Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges

Clinical implications of genetic variations in the VEGF system in relation to colorectal cancer

Colorectal cancer (CRC) constitutes one of the most common malignancies in the world and, despite advances in diagnostics and treatments, patients still face a poor prognosis and a more individualized treatment approach appears necessary. The VEGF system and angiogenesis are involved in many aspects of tumor biology and the efficacy of chemotherapy, and some targeted therapeutics appear to be related to the function of these processes. There are many reasons why genetic variations are optimal biomarkers and in relation to the VEGF system may prove to be of clinical relevance. This review evaluates the literature on SNPs in relation to the risk of CRC and the possible prognostic and predictive value and argues for the role of these biomarkers in the future treatment of patients with CRC.

Predictive biomarkers in colorectal cancer: usage, validation, and design in clinical trials

As cancer treatment development has shifted its attention to targeted therapies, it is becoming increasingly important to provide tools for selecting the right treatment for an individual patient to achieve optimal clinical benefit. Biomarkers, identified and studied in the process of understanding the nature of the disease at the molecular pathogenesis level, have been increasingly recognized as a critical aspect in more accurate diagnosis, prognosis assessment, and therapeutic targeting. Predictive biomarkers, which can aid treatment decisions, require extensive data for validation. In this article, we discuss the definition, clinical usages, and more extensively the clinical trial designs for the validation of predictive biomarkers. Predictive biomarker validation methods can be broadly grouped into retrospective and prospective designs. Retrospective validation utilizes data from previously conducted prospective randomized controlled trials. Prospective designs include enrichment designs, treatment-by-marker interaction designs, marker-based strategy designs, and adaptive designs. We discuss each design with examples and provide comparisons of the advantages and disadvantages among the different designs. We conclude that the combination of scientific, clinical, statistical, ethical, and practical considerations provides guidance for the choice of the clinical trial design for validation of each proposed predictive biomarker.

[Possibilities and limitations of stratified medicine based on biomarkers and targeted therapies in oncology]

Research over the past two decades has untangled the molecular heterogeneity of cancer at the cellular level. The molecular techniques that have been developed in the past 5 to 10 years are dramatically improving our understanding of the genomic aberrations that underlie the malignant transformation of normal cells. At the same time, however, advances in our understanding of the genetic basis of solid tumours and hematologic malignancies have revealed how complex cancer is, and consequently how much more challenging it is in many of the more common cancers to identify the right drug for the right patient in the adequate dose at the right time. Given the slow pace of translation from genome science to individualised medicine in oncology, this expert review, mainly taking into account recently published perspective articles and reviews, describes the molecular heterogeneity of cancer, the difficulties in developing novel molecularly targeted agents, and the need for developing biomarkers to optimise drug development and clinical use. Distinct types of biomarkers, breakthroughs as well as disappointments in the clinical implementation of biomarkers and targeted therapeutics into clinical practice are discussed by focusing on four targeted anti-cancer drugs. Finally, as clinical biomarker tests that predict response to particular therapies will play an important role in achieving stratified medicine in the near future, this article will conclude by giving some recommendations for effective biomarker evaluation and clinical trial designs for predictive biomarker validation.

Clinical trial design in the age of molecular profiling

The accelerating science of molecular profiling has necessitated a rapid evolution in clinical trial design. Traditional clinical research begins with Phase I studies to characterize dose-limiting toxicities and defines maximally tolerated doses of drugs in small numbers of patients. Traditional Phase II studies test these drugs at the doses discovered during Phase I drug development in small numbers of patients evaluating efficacy and safety. Phase III studies test new therapies to demonstrate improved activity or improved tolerability compared with a standard of care regimen or a placebo. The rapid advances in the understanding of signal transduction, and the identification of new potential diagnostic and therapeutic targets, now require the design and implementation of molecular clinical trials that are very different than traditional Phase I, II, or III trials. The main differentiating factor is the use of a molecular end point to stratify a subset of patients to receive a specific treatment regimen. This chapter focuses on the issues surrounding (a) the definition of clinical end points and the assessment of tumor response; (b) clinical trial design models to define the targeted pathway; and (c) the need for appropriate biomarkers to monitor the response.

Design of clinical trials for biomarker research in oncology

The developmental pathway from discovery to clinical practice for biomarkers and biomarker-directed therapies is complex. While several issues need careful consideration, two critical issues that surround the validation of biomarkers are the choice of clinical trial design (which is based on the strength of the preliminary evidence and marker prevalence) and the biomarker assay related issues surrounding the marker assessment methods such as the reliability and reproducibility of the assay. This review focuses on trial designs for marker validation, both in the setting of early phase trials for initial validation, as well as in the context of larger definitive trials. Designs for biomarker validation are broadly classified as retrospective (i.e., using data from previously well-conducted, randomized, controlled trials) or prospective (enrichment, allcomers or adaptive). We believe that the systematic evaluation and implementation of these design strategies are essential to accelerate the clinical validation of biomarker-guided therapy, thereby taking us a step closer to the goal of personalized medicine.

Toxicity as a biomarker of efficacy of molecular targeted therapies: focus on EGFR and VEGF inhibiting anticancer drugs

In addition to being present in tumor cells, many targets of signal transduction inhibitors are also found in normal tissue. Side effects attributable to the mechanism of action of molecular targeted agents thus represent "on-target" modulation in normal tissues. These mechanism-based toxicities can be pharmacodynamic effects of pathway inhibition and, in tumors depending on the inhibited pathway for proliferation, might be biomarkers of efficacy. The development of rash with tyrosine kinase inhibitors or monoclonal antibodies targeting the epidermal growth factor receptor is associated with superior outcomes in lung, head and neck, colorectal, and pancreatic cancer studies. Correlated with superior efficacy in retrospective analyses of large studies in advanced colorectal, breast, and renal cell carcinoma, arterial hypertension as an adverse event of antiangiogenic agents may also be a marker of effective target inhibition. An association between hypothyroidism and the activity of multitargeted tyrosine kinase inhibitors has been identified in renal cell carcinoma patients. Tumor growth addiction to the specific pathway that is effectively targeted may be the link between a mechanism-based toxicity and efficacy. The biological basis for this correlation can be pharmacological, with higher drug exposure being associated with greater toxicity and antitumor activity, and can also be genetic, because single nucleotide polymorphisms play an important role in drug pharmacokinetic and pharmacodynamic processes. Investigators have proposed that interpatient differences and associated toxicities can be exploited for dose selection and titration, and clinical trials are currently exploring intrapatient "dosing-to-toxicity" strategies. Ultimately, the predictive value of a side effect of molecular targeted therapies requires validation in prospective trials.

Hybridization for human epidermal growth factor receptor 2 testing in gastric carcinoma: a comparison of fluorescence in-situ hybridization with a novel fully automated dual-colour silver in-situ hybridization method

Aims:

Amplification of the human epidermal growth factor receptor 2 (HER2) gene has been reported in gastric carcinoma (GC). Accordingly, trastuzumab plus chemotherapy has recently become the new standard treatment for HER2-positive advanced GCs. The aim was to compare the alleged gold standard for hybridization [fluorescence in-situ hybridization (FISH)] with a novel, fully automated brightfield dual-colour silver-enhanced in-situ hybridization (SISH) method.

Methods and results:

The studies series was comprised of 166 GC samples. Additionally, tumours with discordant results obtained by FISH and SISH were analysed by real-time quantitative polymerase chain reaction (PCR) with the LightMix kit HER-2/neu. Of the samples, 17.5% and 21% were amplified by FISH and SISH, respectively. Heterogeneity was identified in up to 52% of cases. In 96.4% of cases, FISH showed the same results as SISH. All six discordant cases were positive by SISH and negative by FISH. On review of the FISH slides, all contradictory cases were polysomic and were confirmed to be negative for amplification by real-time PCR. Interestingly, all ratios in this latter group were between 2.06 and 2.50, so setting the cut-off for amplification at ≥3 resulted in perfect concordance.

Conclusions:

Dual-colour SISH represents a novel method for the determination of HER2 status in GC.

Validation study of a quantitative multigene reverse transcriptase-polymerase chain reaction assay for assessment of recurrence risk in patients with stage II colon cancer

PURPOSE

We developed quantitative gene expression assays to assess recurrence risk and benefits from chemotherapy in patients with stage II colon cancer.

PATIENTS AND METHODS

We sought validation by using RNA extracted from fixed paraffin-embedded primary colon tumor blocks from 1,436 patients with stage II colon cancer in the QUASAR (Quick and Simple and Reliable) study of adjuvant fluoropyrimidine chemotherapy versus surgery alone. A recurrence score (RS) and a treatment score (TS) were calculated from gene expression levels of 13 cancer-related genes (n = 7 recurrence genes and n = 6 treatment benefit genes) and from five reference genes with prespecified algorithms. Cox proportional hazards regression models and log-rank methods were used to analyze the relationship between the RS and risk of recurrence in patients treated with surgery alone and between TS and benefits of chemotherapy.

RESULTS

Risk of recurrence was significantly associated with RS (hazard ratio [HR] per interquartile range, 1.38; 95% CI, 1.11 to 1.74; P = .004). Recurrence risks at 3 years were 12%, 18%, and 22% for predefined low, intermediate, and high recurrence risk groups, respectively. T stage (HR, 1.94; P < .001) and mismatch repair (MMR) status (HR, 0.31; P < .001) were the strongest histopathologic prognostic factors. The continuous RS was associated with risk of recurrence (P = .006) beyond these and other covariates. There was no trend for increased benefit from chemotherapy at higher TS (P = .95).

CONCLUSION

The continuous 12-gene RS has been validated in a prospective study for assessment of recurrence risk in patients with stage II colon cancer after surgery and provides prognostic value that complements T stage and MMR. The TS was not predictive of chemotherapy benefit.

Drug approval challenges in the age of personalized cancer treatment

Cancer treatment is in evolution from nonspecific cytotoxic drugs that damage both tumor and normal cells to more targeted agents and immunotherapy approaches that target unique molecular features of cancer cells or that modulate the tumor immune response to produce greater effectiveness with less toxicity. The development and use of such approaches in biomarker-defined populations enables a more personalized approach to cancer treatment than previously possible and potentially improves the effectiveness, reduces the toxicity and lowers the cost of cancer care although significant barriers remain to realizing the vision of personalized cancer treatment.

Translating biomarkers to clinical practice

Biomarkers are the measurable characteristics of an individual that may represent risk factors for a disease or outcome, or that may be indicators of disease progression or of treatment-associated changes. In general, the process by which biomarkers, once identified, might be translated into clinical practice has received scant attention in recent psychiatric literature. A body of work in diagnostic development suggests a framework for evaluating and validating novel biomarkers, but this work may be unfamiliar to clinical and translational researchers in psychiatry. Therefore, this review focuses on the steps that might follow the identification of putative biomarkers. It first addresses standard approaches to characterizing biomarker performance, followed by demonstrations of how a putative biomarker might be shown to have clinical relevance. Finally, it addresses ways in which a biomarker-based test might be validated for clinical application in terms of efficacy and cost-effectiveness.

Adaptive clinical trial designs for simultaneous testing of matched diagnostics and therapeutics

A critical challenge in the development of new molecularly targeted anticancer drugs is the identification of predictive biomarkers and the concurrent development of diagnostics for these biomarkers. Developing matched diagnostics and therapeutics will require new clinical trial designs and methods of data analysis. The use of adaptive design in phase III trials may offer new opportunities for matched diagnosis and treatment because the size of the trial can allow for subpopulation analysis. We present an adaptive phase III trial design that can identify a suitable target population during the early course of the trial, enabling the efficacy of an experimental therapeutic to be evaluated within the target population as a later part of the same trial. The use of such an adaptive approach to clinical trial design has the potential to greatly improve the field of oncology and facilitate the development of personalized medicine.

Quantifying factors for the success of stratified medicine

Co-developing a drug with a diagnostic to create a stratified medicine - a therapy that is targeted to a specific patient population on the basis of a clinical characteristic such as a biomarker that predicts treatment response - presents challenges for product developers, regulators, payers and physicians. With the aim of developing a shared framework and tools for addressing these challenges, here we present an analysis using data from case studies in oncology and Alzheimer's disease, coupled with integrated computational modelling of clinical outcomes and developer economic value, to quantify the effects of decisions related to key issues such as the design of clinical trials. This illustrates how such analyses can aid the coordination of diagnostic and drug development, and the selection of optimal development and commercialization strategies. It also illustrates the impact of the interplay of these factors on the economic feasibility of stratified medicine, which has important implications for public policy makers.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

Outcome of advanced NSCLC patients harboring sensitizing EGFR mutations randomized to EGFR tyrosine kinase inhibitors or chemotherapy as first-line treatment: a meta-analysis

BACKGROUND

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) are effective as first-line treatment of advanced non-small-cell lung cancer patients with EGFR mutations (EGFR-M+).

PATIENTS AND METHODS

We conducted a literature-based meta-analysis to quantify the magnitude of benefit with upfront EGFR TKI in EGFR-M+ patients. Meta-regression and sensitivity analyses were also carried out to identify additional predictors of outcome and to assess the influence of trial design.

RESULTS

Five trials (805 patients) were identified (three trials prospectively enrolling EGFR-M+ patients and two retrospective analyses of EGFR-M+ patients). TKI significantly increased progression-free survival (PFS) [hazard ratio (HR) 0.45, 95% confidence interval (CI) 0.36-0.58, P < 0.0001] and overall response rate (ORR) (HR 2.08, 95% CI 1.75-2.46, P < 0.0001)] over chemotherapy, while significantly decreasing neutropenia. No significant difference was observed in overall survival. The rate of exon-19 mutations, female gender, and nonsmoking status were identified as additional predictors of outcome at meta-regression analysis. A significant interaction with trial design was found for both PFS (P = 0.028) and ORR (P = 0.008), suggesting a larger advantage for patients treated within prospective trials.

CONCLUSIONS

In EGFR-M+ patients, first-line TKI increase both PFS and ORR by ~25%, while significantly decreasing toxicity. The role of additional predictive factors and the influence of trial design on the magnitude of the observed benefit warrant further investigation.

Statistical considerations for the next generation of clinical trials

In this article, we address some of the statistical issues associated with the next generation of oncology clinical trials. Specifically, we focus on two critical aspects of oncologic clinical trials: study endpoints and study design. In our discussion of study endpoints, we provide an overview of endpoints relevant to each phase of clinical trials (phases I, II, and III) and discuss some of the trends in selecting endpoints in recent years. For phase I designs, the traditional assumption that increasing dose will always lead to increasing efficacy, appropriate for cytotoxic agents, is not applicable to novel therapeutics such as in colorectal carcinoma. We emphasize the role of surrogate endpoints in modern clinical trials. In our discussion of study design, we are particularly interested in the essential role of randomization, and discuss recently developed randomized phase II designs. We consider the role biomarkers play in the design of clinical trials and introduce study designs for biomarker evaluations. Finally, we briefly discuss the application of adaptive designs in clinical trials.

Outcomes of research biopsies in phase I clinical trials: the MD anderson cancer center experience

BACKGROUND

Research biopsies are crucial for exploring the impact of novel agents on putative targets. The current study assesses the safety and success rate associated with performing such biopsies.

METHODS

We reviewed the medical records of 155 consecutive patients who had one or more research biopsies as part of a phase I trial from September 2004 to October 2009.

RESULTS

Of 281 research biopsies performed, 118 were paired before and after treatment biopsies (total = 236 biopsies). The most common sites of biopsy were superficial lymph node (19.9%), followed by liver (16.4%), and then soft tissue (15.7%). Ultrasound-guided biopsies were the most frequent type (53.7%). Among 142 patients who consented for mandatory biopsy, 86.6% had the biopsy performed, compared with 4.4% of 911 patients offered a biopsy on an optional basis (p < .0001). Biopsy was obtained most frequently on industry-sponsored trials; lack of funding on nonindustry trials was the most common reason that biopsies were not obtained. Of 281 single biopsies, only 4 (1.4%) had complications: pneumothorax requiring chest tube placement (n = 2), infection requiring admission (n = 1), and arrhythmia with hypotension (n = 1). All but one biopsy was successful in obtaining tissue. No deaths were attributable to biopsy.

CONCLUSIONS

Our experience demonstrates that research biopsies in early phase clinical trials are safe (1.4% risk of serious complications), and a higher percentage of patients underwent mandatory biopsies (86.6%) compared with that of the patients with optional biopsies (4.4%).

Biomarkers and patient selection for PI3K/Akt/mTOR targeted therapies: current status and future directions

The phosphatidylinositol 3-kinase (PI3K)/Akt/ mammalian target of rapamycin (mTOR) pathway regulates a broad spectrum of physiologic and pathologic processes. In breast cancer mutation, amplification, deletion, methylation, and posttranslational modifications lead to significant dysregulation of this pathway leading to more aggressive and potentially drug-resistant disease. Multiple novel agents, targeting different nodes within the pathway are currently under development by both commercial and academic partners. The key to the successful validation of these markers is selection of the appropriate patient groups using biomarkers. This article reviews current progress in this area, highlighting the key molecular alterations described in genes within the PI3K/Akt/mTOR pathway that may have an effect on response to current and future therapeutic interventions. Herein, gaps in current knowledge are highlighted and suggestions for future research directions given that may facilitate biomarker development in partnership with current drug development.

The ethical use of mandatory research biopsies

Increasingly, clinical trials incorporate translational research questions aimed at identifying biomarkers of response or resistance to agents under investigation. Biomarker assays can require tissue samples to be collected through a research biopsy before therapy, during treatment, or at the time of tumor progression. Such biopsy samples will generally not provide a direct benefit to the patient and, given the risks associated with any surgical procedure, ethical concerns have been raised when the participant's enrollment on a clinical trial depends on their consent to undergo a research biopsy. In this Perspectives article, we present the rationale for mandatory research biopsies and offer suggestions for standardization to ensure that high-quality, patient-centered, clinical trials continue to be designed with scientific and ethical rigor.

Integrating biomarkers in clinical trials

Biomarkers have a growing role in clinical trials. With the advent of the targeted therapy era, molecular biomarkers in particular are becoming increasingly important within both clinical research and clinical practice. This article focuses on biomarkers that anticipate the prognosis of individual patients ('prognostic' biomarkers) and on biomarkers that predict how individual patients will respond to specific treatments ('predictive' biomarkers, also called 'effect modifiers'). Specific Phase II and III clinical trial designs are discussed in detail for their ability to validate the biomarker and/or to establish the effect of an experimental therapy in patient populations defined by the presence or absence of the biomarker. Contemporary biomarker-based clinical trials in oncology are used as examples.

Molecular profiling of cancer--the future of personalized cancer medicine: a primer on cancer biology and the tools necessary to bring molecular testing to the clinic

Cancers arise as a result of an accumulation of genetic aberrations that are either acquired or inborn. Virtually every cancer has its unique set of molecular changes. Technologies have been developed to study cancers and derive molecular characteristics that increasingly have implications for clinical care. Indeed, the identification of key genetic aberrations (molecular drivers) may ultimately translate into dramatic benefit for patients through the development of highly targeted therapies. With the increasing availability of newer, more powerful, and cheaper technologies such as multiplex mutational screening, next generation sequencing, array-based approaches that can determine gene copy numbers, methylation, expression, and others, as well as more sophisticated interpretation of high-throughput molecular information using bioinformatics tools like signatures and predictive algorithms, cancers will routinely be characterized in the near future. This review examines the background information and technologies that clinicians and physician-scientists will need to interpret in order to develop better, personalized treatment strategies.

Genomic markers to tailor treatments: waiting or initiating?

The decade since the publication of the Human Genome Project draft has ended with the discovery of hundreds of genomic markers related to diseases and phenotypes. However, the project has not yet delivered on its promise to tailor treatments for individuals. The number of genomic markers in clinical practice is very small. The number of markers to guide treatment decisions is even smaller. In order to speed up discovery and validation of genomic treatment selection markers, we call for considering the brilliant potential of randomized clinical trials. If biomedical research community can collaborate in organizing large-scale consortium of clinical trials associated with well-designed biobanks, these studies would soon act as huge laboratories for investigating genomic medicine; a big step forward towards personalizing medicine.

Questions from the fourth son: a clinician reflects on immunomonitoring, surrogate markers and systems biology

The fourth son is the one who doesn't even know how to ask a question. Tumor immunology is challenged by the failure to identify reliable surrogate markers in vaccine and other experimental therapies for cancer; perhaps investigators haven't yet asked the right questions. Unlike prophylactic vaccines for infectious disease, where the development of antibody is considered a satisfactory endpoint, no such endpoint exists for human therapeutic vaccines. Why is this? Despite an extensive roster of in vitro assays that correlate immune responses to favorable clinical outcomes, no assay is sufficiently reliable to be usefully predictive for vaccine therapy. The discussion reviews some of the historical developments in tumor immunology and the problem of defining a causal relationship when strong correlations are identified. The development of mathematical models from empirical data may help inform the clinician/scientist about underlying mechanisms and help frame new testable hypotheses.

Personalized colon cancer care in 2010

Colon cancer (CC) therapies have improved patient outcomes significantly over the last decades in both the adjuvant and metastatic settings. With the introduction of a number of novel agents, both traditional chemotherapies and biologically targeted agents, the need to identify subgroups that are likely and not likely to respond to a particular treatment regimen is paramount. This will allow patients who are likely to benefit to receive optimal care, while sparing those unlikely to benefit from unnecessary toxicity and cost. With the identification of several novel biomarkers and a variety of technologies to interrogate the genome, we already are able to rapidly study patient tumor or blood samples and normal tissues to generate a large dataset of aberrations within the cancer. How to digest this complex information to obtain accurate, reliable, and meaningful results that will allow us to provide truly personalized care for CC patients is just starting to be addressed. In this article, we briefly review the history of CC treatment, with an emphasis on current clinical standards that incorporate a "personalized medicine" approach. We then review strategies that will potentially improve our ability to individualize therapy in the future.

All-comers versus enrichment design strategy in phase II trials

Designs for biomarker validation have been proposed and utilized in the Phase III oncology clinical trial setting. Broadly speaking, these designs follow either an enrichment (i.e., targeted) strategy or an all-comers (i.e., unselected) strategy. An enrichment design screens patients for the presence or absence of a marker or a panel of markers, and then only includes patients who either have or do not have a certain marker characteristic or profile. In contrast, all patients meeting the eligibility criteria (regardless of a particular biomarker status) are entered into an all-comers design. The strength of the preliminary evidence, the prevalence of the marker, the reproducibility and validity of the assay and the feasibility of real time marker assessment play a major role in the choice of the design. In this report, we discuss the parameters under which the enrichment or an all-comers design strategy would be appropriate for Phase II trials.

An accelerated pathway for targeted cancer therapies

A well-defined pathway for the accelerated development and approval of targeted cancer therapies and companion diagnostics would reduce uncertainty, improve efficiency in development and provide an effective incentive for developers.

Predictive and prognostic factors in colorectal cancer: a personalized approach

It is an exciting time for all those engaged in the treatment of colorectal cancer. The advent of new therapies presents the opportunity for a personalized approach to the patient. This approach considers the complex genetic mechanisms involved in tumorigenesis in addition to classical clinicopathological staging. The potential predictive and prognostic biomarkers which have stemmed from the study of the genetic basis of colorectal cancer and therapeutics are discussed with a focus on mismatch repair status, KRAS, BRAF, 18qLOH, CIMP and TGF-β.

Value of mismatch repair, KRAS, and BRAF mutations in predicting recurrence and benefits from chemotherapy in colorectal cancer

PURPOSE

It is uncertain whether modest benefits from adjuvant chemotherapy in stage II colorectal cancer justify the toxicity, cost, and inconvenience. We investigated the usefulness of defective mismatch repair (dMMR), BRAF, and KRAS mutations in predicting tumor recurrence and sensitivity to chemotherapy.

PATIENTS AND METHODS

Immunohistochemistry for dMMR and pyrosequencing for KRAS/BRAF were performed for 1,913 patients randomly assigned between fluorouracil and folinic acid chemotherapy and no chemotherapy in the Quick and Simple and Reliable (QUASAR) trial.

RESULTS

Twenty-six percent of 695 right-sided colon, 3% of 685 left-sided colon, and 1% of 407 rectal tumors were dMMR. Similarly, 17% of right colon, 2% of left colon, and 2% of rectal tumors were BRAF mutant. KRAS mutant tumors were more evenly distributed: 40% right colon, 28% left colon, and 36% rectal tumors. Recurrence rate for dMMR tumors was half that for MMR-proficient tumors (11% [25 of 218] v 26% [438 of 1,695] recurred; risk ratio [RR], 0.53; 95% CI, 0.40 to 0.70; P < .001). Risk of recurrence was also significantly higher for KRAS mutant than KRAS wild-type tumors (28% [150 of 542] v 21% [219 of 1,041]; RR, 1.40; 95% CI, 1.12 to 1.74; P = .002) but did not differ significantly between BRAF mutant and wild-type tumors (P = .36). No marker predicted benefit from chemotherapy with efficacy not differing significantly by MMR, KRAS, or BRAF status. The prognostic value of MMR and KRAS was similar in the presence and absence of chemotherapy.

CONCLUSION

MMR assays identify patients with a low risk of recurrence. KRAS mutational analysis provides useful additional risk stratification to guide use of chemotherapy.

Biomarkers for early detection and as surrogate endpoints in cancer prevention trials: issues and opportunities

In order to improve the early detection and diagnosis of cancer, give more accurate prognoses, stratify individuals by risk, predict response to treatment, and help the transition of basic research into clinical application, biomarkers are needed that accurately represent or predict clinical outcomes. To be useful in trials for chemopreventive agent development, biomarkers must be subject to modulation, easy to obtain and quantify, and have biological meaning, ideally representing steps in well-understood carcinogenic pathways. Though difficult to validate fully, wisely chosen biomarkers in early-phase trials can inform the prioritization of large-scale, long-term trials that measure clinical outcomes. When well-designed, smaller trials using biomarkers as surrogate endpoints should promote faster decisions regarding which targeted preventive agents to pursue, promising greater progress in the personalization of medicine. Biomarkers could become useful in distinguishing indolent from aggressive forms of ductal carcinoma in situ as well as localized invasive breast and prostate cancer, lesions that are often overtreated. Chemopreventive strategies that reduce the progression of early forms of premalignancy can benefit patients not only by reducing their risk of cancer and death from cancer but also by reducing their need for invasive interventions. Genomic and proteomic methods offer the possibility of revealing new potential markers, especially for diseases whose biology is complex or not well understood. Panels of markers may be used to accommodate the molecular heterogeneity of cancers. Biomarkers in phase 2 prevention trials of combinations of chemopreventive drugs have been used to demonstrate synergistic action of multiple agents, allowing use of lower doses, with less toxicity, a critical feature of interventions intended for cancer prevention.

The cetuximab experience: developing predictive biomarkers in oncology

The anti-EGF receptor monoclonal antibody cetuximab provides a case study for the development of predictive biomarkers in oncology. The identification and validation of KRAS mutation status as a predictor of lack of benefit from cetuximab in metastatic colorectal cancer provides an important first step. However, KRAS mutation status does not appear to be predictive of cetuximab benefit in advanced non-small-cell lung cancer, illustrating the necessity for separate biomarker validation to occur across tumor types. Numerous candidate biomarkers have been suggested based on noncontrolled exploratory analyses, but they require validation in sufficiently sized controlled studies. Key pending issues include distinguishing markers predictive of treatment benefit from those prognostic of disease outcome, selecting the best specimen for analysis (determining the tissue type and collection site, as well as the sample matrix type); and optimizing and standardizing assay technology and scoring systems, particularly for markers expressed over a continuous dynamic range.

Treatment of pancreatic cancer: what can we really predict today?

Managing pancreatic cancer remains a big challenge due to its worse course and prognosis. However, therapeutic options and multimodal strategies are increasing nowadays, including new agents, new regimens and chemoradiation. Recently, the FOLFIRTNOX regimen has been reported to be more active than gemcitabine in selected metastatic patients. In this setting, it will be of utmost interest to guide our therapeutic choice not only on clinical and pathological findings, but also on specific biomarkers that will predict tumor behavior and patient outcome (prognostic markers), and benefit from specific agents or regimens (predictive markers). In the near future, we will have to build both our therapeutic interventions and our clinical research based on an accurate patients' clinical selection and on biomolecular markers. In this review, we aimed to highlight and discuss some of the recent results reported on biomarkers in pancreatic cancer that may predict, i.e., preferential metastatic diffusion after surgery, like CXCR4, or predict gemcitabine efficacy in an adjuvant setting as well as in advanced disease, like hENT1. An important effort for translational research in pancreatic cancer research is thus required to validate such markers, while some important questions concerning tissue availability and processing, methodology of analysis, and design of future prospective trials, need to be addressed.

Moving from prognostic to predictive factors in chronic lymphocytic leukaemia (CLL)

Many prognostic factors have been identified in chronic lymphocytic leukaemia (CLL). Based on the assessment of B cell receptor (BCR) structure and function, a subdivision into subtypes is possible (e.g., immunoglobulin heavy chain variable gene segment (IGHV) unmutated and mutated, V3-21 usage) with distinct biological and clinical characteristics. Recurrent genomic aberrations (i.e., 11q and 17p deletion) and gene mutations (i.e., TP53 and ATM) help to define biological and clinical subgroups. In addition, serum markers (e.g., thymidine kinase (TK) and beta2-microglobulin (beta2-MG)), cellular markers (e.g., CD38 and ZAP70) and clinical staging have an impact on outcome in CLL. The biological characterisation of CLL has not only led to progress in outcome prediction but also has begun to be translated into novel treatment strategies. Nonetheless, most factors associated with prognosis have not been thoroughly interrogated for their predictive value in the light of different therapeutic approaches. With a growing number of agents acting on specific biological targets and being used in different clinical situations, the future is likely to bring the identification of predictive factors in CLL.

Risk assessment and pharmacogenetics in molecular and genomic epidemiology

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

Prospective randomized phase II study determines the clinical usefulness of genetic biomarkers for sensitivity to primary chemotherapy with paclitaxel in breast cancer

In patients with breast cancer, taxane as well as anthracycline play central roles in systemic chemotherapy. By evaluating the pathological response, we can gauge sensitivity to primary chemotherapy. However, biomarkers that would predict a response to taxane have not yet been established. We conducted a prospective randomized trial to evaluate whether selecting patients using sensitivity testing based on the gene expression of the tumor might enhance the probability of the pathological response. Five genes were identified as biomarkers derived from a microarray of DNA gene profiles from microdisected breast tumors. In the experimental arm (B1), 12 cycles of weekly paclitaxel, 80 mg/m(2) , were preoperatively given when the sensitivity test was positive and therefore judged to be sensitive to paclitaxel. When the test was negative, meaning insensitive to paclitaxel, four cycles of FEC100 were given (arm B2). In the control arm (A), paclitaxel was administered weekly without the use of the sensitivity test. A total of 92 patients were enrolled and 86 patients were analyzed. The pathological response rate (pRR) of each arm was 36.4% in B1 (expected sensitive to paclitaxel), 21.1% in A (control) and 12.5% in B2, respectively. Weekly paclitaxel-treated patients selected by the sensitivity test did not enhance the pRR. The study failed to validate sensitivity testing using five gene expressions for primary chemotherapy with paclitaxel in patients with breast cancer. However, this study suggests that a randomized phase II study is a robust tool for obtaining a rapid conclusion on the usefulness of biomarkers and could be the foundation for further large clinical trials.

Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis

In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of published literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.THE FOLLOWING REPORTS CAN BE PUBLICLY ACCESSED AT THE MAS WEBSITE AT: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.htmlGENE EXPRESSION PROFILING FOR GUIDING ADJUVANT CHEMOTHERAPY DECISIONS IN WOMEN WITH EARLY BREAST CANCER: An Evidence-Based and Economic AnalysisEpidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: An Evidence-Based and Ecopnomic AnalysisK-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis

OBJECTIVE

To review and synthesize the available evidence regarding the laboratory performance, prognostic value, and predictive value of Oncotype-DX for the target population.

CLINICAL NEED

CONDITION AND TARGET POPULATION The target population of this review is women with newly diagnosed early stage (stage I-IIIa) invasive breast cancer that is estrogen-receptor (ER) positive and/or progesterone-receptor (PR) positive. Much of this review, however, is relevant for women with early stage (I and II) invasive breast cancer that is specifically ER positive, lymph node (LN) negative and human epidermal growth factor receptor 2 (HER-2/neu) negative. This refined population represents an estimated incident population of 3,315 new breast cancers in Ontario (according to 2007 data). Currently it is estimated that only 15% of these women will develop a distant metastasis at 10 years; however, a far great proportion currently receive adjuvant chemotherapy, suggesting that more women are being treated with chemotherapy than can benefit. There is therefore a need to develop better prognostic and predictive tools to improve the selection of women that may benefit from adjuvant chemotherapy. TECHNOLOGY OF CONCERN: The Oncotype-DX Breast Cancer Assay (Genomic Health, Redwood City, CA) quantifies gene expression for 21 genes in breast cancer tissue by performing reverse transcription polymerase chain reaction (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tumour blocks that are obtained during initial surgery (lumpectomy, mastectomy, or core biopsy) of women with early breast cancer that is newly diagnosed. The panel of 21 genes include genes associated with tumour proliferation and invasion, as well as other genes related to HER-2/neu expression, ER expression, and progesterone receptor (PR) expression.

RESEARCH QUESTIONS

What is the laboratory performance of Oncotype-DX?How reliable is Oncotype-DX (i.e., how repeatable and reproducible is Oncotype-DX)?How often does Oncotype-DX fail to give a useable result?What is the prognostic value of Oncotype-DX?Is Oncotype-DX recurrence score associated with the risk of distant recurrence or death due to any cause in women with early breast cancer receiving tamoxifen?What is the predictive value of Oncotype-DX?Does Oncoytpe-DX recurrence score predict significant benefit in terms of improvements in 10-year distant recurrence or death due to any cause for women receiving tamoxifen plus chemotherapy in comparison to women receiving tamoxifen alone?How does Oncotype-DX compare to other known predictors of risk such as Adjuvant! Online?How does Oncotype-DX impact patient quality of life and clinical/patient decision-making?

SEARCH STRATEGY

A literature search was performed on March 19(th), 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1(st), 2006 to March 19(th), 2010. A starting search date of January 1(st), 2006 was because a comprehensive systematic review of Oncotype-DX was identified in preliminary literature searching. This systematic review, by Marchionni et al. (2008), included literature up to January 1(st), 2007. All studies identified in the review by Marchionni et al. as well as those identified in updated literature searching were used to form the evidentiary base of this review. The quality of the overall body of evidence was identified as high, moderate, low or very low according to GRADE methodology.

INCLUSION CRITERIA

Any observational trial, controlled clinical trial, randomized controlled trial (RCT), meta-analysis or systematic review that reported on the laboratory performance, prognostic value and/or predictive value of Oncotype-DX testing, or other outcome relevant to the Key Questions, specific to the target population was included.

EXCLUSION CRITERIA

Studies that did not report original data or original data analysis,Studies published in a language other than English,Studies reported only in abstract or as poster presentations (such publications were not sought nor included in this review since the MAS does not generally consider evidence that is not subject to peer review nor does the MAS consider evidence that lacks detailed description of methodology).

OUTCOMES OF INTEREST

Outcomes of interest varied depending on the Key Question. For the Key Questions of prognostic and predictive value (Key Questions #2 and #3), the prospectively defined primary outcome was risk of 10-year distant recurrence. The prospectively defined secondary outcome was 10-year death due to any cause (i.e., overall survival). All additional outcomes such as risk of locoregional recurrence or disease-free survival (DFS) were not prospectively determined for this review but were reported as presented in included trials; these outcomes are referenced as tertiary outcomes in this review. Outcomes for other Key Questions (i.e., Key Questions #1, #4 and #5) were not prospectively defined due to the variability in endpoints relevant for these questions.

SUMMARY OF FINDINGS

A total of 26 studies were included. Of these 26 studies, only five studies were relevant to the primary questions of this review (Key Questions #2 and #3). The following conclusions were drawn from the entire body of evidence: There is a lack of external validation to support the reliability of Oncotype-DX; however, the current available evidence derived from internal industry validation studies suggests that Oncotype-DX is reliable (i.e., Oncotype-DX is repeatable and reproducible).Current available evidence suggests a moderate failure rate of Oncotype-DX testing; however, the failure rate observed across clinical trials included in this review is likely inflated; the current Ontario experience suggests an acceptably lower rate of test failure.In women with newly diagnosed early breast cancer (stage I-II) that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node negative:There is low quality evidence that Oncotype-DX has prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole (the latter for postmenopausal women only),There is very low quality evidence that Oncotype-DX can predict which women will benefit from adjuvant CMF/MF chemotherapy in women being treated with adjuvant tamoxifen.In postmenopausal women with newly diagnosed early breast cancer that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node positive:There is low quality evidence that Oncotype-DX has limited prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole,There is very low quality evidence that Oncotype-DX has limited predictive value for predicting which women will benefit from adjuvant CAF chemotherapy in women who are being treated with adjuvant tamoxifen.There are methodological and statistical limitations that affect both the generalizability of the current available evidence, as well as the magnitude and statistical strength of the observed effect sizes; in particular:Of the major predictive trials, Oncotype-DX scores were only produced for a small subset of women (<40% of the original randomized population) potentially disabling the effects of treatment randomization and opening the possibility of selection bias;Data is not specific to HER-2/neu-negative women;There were limitations with multivariate statistical analyses.Additional trials of observational design may provide further validation of the prognostic and predictive value of Oncotype-DX; however, it is unlikely that prospective or randomized data will become available in the near future due to ethical, time and resource considerations.There is currently insufficient evidence investigating how Oncoytpe-DX compares to other known prognostic estimators of risk, such as Adjuvant! Online, and there is insufficient evidence investigating how Oncotype-DX would impact clinician/patient decision-making in a setting generalizable to Ontario.

Use of standard markers and incorporation of molecular markers into breast cancer therapy: Consensus recommendations from an International Expert Panel

Breast cancer is a heterogeneous disease of different subtypes on the molecular, histopathological, and clinical level. Genomic profiling techniques have led to several prognostic and predictive gene signatures of breast cancer that may further refine outcome prediction, especially in clinically equivocal situations. In particular, the predictive value of today's most important therapeutic targets, ER and HER2, are strongly influenced by the proliferative status of the tumor. Genomic assays are generally performed in a centralized manner, whereas routine pathological evaluation is mostly done on a decentralized basis, making the comparison of these methods difficult. Thus, there remains considerable uncertainty about the use of the new molecular markers in routine clinical decision making and their role in patient selection or stratification for future clinical trials. To address this concern, a group of representatives from breast cancer research groups in the areas of breast pathology, genomic profiling, and clinical trials critically reviewed all available data. Consensus recommendations are made on the practical use of molecular markers in breast cancer management and their incorporation into future clinical trials.

Evaluation of EGFR gene copy number as a predictive biomarker for the efficacy of cetuximab in combination with chemotherapy in the first-line treatment of recurrent and/or metastatic squamous cell carcinoma of the head and neck: EXTREME study

Background: The phase III EXTREME study demonstrated that combining cetuximab with platinum/5-fluorouracil (5-FU) significantly improved overall survival in the first-line treatment of patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) compared with platinum/5-FU alone. The aim of this investigation was to evaluate elevated tumor EGFR gene copy number as a predictive biomarker in EXTREME study patients.

Patients and methods: Dual-color FISH was used to determine absolute and relative EGFR copy number. Models of differing stringencies were used to score and investigate whether increased copy number was predictive for the activity of cetuximab plus platinum/5-FU.

Results: Tumors from 312 of 442 patients (71%) were evaluable by FISH and met the criteria for statistical analysis. A moderate increase in EGFR copy number was common, with high-level amplification of the gene occurring in a small fraction of tumors (∼11%). Considering each of the models tested, no association of EGFR copy number with overall survival, progression-free survival or best overall response was found for patients treated with cetuximab plus platinum/5-FU.

Conclusion: Tumor EGFR copy number is not a predictive biomarker for the efficacy of cetuximab plus platinum/5-FU as first-line therapy for patients with R/M SCCHN.

Statistical consideration for clinical biomarker research in bladder cancer

OBJECTIVE

To critically review and illustrate current methodological and statistical considerations for bladder cancer biomarker discovery and evaluation.

METHODS

Original, review, and methodological articles, and editorials were reviewed and summarized.

RESULTS

Biomarkers may be useful at multiple stages of bladder cancer management: early detection, diagnosis, staging, prognosis, and treatment; however, few novel biomarkers are currently used in clinical practice. The reasons for this disjunction are many and reflect the long and difficult pathway from candidate biomarker discovery to clinical assay, and the lack of coherent and comprehensive processes (pipelines) for biomarker development. Conceptually, the development of new biomarkers should be a process that is similar to therapeutic drug evaluation-a highly regulated process with carefully regulated phases from discovery to human applications. In a further effort to address the pervasive problem of inadequacies in the design, analysis, and reporting of biomarker prognostic studies, a set of reporting recommendations are discussed. For example, biomarkers should provide unique information that adds to known clinical and pathologic information. Conventional multivariable analyses are not sufficient to demonstrate improved prediction of outcomes. Predictive models, including or excluding any new putative biomarker, need to show clinically significant improvement of performance in order to claim any real benefit. Towards this end, proper model building, avoidance of overfitting, and external validation are crucial. In addition, it is important to choose appropriate performance measures dependent on outcome and prediction type and to avoid the use of cutpoints. Biomarkers providing a continuous score provide potentially more useful information than cutpoints since risk fits a continuum model. Combination of complementary and independent biomarkers is likely to better capture the biological potential of a tumor than any single biomarker. Finally, methods that incorporate clinical consequences such as decision curve analysis are crucial to the evaluation of biomarkers.

CONCLUSIONS

Attention to sound design and statistical practice should be delivered as early as possible and will help maximize the promise of biomarkers for patient care. Studies should include a measure of predictive accuracy and clinical decision-analysis. External validation using data from an independent cohort provides the strongest evidence that a model is valid. There is a need for adequately assessed clinical biomarkers in bladder cancer.

Considerations on implementing diagnostic markers into clinical decision making in bladder cancer

Bladder cancer is a common disease that is often detected late and has a high rate of recurrence and progression. Cystoscopy is the main tool in detection and surveillance of bladder cancer but is invasive and can miss some cancers. Cytology is frequently utilized but suffers from a poor sensitivity. There are several commercially available urine-based tumor markers currently available but their use is not recommended by guideline panels. Markers such as the Urovysion FISH assay and the NMP22 BladderChek test are approved for surveillance and detection in patients with hematuria. The added benefit of these markers and other commercially available markers (e.g. Ucyt+, BTA stat) has not been well investigated though it appears these markers are insufficiently sensitive to replace cystoscopy. Additional studies are needed to determine the clinical scenarios where bladder markers are best utilized (screening, surveillance, early detection, evaluating cytologic atypia) and what impact they should have on clinical decision making. Furthermore, a variety of issues and barriers can affect the movement of clinical tests from research to clinical practice. This article addresses some of the challenges facing research and medical communities in the delivery and integration of markers for bladder cancer diagnosis. Moreover, we attempt to outline criteria for the clinical utility of new bladder cancer diagnostic markers.

Translational research in oncology: key bottlenecks and new paradigms

Translational research is about transforming progress in basic research into products that benefit patients. Here I discuss some of the key obstacles to effective translational research in oncology that have previously received limited attention. Basic research often does not go far enough for straightforward clinical translation, and long-term, high-risk endeavours to fill these key gaps have not been adequately addressed either by industry or by the culture of investigator-initiated research. These key gaps include the identification of causative oncogenic mutations and new approaches to regulating currently undruggable targets such as tumour suppressor genes. Even where an inhibitor of a key target has been identified, new approaches to clinical development are needed. The current approach of treating broad populations of patients based primarily on primary cancer site is not well suited to the development of molecularly targeted drugs. Although developing drugs with predictive diagnostics makes drug development more complex, it can improve the success rate of development, as well as provide benefit to patients and the economics of healthcare. I review here some prospective Phase III designs that have been developed for transition from the era of correlative science to one of reliable predictive and personalised oncology.

Measurement of biomarker proteins for point-of-care early detection and monitoring of cancer

This critical review evaluates progress toward viable point-of-care protein biomarker measurements for cancer detection and diagnostics. The ability to measure panels of specific, selective cancer biomarker proteins in physicians' surgeries and clinics has the potential to revolutionize cancer detection, monitoring, and therapy. The dream envisions reliable, cheap, automated, technically undemanding devices that can analyze a patient's serum or saliva in a clinical setting, allowing on-the-spot diagnosis. Existing commercial products for protein assays are reliable in laboratory settings, but have limitations for point-of-care applications. A number of ultrasensitive immunosensors and some arrays have been developed, many based on nanotechnology. Multilabel detection coupled with high capture molecule density in immunosensors and arrays seems to be capable of detecting a wide range of protein concentrations with sensitivity ranging into the sub pg mL(-1) level. Multilabel arrays can be designed to detect both high and ultralow abundance proteins in the same sample. However, only a few of the newer ultrasensitive methods have been evaluated with real patient samples, which is key to establishing clinical sensitivity and selectivity.

Translating cancer research into targeted therapeutics

The emphasis in cancer drug development has shifted from cytotoxic, non-specific chemotherapies to molecularly targeted, rationally designed drugs promising greater efficacy and less side effects. Nevertheless, despite some successes drug development remains painfully slow. Here, we highlight the issues involved and suggest ways in which this process can be improved and expedited. We envision an increasing shift to integrated cancer research and biomarker-driven adaptive and hypothesis testing clinical trials. The goal is the development of specific cancer medicines to treat the individual patient, with treatment selection being driven by a detailed understanding of the genetics and biology of the patient and their cancer.