Guidelines for the development and incorporation of biomarker studies in early clinical trials of novel agents

Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era

The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost-utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations.

Unveiling changes in the landscape of patient populations in cancer early drug development

The introduction of new Molecularly Targeted Agents (MTA) has changed the landscape in Early Drug Development (EDD) over the last two decades, leading to an improvement in clinical trial design. Previous Phase 1 (Ph1) studies with cytotoxics focused on safety objectives, only recruiting heavily pre-treated cancer patients, have been left behind. In this review, we will illustrate the slow although unstoppable change that has increasingly been observed in those populations candidate to participate in EDD trials with the advent of MTA. As more evidence regarding oncogene addiction becomes available, molecular-biomarker driven selection has been implemented among Molecularly-Selected Population (MSP) studies. New Window-Of-Opportunity (WOO) and Phase 0 (Ph0) studies have been developed in order to assess whether a MTA produces the hypothetical proposed biological effect. The rising need of getting early pharmacokinetics and pharmacodynamics data has led to the conduction of Healthy Volunteer (HV) studies, in part favoured for the particular and different toxicity profile of these MTA. However, several challenges will need to be addressed in order to boost the implementation of these new clinical trial designs in the forthcoming years. Among the problems to overcome, we would highlight a better coordination effort between centers for ensuring adequate patient accrual among small patient populations and a deepening into the ethics implied in enrolling patients in studies with no therapeutic intent. However, these tribulations will be certainly compensated by the possibility of opening a new horizon of treatment for diseases with dismal prognosis.

Decision support systems for personalized and participative radiation oncology

A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the development of clinical decision support systems based on prediction models of treatment outcome. In radiation oncology, these models 'learn' using advanced and innovative information technologies (ideally in a distributed fashion - please watch the animation: http://youtu.be/ZDJFOxpwqEA) from all available/appropriate medical data (clinical, treatment, imaging, biological/genetic, etc.) to achieve the highest possible accuracy with respect to prediction of tumor response and normal tissue toxicity. In this position paper, we deliver an overview of the factors that are associated with outcome in radiation oncology and discuss the methodology behind the development of accurate prediction models, which is a multi-faceted process. Subsequent to initial development/validation and clinical introduction, decision support systems should be constantly re-evaluated (through quality assurance procedures) in different patient datasets in order to refine and re-optimize the models, ensuring the continuous utility of the models. In the reasonably near future, decision support systems will be fully integrated within the clinic, with data and knowledge being shared in a standardized, dynamic, and potentially global manner enabling truly personalized and participative medicine.

Biological toxicities as surrogate markers of efficacy in patients treated with mTOR inhibitors for metastatic renal cell carcinoma

Background

Metabolic toxicities of mTOR inhibitors (mTORi) are well characterized. The purpose of the study was to investigate the relationship between these metabolic toxicities and mTORi efficacy.

Methods

From 2007 to 2011, metabolic toxicities were retrospectively collected in patients treated with an mTORi (everolimus, temsirolimus) for a metastatic renal cell carcinoma (mRCC) in a single institution. Patients were eligible if they have received an mTORi for at least 28 days. Changes in the following parameters were analyzed: lymphocytes, serum creatinine, glycemia, serum phosphate, liver transaminases, cholesterol, and triglycerides. The efficacy was assessed by progression-free survival (PFS) and tumor response.

Results

Data were collected from seventy-five patients (everolimus = 44 patients; temsirolimus = 31 patients). Six patients exhibited a partial response, 42 a stable disease and 15 had a progressive disease (12 missing). After a median follow-up of 12.8 months, the median PFS was 6.7 months (95% confidence interval: 4.0-9.1 months). Patients with CB had a statistically more severe absolute increase of glycemia and absolute decrease in phosphatemia (p = 0.002 and p = 0.02 respectively). The Progression Free Survival was significantly higher with the onset rate of hypophosphatemia (p = 0.03) and hyperglycemia (p = 0.001) and lower with the onset rate of lymphopenia (p = 0.004).

Conclusions

Hyperglycemia, hypophosphatemia and lymphopenia, were significantly associated with tumor response and/or PFS. Those events, as well as their onset rate, should be prospectively monitored as predictors of response to mTORi.

Metabolomics combined with pattern recognition and bioinformatics analysis methods for the development of pharmacodynamic biomarkers on liver fibrosis

Metabolomics combined with pattern recognition and network analysis maybe an attractive strategy for the pharmacodynamics biomarkers development on liver fibrosis.

Biomarkers in Search of Precision Medicine in IBD

The completion of the human genome project in 2003 represented a major scientific landmark, ushering in a new era with hopes and expectations of fresh insights into disease mechanisms and treatments. In inflammatory bowel disease (IBD), many important discoveries soon followed, notably the identification of >200 genetic susceptibility loci and characterization of the gut microbiome. As "big data", driven by advances in technology, becomes increasingly available and affordable, individuals with IBD and clinicians alike yearn for tangible outcomes from the promise of "precision medicine"-precise diagnosis, monitoring, and treatment. Here, we provide a commentary on the prospects and challenges of precision medicine and biomarkers in IBD. We focus on the three key areas where precision IBD will have the most impact: (1) disease susceptibility, activity, and behavior; (2) prediction of drug response and adverse effects; and (3) identification of subphenotypic mechanisms to facilitate drug discovery and selection of new treatments in IBD.

Bioanalytical qualification of clinical biomarker assays in plasma using a novel multi-analyte Simple Plex™ platform

Aim: Immune-checkpoint inhibitors are presumed to break down the tolerogenic state of immune cells by activating T-lymphocytes that release cytokines and enhance effector cell function for elimination of tumors. Measurement of cytokines is being pursued for better understanding of the mechanism of action of immune-checkpoint inhibitors, as well as to identify potential predictive biomarkers. Results: In this study, we show bioanalytical qualification of cytokine assays in plasma on a novel multi-analyte immunoassay platform, Simple Plex™. The qualified assays exhibited excellent sensitivity as evidenced by measurement of all samples within the quantifiable range. The accuracy and precision were 80–120% and 10%, respectively. Conclusion: The qualified assays will be useful in assessing mechanism of action cancer immunotherapies.

Experimental Therapeutic Trial Design for Pediatric Brain Tumors

Pediatric brain tumors are the leading cause of cancer-related death during childhood. Since the first pediatric brain tumor clinical trials, the field has seen improved outcomes in some, but not all tumor types. In the past few decades, a number of promising new therapeutic agents have emerged, yet only a few of these agents have been incorporated into clinical trials for pediatric brain tumors. In this review, the authors discuss the process of and challenges in pediatric clinical trial design; this will allow for highly efficient and effective clinical trials with appropriate endpoints to ensure rapid and safe investigation of novel therapeutics for children with brain tumors.

Clinical Application of Circulating Tumour Cells in Prostate Cancer: From Bench to Bedside and Back

Prostate cancer is the most common cancer in men worldwide. To improve future drug development and patient management, surrogate biomarkers associated with relevant outcomes are required. Circulating tumour cells (CTCs) are tumour cells that can enter the circulatory system, and are principally responsible for the development of metastasis at distant sites. In recent years, interest in detecting CTCs as a surrogate biomarker has ghiiukjrown. Clinical studies have revealed that high levels of CTCs in the blood correlate with disease progression in patients with prostate cancer; however, their predictive value for monitoring therapeutic response is less clear. Despite the important progress in CTC clinical development, there are critical requirements for the implementation of their analysis as a routine oncology tool. The goal of the present review is to provide an update on the advances in the clinical validation of CTCs as a surrogate biomarker and to discuss the principal obstacles and main challenges to their inclusion in clinical practice.

Impact of the 2010 Consensus Recommendations of the Clinical Trial Design Task Force of the NCI Investigational Drug Steering Committee

Oncology phase III trials have a high failure rate, leading to high development costs. The Clinical Trials Design Task Force of the Investigational Drug Steering Committee of the NCI Cancer Therapy and Evaluation Program developed Recommendations regarding the design of phase II trials. We report here on the results of a Concordance Group review charged with documenting whether concordance rates improved after the publication of the Recommendations. One hundred and fifty-five trials were reviewed. Letter of Intents (LOI) from the post-Recommendation period were more likely to be randomized (44% vs. 34%) and biomarker selected (19% vs. 10%). Single-arm studies using time-to-event endpoints (benchmarked against historical data) were similar, as was the type of tumor. There was a significant improvement in the rate of concordance, with 74% of LOIs scored as concordant compared with 58% before the Recommendations (P = 0.042). This included a marked decrease in the use of single-arm designs to evaluate the activity of drug combinations (19% vs. 5%, P = 0.009). There were areas for which clarification was warranted, including the need for protocols to include further development plans, the use of realistic benchmarks, the careful evaluation of historical controls, and the use of a standard treatment option as a control. Ongoing critical evaluation of current trial design methodology and the development of new Guidelines when appropriate will continue to improve drug development ensuring that safe and effective cancer therapeutics are made available to our patients as quickly and efficiently as possible.

ESMO consensus guidelines for the management of patients with metastatic colorectal cancer

Colorectal cancer (CRC) is one of the most common malignancies in Western countries. Over the last 20 years, and the last decade in particular, the clinical outcome for patients with metastatic CRC (mCRC) has improved greatly due not only to an increase in the number of patients being referred for and undergoing surgical resection of their localised metastatic disease but also to a more strategic approach to the delivery of systemic therapy and an expansion in the use of ablative techniques. This reflects the increase in the number of patients that are being managed within a multidisciplinary team environment and specialist cancer centres, and the emergence over the same time period not only of improved imaging techniques but also prognostic and predictive molecular markers. Treatment decisions for patients with mCRC must be evidence-based. Thus, these ESMO consensus guidelines have been developed based on the current available evidence to provide a series of evidence-based recommendations to assist in the treatment and management of patients with mCRC in this rapidly evolving treatment setting.

Prognostic relevance of sunitinib toxicities and comparison of continuous vs. intermittent sunitinib dosing schedule in metastatic renal cell cancer patients

Aim of the study

Sunitinib-related side effects may develop as a result of the pharmacokinetic pathway affects the of the drug.

Material and methods

Data on mRCC patients were obtained from the hospital archives. Outcomes of patients were evaluated in terms of related prognostic factors, sunitinib adverse events during the treatment, and two different sunitinib dosing schedules.

Results

Seventy patients diagnosed with mRCC and treated with sunitinib were analyzed for prognostic factors and survival rates. During the mean follow-up of 33.5 months, 38 (54%) patients were alive and 32 (46%) patients died. The median time of overall survival (OS) and progression-free survival (PFS) was 27 months (12–61) and 19 months (5–45), respectively. In univariate analysis, good prognostic risk group according to the Memorial Sloan-Kettering Cancer Center (MSKCC), hypothyroidism as sunitinib toxicity and patients on sunitinib treatment more than 1 year were favorable prognostic factors for OS. Leukopenia and fatigue as sunitinib toxicity were poor prognostic factors for OS. PFS and OS of the patients were not significantly different when we compared intermittent (4/2) vs. continuous treatment dosing schedules.

Conclusions

As a result of this trial, having hypothyroidism as an adverse effect of sunitinib was a favorable prognostic factor for OS and PFS in mRCC patients. It was also found that 4/2 and continuous dosing schedules of sunitinib did not give rise to different outcomes in mRCC patients.

The root causes of pharmacodynamic assay failure

Robust pharmacodynamic assay results are valuable for informing go/no-go decisions about continued development of new anti-cancer agents and for identifying combinations of targeted agents, but often pharmacodynamic results are too incomplete or variable to fulfill this role. Our experience suggests that variable reagent and specimen quality are two major contributors to this problem. Minimizing all potential sources of variability in procedures for specimen collection, processing, and assay measurements is essential for meaningful comparison of pharmacodynamic biomarkers across sample time points. This is especially true in the evaluation of pre- and post-dose tumor biopsies, which suffer from high levels of tumor insufficiency due to variations in biopsy collection techniques and significant specimen heterogeneity within and across patients. Developing methods to assess heterogeneous biopsies is necessary in order to evaluate a majority of tumor biopsies collected for pharmacodynamic biomarker studies. Improved collection devices and standardization of methods are being sought in order to improve the tumor content and quality of tumor biopsies. In terms of reagent variability, we have found that stringent initial reagent qualification and quality control of R&D-grade reagents is critical to minimize lot-to-lot variability and prevent assay failures, especially for clinical pharmacodynamic questions, which often demand assay performance that meets or exceeds clinical diagnostic assay standards. Rigorous reagent specifications and use of appropriate assay quality control methodologies help to ensure consistency between assay runs, laboratories and trials to provide much needed pharmacodynamic insights into the activity of investigational agents.

Metastasis-inducing proteins are widely expressed in human brain metastases and associated with intracranial progression and radiation response

Background:

Understanding the factors that drive recurrence and radiosensitivity in brain metastases would improve prediction of outcomes, treatment planning and development of therapeutics. We investigated the expression of known metastasis-inducing proteins in human brain metastases.

Methods:

Immunohistochemistry on metastases removed at neurosurgery from 138 patients to determine the degree and pattern of expression of the proteins S100A4, S100P, AGR2, osteopontin (OPN) and the DNA repair marker FANCD2. Validation of significant findings in a separate prospective series with the investigation of intra-tumoral heterogeneity using image-guided sampling. Assessment of S100A4 expression in brain metastatic and non-metastatic primary breast carcinomas.

Results:

There was widespread staining for OPN, S100A4, S100P and AGR2 in human brain metastases. Positive staining for S100A4 was independently associated with a shorter time to intracranial progression after resection in multivariate analysis (hazard ratio for negative over positive staining=0.17, 95% CI: 0.04–0.74, P=0.018). S100A4 was expressed at the leading edge of brain metastases in image guided sampling and overexpressed in brain metastatic vs non-brain metastatic primary breast carcinomas. Staining for OPN was associated with a significant increase in survival time after post-operative whole-brain radiotherapy in retrospective (OPN negative 3.43 months, 95% CI: 1.36–5.51 vs OPN positive, 11.20 months 95% CI: 7.68–14.72, Log rank test, P<0.001) and validation populations.

Conclusions:

Proteins known to be involved in cellular adhesion and migration in vitro, and metastasis in vivo are significantly expressed in human brain metastases and may be useful biomarkers of intracranial progression and radiosensitivity.

Immune Checkpoint Therapy and the Search for Predictive Biomarkers

Immune checkpoint therapy has started a revolution in the field of oncology. The concept that the immune system plays a critical role in antitumor responses, which has been around for decades, has finally been proven and firmly established with elegant preclinical studies and dramatic clinical responses in patients as a result of antibodies that block inhibitory T-cell pathways. However, the clinical responses being achieved are only in a subset of patients, and more work is needed to provide a better understanding of the mechanisms that elicit tumor rejection, which will enable identification of appropriate biomarkers, reveal new targets, provide data to guide combination studies, and eventually dictate a platform that allows more patients to derive clinical benefit, including cures, with immune checkpoint therapy.

Correlation of Stomatitis and Cutaneous Toxicity With Clinical Outcome in Patients With Metastatic Renal-Cell Carcinoma Treated With Everolimus

BACKGROUND

In clinical practice, discontinuation or dose reduction of everolimus may be induced not only by grade 3 or 4 toxicities but also by prolonged grade 2 toxicities, such as stomatitis and/or cutaneous toxicity, which share some pathogenetic mechanisms. We assessed the correlation between either everolimus discontinuation or dose reduction induced by stomatitis-cutaneous toxicity events (SCTE) and clinical outcome of patients with metastatic renal-cell cancer (mRCC).

PATIENTS AND METHODS

We retrospectively reviewed the clinical data of patients with mRCC treated with everolimus in 2 Italian centers. Clinical evidence of SCTE was evaluated, and corresponding clinical data were reviewed for response and clinical outcome.

RESULTS

Seventy-nine mRCC patients treated with everolimus (57 male, 22 female; median age 66 years; range, 44-88 years) were evaluated. SCTE were observed in 20 (25%) of 79 patients at a median of 30.5 days of everolimus treatment (range, 10-270 days). Partial response or stable disease was achieved in 15 (79%) of 19 evaluable patients with SCTE compared to 28 (48%) of 58 with no SCTE (P = .03). At a median follow-up of 19 months, a significant difference was found in the median PFS equal to 7.8 months (95% confidence interval [CI], 2.8-24.4) in SCTE patients versus 4.3 months (95% CI, 2.7-7.5) in non-SCTE patients (P = .029), and in the median OS equal to 30.6 months (95% CI, 19.6-not reached) in SCTE patients versus 13.5 months (95% CI, 9.9-17.7) in non-SCTE patients (P = .0007).

CONCLUSION

These data suggest that SCTE may be a predictive marker of favorable outcome in mRCC patients treated with everolimus.

Statistical Aspects in Proteomic Biomarker Discovery

In the pursuit of a personalized medicine, i.e., the individual treatment of a patient, many medical decision problems are desired to be supported by biomarkers that can help to make a diagnosis, prediction, or prognosis. Proteomic biomarkers are of special interest since they can not only be detected in tissue samples but can also often be easily detected in diverse body fluids. Statistical methods play an important role in the discovery and validation of proteomic biomarkers. They are necessary in the planning of experiments, in the processing of raw signals, and in the final data analysis. This review provides an overview on the most frequent experimental settings including sample size considerations, and focuses on exploratory data analysis and classifier development.

Immune monitoring technology primer

Background

Recent biotechnological developments have resulted in increasing interest in immunology biomarkers. These biomarkers have potential clinical utility in the near future as predictors of treatment response. Hence, clinical validation of these predictive markers is critical.

Findings

The process of clinically validating a predictive biomarker is reviewed. Validation of a predictive biomarker requires quantifying the strength of a statistical interaction between marker and a treatment. Different study designs are considered.

Conclusions

Clinical validation of immunology biomarkers can be demanding both in terms of time and resources, and careful planning and study design are critical.

Early Pregnancy Biomarkers in Pre-Eclampsia: A Systematic Review and Meta-Analysis

Pre-eclampsia (PE) complicates 2%–8% of all pregnancies and is an important cause of perinatal morbidity and mortality worldwide. In order to reduce these complications and to develop possible treatment modalities, it is important to identify women at risk of developing PE. The use of biomarkers in early pregnancy would allow appropriate stratification into high and low risk pregnancies for the purpose of defining surveillance in pregnancy and to administer interventions. We used formal methods for a systematic review and meta-analyses to assess the accuracy of all biomarkers that have been evaluated so far during the first and early second trimester of pregnancy to predict PE. We found low predictive values using individual biomarkers which included a disintegrin and metalloprotease 12 (ADAM-12), inhibin-A, pregnancy associated plasma protein A (PAPP-A), placental growth factor (PlGF) and placental protein 13 (PP-13). The pooled sensitivity of all single biomarkers was 0.40 (95% CI 0.39–0.41) at a false positive rate of 10%. The area under the Summary of Receiver Operating Characteristics Curve (SROC) was 0.786 (SE 0.02). When a combination model was used, the predictive value improved to an area under the SROC of 0.893 (SE 0.03). In conclusion, although there are multiple potential biomarkers for PE their efficacy has been inconsistent and comparisons are difficult because of heterogeneity between different studies. Therefore, there is an urgent need for high quality, large-scale multicentre research in biomarkers for PE so that the best predictive marker(s) can be identified in order to improve the management of women destined to develop PE.

Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity

The promise of 'personalized cancer care' with therapies toward specific molecular aberrations has potential to improve outcomes. However, there is recognized heterogeneity within any given tumor-type from patient to patient (inter-patient heterogeneity), and within an individual (intra-patient heterogeneity) as demonstrated by molecular evolution through space (primary tumor to metastasis) and time (after therapy). These issues have become hurdles to advancing cancer treatment outcomes with novel molecularly targeted agents. Classic trial design paradigms are challenged by heterogeneity, as they are unable to test targeted therapeutics against low frequency genomic 'oncogenic driver' aberrations with adequate power. Usual accrual difficulties to clinical trials are exacerbated by low frequencies of any given molecular driver. To address these challenges, there is need for innovative clinical trial designs and strategies implementing novel diagnostic biomarker technologies to account for inter-patient molecular diversity and scarce tissue for analysis. Importantly, there is also need for pre-defined treatment priority algorithms given numerous aberrations commonly observed within any one individual sample. Access to multiple available therapeutic agents simultaneously is crucial. Finally intra-patient heterogeneity through time may be addressed by serial biomarker assessment at the time of tumor progression. This report discusses various 'next-generation' biomarker-driven trial designs and their potentials and limitations to tackle these recognized molecular heterogeneity challenges. Regulatory hurdles, with respect to drug and companion diagnostic development and approval, are considered. Focus is on the 'Expansion Platform Design Types I and II', the latter demonstrated with a first example, 'PANGEA: Personalized Anti-Neoplastics for Gastro-Esophageal Adenocarcinoma'. Applying integral medium-throughput genomic and proteomic assays along with a practical biomarker assessment and treatment algorithm, 'PANGEA' attempts to address the problem of heterogeneity towards successful implementation of molecularly targeted therapies.

Cancer vaccines

Cancer vaccines are designed to promote tumor specific immune responses, particularly cytotoxic CD8 positive T cells that are specific to tumor antigens. The earliest vaccines, which were developed in 1994-95, tested non-mutated, shared tumor associated antigens that had been shown to be immunogenic and capable of inducing clinical responses in a minority of people with late stage cancer. Technological developments in the past few years have enabled the investigation of vaccines that target mutated antigens that are patient specific. Several platforms for cancer vaccination are being tested, including peptides, proteins, antigen presenting cells, tumor cells, and viral vectors. Standard of care treatments, such as surgery and ablation, chemotherapy, and radiotherapy, can also induce antitumor immunity, thereby having cancer vaccine effects. The monitoring of patients' immune responses at baseline and after standard of care treatment is shedding light on immune biomarkers. Combination therapies are being tested in clinical trials and are likely to be the best approach to improving patient outcomes.

Circulating tumor cells: a multifunctional biomarker

One of the most promising developments in translational cancer medicine has been the emergence of circulating tumor cells (CTC) as a minimally invasive multifunctional biomarker. CTCs in peripheral blood originate from solid tumors and are involved in the process of hematogenous metastatic spread to distant sites for the establishment of secondary foci of disease. The emergence of modern CTC technologies has enabled serial assessments to be undertaken at multiple time points along a patient's cancer journey for pharmacodynamic (PD), prognostic, predictive, and intermediate endpoint biomarker studies. Despite the promise of CTCs as multifunctional biomarkers, there are still numerous challenges that hinder their incorporation into standard clinical practice. This review discusses the key technical aspects of CTC technologies, including the importance of assay validation and clinical qualification, and compares existing and novel CTC enrichment platforms. This article discusses the utility of CTCs as a multifunctional biomarker and focuses on the potential of CTCs as PD endpoints either directly via the molecular characterization of specific markers or indirectly through CTC enumeration. We propose strategies for incorporating CTCs as PD biomarkers in translational clinical trials, such as the Pharmacological Audit Trail. We also discuss issues relating to intrapatient heterogeneity and the challenges associated with isolating CTCs undergoing epithelial-mesenchymal transition, as well as apoptotic and small CTCs. Finally, we envision the future promise of CTCs for the selection and monitoring of antitumor precision therapies, including applications in single CTC phenotypic and genomic profiling and CTC-derived xenografts, and discuss the promises and limitations of such approaches. See ALL articles in this CCR focus section, "Progress in pharmacodynamic endpoints."

The changing landscape of phase I trials in oncology

KEY POINTS

Several aspects of phase I trials have evolved in the current era of molecular targeted agents to adapt to the changing nature of anticancer therapy and to increase the efficiency of drug development.

Current phase I designs are increasingly integrating novel dose-escalation approaches and biomarker-driven selection of patients, as well as expanding study objectives to include the evaluation of efficacy and pharmacodynamics/pharmacokinetics in addition to safety.

Changes to the regulatory approval process have helped to expedite drug development, particularly for novel agents with a strong biologic rationale and proof of concept, validated predictive biomarker, and clear evidence of efficacy in early trials.

As a result of the substantial changes in phase I trial goals and conduct, there is a parallel shift toward multi-institutional trials and central study management by clinical research organizations.

The use of multi-institutional trials has a significant impact on the structure of phase I programs and the experience of investigators, particularly because of limited patient enrollment at each site.

Recommendations for adaptation and validation of commercial kits for biomarker quantification in drug development

Increasingly, commercial immunoassay kits are used to support drug discovery and development. Longitudinally consistent kit performance is crucial, but the degree to which kits and reagents are characterized by manufacturers is not standardized, nor are the approaches by users to adapt them and evaluate their performance through validation prior to use. These factors can negatively impact data quality. This paper offers a systematic approach to assessment, method adaptation and validation of commercial immunoassay kits for quantification of biomarkers in drug development, expanding upon previous publications and guidance. These recommendations aim to standardize and harmonize user practices, contributing to reliable biomarker data from commercial immunoassays, thus, enabling properly informed decisions during drug development.

Methodical and pre-analytical characteristics of a multiplex cancer biomarker immunoassay

AIM: To test the methodical and pre-analytical performance of a new multiplex cancer biomarker panel using magnetic beads.

METHODS: The MILLIPLEX^® MAP Human Circulating Cancer Biomarker Magnetic Bead Panel 1 comprises the tumor markers carcinoembryonic antigen, alpha-fetoprotein, total prostate-specific antigen, cancer antigen 15-3, cancer antigen 19-9, cancer antigen 125, cytokeratine 19-fragment, β-human chorionic gonadotropin, human epididymis protein 4, osteopontin, prolactin, the cell death and angiogenesis markers soluble Fas, soluble Fas-ligand, tumor necrosis factor related apoptosis-inducing ligand, vascular endothelial growth factor and the immunological markers interleukin-6 (IL-6), IL-8, tumor necrosis factor-α, transforming growth factor α, fibroblast growth factor-2, macrophage migration inhibitory factor, leptin, hepatocyte growth factor, and stem cell factor. We determined intra- and inter-assay imprecision as well as dilution linearity using quality controls and serum pools. Furthermore, the stability of the 24 biomarkers examined in this panel was ascertained by testing the influence of different storage temperatures and time span before centrifugation.

RESULTS: For all markers measured in the synthetic internal quality controls, the intra-assay imprecision ranged between 2.26% and 9.41%, while for 20 of 24 measured markers in the physiological serum pools, it ranged between 1.68% and 12.87%. The inter-assay imprecision ranged between 1.48%-17.12% for 23 biomarkers in synthetic, and between 4.59%-23.88% for 18 biomarkers in physiological quality controls. Here, single markers with very low concentration levels had increased imprecision rates. Dilution linearity was acceptable (70%-130% recovery) for 20 biomarkers. Regarding pre-analytical influencing factors, most markers were stable if blood centrifugation was delayed or if serum was stored for up to 24 h at 4 °C and 25 °C after centrifugation. Comparable results were obtained in serum and plasma for most markers. However, great changes were observed for single markers.

CONCLUSION: MILLIPLEX^® MAP Human Circulating Cancer Biomarker Magnetic Bead Panel 1 assay is a stable and precise method for detection of most biomarkers included in the kit. However, single markers have to be interpreted with care.

A parallel-arm phase I trial of the humanised anti-IGF-1R antibody dalotuzumab in combination with the AKT inhibitor MK-2206, the mTOR inhibitor ridaforolimus, or the NOTCH inhibitor MK-0752, in patients with advanced solid tumours

Background:

Two strategies to interrogate the insulin growth factor 1 receptor (IGF-1R) pathway were investigated: vertical inhibition with dalotuzumab and MK-2206 or ridaforolimus to potentiate PI3K pathway targeting and horizontal cross-talk inhibition with dalotuzumab and MK-0752 to exert effects against cellular proliferation, angiogenesis, and stem cell propagation.

Methods:

A phase I, multi-cohort dose escalation study was conducted in patients with advanced solid tumours. Patients received dalotuzumab (10 mg kg^–1) and escalating doses of MK-2206 (90–200 mg) or escalating doses of dalotuzumab (7.5–10 mg kg^–1) and MK-0752 (1800 mg) weekly. Upon maximum tolerated dose determination, patients with low-RAS signature, high-IGF1 expression ovarian cancer were randomised to dalotuzumab/MK-2206 versus dalotuzumab/ridaforolimus, whereas patients with high IGF1/low IGF2 expression colorectal cancer received dalotuzumab/MK-0752.

Results:

A total of 47 patients were enrolled: 29 in part A (18 in the dalotuzumab/MK-2206 arm and 11 in the dalotuzumab/MK-0752 arm) and 18 in part B (6 in each arm). Dose-limiting toxicities (DLTs) for dalotuzumab/MK-2206 included grade 4 neutropenia and grade 3 serum sickness-like reaction, maculopapular rash, and gastrointestinal inflammation. For dalotuzumab/MK-0752, DLTs included grade 3 dehydration, rash, and diarrhoea. Seven patients remained on study for >4 cycles.

Conclusions:

Dalotuzumab/MK-2206 and dalotuzumab/MK-0752 combinations were tolerable. Further developments of prospectively validated predictive biomarkers to aid in patient selection for anti-IGF-1R therapies are needed.

UDP glucuronosyltransferase 1A expression levels determine the response of colorectal cancer cells to the heat shock protein 90 inhibitor ganetespib

HSP90 inhibition represents a promising route to cancer therapy, taking advantage of cancer cell-inherent proteotoxic stress. The HSP90-inhibitor ganetespib showed benefit in advanced clinical trials. This raises the need to identify the molecular determinants of treatment response. We tested the efficacy of ganetespib on a series of colorectal cancer (CRC)-derived cell lines and correlated their sensitivities with comprehensive gene expression analysis. Notably, the drug concentration required for 50% growth inhibition (IC₅₀) varied up to 70-fold (from 36 to 2500 nM) between different cell lines. Correlating cell line-specific IC₅₀s with the corresponding gene expression patterns revealed a strong association between ganetespib resistance (IC₅₀>500 nM) and high expression of the UDP glucuronosyltransferase 1A (UGT1A) gene cluster. Moreover, CRC tumor samples showed a comparable distribution of UGT1A expression levels. The members of the UGT1A gene family are known as drug-conjugating liver enzymes involved in drug excretion, but their function in tumor cells is hardly understood. Chemically unrelated HSP90 inhibitors, for example, 17-N-allylamino-17-demethoxygeldanamycin (17-AAG), did not show correlation of drug sensitivities with UGT1A levels, whereas the ganetespib-related compound NVP-AUY922 did. When the most ganetespib-resistant cell line, HT29, was treated with ganetespib, the levels of HSP90 clients were unaffected. However, HT29 cells became sensitized to the drug, and HSP90 client proteins were destabilized by ganetespib upon siRNA-mediated UGT1A knockdown. Conversely, the most ganetespib-sensitive cell lines HCT116 and SW480 became more tolerant toward ganetespib upon UGT1A overexpression. Mechanistically, ganetespib was rapidly glucuronidated and excreted in resistant but not in sensitive CRC lines. We conclude that CRC cell-expressed UGT1A inactivates ganetespib and other resorcinolic Hsp90 inhibitors by glucuronidation, which renders the drugs unable to inhibit Hsp90 and thereby abrogates their biological activity. UGT1A levels in tumor tissues may be a suitable predictive biomarker to stratify CRC patients for ganetespib treatment.

Tissue slide-based microRNA characterization of tumors: how detailed could diagnosis become for cancer medicine?

miRNAs are short, non-coding, regulatory RNAs that exert cell type-dependent, context-dependent, transcriptome-wide gene expression control under physiological and pathological conditions. Tissue slide-based assays provide qualitative (tumor compartment) and semi-quantitative (expression levels) information about altered miRNA expression at single-cell resolution in clinical tumor specimens. Reviewed here are key technological advances in the last 5 years that have led to implementation of fully automated, robust and reproducible tissue slide-based assays for in situ miRNA detection on US FDA-approved instruments; recent tissue slide-based discovery studies that suggest potential clinical applications of specific miRNAs in cancer medicine are highlighted; and the challenges in bringing tissue slide-based miRNA assays into the clinic are discussed, including clinical validation, biomarker performance, biomarker space and integration with other biomarkers.

A critical review of the analytical approaches for circulating tumor biomarker kinetics during treatment

Changes in serum tumor biomarkers may indicate treatment efficacy. Traditional tumor markers may soon be replaced by novel serum biomarkers, such as circulating tumor cells (CTCs) or circulating tumor nucleic acids. Given their promising predictive values, studies of their kinetics are warranted. Many methodologies meant to assess kinetics of traditional marker kinetics during anticancer treatment have been reported. Here, we review the methodologies, the advantages and the limitations of the analytical approaches reported in the literature. Strategies based on a single time point were first used (baseline value, normalization, nadir, threshold at a time t), followed by approaches based on two or more time points [half-life (HL), percentage decrease, time-to-events…]. Heterogeneities in methodologies and lack of consideration of inter- and intra-individual variability may account for the inconsistencies and the poor utility in routine. More recently, strategies based on a population kinetics approach and mathematical modeling have been reported. The identification of equations describing individual kinetic profiles of biomarkers may be an alternative strategy despite its complexity and higher number of necessary measurements. Validation studies are required. Efforts should be made to standardize biomarker kinetic analysis methodologies to ensure the optimized development of novel serum biomarkers and avoid the pitfalls of traditional markers.

Diffuse large B cell lymphoma: using pathologic and molecular biomarkers to define subgroups for novel therapy

Diffuse large B cell lymphoma (DLBCL) comprises specific subtypes, disease entities, and other not otherwise specified (NOS) lymphomas. This review will focus on DLBCL NOS because of their prevalence and their heterogeneity with respect to morphology, clinical presentation, biology, and response to treatment. Gene expression profiling of DLBCL NOS has identified molecular subgroups that correlate with prognosis and may have relevance for treatment based on signaling pathways. New technologies have revealed that the "activated B cell" subgroup is linked to activation of the nuclear factor kB (NF-kB) pathway, with mutations found in CD79A/B, CARD11, and MYD88, and loss of function mutations in TNFAIP3. The "germinal center B cell-like" subgroup is linked to mutational changes in EZH2 and CREBBP. Biomarkers that are related to pathways promoting tumor cell growth and survival in DLBCL have been recognized, although their predictive role requires clinical validation. Immunohistochemistry for detecting the expression of these biomarkers is a practical technique that could provide a rational for clinical trial design.

What could Nintedanib (BIBF 1120), a triple inhibitor of VEGFR, PDGFR, and FGFR, add to the current treatment options for patients with metastatic colorectal cancer?

Increasing knowledge of the pro-angiogenic processes involved in the progression of metastatic colorectal cancer (mCRC) has resulted in the clinical development of several anti-angiogenic agents, with bevacizumab currently being the only approved agent for mCRC. Nintedanib (BIBF 1120) has been shown to block the vascular endothelial growth factor receptor (VEGFR), the platelet-derived growth factor receptor (PDGFR), and the fibroblast growth factor receptor (FGFR). By targeting FGFR signaling, nintedanib may overcome resistance to previous anti-VEGF treatments, and may represent a better approach in patients with high basal levels of circulating FGFs. In this article, the angiogenic mechanisms implicated in mCRC are reviewed (focusing on the signaling pathways activated by VEGFR, PDGFR, and FGFR), along with the clinical data for nintedanib in the context of other anti-angiogenic tyrosine kinase inhibitors under clinical development for mCRC. Biomarkers that could predict response to nintedanib are also discussed.

Biomarker-based Bayesian randomized phase II clinical trial design to identify a sensitive patient subpopulation

The benefits and challenges of incorporating biomarkers into the development of anticancer agents have been increasingly discussed. In many cases, a sensitive subpopulation of patients is determined based on preclinical data and/or by retrospectively analyzing clinical trial data. Prospective exploration of sensitive subpopulations of patients may enable us to efficiently develop definitively effective treatments, resulting in accelerated drug development and a reduction in development costs. We consider the development of a new molecular-targeted treatment in cancer patients. Given preliminary but promising efficacy data observed in a phase I study, it may be worth designing a phase II clinical trial that aims to identify a sensitive subpopulation. In order to achieve this goal, we propose a Bayesian randomized phase II clinical trial design incorporating a biomarker that is measured on a graded scale. We compare two Bayesian methods, one based on subgroup analysis and the other on a regression model, to analyze a time-to-event endpoint such as progression-free survival (PFS) time. The two methods basically estimate Bayesian posterior probabilities of PFS hazard ratios in biomarker subgroups. Extensive simulation studies evaluate these methods' operating characteristics, including the correct identification probabilities of the desired subpopulation under a wide range of clinical scenarios. We also examine the impact of subgroup population proportions on the methods' operating characteristics. Although both methods' performance depends on the distribution of treatment effect and the population proportions across patient subgroups, the regression-based method shows more favorable operating characteristics.

Impact of biomarkers on clinical trial risk

The last decade has witnessed the cost of drug development rise dramatically; concurrently, the number of new drug approvals has declined. Clinical trial failure rates have contributed significantly to this 'innovation' crisis and are directly related to clinical trial risk. One strategy that is often touted to resolve this challenge depends on embracing a personalized medicine approach where treatment is tailored to a patient's unique genetic background. We highlight a new risk-based paradigm of clinical trial risk that evaluates the utility of biomarkers in drug development and their risk mitigation benefits. Furthermore, examples elucidating the current state of biomarker integration during clinical trials and the potential risks posed by doing so will be discussed.

A knowledge-driven approach to extract disease-related biomarkers from the literature

The biomedical literature represents a rich source of biomarker information. However, both the size of literature databases and their lack of standardization hamper the automatic exploitation of the information contained in these resources. Text mining approaches have proven to be useful for the exploitation of information contained in the scientific publications. Here, we show that a knowledge-driven text mining approach can exploit a large literature database to extract a dataset of biomarkers related to diseases covering all therapeutic areas. Our methodology takes advantage of the annotation of MEDLINE publications pertaining to biomarkers with MeSH terms, narrowing the search to specific publications and, therefore, minimizing the false positive ratio. It is based on a dictionary-based named entity recognition system and a relation extraction module. The application of this methodology resulted in the identification of 131,012 disease-biomarker associations between 2,803 genes and 2,751 diseases, and represents a valuable knowledge base for those interested in disease-related biomarkers. Additionally, we present a bibliometric analysis of the journals reporting biomarker related information during the last 40 years.

Current and future molecular diagnostics in colorectal cancer and colorectal adenoma

Colorectal cancer (CRC) is one of the most prevalent cancers in developed countries. On the other hand, CRC is also one of the most curable cancers if it is detected in early stages through regular colonoscopy or sigmoidoscopy. Since CRC develops slowly from precancerous lesions, early detection can reduce both the incidence and mortality of the disease. Fecal occult blood test is a widely used non-invasive screening tool for CRC. Although fecal occult blood test is simple and cost-effective in screening CRC, there is room for improvement in terms of the accuracy of the test. Genetic dysregulations have been found to play an important role in CRC development. With better understanding of the molecular basis of CRC, there is a growing expectation on the development of diagnostic tests based on more sensitive and specific molecular markers and those tests may provide a breakthrough to the limitations of current screening tests for CRC. In this review, the molecular basis of CRC development, the characteristics and applications of different non-invasive molecular biomarkers, as well as the technologies available for the detection were discussed. This review intended to provide a summary on the current and future molecular diagnostics in CRC and its pre-malignant state, colorectal adenoma.

Mammalian target of rapamycin (mTOR) inhibitor-associated non-infectious pneumonitis in patients with renal cell cancer: predictors, management, and outcomes

OBJECTIVE

To characterise the incidence, onset, management, predictors, and clinical impact of mammalian target of rapamycin (mTOR) inhibitor-associated non-infectious pneumonitis (NIP) on patients with metastatic renal cell carcinoma (mRCC).

PATIENTS AND METHODS

Retrospective review of 310 patients with mRCC who received temsirolimus and/or everolimus between June 2007 and October 2010. Clinical correlations were made with serial radiological imaging. Fisher's exact, Wilcoxon rank-sum, and logistic regression analyses were used to evaluate the association of NIP with demographic or clinical factors. Log-rank and Cox proportional hazards regression analyses were used for the time-to-event analysis.

RESULTS

NIP occurred in 6% of temsirolimus-treated and 23% of everolimus-treated patients. Symptoms included cough, dyspnoea, and fever (median of two and three symptoms per patient, respectively). The median National Cancer Institute Common Toxicity Criteria for Adverse Events pneumonitis grade was 2 for both groups. Older age and everolimus treatment were predictive of NIP. Patients who developed NIP had a significantly longer time on treatment (median 4.1 vs 2 months) and overall survival (OS) (median 15.4 vs 7.4 months). NIP was a predictor of improved OS by multivariate analysis.

CONCLUSIONS

There was an increased incidence of NIP in everolimus-treated patients. Improved OS in patients who developed NIP is an intriguing finding and should be further investigated. Given the incidence, morbidity, and outcomes seen in patients on everolimus who develop NIP, management should include proactive monitoring and treatment of NIP with the goal of preserving mTOR inhibitor therapy.