Prognostic markers are factors that predict the likely outcome of disease such as risk of relapse or disease progression4. Thus, a marker of good prognosis suggests prolonged survival and indeed the possibility of cure. In contrast, a marker of poor prognosis indicates an increased probability of early disease recurrence. It should, however, be emphasized that no prognostic marker can accurately predict outcome for an individual patient; it provides a probability estimate of outcome for a heterogeneous population of patients. Prognostic markers are most important at the time of initial diagnosis, especially to determine if additional therapy such as systemic adjuvant chemotherapy is required following surgical removal of the primary tumor. Such markers thus help to minimize overtreatment of patients with indolent disease and avoid under-treatment of patients with aggressive and life-threatening disease4,5. Patients with indolent disease may then be able to avoid the side effects of adjuvant systemic therapies while those with aggressive disease would be recommended to receive the most appropriate local and systemic therapy. Depending on the cancer type, the choice of such therapy may be guided by predictive markers (see below). Measurement of prognostic markers is particularly important in cancers that have wide variation in inter-patient outcome5. This situation clearly applies to patients with localized prostate cancer and lymph node-negative breast cancer patients. In both these situations, validated prognostic markers are particularly urgently required in order to differentiate between those patients who can be followed up with conservative management and those who will require additional therapies following their primary diagnosis. Thus, since the introduction of mammographic screening, most newly diagnosed breast cancer patients present free of lymph node metastases. Approximately 70% of these women are cured of their disease following surgery and radiotherapy. However, since the traditional clinical and histopathological prognostic factors are unable to reliably differentiate between the ‘‘cured’’ patients and those who are likely to develop recurrent/metastatic disease, many women with lymph node-negative disease receive adjuvant chemotherapy. Unfortunately, less than 10% of these women benefit from the chemotherapy6, while many will suffer from the adverse toxic effects of these agents. Clearly, in this situation, prognostic markers that complement existing clinical and histopathological factors are urgently required. Thus, if such a marker or markers were available, high risk patients identified with the marker could be considered for adjuvant chemotherapy. On the other hand, women identified as being at low risk could avoid receiving futile and toxic chemotherapy, thereby increasing their quality of life and reducing their cost of care.

Precision treatment for cancer

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Similarly, an urgent need exists for prognostic markers in newly diagnosed patients with localized prostate cancer. Here, prognostic markers are necessary to differentiate between men who have indolent disease and thus can be managed with active surveillance and those who have aggressive disease and thus might benefit from radical prostatectomy or radiotherapy. Since the advent of prostate specific antigen (PSA) screening, the majority of men diagnosed with prostate cancer have early or localized disease and tend to have a good outcome without any active treatment. Despite this good outcome, almost 90% of men with PSA-screen detected cancer in the USA receive active treatment such as radical prostatectomy or radiotherapy7. These treatments have at best only a modest effect on increasing survival. Yet, they are frequently associated with adverse effects such as impotence, and urinary and gastrointestinal problems. Again, as in women with lymph node-negative breast cancers, prognostic markers are essential for the optimal management of men with localized prostate cancer.

Measurement of prognostic markers Measurement of prognostic markers is usually determined on primary tumor tissue or preoperative blood samples. Tissue-based prognostic markers tend to be molecules causally involved in cell proliferation (e.g. Ki67), cell cycle (e.g. cyclin D), invasion and metastasis (e.g. uPA) and angiogenesis [e.g. vascular endothelial growth factor (VEGF)]. Until relatively recently, most research carried out on prognostic markers investigated single or occasionally two analytes. In recent years, however, the trend has been to measure multiple analytes, such as several mRNA transcripts with microarray, rather than single markers8. The rationale for measuring multiple analytes is based on the expectation that such an approach can provide more reliable data on patient outcome than that obtained with a single marker. In particular, the use of multiple markers can potentially minimize or overcome the problems of intratumor heterogeneity (see below). Although most research on prognostic markers in cancer has been carried out on tumor tissue, it should be pointed out that use of blood has several advantages over tissue. These advantages include ease in sampling and the ability to determine prognosis in real-time. For example, blood-based markers may be used for determining prognosis prior to surgical removal of the primary tumor, following surgical resection of primary tumor, following adjuvant treatment, or at time of recurrence. Furthermore, in contrast to tissue-based markers, automated and standardized assays are currently available for a number of blood-based cancer markers. The rationale for using serum markers for predicting patient outcome is likely to relate to the approximate correlation that exists between blood concentration of the marker and tumor bulk, and indeed, the presence of micrometastasis.

Prognostic markers: many were called but few selected Traditional prognostic factors for cancer include patient age, tumor size, tumor grade, number of local lymph nodes with

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M.J. Duffy & J. Crown

Crit Rev Clin Lab Sci, 2014; 51(1): 30–45


Table 1. Some of the best validated and/or clinically used prognostic markers in oncology. Marker

Cancer

PSA AFP, HCG, LDH LDH MSI CEA uPA and PAI-1 Oncotype Dx MammaPrint

Prostate NSGCT Seminoma CRC CRC Breast Breast Breast

metastasis, and clinical performance status. Although these criteria have been used for decades in determining prognosis and planning treatment across the different cancer types, it is now widely accepted that they lack the necessary accuracy for individualizing treatment in patients with cancer4,5. In recent years, therefore, a vast amount of research has been undertaken in order to identify prognostic markers that might complement existing clinical and pathological parameters. A search of PubMed identified over 20,000 hits relating to cancer prognostic markers (Duffy MJ, personal observation). Despite this enormous number of publications, less than 10 prognostic markers are in clinical use (Table 1). Some reasons for this discrepancy are outlined below.

of prognostic markers in clinical use is that few of the putative markers have undergone appropriate analytical and clinical validation (see below). Tumor markers, however, may have clinical utility in patients with malignancy if they12: provide prognostic information independent of conventional prognostic factors, i.e. give new or additional information to the established parameters; provide stronger prognostic information than the conventional factors; provide prognostic information within clinically important subgroups defined by traditional factors, e.g. lymph node negative breast cancer or stage II colon cancer. In both these situations, prognostic markers may help to differentiate between patients who should or should not receive adjuvant systemic treatment; have undergone appropriate validation in a prospective study in which the marker is the primary aim of the trial, or in a retrospective analysis of archival specimens that were collected prospectively from subjects participating in at least two clinical studies13–15. These two approaches for showing evidence of clinical utility are known as level 1 evidence studies13,14.

Widely investigated prognostic markers Use of PSA as a prognostic marker in prostate cancer

Inadequate study design The vast majority of studies on prognostic markers are retrospective in design. With such a design, the samples may not be representative of the total patient population with a specific malignancy. For example, in studies involving freshly frozen samples, only the larger tumors that have sufficient residual tissue after essential histological diagnosis may be available. A further problem with retrospective studies is that samples may have been handled and stored in different ways, which may in turn have an impact on the stability of the marker undergoing evaluation. Use of inappropriate statistical tests A frequent problem with many of the prognostic marker studies is over-optimistic reporting of results. This may be due to multiple testing, subset analysis and use of multiple cut-off points to obtain the optimum concentration for separating patients into those with good and poor outcome9–11. Another common problem is inadequate sample number, resulting in underpowered studies. Failure to provide independent prognostic information Ideally, a new prognostic marker should provide additional or independent prognostic data that complement the existing prognostic factors such as tumor size, tumor grade and lymph node status. A marker associated with outcome that correlates with these parameters is of little value to clinicians. Inadequate validation The main reason for discrepancy between the large number of publications on prognostic markers and the small number

As mentioned above, a marker that can aid the differentiation of indolent and life-threatening disease is perhaps the most important requirement for the individualized management of men with newly diagnosed localized prostate cancer. Although widely used in screening for prostate cancer16, PSA can also provide prognostic information in patients with newly diagnosed disease. For such purposes, PSA can be used in several different ways. These include the use of absolute pre-treatment levels, the combination of pretreatment levels with established prognostic factors (tumor stage, Gleason tumor grade, seminal vessel invasion and status of surgical margins) to generate nomograms, and the use of serial levels to calculate either PSA velocity (PSAV, change in PSA concentration over time) or PSA doubling time (PSADT, time required for PSA levels to double their concentration)17–23. Of these, the most widely used is the combination of absolute PSA levels, tumor stage and Gleason tumor grade. Thus, the National Comprehensive Cancer Network (NCCN) guidelines recommend these three parameters for categorizing risk of recurrence in newly diagnosed prostate cancer patients24. According to this expert group, men with a low risk of prostate cancer recurrence include those with low tumor stage (T1–T2a), low Gleason grade (2–6) and PSA concentrations510 mg/L. For men with a life expectancy 510 years, active surveillance was recommended for this subgroup. For men with a life expectancy of 410 years, the options include radical prostatectomy, brachytherapy or radiotherapy using either 3D intensity modulated radiation therapy (IMRT) or 3D conformation radiation therapy (3D-CRT)24. Men with an intermediate risk of recurrence include those with stage T2b–T2c disease, Gleason grade of 7 and PSA


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concentrations between 10 and 20 mg/L. For those with a life expectancy of 510 years, active surveillance was regarded as an option. For men with a life expectancy of 410 years, radical prostatectomy and radiotherapy were the options recommended24. High risk of recurrence was defined as clinically localized stage T3a disease, Gleason grade 8–10 and PSA concentrations 420 mg/L. Potential treatments for these high-risk men include radiation (IMRT/3D-CRT) and androgen deprivation therapy. Radical prostatectomy was regarded as an option in selected patients with low tumor volume and no fixation to adjacent organs24. As well as static levels, the rate of change in serial PSA levels can also provide prognostic data. The rate of change in serial levels is usually determined by the PSAV or PSADT. These changes in PSA levels can be determined either prior to diagnosis or during follow-up after primary therapy. Multiple studies show that patients with a high PSAV or a short PSADT have a worse outcome than those with low PSAV or long PSADT25–27. However, whether PSAV or PSADT provides independent prognostic information over absolute pre-therapy PSA levels or Gleason grade is unclear. Although the use of PSA kinetics to predict outcome in patients with prostate cancer is appealing and is recommended by some expert panels24, it has a number of disadvantages. First, multiple demographic and life style factors affect PSAV. These include age, race, energy intake, weight changes and calcium supplements28. Consequently, PSA levels in blood exhibit relatively wide biological variation, i.e. approximately 20% in the concentration range of 0.1–20 mg/L for men over 50 years of age29. Changes in serial levels of PSA should therefore be at least 50% in order to be significant (i.e. p50.05)29. This relatively wide biological variation in PSA levels should be borne in mind when determining PSAV or PSADT. A second problem with the use of PSAV or PSADT is the lack of standardized methodology for their measurements. Thus, the methods used to date varied with respect to the number of determinations used for calculation, the frequency of measurement and the interval over which the measurements were made. In an attempt to standardize the methodology for calculation of PSA doubling time, the Prostate Specific Antigen Working Group recently published guidelines for its measurement30. The main points in these guidelines are summarized below: All PSA concentrations should be 40.2 mg/L and follow an increasing trend. All levels contained during a maximum period of 12 months should be included in the calculation. The maximum period of the last 12 months is recommended to reflect current disease status. Minimum requirements for the calculation are three PSA concentrations obtained during 3 months with a minimum of 4 weeks between measurements. All PSA results must be obtained using the same assay method and preferably in the same laboratory. PSA results should be recorded with a maximum of two significant digits after the decimal point. Serum testosterone concentrations should be relatively stable during the period used for calculation.


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Use of AFP, HCG and LDH in determining prognosis in testicular germ cell tumors Histologically, germ cell tumors (GCT) can be classified as either seminoma or non-seminomatous, depending on the origin of their primordial germ cells31. These relatively rare tumors are most commonly found in the testis and ovary. The best validated prognostic markers for GCT of the testis are serum alpha-fetoprotein (AFP), human gonadotropic hormone (HCG) and lactate dehydrogenase (LDH)31. Elevated concentrations of serum AFP are found in 40–60% of patients with metastatic non-seminomatous germ cell tumors (NSGCT) containing embryonal carcinoma or yolk sac components but are not detected in those with pure seminoma. Serum HCG concentrations are increased in 40–60% of patients with non-seminomatous tumors and in 15–20% of patients with metastatic seminoma31. Elevated LDH activity is found in approximately 60% of subjects with NSGCT and in approximately 80% of those with seminomas31–33. AFP, HCG and LDH are widely used and indeed are mandatory for determining prognosis in patients with metastatic NSGCT31–33. Indeed, pre-therapy concentrations of AFP, HCG and LDH in patients with testicular NSGCT have been included in the Union Internationale Contre le Cancer (UICC) staging system for many years34–36. Consistent with this inclusion, measurement of these three markers for staging patients with advanced NSGCT is recommended by multiple expert panels including the National Academy of Clinical Biochemistry (USA)37, the American Society of Clinical Oncology (ASCO)38 and the European Society of Medical Oncology (ESMO)39. In contrast to non-seminoma tumors, LDH is the only validated marker for assessing prognosis in patients with pure seminoma32,33. As serum AFP levels are never increased in patients with a pure seminoma, it cannot be used for determining prognosis in patients with this form of germ cell cancer. Although serum HCG can be increased in some patients with seminoma, it has not been shown to be a reliable prognostic marker for this malignancy. Use of uPA and PAI-1 in breast cancer in determining prognosis The best-validated prognostic markers for breast cancer are tumor tissue levels of the serine protease uPA and its endogenous inhibitor, plasminogen activator inhibitor 1 (PAI-1)40,41. Multiple single center retrospective studies, a large pooled analysis and a prospective randomized trial have all confirmed that both uPA and PAI-1 proteins, as measured by enzyme-linked imunosorbent assay (ELISA), are potent and independent prognostic markers in breast cancer, including in the subgroup with lymph node-negative disease42–44. Following publication of multiple single center studies, all of which showed a prognostic value for uPA and PAI-1 in breast cancer, a pooled analysis of results from 18 independent studies from several European countries was performed43. In total, more than 8,000 patients with individualized (raw) data were included in the analysis. In order to minimize a possible impact of positive bias due to the more likely


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publication of positive rather than negative findings, results from both unpublished (n ¼ 7) and unpublished (n ¼ 11) trials were analyzed. Following a median follow-up of 79 months, both uPA and PAI-1 were found to be independent prognostic factors for both disease-free and overall survival. Although less potent than lymph node status, both uPA and PAI-1 were stronger predictors of outcome than tumor size, tumor grade, hormone receptor status or patient age. In the node-negative patients, uPA and PAI-1 were the strongest predictors of both diseasefree interval and overall survival. Importantly, both uPA and PAI-1 were also prognostic in the subgroup of node-negative patients who did not receive systemic adjuvant therapy43, indicating that uPA and PAI-1 were pure prognostic markers. In addition to the above-pooled analysis, the prognostic impact of uPA/PAI-1 has been validated in a second level 1 evidence study, i.e. in a multicenter prospective randomized investigation42. In this trial carried out in Germany, almost 600 newly diagnosed axillary node-negative breast cancer patients were randomized as follows: women with low levels of uPA and PAI-1 were not given systemic adjuvant chemotherapy but were subjected to regular surveillance, while patients with high levels of uPA and/or PAI-1 were randomized to receive adjuvant cyclophosphamide-methotrexate-5-fluorouracil (CMF) or to be observed. CMF was the therapy used in this trial as it was the standard form of adjuvant chemotherapy for breast cancer at the time this study commenced. Following an interim analysis after 32 months of followup, patients with low concentrations of both proteins had an estimated 3-year recurrence rate of 6.7%, whereas those with high concentrations of uPA and/or PAI-1 had a recurrence rate of 14.7% (p ¼ 0.006)42. These early results were recently confirmed after a 10-year follow-up period44. With this longterm follow-up, patients with low uPA and PAI-1 concentrations displayed a recurrence rate of 12.9% compared to 23.0% in those with high levels of both markers (p ¼ 0.011)44. Importantly, uPA and PAI-1 were prognostic in patients with grade 2 tumors, a highly heterogeneous subgroup of breast cancer patients with respect to outcome. As well as being prognostic, increased concentrations uPA/PAI-1 were also predictive of benefit from adjuvant chemotherapy (see below)42,44. uPA/PAI-1 are thus the best validated prognostic markers currently available for lymph node-negative breast cancer. Indeed, the main use of uPA and PAI-1 as prognostic markers in breast cancer is likely to be in this subgroup of patients. Lymph node-negative patients with low levels of uPA and PAI-1 have a low probability of developing recurrent disease and thus may be candidates for being able to avoid the side effects and costs of adjuvant chemotherapy37,45,46. On the other hand, lymph node-negative patients with high levels of uPA and/or PAI-1 have a relatively high risk of disease progression. Consequently, these patients should receive adjuvant chemotherapy, especially as patients with increased levels of uPA and PAI-1 derive more benefit from such treatment than those with low levels42,44. Although uPA and PAI-1 are the best validated prognostic markers for breast cancer, they are not widely used in clinical practice. One reason for this limited use is the requirement for


fresh or freshly frozen tissue for their measurement by ELISA. Recently, however, uPA and PAI-1 levels as determined by immunohistochemistry on formalin-fixed paraffin-embedded (FFPE) tissue were found to correlate significantly with a validated ELISA47. It remains to be shown whether immunohistochemically determined uPA and PAI-1 levels predict patient outcome as accurately as values measured with ELISA. A second reason for the limited use of uPA and PAI-1 in determining prognosis is that the original assays used for their detection required relatively large amount of tumor tissue, thus precluding their measurement on small tumors. This again, may be less of a problem in the future, as a recent report found that uPA and PAI-1 could be reliably measured in core needle biopsies48. Use of gene expression profiling for determining prognosis in breast cancer In recent years, several gene expression profiles or multigene signatures have been proposed for determining prognosis, especially in breast cancer. One of the most widely investigated is the Oncotype Dx test, which measures the expression of 21 genes in breast tumor tissue (16 cancerassociated and 5 control genes) at the mRNA level49. The cancer-associated genes include ER, PR, BCl2, SCUBE2, Ki67, STK15, BIRC5, CCNB1, MYBL2, HER2, GRB7, MMP11, CTSL2, GSTM1, CD68 and BACG1. Based on the expression levels of these genes, a recurrence score (RS) is calculated that predicts the risk of distant disease recurrence at 10 years for lymph node-negative, estrogen receptor (ER)-positive breast cancer patients receiving adjuvant tamoxifen. Based on the RS which extends continuously from 0 to 100, newly diagnosed patients with invasive breast cancer can be divided into three groups: low risk of recurrence (RS 518), intermediate risk of recurrence (RS 18–31) and high risk of recurrence (RS 431)49. Importantly, the prognostic impact of the Oncotype Dx RS was found to be independent of the standard clinicopathological factors such as patient age, lymph node status, tumor grade and tumor size. Although originally developed for lymph node-negative ER-positive patients receiving adjuvant tamoxifen, more recent findings suggested that the Oncotype Dx RS is also prognostic in ER-positive patients undergoing treatment with aromatase inhibitors50. Furthermore, as well as being prognostic in ER-positive lymph node-negative patients, Oncotype Dx was also shown to predict outcome in ER-positive patients with 1–3 positive axillary nodes receiving cyclophosphamide-doxorubicin-5-fluorouracil51. Currently, performance of Oncotype Dx is recommended by several expert panels, especially for predicting the risk of disease recurrence in ER-positive lymph node-negative patients receiving tamoxifen and for identifying such patients who might benefit from adjuvant chemotherapy37,45,46,52. As well as the Oncotype Dx test, several other gene expression profiles have been reported for breast cancer (Table 2)53–56. All these appear to provide independent prognostic information in patients with breast cancer, especially in the ER-positive subgroup. Although the number of


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Table 2. Some multigene/multiprotein profiles which have been shown to predict outcome and/or response to therapy in patients with breast cancer. Reviewed in53–56. No. of genes/ proteins


Test uPA/PAI1 Oncotype Dx MammaPrint Rotterdam MapQuant Theros Index PAM50 Mammostrat IHC4 score Endopredict

2 21 70 76 97 7 50 5 4 11

Tissue required

Molecule measured

Fresh/frozen FFPE Fresh/frozen Fresh/frozen Fresh/frozen FFPE FFPE FFPE FFPE FFPE

Protein mRNA mRNA mRNA mRNA mRNA mRNA Protein Protein mRNA

Table 3. Markers shown to have prognostic value that are not used routinely in the clinic. Marker

Malignancy

CA 15-3 Ki-67 CEA CA 125 S-100 CYFRA 21-1

Breast Breast CRC Ovarian Melanoma Lung

Ref. 67 68 69 70 71

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Role of therapy predictive markers in guiding treatment decisions Although prognostic markers are necessary for precision treatment, predictive markers are more important as they dictate the type of therapy administered. Predictive markers are critical in treatment decision planning as cancers of the same histological type vary widely in their response to a specific therapy. Indeed, for most types of cancer, only a minority of patients benefit from a particular anticancer agent. Being able to prospectively identify those patients likely to respond can both save patients from unnecessary side effects and allow them to receive therapy that is more likely to be beneficial1,2. Furthermore, having accurate predictive markers should also result in considerable cost savings as drugs would be used only in patients likely to derive benefit. Cost savings are especially important when the new biological therapies are being considered for administration, as many of these agents are relatively expensive and have efficacy in only a minority of patients with a specific malignancy. Thus, the measurement of predictive markers has become both a clinical and an economic necessity for the wide use of the new molecularly targeted treatments.

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genes and the identity of the genes differ in the various signatures, based on available information, they all appear to provide similar prognostic information56. Although not as extensively investigated as in breast cancer, prognostic gene signatures have been reported for other specific cancers, especially for CRC (colorectal cancer)57–59, NSCLC (nonsmall cell lung cancer)60, prostate cancer61 and lymphoma62. Use of MSI in determining prognosis in colorectal cancer Microsatellites (MS) are short stretches of DNA in which nucleotide sequences are repeated at multiple locations throughout the genome. Microsatellite instability (MSI) occurs when germline MS alleles gains or loses a repeat unit. These alterations result from the absence of mismatch repair (MMR), i.e. dysfunction in enzymes that repair errors occurring during DNA replication. Several studies including prospective randomized trials as well as a pooled analysis have all shown that the presence of MSI is associated with a favorable outcome, especially in patients with stages II and III CRC63–66. MSI may thus be combined with established prognostic factors for identifying stage II CRC patients who may not need adjuvant chemotherapy. Other prognostic markers Several other prognostic markers have been proposed for different cancers (Table 3). Although some of these markers are extensively used in postoperative surveillance and monitoring therapy, they are not widely used for determining prognosis. The main reason for their limited use in this situation relates to lack of data showing that their determination can alter patient management.

Use of estrogen receptor for predicting benefit from endocrine therapy in breast cancer Hormone or endocrine therapy for breast cancer involves blocking or preventing ER from mediating its growth promoting effects on breast tumor cells. Currently, multiple approaches are available for blocking estrogen or ER action in breast cancer (Table 4). Knowledge of the ER status is necessary to predict response to all the forms of hormone therapy listed in Table 4. The ER was also the first therapy predictive marker in oncology, having been introduced into clinical practice in the early 1970s73. ER was thus one of the first markers used in personalizing treatment for patients with any type of cancer. Although ER was originally measured for selecting for response to endocrine ablation (e.g. oophorectomy) in patients with advanced breast cancer73, its main application at present is in identifying patients with early breast cancer for treatment with anti-estrogen therapy such as an aromatase inhibitor (anastrozole, letrozole or exemestane) or tamoxifen. Until relatively recently, tamoxifen was the standard form of hormone therapy for both pre- and postmenopausal patients with ER-positive breast cancer. However, in recent years, tamoxifen has been largely replaced by aromatase inhibitors, at least for first-line endocrine therapy in postmenopausal women. This is because several clinical trials have shown that third generation aromatase inhibitors provide significantly superior efficacy and tolerability vis-a`-vis tamoxifen for postmenopausal ER-positive patients74–76. The superior efficacy applies whether the aromatase inhibitors are used as initial monotherapy or after 2–3 years of treatment with tamoxifen. Recently, however, a 10-year course of adjuvant tamoxifen was shown to be superior to its administration for 5 years77. Indeed, it appears that 10 years of treatment of ER-positive women with adjuvant tamoxifen can reduce breast cancer mortality by approximately 50% during the second decade after initial diagnosis77.

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Table 4. Different forms of hormone therapy for the treatment of breast cancer. Type of agent

Mode of action

Example

SERM Aromatase inhibitor LH-RH agonist ER antagonist

Blocks action of ER Inhibit estrogen synthesis Decrease estrogen synthesis in ovaries Degrades ER

Tamoxifen, toremifene Anastrozole, letrozole, exemestane Leuprolide, goserelin, buserelin Fulvestrant


SERM, selective estrogen receptor modulator; LH-RH, luteinizing hormone releasing hormone.

Although both tamoxifen and aromatase inhibitors are reasonable well tolerated, the use of the latter is associated with fewer cases of endometrial cancer and thromboembolic events than tamoxifen74–76. Tamoxifen, however, causes less arthralgia and fractures than aromatase inhibitors. Furthermore, tamoxifen is the hormone therapy of choice for ER-positive premenopausal patients, as aromatase inhibitors are unable to block production of estrogens in the ovary. While the negative predictive value of ER is high, i.e. ER-negative patients rarely if ever derive benefit from hormone therapy, its positive predictive value is less accurate78. Thus, in patients with advanced breast cancer, only about 50% of ER-positive patients were found to undergo objective response following treatment with hormone therapy71,72, and almost all these ultimately developed resistance. Similarly, in patients with early breast cancer, while adjuvant hormone therapy significantly reduced the risk of recurrence and death in ER-positive patients, approximately 30% relapsed by 15 years79. Clearly, in order to increase the predictive accuracy for identifying hormone-sensitive breast cancer, it will be necessary to enhance the positive predictive value (PPV) of ER. The only marker currently recommended for improving the accuracy of ER for predicting benefit from endocrine therapy is progesterone receptor (PR)37,45,46,78. Although the presence of ER is associated with response to hormone therapy, it was shown in some studies to predict reduced benefit from chemotherapy, especially in the adjuvant and neoadjuvant settings80–83. This relative lack of benefit in ER-positive patients may relate to the lower proliferation rates in ER-positive as compared to ER-negative tumors. ER status, however, should not be used at present for selecting patients with breast cancer who should or should not receive chemotherapy. Because of its proven clinical value for identifying hormone-sensitive tumors, measurement of ER on all newly diagnosed invasive breast cancer patients is now mandatory37,84–87. According to the ASCO guidelines on steroid hormone receptor measurement, ER should be determined on all cases of newly diagnosed invasive breast cancer87. For patients with ductal carcinoma in situ, measurement of ER was not formally recommended but the panel stated that the patient and her surgeon could decide as to whether or not to have the test performed. The method of choice for determining ER levels in breast cancer is immunohistochemistry with a validated antibody87. Use of markers for predicting benefit from chemotherapy in diverse cancer types Although treatment with endocrine therapy is largely confined to patients with breast and prostate cancer,

chemotherapy is used in almost every type of malignancy. Unfortunately, there are no validated markers currently available for identifying patients likely to benefit from specific forms of chemotherapy. Despite this, some markers that were initially developed for aiding prognosis may be used in selecting patients who are likely to benefit from receiving chemotherapy, although they do not identify the most appropriate form of chemotherapy. Perhaps, the best example of a prognostic marker being used for predicting response from chemotherapy is Oncotype DX, which has been shown to predict benefit from chemotherapy in retrospective analysis of at least two randomized trials in patients with early breast cancer51,81. In one of these trials (NSABP B-20), ER-positive lymph node-negative patients were randomized to receive tamoxifen alone or tamoxifen plus chemotherapy (methotrexate and fluorouracil with or without cyclophosphamide)51. Although low-risk patients defined by Oncotype DX RS obtained relatively little benefit from the chemotherapy, high-risk patients derived significantly benefit from the cytotoxic drug regime. It was unclear if the patients with an intermediate RS benefited. In a second retrospective analysis (SWOG-8814), ER-positive lymph node-positive patients (1–3 nodes positive) were randomized to tamoxifen or chemotherapy (cyclophosphamide, doxorubicin and fluorouracil) followed by tamoxifen81. Again, patients with a high Oncotype DX RS score but not those with a low score were found to derive benefit from the chemotherapy. Attempts to further validate the predictive potential of Oncotype DX are currently ongoing in two large prospective clinical trials, the TAILORx and RxPONDER trials88. As with the Oncotype DX RS, high levels of uPA/PAI-1 protein have also been reported to predict an enhanced response to adjuvant chemotherapy in patients with breast cancer. In the German multicenter prospective randomized trial referred to above42, administration of adjuvant chemotherapy to patients with high concentrations of uPA and/or PAI-1 tended to reduce the relative risk of recurrence by approximately 44% (relative risk ¼ 0.56; p40.05). However, if patients who failed to comply with the study protocol were excluded from the analysis, the benefit of the chemotherapy was found to be significance (p ¼ 0.016, relative risk ¼ 0.27). As with the prognostic impact of uPA/PAI-1, these predictive findings were confirmed in the 10-year follow-up analysis of this trial44. Consistent with the above reports, Harbeck et al.89 reported that while uPA/PAI-1 were associated with outcome in breast cancer patients who did not receive systemic adjuvant therapy, the prognostic impact of the markers was lost in those receiving adjuvant chemotherapy. Again, this study suggested benefit from adjuvant treatment in patients with


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Table 5. Candidate chemotherapy predictive markers. Marker MSI MGMT TOPO2A ERCC1 RRM1 Tau

Drug 5-Fluorouracil Alkylating agents Anthracyclines Platinum agents Platinum agents Taxanes

Cancer

Ref.

Colorectal Glioma Breast NSCLC NSCLC Breast

63–65 91 92 93 93 94,95


MGMT, methyl guanine methyl transferase; ERCC1, excision repair cross-complementing 1; RRM1, ribonucleotide reductase M1.

high uPA/PAI-1 concentrations. Further evidence of a chemopredictive potential for uPA/PAI-1 was found in a large two-center study (n ¼ 3,424) that showed that breast cancer patients with high levels of these proteins derived more benefit from adjuvant chemotherapy than those with low levels90. Currently, several other markers are undergoing evaluation for predicting response to cytotoxic agents. The most promising of these are listed in Table 5. Use of HER2 for predicting benefit from anti-HER2 therapy in breast cancer Although originally, HER2 was proposed as a prognostic marker for breast cancer, its current main use is as a marker for predicting benefit from anti-HER2 therapies96. In breast cancer, the HER2 gene can be activated by a variety of mechanisms including amplification, overexpression, truncation and mutation. Amplification or overexpression occurs in about only 20% of invasive breast cancers. Patients with HER2 gene amplification or overexpression are referred to as HER2-positive, which has been defined as tumors displaying either uniform intense membrane immunostaining in430% of invasive cancer cells or amplified HER2 gene (ratio of HER2 to centromere 17 enumeration probe of42.2 or average HER2 gene copy number 46 signals/nucleus)97. Patients with HER2-positive breast cancer are candidates for treatment with trastuzumab (the humanized monoclonal antibody, Herceptin) in the neoadjuvant, adjuvant and advanced disease settings. Trastuzumab was the first antiHER2 therapy approved for clinical use in breast cancer. This antibody binds to the external domain of HER2 (domain 4) and inhibits downstream signaling via multiple mechanisms including disruption of ligand-independent HER2-HER3 dimerization, blockage of MAPK (mitogen-activated protein kinase) and PI3K (phosphatidylinositol 3-kinase) signaling, and activation of antibody-dependent cellular cytotoxicity (ADCC)98. ADCC involves the lysis of trastuzumab-bound breast tumor cells by effector immune cells such as natural killer cells, macrophages and monocytes. In early studies, trastuzumab monotherapy induced response in approximately 15–30% of patients with advanced HER2-positive breast cancer99–101. However, when combined with chemotherapy, administration of trastuzumab resulted in response rates of 30–85%, median times to progression periods of 5–18 months and overall survival periods of 11–39 months102. In newly diagnosed breast cancer patients, administration of adjuvant trastuzumab in combination with

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chemotherapy when compared with chemotherapy alone has been shown to significantly extend disease-free survival and overall survival as well as decrease locoregional recurrence rates and distant recurrences103. In this setting, combined trastuzumab and chemotherapy has been shown to reduce recurrence rates by approximately 50% and decrease mortality by about 30%. In the neoadjuvant or primary treatment setting, single phase 2 studies showed that trastuzumab plus chemotherapy induced pathological complete response in 12–76% of HER2positive patients104. In randomized phase 2 and 3 trials, treatment with combined trastuzumab and chemotherapy resulted in complete pathological response in 26–65% of HER2-positive patients compared to a 19–27% response rate with chemotherapy alone104. While trastuzumab was the first approved anti-HER2 therapy for patients with breast cancer, it was soon followed by lapatinib, a low molecular weight compound that blocks the tyrosine kinase activity of both HER2 and EGFR (epidermal growth factor receptor). In contrast to trastuzumab, lapatinib can be administered orally, has less cardiovascular toxicity and may be able to penetrate the blood–brain barrier105,106. The use of lapatinib in combination with the cytotoxic drug, capecitabine, is approved for treating HER2-positive patients whose disease has progressed while receiving chemotherapy with taxane (an anthracycline) and trastuzumab107. Lapatinib, in combination with the aromatase inhibitor, letrozole, is approved for the treatment of ER and HER2-positive metastatic breast cancers108. Response to lapatinib, like that of trastuzumab, also appears to require HER2 gene amplification/overexpression109,110. Since trastuzumab and lapatinib have different modes of action, a number of trials have investigated combined treatment with both agents in HER2-positive breast cancer patients. In one of these (GesparQuinto trial), trastuzumab was found to be significantly more effective alone or when combined with lapatinib than lapatinib alone in the neoadjuvant treatment of breast cancer111. In another neoadjuvant trial (NeoALTTO), although trastuzumab was not statistically more effective than lapatinib, combined treatment was superior to lapatinib alone112. In addition to trastuzumab and lapatinib, two others anti-HER2 therapies have shown efficacy in advanced HER2-positive breast cancer: pertuzumab (Perjeta)113 and ado-trastuzumab emtansine (T-DM1, Kadcycla)114. Pertuzumab is a humanized monoclonal antibody that binds to domain II of the extracellular region of HER2 and prevents dimerization with HER3. Early preclinical findings showed that combined trastuzumab and pertuzumab treatment produced synergistic antitumor activity in human xenograft models of HER2-positive breast cancers tumors115. This finding led to clinical trials evaluating the combination of trastuzumab and pertuzumab in patients with HER2-positive breast cancer. In the CLinical Evaluation Of Pertuzumab and TRAstuzumab (CLEOPATRA) study, 808 women with HER2-positive advanced metastatic breast cancer were randomized to receive trastuzumab, pertuzumab and docetaxel, or trastuzumab and docetaxel113. Median progression-free survival was 18.5 months in the group given


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the triple combination of therapy versus 12.4 months in those receiving trastuzumab and docetaxel (HR, 0.62; 95% CI 0.51–0.75; p50.001 [HR, hazard ratio; CI, confidence interval]). Based on these results, pertuzumab in combination with trastuzumab and docetaxel was recently approved by the US FDA for the treatment of HER2-positive metastatic breast cancer patients who had not previously received anti-HER2 or chemotherapy for metastatic disease. The most recent anti-HER2 agent to be cleared by the US Food and Drug Administration for clinical use is adotrastuzumab emtansine (T-DM1). T-DM1 is an immunoconjugate of trastuzumab linked via a non-reducible thioether bond to the microtubule-targeting agent DM1 (a derivative of maytansine). T-DM1was shown to be superior to lapatinib plus chemotherapy in enhancing progression-free survival in patients who had relapsed while being treated with trastuzumab and chemotherapy114. As well as exhibiting superior efficacy, the immunoconjugate was also less toxic than the lapatinib–chemotherapy combination114. Similarly, treatment with T-DM1 was shown in a phase II study to be superior to combined administration of trastuzumab and docetaxel in extending progression-free survival in patients with advanced HER-2-positive breast cancer116. The availability of multiple drugs to target HER2-positive breast cancer may, in the near future, eliminate or at least reduce the requirement for chemotherapy in this subgroup of breast cancer patients. Anti-HER2 therapies currently undergoing clinical trials include the pan-HER inhibitors, afatinib, dacomitinib and neratinib. These agents inhibit the tyrosine kinase activity of EGFR and HER4 as well as that of HER2. Although not yet rigorously tested, it is likely that response to these newer antiHER2 agents will also require HER2 gene amplification/ overexpression. Possible exceptions, however, are patients with a specific mutation in HER2. Indeed, recent preclinical findings have shown that breast cancers cells lacking HER2 gene amplification/overexpression but possessing activating mutations in the HER2 gene were sensitive to certain antiHER2 therapies, especially neratinib117,118. Activating HER2 mutations, however, appear to be rare in breast cancer, occurring in only 1–2% of cases. Use of KRAS mutational status in predicting response to anti-EGFR antibodies in colorectal cancer The KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) protein plays a pivotal role in downstream signaling from multiple membrane receptors, including EGFR119. Overall, mutations in KRAS are found in approximately 40% of primary CRC cases and appear to be an early event in their formation. Most of these mutations result in growthfactor-independent and persistent activation of downstream signaling, especially in the MAPK and PI3K pathways. In one of the largest published studies, 78% of the KRAS mutations were detected in codon 12 (GGT), and 22%, in codon 13 (GGC). For codon 12, the most frequent mutations were G12D, G12V, G12C and G12A. In codon 13, the most frequent mutation identified was G13D120. Other mutations


that are infrequently found in KRAS involve codons 61, 63 and 146. Although KRAS is not the direct target for any clinically approved cancer treatment, its gene mutational status is predictive of response to two anti-EGFR antibodies, cetuximab and panitumumab, in patients with advanced CRC. Cetuximab and panitumumab are both monoclonal antibodies that bind to the extracellular domain of EGFR, thereby preventing the binding of the activated endogenous ligands. As a result, EGFR undergoes internalization and degradation119. In addition, cetuximab but not panitumumab can induce antibody-dependent cellular toxicity. Although both cetuximab and panitumumab target EGFR, expression of EGFR protein in CRC, as assayed by conventional immunohistochemistry, has not been shown to correlate with response121. While EGFR protein levels as detected by immunohistochemistry are unrelated to response from anti-EGFR antibodies in CRC, specific activating mutations in the KRAS gene that result in constitutive EGFR signaling are associated with lack of benefit from cetuximab and panitumumab122,123. Thus, multiple retrospective analyses of prospectively performed phase II and III trials have shown that patients with certain KRAS mutations, especially in codon 12, do not benefit from either cetuximab or panitumumab. In contrast, administration of these therapeutic antibodies to patients with wild-type KRAS significantly improves response rates and progression-free survival122,123. Although codon 12 mutations are clearly associated with lack of benefit from anti-EGFR antibodies, the predictive role of the G13D mutation is less clear. Indeed, mutations in codon 13, unlike those in codon 12, appear to be associated with benefit from cetuximab124. Consistent with this observation is a recent computational analysis that concluded that the KRAS G13D mutation conferred the same structural dynamic state as that found with the wild-type form125. Because of the large number of reports, especially with respect to codon 12, measurement of the mutational status of KRAS is now standard practice prior to administering cetuximab or panitumumab to patients with advanced CRC126–128. Thus, according to the NCCN guideline, ‘‘patients with wild-type KRAS who experience progression on therapies not containing an EGFR inhibitor, cetuximab or panitumumab plus irinotecan, cetuximab and panitmumab plus FOLFIRI (folinic acid, fluorouracil and irinotecan), or single agent cetuximab or panitumumab is recommended’’127. Further research is necessary to clarify the predictive value of the KRAS G13D mutation. Although several different assays are available for measuring the mutational status of KRAS128, only one has been approved by the US FDA, i.e. the therascreenÕ RGQ PCR kit. This test detects the presence of seven mutations in codons 12 and 13 of the KRAS gene. These mutations include G12A, G12D, G12R, G12C, G12S, G12V and G13D. Use of EGFR mutational status for predicting response to anti-EGFR kinases in non-small-cell lung cancer As in advanced CRC, anti-EGFR therapy is also used to treat patients with NSCLC. However, in contrast to CRC where


DOI: 10.3109/10408363.2013.865700

targeting with monoclonal antibodies is used, inhibiting EGFR in NSCLC is usually achieved with tyrosine kinase inhibitors (TKIs), especially with the quinazoline derivatives, gefitinib and erlotinib129–131. A further difference is that while cetuximab and panitumumab both bind to the extracellular domain of wild-type EGFR, gefitinib and erlotinib bind to an intracellular domain, thereby selectively inhibiting mutant EGFR TKI activity. Overall, specific activating mutations in EGFR are detected in approximately 10–20% of patients with advanced NSCLC. However, these mutations may be found in approximately 50% of cases with adenocarcinoma-type histology, in East Asian patients, and in subjects who have never smoked tobacco129–131. Although in excess of 200 EGFR mutations have been reported in NSCLC, most are either small in-frame deletions in exon 20 or a specific point mutation in exon 21, i.e. the L858R mutation130. The majority of these are known as activating or sensitizing mutations, as they result in ligandinduced receptor activation. This is turn give rise to enhanced downstream signaling, increased cell proliferation, increased invasion and decreased cell death132. Early trials with anti-EGFR TKIs in unselected patients with advanced NSCLC yielded disease response in only approximately 10% of the patients treated. More recently, however, several randomized phase 3 studies have demonstrated that administration of either gefitinib or erlotinib, when compared to chemotherapy, resulted in improved response rates, longer progression free survival periods, less toxicity and better quality of life in patients with specific activating mutations in EGFR130,132. On the other hand, patients without these activating mutations rarely benefited from the TKIs. Because of its proven clinical utility, testing for activating mutations in the EGFR gene is thus frequently performed prior to administering gefitinib or erlotinib to patients with advanced NSCLC132–135. The Cobas EGFR Mutation Test, an assay for measuring mutations in EGFR in selecting for response to erlotinib, was recently approved by the US FDA. This is a multiplex PCR assay that detects 41 mutations in exons 18, 19, 20 and 21 of the EGFR gene. As with KRAS mutations in CRC, not all EGFR mutations predict benefit from anti-EGFR therapy. Thus, the presence of the T790M mutations in EGFR has been identified as one of the most common mechanisms for acquired resistance to these TKIs131,132. The T790M mutation appears to mediate resistance by preventing gefitinib and erlotinib from interacting with the TKI active site. Although gefitinib and erlotinib are unable to inhibit the T790M mutant form of EGFR, a new generation of irreversible of TKIs (e.g. erlotinib, afatinib and dacomitinib) appears to be effective in this situation. Use of BRAF mutational status in predicting response to anti-BRAF kinases in melanoma The best-identified driver gene in melanoma is BRAF (v-raf murine sarcoma viral oncogene homolog B1), which codes for a protein acting downstream of EGFR and KRAS136. BRAF is a member of the RAF family of kinases and encodes a protein with serine/threonine kinase activity. BRAF mutations are


39

present in approximately 50% of skin melanomas not due to chronic sun exposure, but in less 30% of cases caused by chronic sun exposure137. Approximately 80% of these mutations are V600E136,137. Less frequently found mutations in BRAF include V600K and V600D137. These mutations result in constitutive activation of downstream MAPK signaling, which in turn drives the growth and progression of skin melanomas. A number of inhibitors are now available that selectively target the BRAF-mutated protein. Of these, the most widely investigated are vemurafenib and dabrafenib. Early preclinical studies showed that vemurafenib inhibited proliferation of melanoma cell lines possessing the BRAF V600 mutations but had little effects on cells harboring wild-type BRAF138. Subsequent clinical trials showed that both these agents exhibited strong efficacy in patients with BRAF mutationpositive advanced melanomas139–143. In 2011, the US FDA approved vemurafenib for the treatment of patients with unresectable or metastatic melanoma containing BRAF V600 mutations. Simultaneously, a predictive biomarker assay, the Cobas 4800 BRAF V600 mutation test, was cleared by the US FDA for the identification of patients with metastatic or unresectable melanoma likely to benefit from vemurafenib. Although this assay has high sensitivity (4 99%) and specificity (88%) for the detection of V600E mutations, it appears to be less sensitive for other V600 mutations137 that are potentially predictive for anti-BRAF therapy. In 2013, dabrafenib was approved for clinical use by the US FDA for the treatment of advanced melanomas possessing the BRAF V600E mutations. Simultaneously, a companion diagnostic assay known as the THxID test was approved for use with dabrafenib. Use of predictive markers for other targeted therapies Other predictive markers for targeted therapies in cancer are listed in Table 6.

Barriers to implementing precision therapy in cancer Validation of prognostic and predictive markers Although large numbers of putative prognostic and predictive markers have been described in the literature, it is clear from this article that relatively few have entered routine clinical use. As mentioned above, the main reason for this discrepancy is lack of validation. In order to be used in the clinical setting, a new marker must undergo analytical (technical) validation and clinical validation, and, most importantly, be shown to have clinical utility1,15,144. Analytical validation aims to establish that the test detects what it claims to detect and does so in an accurate and reproducible (both within and between assays) manner. Clinical validation confirms that the results of the assay separate patient cohorts into different categories that will require different treatments or have different outcomes. For clinical application, the marker must also be shown to have clinical utility15. Clinical utility means that measurement of the marker results in a clinical decision that has a positive impact on patient outcome relative to the current standard of

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Table 6. Predictive biomarkers currently available for selecting treatment in patients with different cancers. Taken from Ref. 1 with permission. Therapy

Cancer

Biomarker

Anti-estrogen (tamoxifen, aromatase inhibitors) Anti-HER2 (trastuzumab, lapatinib, pertuzumab, TDM-1) Anti-EGFR (cetuximab, panitumumab) Anti-EGFR (gefitinib, erlotinib) Anti-BRAF (vemurafenib, dabrafenib) Anti-ALK (crizitonib) Anti-HER2 (trastuzumab) Imatinib PARP inhibitors (olaparib)a

Breast Breast CRC NSCLC Melanoma NSCLC Gastric GIST Breast/ovarian

ER, PR HER2 KRAS EGFR BRAF EML4-ALK HER2 KIT BRCA1/2


a

Undergoing clinical trials in patients with advanced BRCA1/2-associated breast and ovarian cancers.

care. Outcome endpoints include increased overall survival, increased disease-free survival, enhanced quality of life or reduced health care costs. As mentioned above, clinical utility should be established using a prospective clinical trial in which the marker is the primary aim of the trial; from retrospective analysis of archival specimens that were collected prospectively from subjects participating in at least two studies; or from a meta/pooled analysis of retrospective/prospective trials, i.e. in a level 1 evidence study. Level 1 evidence studies, however, require considerable time and expense to complete, and thus limit the number of markers available for clinical use. Tumor heterogeneity It is now well established that most if not all cancers exhibit intratumor molecular heterogeneity. This means that cancers are composed of multiple sub-populations of cells or molecular clones with diverse genotypes and phenotypes145. Because of their genetic differences, these different clones may vary with respect to their ability to metastasize or respond to specific therapies. Although morphological heterogeneity in tumors has been known for decades, it is only recently that we have begun to investigate intratumor heterogeneity at a detailed molecular level. A striking example of intratumor molecular heterogeneity was recently shown in clear cell renal cancers following a detailed molecular analysis146. This study showed that approximately two-thirds of all the detected somatic mutations were not present in every tumor region investigated. Furthermore, different gene expression profiles as well as different allelic-imbalance patterns were found in the different regions. Similarly, intratumor molecular heterogeneity has been demonstrated in breast, prostate, pancreatic cancers as well as in leukemias and gliomas (for review, see145). The implication of the above findings is that analysis of a single biopsy may not be informative with respect to the molecular diversity of a tumor, especially in relationship to the markers expressed in that malignancy. Clearly, in order to get a comprehensive picture of the tumor diversity, multiple regions of a tumor may have to be sampled. Although this should be possible with surgically removed specimens, it will be more difficult when only biopsy samples are available. For example, obtaining multiple biopsies from patients may not always be practical and indeed could raise ethical issues, especially if it is part of a research project. Possible ways

of overcoming these problems include carrying out molecular analysis on circulating tumor cells or on plasma. Although modern methods of analysis have shown molecular heterogeneity in many tumor types, this does not appear to be a major clinical problem with two of the most frequently measured predictive markers, i.e. ER and HER2 in breast cancer. Thus, the concordance found for ER expression in core needle biopsies and surgically resected specimens was approximately 94%, while the concordance for HER2 in the two specimen types was about 96%147. In contrast to breast cancer however, HER2 expression in gastric cancer can be heterogeneous, necessitating analysis of multiple tumor areas148. Primary or metastatic tumor for marker determination? The traditional clinical approach with predictive markers was to measure these analytes on the primary tumor and use this information in informing treatment decision making if and when subsequently-formed metastases had to undergo treatment. This approach assumed that the marker status of the metastatic lesion was similar to that of the primary tumor. While in the majority of cases this appears to be true, concordance in marker status does not always occur between primary and metastatic lesions. The relationship between marker status of primary and metastatic cancers has been most thoroughly investigated for ER and HER2 in breast cancer, EGFR mutational status in lung cancer and KRAS mutational status in CRC. For both ER and HER2 in breast cancer, discordance between the primary and secondary site has been found in 15–20% of patients149,150. In one report, the discordance between EGFR mutational status in primary and corresponding metastatic lung lesions was 17%151, while the discordance rate for KRAS mutation status in primary and corresponding metastatic CRC sites was 56%152,153. Clearly, therefore, where feasible, marker determination should be performed on the metastatic site to be targeted with the relevant therapy. Other barriers to implementing precision treatment in cancer Some other potential barriers in using prognostic and predictive markers for precision treatment in cancer are listed in Table 7.


DOI: 10.3109/10408363.2013.865700

Table 7. Barriers in the use of markers for precision treatment of cancer.


Requirement for analytical and clinical validation of marker Requirement for demonstration of clinical utility of marker Obtaining suitable tumor tissue with sufficient number of malignant cells Tumor heterogeneity Cost of marker measurement Turn-around-time for measurement of marker Requirement for appropriate quality assurance schemes Laboratory certification and accreditation Staff training in performance of marker assays and interpretation of results Reimbursement

Conclusion It is clear that, with the increasing availability of validated prognostic and predictive markers, precision treatment is becoming available for an increasing number of patients with malignancy. However, with more and more patients being diagnosed with early tumors, we require more accurate markers for selecting newly diagnosed patients who do not require systemic therapy, in order to prevent overtreatment. We also need new markers for increasing the accuracy of the existing predictive tests, especially for increasing the PPV for antiHER2 therapies in breast cancer and anti-EGFR antibodies in CRC. Finally, we need validated markers to predict benefit from the widely used cytotoxic drugs, anti-angiogenic agents such as bevacizumab, and immunotherapies such as ipilimumab and PD-1 (programmed cell death protein 1) antibodies. For truly molecularly based precision treatment, however, it will be necessary to move beyond ‘‘one drug one marker’’. Hopefully, in the future, exome or whole genome sequencing will accelerate this transition. Indeed, as the cost of DNA sequencing is reduced and our ability to interpret this data improves, tumor and germline DNA assessment may pave the way to precision treatment in cancer. The practice of precision treatment should, however, not depend exclusively on the use of molecular markers. Rather, markers should be combined with, and certainly not replace, the conventional histopathological factors such as tumor size, tumor grade and lymph node status. Perhaps, most important of all, precision treatment should take into consideration the wishes of patients with respect to how and when they should be treated.

Acknowledgements The authors wish to thank Science Foundation Ireland, Strategic Research Cluster Award (08/SRC/B1410) to Molecular Therapeutics for Cancer Ireland (MTCI)/National Cancer Research Centre in Ireland (NCRCI) and the BREAST-PREDICT (CCRC13GAL) program of the Irish Cancer Society for funding this work. The opinions, findings and conclusions or recommendations expressed in this article, however, are those of the authors and do not necessarily reflect the views of the Irish Cancer Society.

Declaration of interest M.J.D. has no conflict of interest to report. JC has received speaker’s fees and research support from GlaxoSmithKline, Roche, Novartis, Sanofi-Aventis and Pfizer.

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Role of NRAS mutations as prognostic and predictive markers in metastatic colorectal cancer.

Molecular Markers with Predictive and Prognostic Relevance in Lung Cancer.

Predictive and prognostic markers in the treatment of metastatic colorectal cancer (mCRC): personalized medicine at work.

Prognostic factors, predictive markers and cancer biology: the triad for successful oral cancer chemoprevention.

[Prognostic and predictive molecular markers for urologic cancers].

Streptozocin-Based Chemotherapy in Patients with Advanced Neuroendocrine Neoplasms--Predictive and Prognostic Markers for Treatment Stratification.

Predictive and prognostic biomarkers in personalized gastrointestinal cancer treatment.

Looking for predictive markers in breast cancer.

Diagnostic, prognostic and predictive relevance of molecular markers in gliomas.

TGF-β1 precursor and CD8 are potential prognostic and predictive markers in operated breast cancer.

Update on prognostic markers for endometrial cancer.

Serum microRNA profiles as prognostic or predictive markers in the multimodality treatment of patients with gastric cancer.

Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer.

Prognostic DNA methylation markers for prostate cancer.

Prognostic, predictive and potential surrogate markers in castration-resistant prostate cancer.

Predictive and prognostic cancer biomarkers revisited.

Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

Predictive and prognostic role of serum neopterin and tryptophan breakdown in prostate cancer.

Diagnostic and Prognostic Markers in Bladder Cancer.

Looking for predictive markers in breast cancer--authors' reply.

The Prognostic and Predictive Role of Epidermal Growth Factor Receptor in Surgical Resected Pancreatic Cancer.

Predictive and prognostic molecular markers for cholangiocarcinoma in Han Chinese population.

Prognostic markers for AIDS.

Prognostic and predictive value of PDL1 expression in breast cancer.