Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization

Biomarkers for progressive multifocal leukoencephalopathy: emerging data for use of JC virus DNA copy number in clinical trials

Progressive multifocal leukoencephalopathy is a rare but devastating demyelinating disease caused by the JC virus (JCV), for which no therapeutics are approved. To make progress towards addressing this unmet medical need, innovations in clinical trial design are needed. Quantitative JCV DNA in CSF has the potential to serve as a valuable biomarker of progressive multifocal leukoencephalopathy disease and treatment response in clinical trials to expedite therapeutic development, as do neuroimaging and other fluid biomarkers such as neurofilament light chain. Specifically, JCV DNA in CSF could be used in clinical trials as an entry criterion, stratification factor, or predictor of clinical outcomes. Insights from the investigation of candidate biomarkers for progressive multifocal leukoencephalopathy might inform approaches to biomarker development for other rare diseases.

Enhanced interhemispheric resting-state functional connectivity of the visual network is an early treatment response of paroxetine in patients with panic disorder

This study aimed to detect alterations in interhemispheric interactions in patients with panic disorder (PD), determine whether such alterations could serve as biomarkers for the diagnosis and prediction of therapeutic outcomes, and map dynamic changes in interhemispheric interactions in patients with PD after treatment. Fifty-four patients with PD and 54 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessment and a resting-state functional magnetic resonance imaging scan at (i) baseline and (ii) after paroxetine treatment for 4 weeks. A voxel-mirrored homotopic connectivity (VMHC) indicator, support vector machine (SVM), and support vector regression (SVR) were used in this study. Patients with PD showed reduced VMHC in the fusiform, middle temporal/occipital, and postcentral/precentral gyri, relative to those of HCs. After treatment, the patients exhibited enhanced VMHC in the lingual gyrus, relative to the baseline data. The VMHC of the fusiform and postcentral/precentral gyri contributed most to the classification (accuracy = 87.04%). The predicted changes were accessed from the SVR using the aberrant VMHC as features. Positive correlations (p < 0.001) were indicated between the actual and predicted changes in the severity of anxiety. These findings suggest that impaired interhemispheric coordination in the cognitive-sensory network characterized PD and that VMHC can serve as biomarkers and predictors of the efficiency of PD treatment. Enhanced VMHC in the lingual gyrus of patients with PD after treatment implied that pharmacotherapy recruited the visual network in the early stages.

Biological exposure indices of occupational exposure to benzene: A systematic review

The current study aimed to systematically review the studies concerning the biological monitoring of benzene exposure in occupational settings. A systematic literature review was conducted in Scopus, EMBASE, Web of Science, and Medline from 1985 through July 2021. We included peer-reviewed original articles that investigated the association between occupational exposure to benzene and biological monitoring. We identified 4786 unique citations, of which 64 cross-sectional, one case-control, and one cohort study met our inclusion criteria. The most studied biomarkers were urinary trans-trans muconic acid, S- phenyl mercapturic acid, and urinary benzene, respectively. We found the airborne concentration of benzene as a key indicator for choosing a suitable biomarker. We suggest considering urinary benzene at low (0.5-5.0 TLV), urinary SPMA and TTMA at medium (5.0-25 and 25-50 TLV, respectively), and urinary phenol and hydroquinone and catechol at very high concentrations (500 and 1000 TLV ≤, respectively). Genetic polymorphism of glutathione S-transferase and oral intake of sorbic acid have confounding effects on the level of U-SPMA and U-TTMA, respectively. The airborne concentration, smoking habit, oral consumption of sorbic acid, and genetic polymorphism of workers should be considered in order to choose the appropriate indicator for biological monitoring of benzene exposure.

Prioritizing Early Disease Intervention

Scholars and practitioners have described how investing in health care earlier rather than later can be beneficial, from how "biomarkers" offer promise for early disease detection to healthcare system "incentives" that can promote early preventive medicine. Work by health economists has also made clear that the "health capital" of an individual depreciates over time in the absence of investments in health. Yet, our current policy makers and healthcare system continue prioritizing care of late-stage complex symptomatic illness, often when cure is impossible and disease reversal is improbable, thus exacerbating public health burdens. Critically missing are predicates to address this challenge include the following: first, identifying and validating the specific set of presymptomatic biomarkers that will inform the most appropriate intervention timing for those medical conditions amenable to early intervention; second, shifting fundamental health economic incentives to influence the appropriate disease prevention market; and third, formulating and executing a viable economic framework of reimbursement. We examine these predicates and propose actionable policy recommendations that may help align stakeholder interests to improve public health.

Inflammatory Mechanisms in a Neurovascular Disease: Cerebral Cavernous Malformation

Cerebral cavernous malformation (CCM) is a common cerebrovascular malformation causing intracranial hemorrhage, seizures, and focal neurologic deficits. A unique CCM lesional inflammatory microenvironment has been shown to influence the clinical course of the disease. This review addresses the inflammatory cell infiltrate in the CCM lesion and the role of a defined antigen-driven immune response in pathogenicity. We summarize immune mechanisms associated with the loss of the CCM gene and disease progression, including the potential role of immunothrombosis. We also review evidence of circulating inflammatory biomarkers associated with CCM disease and its clinical activity. We articulate future directions for this research, including the role of individual cell type contributions to the immune response in CCM, single cell transcriptomics of inflammatory cells, biomarker development, and therapeutic implications. The concepts are applicable for developing diagnostic and treatment strategies for CCM and for studying other neurovascular diseases.

Circulating Plasma miRNA Homologs in Mice and Humans Reflect Familial Cerebral Cavernous Malformation Disease

Patients with familial cerebral cavernous malformation (CCM) inherit germline loss of function mutations and are susceptible to progressive development of brain lesions and neurological sequelae during their lifetime. To date, no homologous circulating molecules have been identified that can reflect the presence of germ line pathogenetic CCM mutations, either in animal models or patients. We hypothesize that homologous differentially expressed (DE) plasma miRNAs can reflect the CCM germline mutation in preclinical murine models and patients. Herein, homologous DE plasma miRNAs with mechanistic putative gene targets within the transcriptome of preclinical and human CCM lesions were identified. Several of these gene targets were additionally found to be associated with CCM-enriched pathways identified using the Kyoto Encyclopedia of Genes and Genomes. DE miRNAs were also identified in familial-CCM patients who developed new brain lesions within the year following blood sample collection. The miRNome results were then validated in an independent cohort of human subjects with real-time-qPCR quantification, a technique facilitating plasma assays. Finally, a Bayesian-informed machine learning approach showed that a combination of plasma levels of miRNAs and circulating proteins improves the association with familial-CCM disease in human subjects to 95% accuracy. These findings act as an important proof of concept for the future development of translatable circulating biomarkers to be tested in preclinical studies and human trials aimed at monitoring and restoring gene function in CCM and other diseases.

Blood-Based Biomarkers for Managing Workload in Athletes: Considerations and Recommendations for Evidence-Based Use of Established Biomarkers

Blood-based biomarkers can provide an objective individualized measure of training load, recovery, and health status in order to reduce injury risk and maximize performance. Despite enormous potentials, especially owing to currently evolving technology, such as point-of-care testing, and advantages, in terms of objectivity and non-interference with the training process, there are several pitfalls in the use and interpretation of biomarkers. Confounding variables such as preanalytical conditions, inter-individual differences, or an individual chronic workload can lead to variance in resting levels. In addition, statistical considerations such as the detection of meaningful minimal changes are often neglected. The lack of generally applicable and individual reference levels further complicates the interpretation of level changes and thus load management via biomarkers. Here, the potentials and pitfalls of blood-based biomarkers are described, followed by an overview of established biomarkers currently used to support workload management. Creatine kinase is discussed in terms of its evidence for workload management to illustrate the limited applicability of established markers for workload management to date. We conclude with recommendations for best practices in the use and interpretation of biomarkers in a sport-specific context.

Prospective validation of diffusion-weighted MRI as a biomarker of tumor response and oncologic outcomes in head and neck cancer: Results from an observational biomarker pre-qualification study

PURPOSE

To determine DWI parameters associated with tumor response and oncologic outcomes in head and neck (HNC) patients treated with radiotherapy (RT).

METHODS

HNC patients in a prospective study were included. Patients had MRIs pre-, mid-, and post-RT completion. We used T2-weighted sequences for tumor segmentation which were co-registered to respective DWIs for extraction of apparent diffusion coefficient (ADC) measurements. Treatment response was assessed at mid- and post-RT and was defined as: complete response (CR) vs. non-complete response (non-CR). The Mann-Whitney U test was used to compare ADC between CR and non-CR. Recursive partitioning analysis (RPA) was performed to identify ADC threshold associated with relapse. Cox proportional hazards models were done for clinical vs. clinical and imaging parameters and internal validation was done using bootstrapping technique.

RESULTS

Eighty-one patients were included. Median follow-up was 31 months. For patients with post-RT CR, there was a significant increase in mean ADC at mid-RT compared to baseline ((1.8 ± 0.29) × 10-3 mm2/s vs. (1.37 ± 0.22) × 10-3 mm2/s, p < 0.0001), while patients with non-CR had no significant increase (p > 0.05). RPA identified GTV-P delta (Δ)ADCmean < 7% at mid-RT as the most significant parameter associated with worse LC and RFS (p = 0.01). Uni- and multi-variable analysis showed that GTV-P ΔADCmean at mid-RT ≥ 7% was significantly associated with better LC and RFS. The addition of ΔADCmean significantly improved the c-indices of LC and RFS models compared with standard clinical variables (0.85 vs. 0.77 and 0.74 vs. 0.68 for LC and RFS, respectively, p < 0.0001 for both).

CONCLUSION

ΔADCmean at mid-RT is a strong predictor of oncologic outcomes in HNC. Patients with no significant increase of primary tumor ADC at mid-RT are at high risk of disease relapse.

Drug Development in Autosomal Dominant Polycystic Kidney Disease: Opportunities and Challenges

Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disorder characterized by relentless growth of innumerable renal cysts bilaterally, associated with decline in glomerular filtration rate over the course of decades. The burden of ADPKD and its treatment is associated with a significant economic and societal cost. Despite several clinical studies conducted over the past decade, only one treatment has been approved by regulatory agencies to slow disease progression in ADPKD. Elucidating feasible endpoints and clear regulatory pathway may stimulate interest in developing and translating novel therapeutics. This review summarizes the recent progress, challenges, and opportunities in drug development for ADPKD. We discuss the traditional and accelerated regulatory approval pathways, the various clinical trials endpoints, and biomarkers in ADPKD. Furthermore, we propose strategies that could optimize the clinical trial design in ADPKD. Finally, we owe it to our ADPKD patient community to strive for international collaborative studies geared toward discovery and validation of surrogate endpoints and to rally for funded infrastructure that would allow phase 3 master protocols in ADPKD. These advances will serve to derisk and potentially accelerate the development of therapies and eventually bring hope to patients and families who endure through this devastating disease.

NAFLD and NASH biomarker qualification in the LITMUS consortium - Lessons learned

Biomarkers have the potential to accelerate drug development, as early indicators of improved clinical response, to improve patient safety, and for personalised medicine. However, few have been approved through the biomarker qualification pathways of the regulatory agencies. This paper outlines how biomarkers can accelerate drug development, and reviews the lessons learned by the EU IMI2-funded LITMUS consortium, which has had several interactions with regulatory agencies in both the US and EU regarding biomarker qualification in patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. Sharing knowledge of such interactions with the scientific community is of paramount importance to increase the chances of qualification of relevant biomarkers that may accelerate drug development, and thereby help patients, across disease indications. A qualified biomarker enables a decision to be made that all understand and support in a common framework.

Gaps and challenges in nonclinical assessments of pharmaceuticals: An FDA/CDER perspective on considerations for development of new approach methodologies

Previously, we provided an FDA/CDER perspective on nonclinical testing strategies and briefly discussed the opportunities and challenges of using new approach methodologies (NAMs) in drug development, especially for regulatory purposes. To facilitate the integration of NAMs into nonclinical regulatory testing, we surveyed the CDER Pharmacology/Toxicology community to identify the nonclinical challenges faced by CDER review staff, including gaps and areas of concern underserved by current nonclinical testing approaches, and to understand how development of NAMs with specific contexts of use (COUs) could potentially alleviate them. Survey outcomes were coalesced into CDER-identified needs for which NAMs with specific COUs could potentially be developed to address gaps and challenges in nonclinical safety assessments. We also discussed the current FDA procedure for validation and qualification of NAMs intended to inform regulatory decisions. This manuscript is intended to facilitate productive discussions and collaborations with regulatory, government, and academic stakeholders within the drug development community regarding the development and regulatory use of NAMs and their role in safety and efficacy assessment of pharmaceuticals.

A unified classification approach rating clinical utility of protein biomarkers across neurologic diseases

A major evolution from purely clinical diagnoses to biomarker supported clinical diagnosing has been occurring over the past years in neurology. High-throughput methods, such as next-generation sequencing and mass spectrometry-based proteomics along with improved neuroimaging methods, are accelerating this development. This calls for a consensus framework that is broadly applicable and provides a spot-on overview of the clinical validity of novel biomarkers. We propose a harmonized terminology and a uniform concept that stratifies biomarkers according to clinical context of use and evidence levels, adapted from existing frameworks in oncology with a strong focus on (epi)genetic markers and treatment context. We demonstrate that this framework allows for a consistent assessment of clinical validity across disease entities and that sufficient evidence for many clinical applications of protein biomarkers is lacking. Our framework may help to identify promising biomarker candidates and classify their applications by clinical context, aiming for routine clinical use of (protein) biomarkers in neurology.

Are there foetal extracellular vesicles in maternal blood? Prospects for diagnostic biomarker discovery

Prenatal diagnosis of congenital disease improves clinical outcomes; however, as many as 50% of congenital heart disease cases are missed by current ultrasound screening methods. This indicates a need for improved screening technology. Extracellular vesicles (EVs) have attracted enormous interest in recent years for their potential in diagnostics. EVs mediate endocrine signalling in health and disease and are known to regulate aspects of embryonic development. Here, we critically evaluate recent evidence suggesting that EVs released from the foetus are able to cross the placenta and enter the maternal circulation. Furthermore, EVs from the mother appear to be transported in the reverse direction, whilst the placenta itself acts as a source of EVs. Experimental work utilising rodent models employing either transgenically encoded reporters or application of fluorescent tracking dyes provide convincing evidence of foetal-maternal crosstalk. This is supported by clinical data demonstrating expression of placental-origin EVs in maternal blood, as well as limited evidence for the presence of foetal-origin EVs. Together, this work raises the possibility that foetal EVs present in maternal blood could be used for the diagnosis of congenital disease. We discuss the challenges faced by researchers in translating these basic science findings into a clinical non-invasive prenatal test.

Advancing microfluidic diagnostic chips into clinical use: a review of current challenges and opportunities

Microfluidic diagnostic (μDX) technologies miniaturize sensors and actuators to the length-scales that are relevant to biology: the micrometer scale to interact with cells and the nanometer scale to interrogate biology's molecular machinery. This miniaturization allows measurements of biomarkers of disease (cells, nanoscale vesicles, molecules) in clinical samples that are not detectable using conventional technologies. There has been steady progress in the field over the last three decades, and a recent burst of activity catalyzed by the COVID-19 pandemic. In this time, an impressive and ever-growing set of technologies have been successfully validated in their ability to measure biomarkers in clinical samples, such as blood and urine, with sensitivity and specificity not possible using conventional tests. Despite our field's many accomplishments to date, very few of these technologies have been successfully commercialized and brought to clinical use where they can fulfill their promise to improve medical care. In this paper, we identify three major technological trends in our field that we believe will allow the next generation of μDx to have a major impact on the practice of medicine, and which present major opportunities for those entering the field from outside disciplines: 1. the combination of next generation, highly multiplexed μDx technologies with machine learning to allow complex patterns of multiple biomarkers to be decoded to inform clinical decision points, for which conventional biomarkers do not necessarily exist. 2. The use of micro/nano devices to overcome the limits of binding affinity in complex backgrounds in both the detection of sparse soluble proteins and nucleic acids in blood and rare circulating extracellular vesicles. 3. A suite of recent technologies that obviate the manual pre-processing and post-processing of samples before they are measured on a μDX chip. Additionally, we discuss economic and regulatory challenges that have stymied μDx translation to the clinic, and highlight strategies for successfully navigating this challenging space.

Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized phase III-trial AGITG-MAX

The VEGF‐A monoclonal antibody bevacizumab is currently recommended for first‐line treatment of all metastatic colorectal cancer (mCRC) patients. Cost‐benefit ratio and side‐effects however necessitate patient selection. A large retrospective yet nonrandomized study showed that patients with loss of chromosome 18q11.2‐q12.1 in the tumor and treated with bevacizumab have 3 months improved median progression‐free (PFS) and overall survival (OS) benefit compared to patients without this loss and/or treatment modality. Implementation for loss of chromosome 18q11.2‐q12.1 as a marker in clinical practice mandates evidence in a randomized controlled trial for bevacizumab. Of the trials with randomization of chemotherapy vs chemotherapy with bevacizumab, the AGITG‐MAX trial was the only one with tumor materials available. Chromosome 18q11.2‐q12.1 copy number status was measured for 256 AGITG‐MAX trial patients and correlated with PFS according to a predefined analysis plan with marker‐treatment interaction as the primary end‐point. Chromosome 18q11.2‐q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the nonrandomized study, significant PFS benefit of bevacizumab was observed in patients with chromosome 18q11.2‐q12.1 loss (P = .009), and not in patients without 18q loss (P = .67). Although significance for marker‐treatment interaction was not reached (P_interaction = .28), hazard ratio and 95% confidence interval of this randomized cohort (HR_interaction = 0.72; 95% CI = 0.39‐1.32) shows striking overlap with the nonrandomized study cohorts (HR_interaction = 0.41; 95% CI = 0.32‐0.8) supported by a nonsignificant Cochrane χ² test (P = .11) for heterogeneity. We conclude that post hoc analysis of the AGITG‐MAX RCT provides supportive evidence for chromosome 18q11.2‐q12.1 as a predictive marker for bevacizumab in mCRC patients.

Informatics in Medical Product Regulation: The Right Drug at the Right Dose for the Right Patient

This chapter describes the role of regulatory medical product review in furthering precision medicine. Efficient data processing and appropriate analyses are needed to synthesize information and provide directions for use in a medical product label. We describe opportunities and challenges in outcome assessment through informatics, as bioengineered therapeutics are increasingly developed for the unmet needs of molecularly defined diseases. Data submission requirements and analytic principles are outlined, and regulatory resources and foundational law and statute are cited for the reader.

Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes

Background

Blood plasma proteins play an important role in immune defense against pathogens, including cytokine signaling, the complement system, and the acute-phase response. Recent large-scale studies have reported genetic (i.e., protein quantitative trait loci, pQTLs) and non-genetic factors, such as age and sex, as major determinants to inter-individual variability in immune response variation. However, the contribution of blood-cell composition to plasma protein heterogeneity has not been fully characterized and may act as a mediating factor in association studies.

Methods

Here, we evaluated plasma protein levels from 400 unrelated healthy individuals of western European ancestry, who were stratified by sex and two decades of life (20–29 and 60–69 years), from the Milieu Intérieur cohort. We quantified 229 proteins by Luminex in a clinically certified laboratory and their levels of variation were analyzed together with 5.2 million single-nucleotide polymorphisms. With respect to non-genetic variables, we included 254 lifestyle and biochemical factors, as well as counts of seven circulating immune cell populations measured by hemogram and standardized flow cytometry.

Results

Collectively, we found 152 significant associations involving 49 proteins and 20 non-genetic variables. Consistent with previous studies, age and sex showed a global, pervasive impact on plasma protein heterogeneity, while body mass index and other health status variables were among the non-genetic factors with the highest number of associations. After controlling for these covariates, we identified 100 and 12 pQTLs acting in cis and trans, respectively, collectively associated with 87 plasma proteins and including 19 novel genetic associations. Genetic factors explained the largest fraction of the variability of plasma protein levels, as compared to non-genetic factors. In addition, blood-cell fractions, including leukocytes, lymphocytes, monocytes, neutrophils, eosinophils, basophils, and platelets, had a larger contribution to inter-individual variability than age and sex and appeared as confounders of specific genetic associations. Finally, we identified new genetic associations with plasma protein levels of five monogenic Mendelian disease genes including two primary immunodeficiency genes (Ficolin-3 and FAS).

Conclusions

Our study identified novel genetic and non-genetic factors associated to plasma protein levels which may inform health status and disease management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01032-y.

Update on International Medical Taxonomies of Biomarkers and Their Applications in Management of Thyroid Cancers

Biomarkers (BMs) are medical signs which can be precisely measured and reproduced. Mainly, BMs provide information on the likely disease which can occur in an individual. On the other hand, BMs also signal disease recurrence in patients receiving therapy. The U.S. Food and Drug Administration coupled with the National Institutes of Health and the European Medicines Agency have proposed two distinct procedures to validate BMs. These agencies have elaborated two glossaries to describe the role of BMs. The aim of this study was to investigate medical taxonomies adopted by different governmental agencies for BM validation. Additional goals were to analyze efficiencies of the validated and candidate BMs for thyroid cancers (TCs). Currently, thyroglobulin is validated for monitoring TCs. Sorafenib-tosylate, Doxorubicin-hydrochloride, Vandetanib, Cabozantinib-s-malate, Dabrafenib-mesylate, Trametinib-dimethyl-sulfoxide, Lenvatinib-mesylate, Pralsetinib and Selpercatinib are validated for TC treatment. Among candidate BMs for TC diagnosis, there are molecular combinations including BRAF, RAS, RET/PTC and PAX8-PPARγ mutations. Noteworthy are BRAF and RET/PTC alterations already validated as targets of Dabrafenib-mesylate, Pralsetinib and Selpercatinib. Finally, cellular expressions of c-met in nodal TC metastases have diagnostic imaging applications. On the basis of this analysis, BM taxonomies should have common standards internationally recognized. BMs show different efficiencies depending on their diagnostic or therapeutic use.

FeNO in Asthma

Asthma is a common disease affecting 350 million people worldwide, which is characterized by airways inflammation and hyperreactivity. Historically diagnosis and treatment have been mainly based on symptoms, which have the potential to result in misdiagnosis and inappropriate treatment. Nitric oxide (NO) is exhaled in human breath and is a marker of airways inflammation. Levels of NO are increased in the exhaled breath of patients with type 2 asthma and fractional exhaled nitric oxide (FeNO) provides an objective biomarker of airway inflammation. FeNO testing is an accessible, noninvasive, and easy-to-use test. Cut-off values have been established by the American Thoracic Society (ATS), the Global Initiative for Asthma (GINA), and the National Institute for Health and Care Excellence (NICE) but vary between guidance. FeNO levels have been shown to be predictive of blood and sputum eosinophil levels but should not be used in isolation and current guidance emphasizes the importance of incorporating clinical symptoms and testing when utilizing FeNO results. The inclusion of FeNO testing can increase diagnostic accuracy of asthma, while high levels in asthmatic patients can help predict response to inhaled corticosteroids (ICS) and suppression of levels with ICS to monitor adherence. FeNO levels are also a predictor of asthma risk with increased exacerbation rates and accelerated decline in lung function associated with high levels as well as having an emerging role in predicting response to some biologic therapies in severe asthma. FeNO testing is cost-effective and has been shown, when combined with clinical assessment, to improve asthma management.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

Biomarker qualification at the European Medicines Agency: a review of biomarker qualification procedures from 2008 to 2020

Regulatory qualification of biomarkers facilitates their harmonized use across drug developers, enabling more personalized medicine. This study reviews various aspects of the European Medicines Agency’s (EMA’s) biomarker qualification procedure, including frequency and outcome, common challenges, and biomarker characteristics. Our findings provide insights into the EMA’s biomarker qualification process and will thereby support future applications. All biomarker‐related “Qualification of Novel Methodologies for Medicine Development” procedures that started from 2008 to 2020 were included. Procedural data were extracted from relevant documents and analyzed descriptively. In total, 86 biomarker qualification procedures were identified, of which 13 resulted in qualified biomarkers. Whereas initially many biomarker qualification procedures were linked to a single company and specific drug development program, a shift was observed to qualification efforts by consortia. Most biomarkers were proposed (n = 45) and qualified (n = 9) for use in patient selection, stratification, and/or enrichment, followed by efficacy biomarkers (37 proposed, 4 qualified). Overall, many issues were raised during qualification procedures, mostly related to biomarker properties and assay validation (in 79% and 77% of all procedures, respectively). Issues related to the proposed context of use and rationale were least common yet were still raised in 54% of all procedures. While few qualified biomarkers are currently available, procedures focus increasingly on biomarkers for general use instead of those linked to specific drug compounds. The issues raised during qualification procedures illustrate the thorough discussions taking place between applicants and regulators—highlighting aspects that need careful consideration and underlining the importance of an appropriate validation strategy.

Neurobehavioral Biomarkers: An EEG Family Reunion

SUMMARY

The field of clinical EEG has had an uneasy relationship with the use of this technology for clinical cognitive applications and often for good reason. However, apart from its clinical use, EEG has had a tradition as a major tool in cognitive psychology and cognitive neuroscience dating back at least to the 1960s. Based on accumulated knowledge from its research application, EEG-based biomarkers are beginning to see applications in clinical trials and may eventually enter clinical care. We address concerns surrounding quality control, the treatment of artifact, and normal variants and how developments in engineering, biomarker validation, and implementation science rigorously applied to these tools can lead to well-justified approaches.

How paediatric drug development and use could benefit from OMICs: a c4c expert group white paper

The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates, and infants, is limited by a paucity of good quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts, by complementary information about targeted and non-targeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a sub-division into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as well as type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, non-invasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (e.g. liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, like artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to identify complex phenotypes and subpopulations of patients to improve development of medicines for children with potential economic advantages.

Validation of the Surrogate Threshold Effect for Change in Bone Mineral Density as a Surrogate Endpoint for Fracture Outcomes: The FNIH-ASBMR SABRE Project

The surrogate threshold effect (STE) is defined as the minimum treatment effect on a surrogate that is reliably predictive of a treatment effect on the clinical outcome. It provides a framework for implementing a clinical trial with a surrogate endpoint. The aim of this study was to update our previous analysis by validating the STE for change in total hip (TH) BMD as a surrogate for fracture risk reduction; the novelty of this study was this validation. To do so, we used individual patient data from 61,415 participants in 16 RCTs that evaluated bisphosphonates (nine trials), selective estrogen receptor modulators (four trials), denosumab (one trial), odanacatib (one trial), and teriparatide (one trial) to estimate trial-specific treatment effects on TH BMD and all, vertebral, hip, and nonvertebral fractures. We then conducted a random effects meta-regression of the log relative fracture risk reduction against 24-month change in TH BMD, and computed the STE as the intersection of the upper 95% prediction limit of this regression with the line of no fracture reduction. We validated the STE by checking whether the number of fractures in each trial provided 80% power and determining what proportion of trials with BMD changes ≥ STE reported significant reductions in fracture risk. We applied this analysis to (i) the trials on which we estimated the STE; and (ii) trials on which we did not estimate the STE. We found that the STEs for all, vertebral, hip, and nonvertebral fractures were 1.83%, 1.42%, 3.18%, and 2.13%, respectively. Among trials used to estimate STE, 27 of 28 were adequately powered, showed BMD effects exceeding the STE, and showed significant reductions in fracture risk. Among the validation set of 11 trials, 10 met these criteria. Thus STE differs by fracture type and has been validated in trials not used to develop the approach. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Characterization and standardization of multiassay platforms for four commonly studied traumatic brain injury protein biomarkers: a TBI Endpoints Development Study

Aim: There is a critical need to validate biofluid-based biomarkers as diagnostic and drug development tools for traumatic brain injury (TBI). As part of the TBI Endpoints Development Initiative, we identified four potentially predictive and pharmacodynamic biomarkers for TBI: astroglial markers GFAP and S100B and the neuronal markers UCH-L1 and Tau. Materials & methods: Several commonly used platforms for these four biomarkers were identified and compared on analytic performance and ability to detect gold standard recombinant protein antigens and to pool control versus TBI cerebrospinal fluid (CSF). Results: For each marker, only some assay formats could differentiate TBI CSF from the control CSF. Also, different assays for the same biomarker reported divergent biomarker values for the same biosamples. Conclusion: Due to the variability of TBI marker assay in performance and reported values, standardization strategies are recommended when comparing reported biomarker levels across assay platforms.

Single patient classifier as a prognostic biomarker in pT1N1 gastric cancer: Results from two large Korean cohorts

Objective

Benefits of adjuvant treatment in pT1N1 gastric cancer (GC) remain controversial. Additionally, an effective biomarker for early GC is the need of the hour. The prognostic and predictive roles of single patient classifier (SPC) were validated in stage II/III GC. In this study, we aimed to elucidate the role of SPC as a biomarker for pT1N1 GC.

Methods

The present retrospective biomarker study (NCT03485105) enrolled patients treated for pT1N1 GC between 1996 and 2012 from two large hospitals (the Y cohort and S cohort). For SPC, mRNA expression of four classifier genes (GZMB, WARS, SFRP4 and CDX1) were evaluated by real-time reverse transcription-polymerase chain reaction assay. The SPC was revised targeting pT1 stages and the prognosis was stratified as high- and low-risk group by the expression of SFRP4, a representative epithelial-mesenchymal transition marker.

Results

SPC was evaluated in 875 patients (n=391 and 484 in the Y and S cohorts, respectively). Among 864 patients whose SPC result was available, 41 (4.7%) patients experience GC recurrence. According to revised SPC, 254 (29.4%) patients were classified as high risk [123 (31.5%) and 131 (27.1%) in the Y and S cohorts, respectively]. The high risk was related to frequent recurrence in both Y and S cohort (log-rank P=0.023, P<0.001, respectively), while there was no difference byGZMB and WARS expression. Multivariable analyses of the overall-cohort confirmed the high risk of revised SPC as a significant prognostic factor [hazard ratio (HR): 4.402 (2.293−8.449), P<0.001] of GC. A significant difference was not detected by SPC in the prognosis of patients in the presence and absence of adjuvant treatment (log-rank P=0.670).

Conclusions

The present study revealed the revised SPC as a prognostic biomarker of pT1N1 GC and suggested the use of the revised SPC for early-stage GC as like stage II/III.

The Impact of Sub-maximal Exercise on Neuropathic Pain, Inflammation, and Affect Among Adults With Spinal Cord Injury: A Pilot Study

Introduction: Persons with spinal cord injury (SCI) often report high levels of neuropathic pain (NP) and poor well-being, which may result from increased inflammation. This study examined the impact of sub-maximal aerobic exercise on NP, inflammation and psychological affect among adults with SCI. Methods: Eight active adults with tetraplegia (n-4, AIS A-C) and paraplegia (n = 4, AIS A-C) performed 30-min of arm-crank aerobic exercise and reported their ratings of perceived exertion (RPE) each minute. Measures of NP, affect, and inflammatory cytokines (IL-6, IL-10, IL-1ra, TNF-α) were taken pre-(T₀), immediately post-(T₁), and 90-min post-exercise (T₂). Results: NP decreased between T₀ and T₁ for tetraplegics (-60%, d = 0.47; CI = -0.32, 2.02) and paraplegics (-16%, d = 0.15; CI = -0.30, 0.90). Correlations between change in cytokines and change in NP were medium-to large for tetraplegics (rs ranged from -0.820 to 0.965) and paraplegics (rs ranged from -0.598 to 0.833). However, the pattern of correlations between change in cytokines and affect was inconsistent between groups. Lower baseline levels of IL-1ra predicted greater decreases in NP immediately post-exercise (r = 0.83, p = 0.01). Conclusion: Sub-maximal exercise can positively impact NP for some persons with SCI. Further experimental research should identify the optimal exercise intensity to reduce NP for persons with SCI, in addition to understanding biomarkers which may predict changes in NP. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03955523.

Rhesus macaques self-curing from a schistosome infection can display complete immunity to challenge

The rhesus macaque provides a unique model of acquired immunity against schistosomes, which afflict >200 million people worldwide. By monitoring bloodstream levels of parasite-gut-derived antigen, we show that from week 10 onwards an established infection with Schistosoma mansoni is cleared in an exponential manner, eliciting resistance to reinfection. Secondary challenge at week 42 demonstrates that protection is strong in all animals and complete in some. Antibody profiles suggest that antigens mediating protection are the released products of developing schistosomula. In culture they are killed by addition of rhesus plasma, collected from week 8 post-infection onwards, and even more efficiently with post-challenge plasma. Furthermore, cultured schistosomula lose chromatin activating marks at the transcription start site of genes related to worm development and show decreased expression of genes related to lysosomes and lytic vacuoles involved with autophagy. Overall, our results indicate that enhanced antibody responses against the challenge migrating larvae mediate the naturally acquired protective immunity and will inform the route to an effective vaccine.

To date there is only one single drug with modest efficacy and no vaccine available to protect from schistosomiasis. Here, Amaral et al. characterize the self-cure process of rhesus macaques following primary infection and secondary challenge with Schistosoma mansoni to inform future vaccine development studies.

Potential policy reforms to strengthen the accelerated approval pathway

The accelerated approval pathway for new drugs in the United States is often praised but faces growing criticism of whether it is finding the appropriate balance between uncertainty, access and cost. To support efforts to strengthen the pathway, this paper provides an analysis of key concerns and the advantages and disadvantages of ten potential policy reforms - those achievable through the US FDA action alone, and those that would require a combination of government, payer and life science industry actions. Accelerated approval sits at the heart of many of the controversies regarding drug approvals and pricing, and this analysis provides perspectives on how best to strengthen the pathway within the broader landscape of an innovative US healthcare system.

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders

In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the 'New Frontiers Meeting' on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies.

Potential clinical biomarkers in rheumatoid arthritis with an omic approach

Objective

To aid in the selection of the most suitable therapeutic option in patients with diagnosis of rheumatoid arthritis according to the phase of disease, through the review of articles that identify omics biological markers.

Methods

A systematic review in PubMed/Medline databases was performed. We searched articles from August 2014 to September 2019, in English and Spanish, filtered by title and full text; and using the terms "Biomarkers" AND “Rheumatoid arthritis".

Results

This article supplies an exhaustive review from research of objective measurement, omics biomarkers and how disease activity appraise decrease unpredictability in treatment determinations, and finally, economic, and clinical outcomes of treatment options by biomarkers’ potential influence. A total of 122 articles were included. Only 92 met the established criteria for review purposes and 17 relevant references about the topic were included as well. Therefore, it was possible to identify 196 potential clinical biomarkers: 22 non-omics, 20 epigenomics, 33 genomics, 21 transcriptomics, 78 proteomics, 4 glycomics, 1 lipidomics and 17 metabolomics.

Conclusion

A biomarker is a measurable indicator of some, biochemical, physiological, or morphological condition; evaluable at a molecular, biochemical, or cellular level. Biomarkers work as indicators of physiological or pathological processes, or as a result of a therapeutic management. In the last five years, new biomarkers have been identified, especially the omics, which are those that proceed from the investigation of genes (genomics), metabolites (metabolomics), and proteins (proteomics). These biomarkers contribute to the physician choosing the best therapeutic option in patients with rheumatoid arthritis.

A Roadmap for Developing Plasma Diagnostic and Prognostic Biomarkers of Cerebral Cavernous Angioma With Symptomatic Hemorrhage (CASH)

BACKGROUND

Cerebral cavernous angioma (CA) is a capillary microangiopathy predisposing more than a million Americans to premature risk of brain hemorrhage. CA with recent symptomatic hemorrhage (SH), most likely to re-bleed with serious clinical sequelae, is the primary focus of therapeutic development. Signaling aberrations in CA include proliferative dysangiogenesis, blood-brain barrier hyperpermeability, inflammatory/immune processes, and anticoagulant vascular domain. Plasma levels of molecules reflecting these mechanisms and measures of vascular permeability and iron deposition on magnetic resonance imaging are biomarkers that have been correlated with CA hemorrhage.

OBJECTIVE

To optimize these biomarkers to accurately diagnose cavernous angioma with symptomatic hemorrhage (CASH), prognosticate the risk of future SH, and monitor cases after a bleed and in response to therapy.

METHODS

Additional candidate biomarkers, emerging from ongoing mechanistic and differential transcriptome studies, would further enhance the sensitivity and specificity of diagnosis and prediction of CASH. Integrative combinations of levels of plasma proteins and characteristic micro-ribonucleic acids may further strengthen biomarker associations. We will deploy advanced statistical and machine learning approaches for the integration of novel candidate biomarkers, rejecting noncorrelated candidates, and determining the best clustering and weighing of combined biomarker contributions.

EXPECTED OUTCOMES

With the expertise of leading CA researchers, this project anticipates the development of future blood tests for the diagnosis and prediction of CASH to clinically advance towards precision medicine.

DISCUSSION

The project tests a novel integrational approach of biomarker development in a mechanistically defined cerebrovascular disease with a relevant context of use, with an approach applicable to other neurological diseases with similar pathobiologic features.

Biomarkers and Surrogate End points in Multiple Sclerosis Trials: Regulatory Issues

SUMMARY

Evoked potentials have assisted in the diagnosis of multiple sclerosis for years, but the potential to demonstrate pathophysiologic change has prompted a reconsideration of their potential role as outcome measures in clinical trials of multiple sclerosis. The use of any surrogate end point or biomarker in clinical trials requires a thorough understanding of that end point's performance characteristics and utility in a particular setting. This article explores regulatory issues regarding the use of biomarkers and surrogate end points in clinical trials of multiple sclerosis with particular emphasis on challenges faced by evoked potential studies.

An integrated workflow for biomarker development using microRNAs in extracellular vesicles for cancer precision medicine

EV-miRNAs are microRNA (miRNA) molecules encapsulated in extracellular vesicles (EVs), which play crucial roles in tumor pathogenesis, progression, and metastasis. Recent studies about EV-miRNAs have gained novel insights into cancer biology and have demonstrated a great potential to develop novel liquid biopsy assays for various applications. Notably, compared to conventional liquid biomarkers, EV-miRNAs are more advantageous in representing host-cell molecular architecture and exhibiting higher stability and specificity. Despite various available techniques for EV-miRNA separation, concentration, profiling, and data analysis, a standardized approach for EV-miRNA biomarker development is yet lacking. In this review, we performed a substantial literature review and distilled an integrated workflow encompassing important steps for EV-miRNA biomarker development, including sample collection and EV isolation, EV-miRNA extraction and quantification, high-throughput data preprocessing, biomarker prioritization and model construction, functional analysis, as well as validation. With the rapid growth of "big data", we highlight the importance of efficient mining of high-throughput data for the discovery of EV-miRNA biomarkers and integrating multiple independent datasets for in silico and experimental validations to increase the robustness and reproducibility. Furthermore, as an efficient strategy in systems biology, network inference provides insights into the regulatory mechanisms and can be used to select functionally important EV-miRNAs to refine the biomarker candidates. Despite the encouraging development in the field, a number of challenges still hinder the clinical translation. We finally summarize several common challenges in various biomarker studies and discuss potential opportunities emerging in the related fields.

Targeting for Success: Demonstrating Proof-of-Concept with Mechanistic Early Phase Clinical Pharmacology Studies for Disease-Modification in Neurodegenerative Disorders

The clinical failure rate for disease-modifying treatments (DMTs) that slow or stop disease progression has been nearly 100% for the major neurodegenerative disorders (NDDs), with many compounds failing in expensive and time-consuming phase 2 and 3 trials for lack of efficacy. Here, we critically review the use of pharmacological and mechanistic biomarkers in early phase clinical trials of DMTs in NDDs, and propose a roadmap for providing early proof-of-concept to increase R&D productivity in this field of high unmet medical need. A literature search was performed on published early phase clinical trials aimed at the evaluation of NDD DMT compounds using MESH terms in PubMed. Publications were selected that reported an early phase clinical trial with NDD DMT compounds between 2010 and November 2020. Attention was given to the reported use of pharmacodynamic (mechanistic and physiological response) biomarkers. A total of 121 early phase clinical trials were identified, of which 89 trials (74%) incorporated one or multiple pharmacodynamic biomarkers. However, only 65 trials (54%) used mechanistic (target occupancy or activation) biomarkers to demonstrate target engagement in humans. The most important categories of early phase mechanistic and response biomarkers are discussed and a roadmap for incorporation of a robust biomarker strategy for early phase NDD DMT clinical trials is proposed. As our understanding of NDDs is improving, there is a rise in potentially disease-modifying treatments being brought to the clinic. Further increasing the rational use of mechanistic biomarkers in early phase trials for these (targeted) therapies can increase R&D productivity with a quick win/fast fail approach in an area that has seen a nearly 100% failure rate to date.

Treatment-Related Changes in Bone Turnover and Fracture Risk Reduction in Clinical Trials of Antiresorptive Drugs: Proportion of Treatment Effect Explained

Few analyses of antiresorptive (AR) treatment trials relate short-term changes in bone turnover markers (BTMs) to subsequent fracture reduction seeking to estimate the proportion of treatment effect explained (PTE) by BTMs. Pooling such information would be useful to assess new ARs or novel dosing regimens. In the Foundation for the National Institutes of Health (FNIH) Bone Quality project, we analyzed individual-level data from up to 62,000 participants enrolled in 12 bisphosphonate (BP) and four selective estrogen receptor modulator (SERM) placebo-controlled fracture endpoint trials. Using BTM results for two bone formation markers (bone-specific alkaline phosphatase [bone ALP] and pro-collagen I N-propeptide [PINP]) and one bone resorption marker (C-terminal telopeptide of type I collagen [CTX]) and incident fracture outcome data, we estimated the PTE using two different models. Separate analyses were performed for incident morphometric vertebral, nonvertebral, and hip fractures over 1 to 5 years of follow-up. For vertebral fracture, the results showed that changes in all three BTMs at 6 months explained a large proportion of the treatment effect of ARs (57 to >100%), but not for and non-vertebral or hip fracture. We conclude that short-term AR treatment-related changes in bone ALP, PINP, and CTX account for a large proportion of the treatment effect for vertebral fracture. Change in BTMs is a useful surrogate marker to study the anti-fracture efficacy of new AR compounds or novel dosing regiments with approved AR drugs. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

The acute respiratory distress syndrome biomarker pipeline: crippling gaps between discovery and clinical utility

Recent innovations in translational research have ushered an exponential increase in the discovery of novel biomarkers, thereby elevating the hope for deeper insights into "personalized" medicine approaches to disease phenotyping and care. However, a critical gap exists between the fast pace of biomarker discovery and the successful translation to clinical use. This gap underscores the fundamental biomarker conundrum across various acute and chronic disorders: how does a biomarker address a specific unmet need? Additionally, the gap highlights the need to shift the paradigm from a focus on biomarker discovery to greater translational impact and the need for a more streamlined drug approval process. The unmet need for biomarkers in acute respiratory distress syndrome (ARDS) is for reliable and validated biomarkers that minimize heterogeneity and allow for stratification of subject selection for enrollment in clinical trials of tailored therapies. This unmet need is particularly highlighted by the ongoing SARS-CoV-2/COVID-19 pandemic. The unprecedented numbers of COVID-19-induced ARDS cases has strained health care systems across the world and exposed the need for biomarkers that would accelerate drug development and the successful phenotyping of COVID-19-infected patients at risk for development of ARDS and ARDS mortality. Accordingly, this review discusses the current state of ARDS biomarkers in the context of the drug development pipeline and highlight gaps between biomarker discovery and clinical implementation while proposing potential paths forward. We discuss potential ARDS biomarkers by category and by context of use, highlighting progress in the development continuum. We conclude by discussing challenges to successful translation of biomarker candidates to clinical impact and proposing possible novel strategies.

Improving cardiotoxicity prediction in cancer treatment: integration of conventional circulating biomarkers and novel exploratory tools

Early detection strategies and improvements in cancer treatment have dramatically reduced the cancer mortality rate in the United States (US). However, cardiovascular (CV) side effects of cancer therapy are frequent among the 17 million cancer survivors in the US today, and cardiovascular disease (CVD) has become the second leading cause of morbidity and mortality among cancer survivors. Circulating biomarkers are ideal for detecting and monitoring CV side effects of cancer therapy. Here, we summarize the current state of clinical studies on conventional serum and plasma CVD biomarkers to detect and prevent cardiac injury during cancer treatment. We also review how novel exploratory tools such as genetic testing, human stem cell-derived cardiomyocytes, Omics technologies, and artificial intelligence can elucidate underlying molecular and genetic mechanisms of CV injury and to improve predicting cancer therapy-related cardiotoxicity (CTRC). Current regulatory requirements for biomarker qualifications are also addressed. We present generally applicable lessons learned from published studies, particularly on how to improve reproducibility. The combination of conventional circulating biomarkers and novel exploratory tools will pave the way for precision medicine and improve the clinical practice of prediction, detection, and management of CTRC.

miRNAs as Potential Biomarkers for Traumatic Brain Injury: Pathway From Diagnosis to Neurorehabilitation

BACKGROUND

Biomarkers that can advance precision neurorehabilitation of the traumatic brain injury (TBI) are needed. MicroRNAs (miRNAs) have biological properties that could make them well suited for playing key roles in differential diagnoses and prognoses and informing likelihood of responsiveness to specific treatments.

OBJECTIVE

To review the evidence of miRNA alterations after TBI and evaluate the state of science relative to potential neurorehabilitation applications of TBI-specific miRNAs.

METHODS

This scoping review includes 57 animal and human studies evaluating miRNAs after TBI. PubMed, Scopus, and Google Scholar search engines were used.

RESULTS

Gold standard analytic steps for miRNA biomarker assessment are presented. Published studies evaluating the evidence for miRNAs as potential biomarkers for TBI diagnosis, severity, natural recovery, and treatment-induced outcomes were reviewed including statistical evaluation. Growing evidence for specific miRNAs, including miR21, as TBI biomarkers is presented.

CONCLUSIONS

There is evidence of differential miRNA expression in TBI in both human and animal models; however, gaps need to be filled in terms of replication using rigorous, standardized methods to isolate a consistent set of miRNA changes. Longitudinal studies in TBI are needed to understand how miRNAs could be implemented as biomarkers in clinical practice.

Age-Dependent Changes of Kidney Injury Biomarkers in Pediatrics

Currently used creatinine-based parameters for monitoring kidney function are not reliable for early detection of kidney injury (KI), particularly tubular damage. Several KI biomarkers allow for early detection of glomerular and tubular damage and may help to prevent drug-related chronic kidney diseases in pediatrics. This literature review describes the state of current research and investigates reference values for these KI biomarkers in neonates, infants, and children to better understand age-related changes. A total of 12 of 237 screened studies fulfilled predefined criteria, including 219 preterm neonates, 70 neonates, 596 infants, and 1726 children. KI biomarkers were analyzed in urine (6 studies), in serum/plasma (5 studies) and in serum and urine (1 study). Four studies (n = 555) measured urinary kidney injury molecule-1, whereas urinary neutrophil gelatinase-associated lipocalin was assessed in 5 studies (n = 888), and 2 studies (n = 203) investigated serum cystatin C. This review of KI biomarkers in different pediatric age groups indicates that (1) the majority of KI biomarkers are measured in urine; (2) the 3 most commonly analyzed KI biomarkers are urinary neutrophil gelatinase-associated lipocalin, urinary kidney injury molecule-1, and serum cystatin C; (3) values of KI biomarkers appear to decrease from prematurity to infancy; and (4) there is an unmet need to further enhance knowledge on age-dependent changes of KI biomarkers in pediatrics. Studies are needed to better characterize reference values for these key KI biomarkers in healthy pediatric populations and to evaluate the value of these markers in the early detection of drug-related KI in neonates, infants, and children.

Accelerated Approval or Risk Reduction? How Response Biomarkers Advance Therapeutics through Clinical Trials in Cystic Fibrosis

Progress in the development of new therapies for cystic fibrosis (CF) has benefited from therapeutically responsive biomarkers to streamline drug development. Paradoxically, these response biomarkers have been proven to be essential even in the presence of data demonstrating a lack of correlation with clinical outcomes across individuals with CF. This finding is unsurprising, particularly in the setting of a rare disease given complex disease processes and an often-limited pool of clinically effective therapies by which to link biomarkers and clinical responsiveness. While many response biomarkers will be unable to progress from their status as markers of biological efficacy to either established correlates of clinical efficacy or surrogate endpoints, they remain critical to the overall success of therapeutic development.

Can the Onset of Atrophic Age-Related Macular Degeneration Be an Acceptable Endpoint for Preventative Trials?

The slowly progressive nature of age-related macular degeneration (AMD) means that establishing the efficacy of novel preventative treatments aiming to slow progression of disease, remains challenging, and where earlier endpoints are needed to improve their feasibility. This review examines whether the onset of atrophic AMD, as seen as anatomical signs on optical coherence tomography termed nascent geographic atrophy, could act as a useful surrogate endpoint for early intervention trials.

Pharmacodynamic Biomarkers for Emerging LRRK2 Therapeutics

Genetic studies have identified variants in the LRRK2 gene as important components of Parkinson's disease (PD) pathobiology. Biochemical and emergent biomarker studies have coalesced around LRRK2 hyperactivation in disease. Therapeutics that diminish LRRK2 activity, either with small molecule kinase inhibitors or anti-sense oligonucleotides, have recently advanced to the clinic. Historically, there have been few successes in the development of therapies that might slow or halt the progression of neurodegenerative diseases. Over the past few decades of biomedical research, retrospective analyses suggest the broad integration of informative biomarkers early in development tends to distinguish successful pipelines from those that fail early. Herein, we discuss the biomarker regulatory process, emerging LRRK2 biomarker candidates, assays, underlying biomarker biology, and clinical integration.