Biomarker-Driven Early Clinical Trials in Oncology: A Paradigm Shift in Drug Development

A quantitative systems pharmacology workflow toward optimal design and biomarker stratification of atopic dermatitis clinical trials

BACKGROUND

The development of atopic dermatitis (AD) drugs is challenged by many disease phenotypes and trial design options, which are hard to explore experimentally.

OBJECTIVE

We aimed to optimize AD trial design using simulations.

METHODS

We constructed a quantitative systems pharmacology model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution was derived from known relationships between AD biomarkers and disease severity and calibrated using disease severity evolution under SoC regimens.

RESULTS

We applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated the investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example the choice of end point is more important than the choice of dosing regimen and patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis revealed that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual population.

CONCLUSIONS

This AD quantitative systems pharmacology workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases to optimize several trial protocol parameters and biomarker stratification and therefore has promise to become a powerful model-informed AD drug development and personalized medicine tool.

Overcoming Lot-to-Lot Variability in Protein Activity Using Epitope-Specific Calibration-Free Concentration Analysis

Concentration determination is a fundamental hallmark of protein reagent characterization, providing a means to ensure reproducibility and unify measurements from various assays. However, lot-to-lot differences in protein activity often still occur, leading to uncertainty in the accuracy of downstream measurements. Here, we postulate that those differences are caused by a misrepresentation of the protein concentration as measured by traditional total protein techniques, which can include multiple types of inactive protein species. To overcome this, we developed a standardized method to quantify a protein's active concentration via calibration-free concentration analysis (CFCA). As a pilot study, we compare the biophysical and immunoassay responses from three batches of recombinant soluble lymphocyte-activation gene 3 (sLAG3), as defined by either their total or active concentrations. Defining the sLAG3 reagents by their assay-specific concentration improved consistency in reported kinetic binding parameters and decreased immunoassay lot-to-lot coefficients of variation (CVs) by over 600% compared to the total protein concentration. These findings suggest that the total concentration of a protein reagent may not be the ideal metric to correlate in-assay signals between lots, and by instead quantifying the concentrations of a reagent's assay-specific epitopes, CFCA may prove a useful tool in overcoming lot-to-lot variability.

Targeting Breast Cancer Signaling via Phytomedicine and Nanomedicine

BACKGROUND

The development of breast cancer (BC) and how it responds to treatment have both been linked to the involvement of inflammation. Chronic inflammation is critical in carcinogenesis, leading to elevated DNA damage, impaired DNA repair machinery, cell growth, apoptosis, angiogenesis, and invasion. Studies have found several targets that selectively modulate inflammation in cancer, limit BC's growth, and boost treatment effectiveness. Drug resistance and the absence of efficient therapeutics for metastatic and triple-negative BC contribute to the poor outlook of BC patients.

SUMMARY

To treat BC, small-molecule inhibitors, phytomedicines, and nanoparticles are conjugated to attenuate BC signaling pathways. Due to their numerous target mechanisms and strong safety records, phytomedicines and nanomedicines have received much attention in studies examining their prospects as anti-BC agents by such unfulfilled demands.

KEY MESSAGES

The processes involved in the affiliation across the progression of tumors and the spread of inflammation are highlighted in this review. Furthermore, we included many drugs now undergoing clinical trials that target cancer-mediated inflammatory pathways, cutting-edge nanotechnology-derived delivery systems, and a variety of phytomedicines that presently address BC.

Pharmacogenetics of Anticancer Drugs: Clinical Response and Toxicity

Cancer is the most challenging disease for medical professionals to treat. The factors underlying the complicated situation include anticancer drug-associated toxicity, non-specific response, low therapeutic window, variable treatment outcomes, development of drug resistance, treatment complications, and cancer recurrence. The remarkable advancement in biomedical sciences and genetics, over the past few decades, however, is changing the dire situation. The discovery of gene polymorphism, gene expression, biomarkers, particular molecular targets and pathways, and drug-metabolizing enzymes have paved the way for the development and provision of targeted and individualized anticancer treatment. Pharmacogenetics is the study of genetic factors having the potential to affect clinical responses and pharmacokinetic and pharmacodynamic behaviors of drugs. This chapter emphasizes pharmacogenetics of anticancer drugs and its applications in improving treatment outcomes, selectivity, toxicity of the drugs, and discovering and developing personalized anticancer drugs and genetic methods for prediction of drug response and toxicity.

PDI inhibitor LTI6426 enhances panobinostat efficacy in preclinical models of multiple myeloma

The histone deacetylase inhibitor (HDACi), panobinostat (Pano), is approved by the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA) for treatment of relapsed/refractory multiple myeloma (MM). Despite regulatory approvals, Pano is used on a limited basis in MM due largely to an unfavorable toxicity profile. The MM treatment landscape continues to evolve, and for Pano to maintain a place in that paradigm it will be necessary to identify treatment regimens that optimize its effectiveness, particularly those that permit dose reductions to eliminate unwanted toxicity. Here, we propose such a regimen by combining Pano with LTI6426, a first-in-class orally bioavailable protein disulfide isomerase (PDI) inhibitor. We show that LTI6426 dramatically enhances the anti-MM activity of Pano in vitro and in vivo using a proteasome inhibitor resistant mouse model of MM and a low dose of Pano that exhibited no signs of toxicity. We go on to characterize a transcriptional program that is induced by the LTI6426/Pano combination, demonstrating a convergence of the two drugs on endoplasmic reticulum (ER) stress pathway effectors ATF3 (Activating Transcription Factor 3), DDIT3/CHOP (DNA Damage Inducible Transcript 3, a.k.a. C/EBP Homologous Protein), and DNAJB1 (DnaJ homolog subfamily B member 1, a.k.a. HSP40). We conclude that LTI6426 may safely enhance low-dose Pano regimens and that ATF3, DDIT3/CHOP, and DNAJB1 are candidate pharmacodynamic biomarkers of response to this novel treatment regimen.

Graphene and graphene oxide with anticancer applications: Challenges and future perspectives

Graphene-based materials have shown immense pertinence for sensing/imaging, gene/drug delivery, cancer therapy/diagnosis, and tissue engineering/regenerative medicine. Indeed, the large surface area, ease of functionalization, high drug loading capacity, and reactive oxygen species induction potentials have rendered graphene- (G-) and graphene oxide (GO)-based (nano)structures promising candidates for cancer therapy applications. Various techniques namely liquid-phase exfoliation, Hummer's method, chemical vapor deposition, chemically reduced GO, mechanical cleavage of graphite, arc discharge of graphite, and thermal fusion have been deployed for the production of G-based materials. Additionally, important criteria such as biocompatibility, bio-toxicity, dispersibility, immunological compatibility, and inflammatory reactions of G-based structures need to be systematically assessed for additional clinical and biomedical appliances. Furthermore, surface properties (e.g., lateral dimension, charge, corona influence, surface structure, and oxygen content), concentration, detection strategies, and cell types are vital for anticancer activities of these structures. Notably, the efficient accumulation of anticancer drugs in tumor targets/tissues, controlled cellular uptake properties, tumor-targeted drug release behavior, and selective toxicity toward the cells are crucial criteria that need to be met for developing future anticancer G-based nanosystems. Herein, important challenges and future perspectives of cancer therapy using G- and GO-based nanosystems have been highlighted, and the recent advancements are deliberated.

Precision patients: Selection practices and moral pathfinding in experimental oncology

This paper addresses selection practices in a Danish phase 1 unit specialised in precision medicine in the field of oncology. Where precision medicine holds the ambition of selecting genetically fit medicine for the patient, we find that precision medicine in the early trial setting is oriented towards selecting clinically and genetically fit patients for available treatment protocols. Investigating how phase 1 oncologists experience and respond to the moral challenges of selecting patients for early clinical trials, we show that inclusion criteria and patient categories are not always transparent to patients. Lack of transparency about inclusion criteria has been interpreted as morally problematic. Yet drawing on social science studies of 'unknowing', we argue that silence and non-transparency in interactions between oncologists and patients are crucial to respect the moral agency of patients at the edge of life and recognise them as belonging to the public of Danish health care. In the discussion, we consider the practice of placing 'unfit' patients on a waiting list for trial participation. Rather than representing an ethical and political problem, we argue, the waiting list can act as a valve enabling oncologists to navigate the scientific and as well as the moral uncertainties in phase 1 oncology.

MXenes in photomedicine: Advances and prospects

MXenes and their related nanocomposites with superior physicochemical properties such as high surface area, ease of synthesis and functionalization, high drug loading capacity, collective therapy potentials, pH-triggered drug release behavior,...

Patient Knowledge and Expectations About Return of Genomic Results in a Biomarker-Driven Master Protocol Trial (SWOG S1400GEN)

PURPOSE

Biomarker-driven master protocols represent a new paradigm in oncology clinical trials, but their complex designs and wide-ranging genomic results returned can be difficult to communicate to participants. The objective of this pilot study was to evaluate patient knowledge and expectations related to return of genomic results in the Lung Cancer Master Protocol (Lung-MAP).

METHODS

Eligible participants with previously treated advanced non-small-cell lung cancer were recruited from patients enrolled in Lung-MAP. Participants completed a 38-item telephone survey ≤ 30 days from Lung-MAP consent. The survey assessed understanding about the benefits and risks of Lung-MAP participation and knowledge of the potential uses of somatic testing results returned. Descriptive statistics and odds ratios for associations between demographic factors and correct responses to survey items were assessed.

RESULTS

From August 1, 2017, to June 30, 2019, we recruited 207 participants with a median age of 67, 57.3% male, and 94.2% White. Most participants "strongly/somewhat agreed" with statements that they "received enough information to understand" Lung-MAP benefits (82.6%) and risks (69.5%). In items asking about potential uses of Lung-MAP genomic results, 87.0% correctly indicated that the results help to select cancer treatment, but < 20% correctly indicated that the results are not used to confirm cancer diagnosis, would not reveal risk of developing diseases besides cancer, and would not indicate if family members had increased cancer risk. There were no associations between sociodemographic factors and proportions providing correct responses.

CONCLUSION

In a large National Clinical Trials Network biomarker-driven master protocol, most participants demonstrated incorrect knowledge and expectations about the uses of genomic results provided in the study despite most indicating that they had enough information to understand benefits and risks.

Identification of putative actionable alterations in clinically relevant genes in breast cancer

BACKGROUND

Individualising treatment in breast cancer requires effective predictive biomarkers. While relatively few genomic aberrations are clinically relevant, there is a need for characterising patients across different subtypes to identify actionable alterations.

METHODS

We identified genomic alterations in 49 potentially actionable genes for which drugs are available either clinically or via clinical trials. We explored the landscape of mutations and copy number alterations (CNAs) in actionable genes in seven breast cancer subtypes utilising The Cancer Genome Atlas. To dissect the genomic complexity, we analysed the patterns of co-occurrence and mutual exclusivity in actionable genes.

RESULTS

We found that >30% of tumours harboured putative actionable events that are targetable by currently available drugs. We identified genes that had multiple targetable alterations, representing candidate targets for combination therapy. Genes predicted to be drivers in primary breast tumours fell into five categories: mTOR pathway, immune checkpoints, oestrogen signalling, tumour suppression and DNA damage repair. Our analysis also revealed that CNAs in 34/49 (69%) and mutations in 13/49 (26%) genes were significantly associated with gene expression, validating copy number events as a dominant oncogenic mechanism in breast cancer.

CONCLUSION

These results may enable the acceleration of personalised therapy and improve clinical outcomes in breast cancer.

Modern Challenges for Early-Phase Clinical Trial Design and Biomarker Discovery in Metastatic Non-Small-Cell Lung Cancer

Oncology research has changed extensively due to the possibility to categorize each cancer type into smaller subgroups based on histology and particularly on different genetic alterations due to their heterogeneity. The consequences of this heterogeneity are particularly evident in the management of metastatic non-small-cell lung cancer (NSCLC). This review will discuss the benefits and challenges of incorporating precision medicine into early- through late-phase metastatic NSCLC clinical trials, discussing examples of drug development programs in oncogene- and non-oncogene-addicted NSCLC. The experiences of clinical development of crizotinib, gefitinib and osimertinib are depicted showing that when a targeted drug is administrated in a study population not selected by any biomarker, trials could produce negative results. However, the early detection of biomarker-driven biology helps to obtain a greater benefit for a selected population and can reduce the required time for drug approval. Early clinical development programs involving nivolumab, pembrolizumab and avelumab, immune checkpoint inhibitors, taught us that, beyond safety and activity, the optimal selection of patients should be based on pre-specified biomarkers. Overall, the identification of predictive biomarkers is one of the greatest challenges of NSCLC research that should be optimized with solid methodological trial designs to maximize the clinical outcomes.

MXenes for Cancer Therapy and Diagnosis: Recent Advances and Current Challenges

MXenes endowed with several attractive physicochemical attributes, namely, specific large surface area, significant electrical conductivity, magnetism, low toxicity, luminescence, and high biocompatibility, have been considered as promising candidates for cancer therapy and theranostics. These two-dimensional (2D) nanostructures endowed with photothermal, chemotherapeutic synergistic, and photodynamic effects have shown promising potential for decidedly effectual and noninvasive anticancer treatments. They have been explored for photothermal/chemo-photothermal therapy (PTT) and for targeted anticancer drug delivery. Remarkably, MXenes with their unique optical properties have been employed for bioimaging and biosensing, and their excellent light-to-heat transition competence renders them an ideal biocompatible and decidedly proficient nanoscaled agent for PTT appliances. However, several important challenging issues still linger regarding their stability in physiological environments, sustained/controlled release of drugs, and biodegradability that need to be addressed. This Perspective emphasizes the latest advancements of MXenes and MXene-based materials in the domain of targeted cancer therapy/diagnosis, with a focus on the current trends, important challenges, and future perspectives.

Lignin, lipid, protein, hyaluronic acid, starch, cellulose, gum, pectin, alginate and chitosan-based nanomaterials for cancer nanotherapy: Challenges and opportunities

Although nanotechnology-driven drug delivery systems are relatively new, they are rapidly evolving since the nanomaterials are deployed as effective means of diagnosis and delivery of assorted therapeutic agents to targeted intracellular sites in a controlled release manner. Nanomedicine and nanoparticulate drug delivery systems are rapidly developing as they play crucial roles in the development of therapeutic strategies for various types of cancer and malignancy. Nevertheless, high costs, associated toxicity and production of complexities are some of the critical barriers for their applications. Green nanomedicines have continually been improved as one of the viable approaches towards tumor drug delivery, thus making a notable impact on which considerably affect cancer treatment. In this regard, the utilization of natural and renewable feedstocks as a starting point for the fabrication of nanosystems can considerably contribute to the development of green nanomedicines. Nanostructures and biopolymers derived from natural and biorenewable resources such as proteins, lipids, lignin, hyaluronic acid, starch, cellulose, gum, pectin, alginate, and chitosan play vital roles in the development of cancer nanotherapy, imaging and management. This review uncovers recent investigations on diverse nanoarchitectures fabricated from natural and renewable feedstocks for the controlled/sustained and targeted drug/gene delivery systems against cancers including an outlook on some of the scientific challenges and opportunities in this field. Various important natural biopolymers and nanomaterials for cancer nanotherapy are covered and the scientific challenges and opportunities in this field are reviewed.

Association Between the Size and 3D CT-Based Radiomic Features of Breast Cancer Hepatic Metastasis

PURPOSE

To evaluate the effect of the anatomic size on 3D radiomic imaging features of the breast cancer hepatic metastases.

MATERIALS AND METHODS

CT scans of 81 liver metastases from 54 patients with breast cancer were evaluated. Ten most common 3D radiomic features from the histogram and gray level co-occurrence matrix (GLCM) categories were calculated for the hepatic metastases (HM) and compared to normal liver (NL). The effect of size was evaluated by using linear mixed-effects regression models. The effect of size on different radiomic features was analyzed for both liver lesions and background liver.

RESULTS

Three-dimensional radiomic features from GLCM demonstrate an important size dependence. The texture-feature size dependence was found to be different among feature categories and between the HM and NL, thus demonstrating a discriminatory power for the tissue type. Significant difference in the slope was found for GLCM homogeneity (NL slope = 0.004, slope difference 95% confidence interval [CI] 0.06-0.1, p <0.001), contrast (NL slope = 45, slope difference 95% CI 205-305, p <0.001), correlation (NL slope = 0.04, slope difference 95% CI 0.11-0.21, p <0.001), and dissimilarity (NL slope = 0.7, slope difference 95% CI 3.6-5.4, p <0.001). The GLCM energy (NL slope = 0.002, slope difference 95% CI -0.0005 to -0.0003, p <0.007), and entropy (NL slope = 1.49, slope difference 95% CI 0.07-0.52, p <0.009) exhibited size-dependence for both NL and HM, although demonstrating a difference in the slope between themselves.

CONCLUSION

Radiomic features of breast cancer hepatic metastasis exhibited significant correlation with tumor size. This finding demonstrates the complex behavior of imaging features and the need to include feature-specific properties into radiomic models.

Low participation rates and disparities in participation in interventional clinical trials for myelodysplastic syndromes

BACKGROUND

The development of novel therapies for the myelodysplastic syndromes (MDS) is hampered by inadequate trial recruitment. Factors contributing to low trial accrual are incompletely understood.

METHODS

This study analyzed a pooled patient database from institutions of the US MDS Clinical Research Consortium to compare the characteristics of participants in interventional trials with those of patients who did not enroll in a trial.

RESULTS

Data were identified for 1919 patients with MDS, and 449 of these patients (23%) participated in an interventional clinical trial. The median age of all patients was 68 years, and 64% were male. Patients who participated in trials were significantly younger than nonparticipants (P = .014), and men were more likely to participate in a trial (71% of trial participants were male, whereas 61% of nonparticipants were; P < .001). Race and ethnicity were not associated with trial enrollment. Patients in more affluent ZIP codes had a higher participation rate (P < .001). Patients with intermediate- and high-risk disease according to the revised International Prognostic Scoring System were overrepresented (P = .004), and trial participants less frequently had treatment-related disease (P < .001). In multivariable analyses, participation in a clinical trial was associated with a reduced hazard of death (P = .004). Even at large referral centers, only a minority of patients with MDS enrolled in interventional trials.

CONCLUSIONS

Restrictive trial eligibility criteria that exclude patients with MDS on account of age, comorbidities, or a history of another cancer are limit enrollment of MDS patients to clinical trials. Gaining insight into the barriers to trial accrual may help investigators and study sponsors to design trials that will accrue more rapidly and augment treatment options for patients with MDS.

The ProBio trial: molecular biomarkers for advancing personalized treatment decision in patients with metastatic castration-resistant prostate cancer

BACKGROUND

Multiple therapies exist for patients with metastatic castration-resistant prostate cancer (mCRPC). However, their improvement on progression-free survival (PFS) remains modest, potentially explained by tumor molecular heterogeneity. Several prognostic molecular biomarkers have been identified for mCRPC that may have predictive potential to guide treatment selection and prolong PFS. We designed a platform trial to test this hypothesis.

METHODS

The Prostate-Biomarker (ProBio) study is a multi-center, outcome-adaptive, multi-arm, biomarker-driven platform trial for tailoring treatment decisions for men with mCRPC. Treatment decisions in the experimental arms are based on biomarker signatures defined as mutations in certain genes/pathways suggested in the scientific literature to be important for treatment response in mCRPC. The biomarker signatures are determined by targeted sequencing of circulating tumor and germline DNA using a panel specifically designed for mCRPC.

DISCUSSION

Patients are stratified based on the sequencing results and randomized to either current clinical practice (control), where the treating physician decides treatment, or to molecularly driven treatment selection based on the biomarker profile. Outcome-adaptive randomization is implemented to early identify promising treatments for a biomarker signature. Biomarker signature-treatment combinations graduate from the platform when they demonstrate 85% probability of improving PFS compared to the control arm. Graduated combinations are further evaluated in a seamless confirmatory trial with fixed randomization. The platform design allows for new drugs and biomarkers to be introduced in the study.

CONCLUSIONS

The ProBio design allows promising treatment-biomarker combinations to quickly graduate from the platform and be confirmed for rapid implementation in clinical care.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT03903835. Date of registration: April 4, 2019. Status: Recruiting.

Integrated Biobanking and Tumor Model Establishment of Human Colorectal Carcinoma Provides Excellent Tools for Preclinical Research

Over the time period from 2006 to 2017, consecutive patients operated on at the University Medical Center Rostock participated in the comprehensive biobanking and tumor-modelling approach known as the HROC collection. Samples were collected using strict standard operating procedures including blood (serum and lymphocytes), tumor tissue (vital and snap frozen), and adjacent normal epithelium. Patient and tumor data including classification, molecular type, clinical outcome, and results of the model establishment are the essential pillars. Overall, 149 patient-derived xenografts with 34 primary and 35 secondary cell lines were successfully established and encompass all colorectal carcinoma anatomic sites, grading and staging types, and molecular classes. The HROC collection represents one of the largest model assortments from consecutive clinical colorectal carcinoma (CRC) cases worldwide. Statistical analysis identified a variety of clinicopathological and molecular factors associated with model success in univariate analysis. Several of them not identified before include localization, mutational status of K-Ras and B-Raf, MSI-status, and grading and staging parameters. In a multivariate analysis model, success solely correlated positively with the nodal status N1 and mutations in the genes K-Ras and B-Raf. These results imply that generating CRC tumor models on the individual patient level is worth considering especially for advanced tumor cases with a dismal prognosis.

New designs in early clinical drug development

The availability of an unprecedented massive amount of data has provided a magnificent window of opportunity for the development of new drugs. There are currently more drugs in development targeting cancer than any other disease. While this has brought us new waves of drugs, the counterpart is that with these new molecules we have different mechanisms of action, drug kinetics and dynamics, response types and toxicity profiles, which impair classical early clinical trial designs from being effective and efficient. What we once treated as a 'one-size-fits-all' homogeneous disease, has now been uncovered to be a rather heterogeneous condition with multiple targetable mutations. As this generates endless scenarios, it will be impossible to design single 'me-too' trials for every different disease, target, biomarker and agent. To overcome this, we must focus on improving early phase studies, undoubtedly the most critical step from bench to bedside. Goals include decreasing clinical development times, lowering research and development costs and optimizing decisions in advancing through the several phases with a higher degree of certainty in exchange for less failed attempts. We need more informative and, really, transformative early phase designs that seek to obtain the typical late phase objectives in a time continuum and to allow for more robust and efficient go/no-go decisions. With this in mind, different classes of drugs seem to fit with different designs, which present solutions to the different challenges that they pose after finding the maximum tolerated dose/optimum biological dose. This article reviews these concepts and designs and how they can adapt to this new reality in early phase investigation.

Agreement Between the European Organization for Research and Treatment of Cancer and Positron Emission Tomography Response Criteria in Solid Tumors in Evaluating Treatment Response in Solid Malignant Tumors

Introduction Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-CT) is used for non-invasive staging and restaging of solid malignant tumors. PET-CT based criteria have been developed to evaluate the response to targeted therapy. These include the European Organization for Research and Treatment of Cancer (EORTC) and the PET Response Criteria in Solid Tumors (PERCIST). The aim of this study was to determine the agreement between EORTC and PERCIST criteria for treatment response evaluation in patients with solid malignant tumors. Materials and methods This was a retrospective study conducted from February 2017 till July 2017. Electronic medical records of patients diagnosed with solid malignant tumors were searched. Experienced radiologists evaluated the PET-CT images based on EORTC and PERCIST criteria. The Kappa (κ) test was used for evaluation of agreement between treatment response according to EORTC and PERCIST criteria. Results Out of 54 patients, 41 (75.9%) were male and 13 (24.1%) were female with a mean age of 57.09 ± 10.65 years. According to EORTC criteria, complete metabolic response (CMR) was seen in five (9.3%) of patients, partial metabolic response (PMR) was seen in 36 (66.7%) of patients, progressive metabolic disease (PMD) was seen in nine (16.7%) of patients and stable metabolic disease (SMD) was seen in four (7.4%) of patients. According to PERCIST criteria, CMR was seen in five (9.3%) of patients, PMR was seen in 33 (61.1%) of patients, PMD was seen in nine (16.7%) of patients and SMD was seen in seven (13.0%) of patients. EORTC and PERCIST agreed on 43 (79.6%) of the patients with κ-coefficient of 0.62 indicating good agreement (p-value of <0.001). Conclusion EORTC and PERCIST criteria have a good agreement in evaluating treatment response in solid malignant tumors. Therefore, adoption of EORTC or PERCIST in PET-CT reporting can standardize the evaluation of oncological treatment results.

Cell-free DNA in cancer: current insights

BACKGROUND

The field of liquid biopsies in oncology is rapidly expanding, with the application of cell-free circulating tumour DNA (ctDNA) showing promise in this era of precision medicine. Compared with traditional clinical and radiographic tumour monitoring methods, the analysis of ctDNA provides a minimally-invasive and technically feasible approach to assess temporal and spatial molecular evolutions of the tumour landscape. The constantly advancing technological platforms available for ctDNA extraction and analysis allow greater analytical sensitivities than ever before. The potential translational impact of ctDNA as a blood-based biomarker for the identification, characterization and monitoring of cancer has been demonstrated in numerous proof-of-concept studies, with ctDNA analysis beginning to be applied clinically across multiple facets of oncology.

CONCLUSIONS

In this review we discuss the biology, recent advancements, technical considerations and clinical implications of ctDNA in the context of cancer, and highlight important challenges and future directions for the integration of ctDNA into standardised patient care.

Arrayed microfluidic chip for detection of circulating tumor cells and evaluation of drug potency

Circulating tumor cells (CTCs) from peripheral blood of cancer patients are considered as one of the most promising pharmacodynamic (PD) biomarkers due to its non-invasive property in disease diagnosis and prognosis. However, the detection of extremely low number of CTCs in patient blood requires methods with high sensitivity and accuracy. We fabricated an arrayed geometrically enhanced mixing (GEM) chip with a "dislocation herringbone" layout based on cell immunoaffinity. By optimizing the injection and rinsing flow rate, an average cell capture rate of 87.02% and an average capture purity of 99.58% were achieved using the human lung adenocarcinoma cell lines H1975. In addition, we determined the specificity, precision, accuracy, and detection limit of our chip. The results demonstrated the chip was stable, accurate and reliable for the "liquid biopsy" of lung cancer cells using the peripheral blood of patients. Our chip can also be used to evaluate the potency of different drugs against tumor cells in parallel due to the presence of four independent microchannels.

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses.

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

Apparent Diffusion Coefficient Value to Evaluate Tumor Response After Neoadjuvant Chemotherapy in Patients with Breast Cancer

RATIONALE AND OBJECTIVES

This study explored tumor behavior in patients with breast cancer during neoadjuvant chemotherapy (NAC) by sequential measurements of tumor apparent diffusion coefficient (ADC) after each chemotherapy cycle. The aim was to determine if the tumor ADC is useful to differentiate complete pathological response (cPR) from partial pathological response (pPR) during NAC.

MATERIALS AND METHODS

A total of 16 cases (in 14 patients) with diagnosis of breast cancer eligible to receive NAC were included. There were 70 magnetic resonance imaging examinations performed, 5 for each patient, during NAC cycles. Diffusion-weighted imaging was performed on a 1.5T system (b values of 0 and 700s/mm²). Four ADC ratios between the five MRI examinations were obtained to assess ADC changes during NAC. Absence of invasive breast cancer at surgical specimens (Miller-Payne 5) was considered as cPR and was used as reference for ADC cutoff ratios.

RESULTS

In this study, we were able to differentiate between cPR and pPR, after two cycles of NAC until the end of NAC before surgery (ADC ratios 2-4). The thresholds to differentiate between cPR and pPR of ADC ratios 2, 3, and 4, were 1.14 × 10^-3mm²/s, 1.08 × 10^-3mm²/s, and 1.25 × 10^-3mm²/s, respectively, and have a cross-validated sensitivity and specificity of 79.2%, 79.7% (ADC ratio 2); 100%, 66.7% (ADC ratio 3); and 100%, 83.8% (ADC ratio 4), respectively.

CONCLUSIONS

The ADC ratios were useful to differentiate cPR from pPR in breast cancer tumors after NAC. Thus, it may be useful in tailoring treatment in these patients.

Biologic Impact and Clinical Implication of mTOR Inhibition in Metastatic Breast Cancer

The goal of therapy for patients with metastatic breast cancer (MBC) is prolonging life and palliation of symptoms. Thus the preferred approach remains to use, at least initially, non-cytotoxic drugs. In hormone receptor-positive breast cancer the sequential use of single anti-estrogen drugs, e.g. tamoxifen, aromatase inhibitors, and many others is standard, but eventually drug resistance will lead to failure of these compounds and a switch to chemotherapy will be necessary. Reversing resistance to anti-estrogen therapy in MBC is one of the strategies to avoid and delay the use of cytotoxic compounds. The mammalian target of rapamycin (mTOR) has been recently associated with in vitro reversal of drug resistance, including tamoxifen resistance. A number of early clinical studies have confirmed the concept and, more recently, everolimus was successfully tested in a randomized controlled trial in postmenopausal patients who progressed on previous anti-estrogen therapy for MBC. This manuscript will review the biology, preclinical and clinical data including the randomized controlled trial that lead to the approval of everolimus by the US FDA.

Pharmacokinetic/Pharmacodynamic Modeling for Drug Development in Oncology

High drug attrition rates remain a critical issue in oncology drug development. A series of steps during drug development must be addressed to better understand the pharmacokinetic (PK) and pharmacodynamic (PD) properties of novel agents and, thus, increase their probability of success. As available data continues to expand in both volume and complexity, comprehensive integration of PK and PD information into a robust mathematical model represents a very useful tool throughout all stages of drug development. During the discovery phase, PK/PD models can be used to identify and select the best drug candidates, which helps characterize the mechanism of action and disease behavior of a given drug, to predict clinical response in humans, and to facilitate a better understanding about the potential clinical relevance of preclinical efficacy data. During early drug development, PK/PD modeling can optimize the design of clinical trials, guide the dose and regimen that should be tested further, help evaluate proof of mechanism in humans, anticipate the effect in certain subpopulations, and better predict drug-drug interactions; all of these effects could lead to a more efficient drug development process. Because of certain peculiarities of immunotherapies, such as PK and PD characteristics, PK/PD modeling could be particularly relevant and thus have an important impact on decision making during the development of these agents.

Early Phase Clinical Trial Designs - State of Play and Adapting for the Future

The process of anti-cancer drug development is complex, with high attrition rates. Factors that may optimise this process include well-constructed and relevant pre-clinical testing and use of biomarkers for patient selection. However, the design of early phase clinical trials will probably play a vital role in both the robust clinical investigation of new targeted therapies and in streamlining drug development. In this overview, we assess current concepts in phase I clinical trials, highlighting issues and opportunities to improve their meaningfulness. The particular challenge of how to design combination trials is addressed, with focus on the potential of new adaptive and model-based designs.

Underreporting of Research Biopsies from Clinical Trials in Oncology

Purpose: Research biopsies are frequently incorporated within clinical trials in oncology and are often a mandatory requirement for trial enrollment. However, limited information is available regarding the extent and completeness of research biopsy reporting.Experimental Design: We identified a cohort of therapeutic clinical trials where research biopsies were performed between January 2005 and October 2010 from an IR database at our institution. Clinical trial protocols were compared with the highest level of corresponding publication as a manuscript or registry report.Results: A total of 866 research biopsies were performed across 46 clinical trials, with a median of 8 patients biopsied/trial and 19 biopsies collected/trial. After a median follow-up time of 4.3 years from trial completion, 36 of 46 trials (78%) reported trial results: published manuscripts (n = 35), or registry report (n = 1). A total of 635 conducted biopsies were reported in 18 of the 46 trials (39%). Six (33%) of these 18 trials underreported the number of biopsies performed. Of 33 trials with mandatory research biopsies, 13 (39%) trials reported on these biopsies. Biopsy complications occurred in 8 trials [n = 39 patients, 6 grade 3/4 adverse events (AE)] but only 1 trial reported these. Factors associated with biopsy reporting included a larger number of biopsies (P ≤ 0.001) and serial biopsies (P < 0.001). Twelve of 16 (75%) trials with >12 biopsies performed reported on these biopsies compared with only 20% (6/30) that performed ≤12 biopsies.Conclusions: Despite ethical obligations to report research biopsies, the majority (61%) of trials do not report results from research biopsies. Complications are rarely reported in these studies. Improved reporting of results and AEs from research biopsies is needed. Clin Cancer Res; 23(21); 6450-7. ©2017 AACR.

Long noncoding RNA EGFR-AS1 mediates epidermal growth factor receptor addiction and modulates treatment response in squamous cell carcinoma

Targeting EGFR is a validated approach in the treatment of squamous-cell cancers (SCCs), although there are no established biomarkers for predicting response. We have identified a synonymous mutation in EGFR, c.2361G>A (encoding p.Gln787Gln), in two patients with head and neck SCC (HNSCC) who were exceptional responders to gefitinib, and we showed in patient-derived cultures that the A/A genotype was associated with greater sensitivity to tyrosine kinase inhibitors (TKIs) as compared to the G/A and G/G genotypes. Remarkably, single-copy G>A nucleotide editing in isogenic models conferred a 70-fold increase in sensitivity due to decreased stability of the EGFR-AS1 long noncoding RNA (lncRNA). In the appropriate context, sensitivity could be recapitulated through EGFR-AS1 knockdown in vitro and in vivo, whereas overexpression was sufficient to induce resistance to TKIs. Reduced EGFR-AS1 levels shifted splicing toward EGFR isoform D, leading to ligand-mediated pathway activation. In co-clinical trials involving patients and patient-derived xenograft (PDX) models, tumor shrinkage was most pronounced in the context of the A/A genotype for EGFR-Q787Q, low expression of EGFR-AS1 and high expression of EGFR isoform D. Our study reveals how a 'silent' mutation influences the levels of a lncRNA, resulting in noncanonical EGFR addiction, and delineates a new predictive biomarker suite for response to EGFR TKIs.

Novel therapeutic targets on the horizon for lung cancer

Lung cancer is a leading cause of cancer-related mortality worldwide, and is classically divided into two major histological subtypes: non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). Although NSCLC and SCLC are considered distinct entities with different genomic landscapes, emerging evidence highlights a convergence in therapeutically relevant targets for both histologies. In adenocarcinomas with defined alterations such as EGFR mutations and ALK translocations, targeted therapies are now first-line standard of care. By contrast, many experimental and targeted agents remain largely unsuccessful for SCLC. Intense preclinical research and clinical trials are underway to exploit unique traits of lung cancer, such as oncogene dependency, DNA damage response, angiogenesis, and cellular plasticity arising from presence of cancer stem cell lineages. In addition, the promising clinical activity observed in NSCLC in response to immune checkpoint blockade has spurred great interest in the field of immunooncology, with the scope to develop a diverse repertoire of synergistic and personalised immunotherapeutics. In this Review, we discuss novel therapeutic agents for lung cancer that are in early-stage development, and how prospective clinical trials and drug development may be shaped by a deeper understanding of this heterogeneous disease.

Molecular image-directed biopsies: improving clinical biopsy selection in patients with multiple tumors

Site selection for image-guided biopsies in patients with multiple lesions is typically based on clinical feasibility and physician preference. This study outlines the development of a selection algorithm that, in addition to clinical requirements, incorporates quantitative imaging data for automatic identification of candidate lesions for biopsy. The algorithm is designed to rank potential targets by maximizing a lesion-specific score, incorporating various criteria separated into two categories: (1) physician-feasibility category including physician-preferred lesion location and absolute volume scores, and (2) imaging-based category including various modality and application-specific metrics. This platform was benchmarked in two clinical scenarios, a pre-treatment setting and response-based setting using imaging from metastatic prostate cancer patients with high disease burden (multiple lesions) undergoing conventional treatment and receiving whole-body [¹⁸F]NaF PET/CT scans pre- and mid-treatment. Targeting of metastatic lesions was robust to different weighting ratios and candidacy for biopsy was physician confirmed. Lesion ranked as top targets for biopsy remained so for all patients in pre-treatment and post-treatment biopsy selection after sensitivity testing was completed for physician-biased or imaging-biased scenarios. After identifying candidates, biopsy feasibility was evaluated by a physician and confirmed for 90% (32/36) of high-ranking lesions, of which all top choices were confirmed. The remaining cases represented lesions with high anatomical difficulty for targeting, such as proximity to sciatic nerve. This newly developed selection method was successfully used to quantitatively identify candidate lesions for biopsies in patients with multiple lesions. In a prospective study, we were able to successfully plan, develop, and implement this technique for the selection of a pre-treatment biopsy location.

Fit-for-purpose biomarker immunoassay qualification and validation: three case studies

AIM

To improve on the efficiency of biomarker assay readiness, and for reliable biomarker data to support three drug programs, we implemented a fit-for-purpose approach, qualifying two biomarker assays and validating a third. Results/methodology: The qualification strategy and selection of experiments for two exploratory biomarkers (CXCL1, CCL19) was determined by the intended use of the biomarker data. The third biomarker, IL-6, was validated as the data would be used in monitoring patient safety during dose-escalation studies in a Phase I trial. All three assays passed a priori acceptance criteria.

CONCLUSION

These assays highlight strategies and methodologies for a fit-for-purpose approach. Minimum qualification, full qualification and validation were chosen and supported programs at different stages of drug development.

Comparison of WHO, RECIST 1.1, EORTC, and PERCIST criteria in the evaluation of treatment response in malignant solid tumors

AIM

To compare response assessment according to the WHO, RECIST 1.1, EORTC, and PERCIST criteria in patients diagnosed with malignant solid tumors and who had received cytotoxic chemotherapy to establish the strength of agreement between each criterion.

MATERIALS AND METHODS

Sixty patients with malignant solid tumors were included in this retrospective study. The baseline and the sequential follow-up fluorine-18-fluorodeoxyglucose PET/computed tomography (CT) of each patient were evaluated according to the WHO, RECIST 1.1, EORTC, and PERCIST criteria. PET/CT images were used for both metabolic and anatomic evaluation. The concurrent diagnostic CT and MRI images (performed within 1 week of PET/CT) were also utilized when needed. The results were compared using the κ-statistics.

RESULTS

The response and progression rates according to the WHO criteria were 37 and 38%, respectively. The same ratios were also found for RECIST 1.1 (κ=1). The response and progression rates according to the EORTC criteria were 47 and 40%, respectively. When PERCIST criteria were used, one patient with progressive disease was upgraded to stable disease (κ=0.976). As we found the same results with WHO and RECIST 1.1 criteria, we used WHO criteria to compare the anatomic and metabolic criteria. When we compared the WHO and EORTC criteria, there was an agreement in 80% of the patients (κ=0.711). With WHO and PERCIST criteria, there was an agreement in 81.6% of the patients (κ=0.736).

CONCLUSION

Significant agreement was detected when the WHO, RECIST 1.1, EORTC, and PERCIST criteria were compared both within as well as between each other.

Critical parameters in targeted drug development: the pharmacological audit trail

The Pharmacological Audit Trail (PhAT) comprises a set of critical questions that need to be asked during discovery and development of an anticancer drug. Key aspects include: (1) defining a patient population; (2) establishing pharmacokinetic characteristics; (3) providing evidence of target engagement, pathway modulation, and biological effect with proof of concept pharmacodynamic biomarkers; (4) determining intermediate biomarkers of response; (5) assessing tumor response; and (6) determining how to overcome resistance by combination or sequential therapy and new target/drug discovery. The questions asked in the PhAT should be viewed as a continuum and not used in isolation. Different drug development programmes derive different types of benefit from these questions. The PhAT is critical in making go-no-go decisions in the development of currently studied drugs and will continue to be relevant to discovery and development of future generations of anticancer agents.

Phosphorylated ribosomal S6 (p-rpS6) as a post-treatment indicator of HER2 signalling targeted drug resistance

OBJECTIVE

To identify clinically relevant predictive biomarkers of trastuzumab resistance.

MATERIAL AND METHODS

MTT, FACS assays, immunoblotting and immunocytochemistry were used to phenotypically characterize drug responses of two cell models BT474R and SKBR3R. Student's t-test and Spearman's correlation were applied for statistic analysis.

RESULTS

The activity of a downstream effector of the HER2 pathway phosphorylated ribosomal protein S6 (p-rpS6), was suppressed by trastuzumab in the parental cell lines yet remained unchanged in the resistant cells following treatment. The level of p-rpS6 was inversely correlated to the drug induced growth inhibition of trastuzumab-resistant cells when they are treated with selected HER2 targeting drugs.

CONCLUSION

p-rpS6 is a robust post-treatment indicator of HER2 pathway-targeted therapy resistance.

Current targeted therapies in the treatment of advanced colorectal cancer: a review

Treatment strategies for metastatic colorectal cancer (mCRC) patients have undergone dramatic changes in the past decade and despite improved patient outcomes, there still exist areas for continued development. The introduction of targeted agents has provided clinicians with additional treatment options in mCRC, however, results have been mixed at best. These novel therapies were designed to interfere with specific molecules involved in the cellular carcinogenesis pathway and ultimately deliver a more focused treatment. Currently, their use in mCRC has been limited primarily as an adjunct to conventional chemotherapy regimens. This review explores the relevant cell-signaling networks in colorectal cancer, provides focus on the current targeted agent armamentarium approved for use in mCRC and explores the usefulness of predictive mCRC biomarkers.

Circulating Tumor Cell Isolation and Analysis

Isolation and analysis of cancer cells from body fluids have significant implications in diagnosis and therapeutic treatment of cancers. Circulating tumor cells (CTCs) are cancer cells circulating in the peripheral blood or spreading iatrogenically into blood vessels, which is an early step in the cascade of events leading to cancer metastasis. Therefore, CTCs can be used for diagnosing for therapeutic treatment, prognosing a given anticancer intervention, and estimating the risk of metastatic relapse. However, isolation of CTCs is a significant technological challenge due to their rarity and low recovery rate using traditional purification techniques. Recently microfluidic devices represent a promising platform for isolating cancer cells with high efficiency in processing complex cellular fluids, with simplicity, sensitivity, and throughput. This review summarizes recent methods of CTC isolation and analysis, as well as their applications in clinical studies.

Why and how have drug discovery strategies in pharma changed? What are the new mindsets?

In the pharmaceutical industry the long-term challenge of drug innovation is the key phrase throughout R&D that refers to increasing the output of original drug candidate molecules. To increase R&D productivity, implementation of new and strategic R&D orientations to develop new approaches or systems to identify hits and leads efficiently has taken place and enabled all scientists working in the drug discovery domain to develop innovative medicines for the 21st century.

Improving the drug development process by reducing the impact of adverse events: the case of cataracts considered

Cataract was used as a model for the prevalence and economic impact of adverse events during the drug development process. Meta-analysis revealed a reported prevalence of cataract at 12.0% (1.0-43.3%), 3.8% (2.4-12.5%), 1.0% (0.0-8.1%), 1.7% (0.0-34.8%) and 3.8% (2.3-5.7%) of compounds in preclinical, Phase I, II, III and IV clinical trials, respectively. Utilising a human-based in vitro screening assay to predict cataractogenic potential in human could allow better selection of novel compounds at early-stage drug development. This could significantly reduce costs and ultimately increase the probability of a drug obtaining FDA approval for a clinical application.

Analysis of Impact of Post-Treatment Biopsies in Phase I Clinical Trials

PURPOSE

The use of biopsy-derived pharmacodynamic biomarkers is increasing in early-phase clinical trials. It remains unknown whether drug development is accelerated or enhanced by their use. We examined the impact of biopsy-derived pharmacodynamic biomarkers on subsequent drug development through a comprehensive analysis of phase I oncology studies from 2003 to 2010 and subsequent publications citing the original trials.

METHODS

We conducted a search to identify and examine publications of phase I oncology studies including the use of biopsy-derived pharmacodynamic biomarkers between 2003 and 2010. Characteristics of those studies were extracted and analyzed, along with outcomes from the biomarker data. We then compiled and reviewed publications of subsequent phase II and III trials citing the original phase I biomarker studies to determine the impact on drug development.

RESULTS

We identified 4,840 phase I oncology publications between 2003 and 2010. Seventy-two studies included a biopsy-derived pharmacodynamic biomarker. The proportion of biomarker studies including nondiagnostic biopsies increased over time (P = .002). A minimum of 1,873 tumor biopsies were documented in the 72 studies, 12 of which reported a statistically significant biomarker result. Thirty-three percent of studies (n = 24) were referenced by subsequent publications specifically with regard to the biomarkers. Only five positive biomarker studies were cited subsequently, and maximum tolerated dose was used for subsequent drug development in all cases.

CONCLUSION

Despite their increased use, the impact of biopsy-derived pharmacodynamic biomarkers in phase I oncology studies on subsequent drug development remains uncertain. No impact on subsequent dose or schedule was demonstrated. This issue requires further evaluation, given the risk and cost of such studies.

Identifying potential indicators to measure the outcome of translational cancer research: a mixed methods approach

Background

In a context where there is an increasing demand to evaluate the outcome of bio-medical research, our work aims to develop a set of indicators to measure the impact of translational cancer research. The objective of our study was to explore the scope and issues of translational research relevant to evaluation, explore the views of researchers on the evaluation of oncological translational research, and select indicators measuring the outcomes and outputs of translational research in oncology by consensus.

Methods

Semi-structured interviews amongst 23 researchers involved in translational cancer research were conducted and analysed using thematic analysis. A two-round modified Delphi survey of 35 participants with similar characteristics was then performed followed by a physical meeting. Participants rated the feasibility and validity of 60 indicators. The physical meeting was held to discuss the methodology of the new indicators.

Results

The main themes emerging from the interviews included a common definition for translational research but disagreements about the exact scope and limits of this research, the importance of multidisciplinarity and collaboration for the success of translational research, the disadvantages that translational research faces in current evaluation systems, the relative lack of pertinence of existing indicators, and propositions to measure translational cancer research in terms of clinical applications and patient outcomes. A total of 35 participants took part in the first round survey and 12 in the second round. The two-round survey helped us select a set of 18 indicators, including four that seemed to be particularly adapted to measure translational cancer research impact on health service research (number of biomarkers identified, generation of clinical guidelines, citation of research in clinical guidelines, and citation of research in public health guidelines). The feedback from participants helped refine the methodology and definition of indicators not commonly used.

Conclusion

Indicators need to be accepted by stakeholders under evaluation. This study helped the selection and refinement of indicators considered as the most relevant by researchers in translational cancer research. The feasibility and validity of those indicators will be tested in a scientometric study.

Electronic supplementary material

The online version of this article (doi:10.1186/s12961-015-0060-5) contains supplementary material, which is available to authorized users.

ImmunoPET with Anti-Mesothelin Antibody in Patients with Pancreatic and Ovarian Cancer before Anti-Mesothelin Antibody-Drug Conjugate Treatment

PURPOSE

Mesothelin (MSLN) is frequently overexpressed in pancreatic and ovarian cancers, making it a potential drug target. We performed an (89)Zr-PET imaging study with MMOT0530A, a MSLN antibody, in conjunction with a phase I study with the antibody-drug conjugate DMOT4039A, containing MMOT0530A bound to MMAE. The aim was to study antibody tumor uptake, whole-body distribution, and relation between uptake, response to treatment, and MSLN expression.

EXPERIMENTAL DESIGN

Before DMOT4039A treatment, patients received 37 MBq (89)Zr-MMOT0530A followed by PET/CT imaging 2, 4, and 7 days postinjection. Tracer uptake was expressed as standardized uptake value (SUV). MSLN expression was determined with immunohistochemistry (IHC) on archival tumor tissue.

RESULTS

Eleven patients were included, 7 with pancreatic and 4 with ovarian cancer. IHC MSLN expression varied from absent to strong. Suitable tracer antibody dose was 10 mg MMOT0530A and optimal imaging time was 4 and 7 days postinjection. Tumor tracer uptake occurred in 37 lesions with mean SUVmax of 13.1 (±7.5) on PET 4 days postinjection, with 11.5 (±7.5) in (N= 17) pancreatic and 14.5 (±8.7) in (N= 20) ovarian cancer lesions. Within patients, a mean 2.4-fold (±1.10) difference in uptake between tumor lesions existed. Uptake in blood, liver, kidneys, spleen, and intestine reflected normal antibody distribution. Tracer tumor uptake was correlated to IHC. Best response to DMOT4039A was partial response in one patient.

CONCLUSIONS

With (89)Zr-MMOT0530A-PET, pancreatic and ovarian cancer lesions as well as antibody biodistribution could be visualized. This technique can potentially guide individualized antibody-based treatment.