Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Blood-brain barrier biomarkers

The blood-brain barrier (BBB) is a dynamic interface that regulates the exchange of molecules and cells between the brain parenchyma and the peripheral blood. The BBB is mainly composed of endothelial cells, astrocytes and pericytes. The integrity of this structure is essential for maintaining brain and spinal cord homeostasis and protection from injury or disease. However, in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, and multiple sclerosis, the BBB can become compromised thus allowing passage of molecules and cells in and out of the central nervous system parenchyma. These agents, however, can serve as biomarkers of BBB permeability and neuronal damage, and provide valuable information for diagnosis, prognosis and treatment. Herein, we provide an overview of the BBB and changes due to aging, and summarize current knowledge on biomarkers of BBB disruption and neurodegeneration, including permeability, cellular, molecular and imaging biomarkers. We also discuss the challenges and opportunities for developing a biomarker toolkit that can reliably assess the BBB in physiologic and pathophysiologic states.

Atherosclerosis and the Bidirectional Relationship between Cancer and Cardiovascular Disease: From Bench to Bedside-Part 1

Atherosclerosis, a complex metabolic-immune disease characterized by chronic inflammation driven by the buildup of lipid-rich plaques within arterial walls, has emerged as a pivotal factor in the intricate interplay between cancer and cardiovascular disease. This bidirectional relationship, marked by shared risk factors and pathophysiological mechanisms, underscores the need for a comprehensive understanding of how these two formidable health challenges intersect and influence each other. Cancer and its treatments can contribute to the progression of atherosclerosis, while atherosclerosis, with its inflammatory microenvironment, can exert profound effects on cancer development and outcomes. Both cancer and cardiovascular disease involve intricate interactions between general and personal exposomes. In this review, we aim to summarize the state of the art of translational data and try to show how oncologic studies on cardiotoxicity can broaden our knowledge of crucial pathways in cardiovascular biology and exert a positive impact on precision cardiology and cardio-oncology.

Socioeconomic inequalities in cardiovascular disease: a causal perspective

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Endpoints for clinical trials in ophthalmology

With the identification of novel targets, the number of interventional clinical trials in ophthalmology has increased. Visual acuity has for a long time been considered the gold standard endpoint for clinical trials, but in the recent years it became evident that other endpoints are required for many indications including geographic atrophy and inherited retinal disease. In glaucoma the currently available drugs were approved based on their IOP lowering capacity. Some recent findings do, however, indicate that at the same level of IOP reduction, not all drugs have the same effect on visual field progression. For neuroprotection trials in glaucoma, novel surrogate endpoints are required, which may either include functional or structural parameters or a combination of both. A number of potential surrogate endpoints for ophthalmology clinical trials have been identified, but their validation is complicated and requires solid scientific evidence. In this article we summarize candidates for clinical endpoints in ophthalmology with a focus on retinal disease and glaucoma. Functional and structural biomarkers, as well as quality of life measures are discussed, and their potential to serve as endpoints in pivotal trials is critically evaluated.

Clinically important effect sizes for clinical trials using infarct growth reduction as the primary outcome: a systematic review

BACKGROUND

Infarct growth on multimodal imaging is a common lead outcome in phase 2 proof-of-concept and dose-optimization neuroprotective agent stroke trials. However, the effect size in infarct growth reduction that correlates with clinically meaningful differences in clinical global disability outcomes has not been well delineated.

METHODS

A systematic literature search identified all endovascular thrombectomy randomized trials reporting magnitude of treatment effect on both infarct growth reduction and increase in functional independence (modified Rankin Scale (mRS) 0-2). Data aggregation determined the size of infarct growth reductions salient to four types of clinically meaningful effect sizes of increase in functional independence: (1) the minimal clinically important difference (MCID)-outcome specific; (2) the MCID-practice changing; (3) the realistic target difference; and (4) the reasonable comparability effect size.

RESULTS

A systematic search identified four trials enrolling 612 imaged participants. Across the trials, the amount of functional independence (mRS 0-2) increase associated with each 1 mL reduction in infarct growth was mean 2.3±0.6%. An infarct growth reduction of 0.57 mL correlated with the mRS 0-2 increase MCID of 1.3%. Infarct growth reductions of 2.27 mL, 4.35 mL, and 6.53 mL correlated with realistic effect and reasonable comparability effects sizes of mRS 0-2 increases of 5%, 10%, and 15%, respectively.

CONCLUSION

In formal meta-analysis of randomized treatment trials, every 1 mL reduction in infarct growth was associated with a 2.3% increase in functional independence (mRS 0-2) at 3 months. This conversion factor can inform selection of infarct growth effect size targets for phase 2 trials of neuroprotective agents.

Human Gut Microbiota in Heart Failure: Trying to Unmask an Emerging Organ

There is a bidirectional relationship between the heart and the gut. The gut microbiota, the community of gut micro-organisms themselves, is an excellent gut-homeostasis keeper since it controls the growth of potentially harmful bacteria and protects the microbiota environment. There is evidence suggesting that a diet rich in fatty acids can be metabolized and converted by gut microbiota and hepatic enzymes to trimethyl-amine N-oxide (TMAO), a product that is associated with atherogenesis, platelet dysfunction, thrombotic events, coronary artery disease, stroke, heart failure (HF), and, ultimately, death. HF, by inducing gut ischemia, congestion, and, consequently, gut barrier dysfunction, promotes the intestinal leaking of micro-organisms and their products, facilitating their entrance into circulation and thus stimulating a low-grade inflammation associated with an immune response. Drugs used for HF may alter the gut microbiota, and, conversely, gut microbiota may modify the pharmacokinetic properties of the drugs. The modification of lifestyle based mainly on exercise and a Mediterranean diet, along with the use of pre- or probiotics, may be beneficial for the gut microbiota environment. The potential role of gut microbiota in HF development and progression is the subject of this review.

Migraine: Advances in the Pathogenesis and Treatment

This article presents a comprehensive review on migraine, a prevalent neurological disorder characterized by chronic headaches, by focusing on their pathogenesis and treatment advances. By examining molecular markers and leveraging imaging techniques, the research identifies key mechanisms and triggers in migraine pathology, thereby improving our understanding of its pathophysiology. Special emphasis is given to the role of calcitonin gene-related peptide (CGRP) in migraine development. CGRP not only contributes to symptoms but also represents a promising therapeutic target, with inhibitors showing effectiveness in migraine management. The article further explores traditional medical treatments, scrutinizing the mechanisms, benefits, and limitations of commonly prescribed medications. This provides a segue into an analysis of emerging therapeutic strategies and their potential to enhance migraine management. Finally, the paper delves into neuromodulation as an innovative treatment modality. Clinical studies indicating its effectiveness in migraine management are reviewed, and the advantages and limitations of this technique are discussed. In summary, the article aims to enhance the understanding of migraine pathogenesis and present novel therapeutic possibilities that could revolutionize patient care.

Prognostic Value of Plasma Biomarkers S100B and Osteopontin in Pediatric TBI: A Prospective Analysis Evaluating Acute and 6-Month Outcomes after Mild to Severe TBI

Blood based traumatic brain injury (TBI) biomarkers offer additional diagnostic, therapeutic, and prognostic utility. While adult studies are robust, the pediatric population is less well studied. We sought to determine whether plasma osteopontin (OPN) and S100B alone or in combination predict mortality, head Computed tomography (CT) findings, as well as 6-month functional outcomes after TBI in children. This is a prospective, observational study between March 2017 and June 2021 at a tertiary pediatric hospital. The sample included children with a diagnosed head injury of any severity admitted to the Emergency Department. Control patients sustained trauma-related injuries and no known head trauma. Serial blood samples were collected at admission, as well as at 24, 48, and 72 h. Patient demographics, acute clinical symptoms, head CT, and 6-month follow-up using the Glasgow outcome scale, extended for pediatrics (GOSE-Peds), were also obtained. The cohort included 460 children (ages 0 to 21 years) and reflected the race and sex distribution of the population served. Linear mixed effect models and logistic regressions were utilized to evaluate the trajectory of biomarkers over time and predictors of dichotomous outcomes. Both OPN and S100B correlated with injury severity based on GCS. S100B and OPN showed lower AUC values (0.59) in predicting positive head CT. S100B had the largest AUC (0.87) in predicting mortality, as well as 6-month outcomes (0.85). The combination of the two biomarkers did not add meaningfully to the model. Our findings continue to support the utility of OPN as a marker of injury severity in this population. Our findings also show the importance of S100B in predicting mortality and 6-month functional outcomes. Continued work is needed to examine the influence of age-dependent neurodevelopment on TBI biomarker profiles in children.

Valero's host index is useful in predicting radiation-induced trismus and osteoradionecrosis of the jaw risks in locally advanced nasopharyngeal carcinoma patients

BACKGROUND

In the absence of previous research, we sought to assess the H-Index's predictive significance for radiation-induced trismus (RIT) and osteoradionecrosis of the jaw (ORNJ) in patients with locally advanced nasopharyngeal carcinoma (LA-NPC) receiving concurrent chemoradiotherapy (C-CRT).

PATIENTS AND METHODS

The research comprised 295 LA-NPC patients who had C-CRT and pre- and post-C-CRT oral exams between June 2010 and December 2021. The H-Index was calculated using neutrophils, monocytes, lymphocytes, hemoglobin, and albumin measurements obtained on the first day of C-CRT. Patients were divided into three and two H-index groups, respectively, based on previously established cutoff values (1.5 and 3.5) and the cutoff value determined by our receiver operating characteristic (ROC) curve analysis. The primary objective was the presence of any significant connections between pretreatment H-Index groups and post-C-CRT RIT and ORNJ rates.

RESULTS

RIT and ORNJ was diagnosed in 46 (15.6%) and 13 (7.8%) patients, respectively. The original H-Index grouping could only categorize RIT and ORNJ risks at a cutoff value of 3.5, with no significant differences in RIT and ORNJ rates between groups with H-Index 1.5 and 1.5 to 3.5 (P < 0.05 for each). The ideal H-Index cutoff for both RIT and ORNJ rates was found to be 5.5 in ROC curve analysis, which divided the entire research population into two groups: H-Index ≤ 5.5 (N = 195) and H-Index > 5.5 (N = 110). Intergroup comparisons revealed that patients in the H-Index > 5.5 group had significantly higher rates of either RIT (31.8% vs. 5.9%; P < 0.001) or ORNJ (17.3% vs. 2.2%; P < 0.001) than their H-Index ≤ 5.5 counterparts. The results of the multivariate analysis showed that H-Index > 5.5 was independently linked to significantly higher RIT (P < 0.001) and ORNJ (P < 0.001) rates.

CONCLUSION

Pre-C-CRT H-Index > 5.5 is associated with significantly increased RIT and ORNJ rates in LA-NPC patients receiving definitive C-CRT.

Vitamin D serum level in participants with positive history of recurrent herpes labialis

AIM

Vitamin D plays an important role in immune system regulation, also its deficiency is assumed to affect the patients' predisposition to viral diseases such as recurrent herpes labialis. In this cross-sectional study, we tried to compare the mean serum level of vitamin D in participants with a positive history of recurrent herpes labial lesions and healthy controls.

MATERIALS AND METHODS

The vitamin D serum level of 43 participants with a positive history of recurrent herpes labial lesions who were referred to the Motahhari laboratory in Shiraz during 2020-2022, was compared with 42 healthy controls. It was assessed by an Elisa kit. An Independent T-test was used to compare the vitamin D serum level between two genders. In order to assess the mean age value and gender distribution, an independent T-test and Pearson Chi-Square were used, respectively for the two groups. The serum vitamin D level was compared between both control and test groups.

RESULTS

There was no significant difference between vitamin D mean serum levels in the two evaluated groups (p.value = 0.72). Although the age (p.value = 0.09) and recurrence (p.value = 0.13) of herpes labialis had no statistically significant relation to the vitamin D serum level, the healing duration of herpes labialis was inversely related (p.value = 0.01). Lower-level of serum vitamin D were accompanied by a longer healing duration of the lesions.

CONCLUSION

Although the vitamin D serum level of participants with a history of recurrent herpes labialis had no relation with age and herpes virus recurrence frequency, a longer healing duration of lesions had been reported in patients with lower serum levels of vitamin D.

Decreased kynurenine in cerebrospinal fluid and potential role in neuromyelitis optica spectrum disorder

Tryptophan (Trp) metabolism has been implicated in neuroinflammatory and neurodegenerative disorders, but its relationship with neuromyelitis optica spectrum disorder (NMOSD) is unclear. In this pilot study, cerebrospinal fluid (CSF) was prospectively collected from 26 NMOSD patients in relapse and 16 controls with noninflammatory diseases and 6 neurometabolites in the tryptophan metabolic pathway, including 5-hydroxytryptamine (5-HT), kynurenine (KYN), melatonin (MLT), 5-hydroxyindoleacetic acid (5HIAA), 3-hydroxy-o-aminobenzoic acid (3-HAA), and kynurenic acid (KYA), were measured by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The association of Trp metabolites with NMOSD and its clinical parameters was evaluated. The role of KYN, which is a Trp metabolite involved in the binding of NMOSD-IgG antibody to aquaporin 4 (AQP4), was also evaluated in vitro. CSF KYN was significantly decreased in patients with relapsing NMOSD compared to controls, and CSF KYN was associated with CSF white blood cells in NMOSD. In vitro experiments showed that NMOSD-IgG specifically recognized KYN, which reversed the NMOSD-IgG-induced downregulation of AQP4 expression. Our results show that abnormal Trp metabolism occurs in NMOSD and that KYN might be a potential target for the treatment of AQP4-IgG-positive NMOSD patients.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

The spectrum of clinical biomarkers in severe malaria and new avenues for exploration

Globally, malaria is a public health concern, with severe malaria (SM) contributing a major share of the disease burden in malaria endemic countries. In this context, identification and validation of SM biomarkers are essential in clinical practice. Some biomarkers (C-reactive protein, angiopoietin 2, angiopoietin-2/1 ratio, platelet count, histidine-rich protein 2) have yielded interesting results in the prognosis of Plasmodium falciparum severe malaria, but for severe P. vivax and P. knowlesi malaria, similar evidence is missing. The validation of these biomarkers is hindered by several factors such as low sample size, paucity of evidence-evaluating studies, suboptimal values of sensitivity/specificity, poor clinical practicality of measurement methods, mixed Plasmodium infections, and good clinical value of the biomarkers for concurrent infections (pneumonia and current COVID-19 pandemic). Most of these biomarkers are non-specific to pathogens as they are related to host response and hence should be regarded as prognostic/predictive biomarkers that complement but do not replace pathogen biomarkers for clinical evaluation of SM patients. This review highlights the importance of research on diagnostic/predictive/therapeutic biomarkers, neglected malaria species, and clinical practicality of measurement methods in future studies. Finally, the importance of omics technologies for faster identification/validation of SM biomarkers is also included.

Reduced subgenual cingulate-dorsolateral prefrontal connectivity as an electrophysiological marker for depression

Major Depressive Disorder (MDD) is a widespread mental illness that causes considerable suffering, and neuroimaging studies are trying to reduce this burden by developing biomarkers that can facilitate detection. Prior fMRI- and neurostimulation studies suggest that aberrant subgenual Anterior Cingulate (sgACC)-dorsolateral Prefrontal Cortex (DLPFC) functional connectivity is consistently present within MDD. Combining the need for reliable depression markers with the electroencephalogram's (EEG) high clinical utility, we investigated whether aberrant EEG sgACC-DLPFC functional connectivity could serve as a marker for depression. Source-space Amplitude Envelope Correlations (AEC) of 20 MDD patients and 20 matched controls were contrasted using non-parametric permutation tests. In addition, extracted AEC values were used to (a) correlate with characteristics of depression and (b) train a Support Vector Machine (SVM) to determine sgACC-DLPFC connectivity's discriminative power. FDR-thresholded statistical maps showed reduced sgACC-DLPFC AEC connectivity in MDD patients relative to controls. This diminished AEC connectivity is located in the beta-1 (13-17 Hz) band and is associated with patients' lifetime number of depressive episodes. Using extracted sgACC-DLPFC AEC values, the SVM achieved a classification accuracy of 84.6% (80% sensitivity and 89.5% specificity) indicating that EEG sgACC-DLPFC connectivity has promise as a biomarker for MDD.

The Key Role of Magnetic Resonance Imaging in the Detection of Neurodegenerative Diseases-Associated Biomarkers: A Review

Neurodegenerative diseases (NDs), including chronic disease such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis, and acute diseases like traumatic brain injury and ischemic stroke are characterized by progressive degeneration, brain tissue damage and loss of neurons, accompanied by behavioral and cognitive dysfunctions. So far, there are no complete cures for NDs; thus, early and timely diagnoses are essential and beneficial to patients' treatment. Magnetic resonance imaging (MRI) has become one of the advanced medical imaging techniques widely used in the clinical examination of NDs due to its non-invasive diagnostic value. In this review, research published in English in current decade from PubMed electronic database on the use of MRI to detect specific biomarkers of NDs was collected, summarized, and discussed, which provides valuable suggestions for the early diagnosis, prevention, and treatment of NDs in the clinic.

Unlocking the Potential of the Human Microbiome for Identifying Disease Diagnostic Biomarkers

The human microbiome encodes more than three million genes, outnumbering human genes by more than 100 times, while microbial cells in the human microbiota outnumber human cells by 10 times. Thus, the human microbiota and related microbiome constitute a vast source for identifying disease biomarkers and therapeutic drug targets. Herein, we review the evidence backing the exploitation of the human microbiome for identifying diagnostic biomarkers for human disease. We describe the importance of the human microbiome in health and disease and detail the use of the human microbiome and microbiota metabolites as potential diagnostic biomarkers for multiple diseases, including cancer, as well as inflammatory, neurological, and metabolic diseases. Thus, the human microbiota has enormous potential to pave the road for a new era in biomarker research for diagnostic and therapeutic purposes. The scientific community needs to collaborate to overcome current challenges in microbiome research concerning the lack of standardization of research methods and the lack of understanding of causal relationships between microbiota and human disease.

Making Biomarkers Relevant to Healthcare Innovation and Precision Medicine

Translational medicine, the exchange between laboratory (bench) and the clinic (bedside), is decidedly taking on a vital role. Many companies are now focusing on a translational medicinal approach as a therapeutic strategy in decision making upon realizing the expenses of drug attrition in late-stage advancement. In addition, the utility of biomarkers in clinical decision and therapy guidance seeks to improve the patient outcomes and decrease wasteful and harmful treatment. Efficient biomarkers are crucial for the advancement of diagnoses, better molecular targeted therapy, along with therapeutic advantages in a broad spectrum of various diseases. Despite recent advances in the discovery of biomarkers, the advancement route to a clinically validated biomarker remains intensely challenging, and many of the candidate biomarkers do not progress to clinical applications, thereby widening the innovation gap between research and application. The present article will focus on the clinical view of biomarkers in a reverse design, addressing how a biomarker program should appear if it is expected to create an impact on personalized medicine and patient care.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

HIV-Associated Cancer Biomarkers: A Requirement for Early Diagnosis

Globally, HIV/AIDS and cancer are increasingly public health problems and continue to exist as comorbidities. The sub-Saharan African region has the largest number of HIV infections. Malignancies previously associated with HIV/AIDS, also known as the AIDS-defining cancers (ADCs) have been documented to decrease, while the non-AIDS defining cancer (NADCs) are on the rise. On the other hand, cancer is a highly heterogeneous disease and precision oncology as the most effective cancer therapy is gaining attraction. Among HIV-infected individuals, the increased risk for developing cancer is due to the immune system of the patient being suppressed, frequent coinfection with oncogenic viruses and an increase in risky behavior such as poor lifestyle. The core of personalised medicine for cancer depends on the discovery and the development of biomarkers. Biomarkers are specific and highly sensitive markers that reveal information that aid in leading to the diagnosis, prognosis and therapy of the disease. This review focuses mainly on the risk assessment, diagnostic, prognostic and therapeutic role of various cancer biomarkers in HIV-positive patients. A careful selection of sensitive and specific HIV-associated cancer biomarkers is required to identify patients at most risk of tumour development, thus improving the diagnosis and prognosis of the disease.

Biomarkers in Migraine

Background

Disability from migraine has a profound impact on the world's economy. Research has been ongoing to identify biomarkers to aid in diagnosis and treatment.

Objective

The aim of this study was to highlight the purported diagnostic and therapeutic migraine biomarkers and their role in precision medicine.

Methods

A comprehensive literature search was conducted using PubMed, Google Scholar, and clinicaltrials.gov using keywords: "migraine" OR "headache" combined with "biomarkers" OR "marker." Other keywords included "serum," "cerebral spinal fluid," "inflammatory," and "neuroimaging."

Results

After a review of 88 papers, we find the literature supports numerous biomarkers in the diagnosis of migraine. Therapeutic biomarkers, while not as extensively published, highlight calcitonin gene-related peptide (CGRP) and pituitary adenylate cyclase-activating peptide-38 (PACAP-38) as biomarkers with the most substantiated clinical relevance. Genetic markers mainly focusing on gene mutations with resultant biochemical alterations continue to be studied and show promise.

Conclusion

Although there are several proposed biomarkers for migraine, continued research is needed to substantiate their role in clinical practice.

Patient-reported outcome measures in ophthalmology: too difficult to read?

Objective

Patient-reported outcome measures (PROMs) are commonly used in clinical trials and research. Yet, in order to be effective, a PROM needs to be understandable to respondents. The aim of this cross-sectional analysis was to assess reading level of PROMs validated for use in common eye conditions.

Methods and analysis

Readability measures determine the level of education a person is expected to have attained to be able to read a passage of text; this was calculated using the Flesch-Kincaid Grade Level, FORCAST and Gunning-Fog tests within readability calculations software package Oleander Readability Studio 2012.1. Forty PROMs, previously validated for use in at least one of age-related macular degeneration, glaucoma and/or diabetic retinopathy, were identified for inclusion via a systematic literature search. The American Medical Association (AMA) and National Institutes of Health (NIH) recommend patient materials should not exceed a sixth-grade reading level. Number of PROMs exceeding this level was calculated.

Results

Median (IQR) readability scores were 7.9 (5.4-10.5), 9.9 (8.9-10.7) and 8.4 (6.9-11.1) for Flesch-Kincaid Grade Level, FORCAST and Gunning-Fog test, respectively. Depending on metric used, this meant 61% (95% CI 45% to 76%), 100% (95% CI 91% to 100%) and 80% (95% CI 65% to 91%) exceeded the recommended threshold.

Conclusion

Most PROMs commonly used in ophthalmology require a higher reading level than that recommended by the AMA and NIH and likely contain questions that are too difficult for many patients to read. Greater care is needed in designing PROMs appropriate for the literacy level of a population.

Disease control and objective responsive rates in randomized phase II trials evaluating non-first-line chemotherapy for non-small cell lung cancer: a systematic review of 74 trials

Although objective response rate and disease control rate are commonly used as primary endpoints of lung cancer trials, it remains unclear whether objective response rate and disease control rate correctly reflect the overall survival in a non-small cell lung cancer phase II trial evaluating a non-first-line chemotherapy. Objective response rate might be easily affected by chance because the small number of patients in each trial achieved complete or partial response in the phase II non-first-line setting. This study was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (UMIN000040412). Four databases were searched for eligible trials. A Spearman's rank correlation with hazard ratio of overall survival was calculated each for odds ratio of objective response rate, difference of objective response rate (%), odds ratio of disease control rate, and difference of disease control rate (%). Of 74 eligible trials, 73 reported objective response rate and 68 reported disease control rates. Nine (12%) trials included patients with driver mutation status. Thirteen (18%) and two (3%) RCTs specifically included adenocarcinoma/non-squamous and squamous subtype of non-small cell lung cancer, respectively. The Eastern Cooperative Oncology Group performance status 0-2 (N=41, 55%) and the performance status 0-1 (N=25, 34%) were frequently used performance status criteria. The median number of patients in the two arms was 116 (interquartile range, 82-159). The correlation between trial-level odds ratio of objective response rate and hazard ratio of overall survival was weak (r=-0.29, 95% CI: -0.49 to -0.05, P=0.014). An exploratory subgroup analysis suggested that fewer responders were associated with poorer correlation. Odds ratio of disease control survival (r=-0.53, 95% CI: -0.68 to -0.32, P<0.001) had moderate rank correlations with hazard ratio of overall survival. Instead of objective response rate, disease control rate should be used as the primary endpoint in a randomized phase II trial evaluating non-first-line chemotherapy for non-small cell lung cancer.

A Survey of Survival Outcomes for Targeted Cancer Drugs Approved by the US Food and Drug Administration

BACKGROUND

The last two decades have witnessed the vigorous development of targeted cancer drugs and the potent therapeutic effects of these drugs have been validated by various true and surrogate end points. Overall survival (OS) and progression-free survival (PFS) outcomes were two important end points used in targeted cancer drugs clinical trials but investigation on which was rare as a consequence of inherent heterogeneity and complexity. Here, we present the review and analysis of OS and PFS outcomes of all targeted cancer drugs approved by the U.S. Food and Drug Administration (FDA) through December 31, 2019, in the setting of clinical studies.

METHODS

The targeted cancer drug directory was accessed via NCI website. The survival outcomes of those drugs in the setting of clinical trials were collected from publicly available Package Inserts and ClinicalTrials.gov. Median overall (OS) and progression-free survival (PFS) outcomes were summarized for targeted cancer drugs that were evaluated as monotherapies in clinical trials, contributions of targeted drugs to combination therapies in terms of survival benefit were analyzed, survival outcomes of FDA-approved first-line targeted therapies in different cancers were investigated, and the correlation between the absolute OS gain (ΔOS) and PFS gain (ΔPFS) as well as the hazard ratios for PFS (HR_PFS) and OS (HR_OS) between comparative arms of available randomized clinical trials was evaluated.

RESULTS

A total of 223 indications for 126 targeted cancer drugs have been approved by the FDA through December 31, 2019, among which 28 indications of 23 drugs have been approved for first-line therapies. Eighty indications for leukemia, lymphoma, and rare cancer types without survival data were excluded in the investigation of survival outcomes. For the remaining 143 indications, 99 were approved as monotherapies and 72 were approved as combination therapies. Among monotherapy subset, 18 of 72 (25%) indications with available OS outcomes have maximum median OS less than 12 months, 55 of 72 (76%) drug indications have maximum median OS less than 24 months, and 67 of 72 (93%) have maximum median OS less than 36 months. Regarding PFS, 38 of 88 (43%) drug indications have maximum median PFS less than 6 months, 69 of 88 (78%) drug indications have maximum median PFS less than 12 months, and 84 of 88 (95%) drug indications have maximum median PFS less than 24 months. The addition of targeted drugs to combination regimens under FDA's approval provided notable survival benefit, but the median value of OS gain rate of the available combination regimens was lower than that of PFS. The univariate Spearman Rank correlation coefficient suggested a significant positive correlation between ΔOS and ΔPFS (R = 0.62) but a weak correlation between HR_OS and HR_PFS (R = 0.11) in 46 randomized clinical trials that investigated contributions of targeted cancer drugs to combination therapies with available data. A moderate correlation between ΔOS and ΔPFS (R = 0.43) and a rather weak correlation between HR_OS and HR_PFS (R = 0.07) were also found in other randomized clinical trials that included in our study with available data.

CONCLUSIONS

The survival benefit provided by targeted cancer drugs varied a lot among cancer types. Though targeted cancer drugs showed improvements in both OS and PFS in approved combination regimens, the median value of OS gain rate was lower than that of PFS. As only weak correlation was found between HR_PFS and HR_OS, the evidence supporting the use of PFS as a surrogate to OS in the setting of targeted cancer drugs might also be limited.

Use of artificial intelligence to enhance phenotypic drug discovery

Research and development (R&D) productivity across the pharmaceutical industry has received close scrutiny over the past two decades, especially taking into consideration reports of attrition rates and the colossal cost for drug development. The respective merits of the two main drug discovery approaches, phenotypic and target based, have divided opinion across the research community, because each hold different advantages for identifying novel molecular entities with a successful path to the market. Nevertheless, both have low translatability in the clinic. Artificial intelligence (AI) and adoption of machine learning (ML) tools offer the promise of revolutionising drug development, and overcoming obstacles in the drug discovery pipeline. Here, we assess the potential of target-driven and phenotypic-based approaches and offer a holistic description of the current state of the field, from both a scientific and industry perspective. With the emerging partnerships between AI/ML and pharma still in their relative infancy, we investigate the potential and current limitations with a particular focus on phenotypic drug discovery. Finally, we emphasise the value of public-private partnerships (PPPs) and cross-disciplinary collaborations to foster innovation and facilitate efficient drug discovery programmes.

Salivary IgA as a Potential Biomarker in the Evaluation of Respiratory Tract Infection Risk in Athletes

In recent years, there has been attention focused on the value of salivary IgA (sIgA) as a potential biomarker for the identification of athletes who may be at increased risk of developing respiratory tract infection (RTI). The utility of sIgA, in this context, is based on biological plausibility and several observational studies revealing an apparent association between sIgA and RTI susceptibility. The overall published evidence evaluating the value of sIgA in this context is however conflicting, and there is currently a lack of clear guidance as to whether this marker has a place in the health surveillance and care of athletes. In this review, we critically appraise the literature assessing the potential for sIgA to be used in this context, evaluating it against 4 key biomarker characteristics, including its (1) practicality, (2) reproducibility, (3) specificity/sensitivity, and (4) potential clinical impact and relevance. This process reveals that although there is an apparent association between respiratory illness and sIgA in many studies, with some promising results, overall there remains a paucity of evidence supporting its overall value in this context. Key deficiencies in the metrics employed to endorse a valid biomarker are apparent, including a lack of reproducibility and low specificity and sensitivity in the detection of RTI susceptibility. The review outlines these issues and makes future recommendations.

Evaluation of serum MMP-2 and MMP-3, synovial fluid IL-8, MCP-1, and KC concentrations as biomarkers of stifle osteoarthritis associated with naturally occurring cranial cruciate ligament rupture in dogs

The purpose of this study was to evaluate matrix metalloproteinases (MMP) -2 and MMP-3 in serum, and keratinocyte-derived chemoattractant (KC), interleukin 8 (IL-8) and monocyte chemoattractant 1 (MCP-1) in synovial fluid (SF) as stifle osteoarthritis (OA) biomarkers in dogs. Dogs with naturally occurring cranial cruciate ligament (CrCL) rupture (OA group) and healthy controls were recruited. Stifles with CrCL deficiency were surgically stabilized. Serum, SF, and synovial biopsy samples were collected from the OA group preoperatively, whereas samples were collected once from control dogs. A blinded veterinary pathologist graded synovial biopsies. Serum and SF analyses were performed using xMAP technology. General linear regression was used for statistical comparisons of serum biomarkers, and mixed linear regression for SF biomarkers and temporal concentration changes. The overall discriminative ability was quantified using area under curve (AUC). Spearman's correlation coefficient was used to assess correlations between synovial histology grades and the biomarkers. Samples from 62 dogs in the OA group and 50 controls were included. The MMP-2 and MMP-3 concentrations between the OA and control groups were not significantly different, and both with an AUC indicating a poor discriminative ability. All three SF biomarker concentrations were significantly different between the OA group and controls (P <0.05). The MCP-1 was the only biomarker showing an acceptable discriminative performance with an AUC of 0.91 (95% confidence interval: 0.83-0.98). The sum of the inflammatory infiltrate score was significantly correlated with all three SF biomarkers (P <0.01). Summed synovial stroma, and all scores combined were significantly correlated with IL-8 and MCP-1 concentrations (P <0.003), and the summed synoviocyte scores were significantly correlated with MCP-1 concentrations (P <0.001). Correlations between MCP-1 concentrations and synovial histopathologic grading and its discriminative ability suggest its potential as a synovitis biomarker in canine stifle OA associated with CrCL rupture.

Recent Advances in Blood-Based Biomarkers of Remote Combat-Related Traumatic Brain Injury

PURPOSE OF REVIEW

Traumatic brain injury (TBI) is highly prevalent among service members and Veterans (SMVs) and associated with changes in blood-based biomarkers. This manuscript reviews candidate biomarkers months/years following military-associated TBI.

RECENT FINDINGS

Several blood-based biomarkers have been investigated for diagnostic or prognostic use to inform care years after military-associated TBI. The most promising include increased levels of plasma/serum and exosomal proteins reflecting neuronal, axonal and/or vascular injury, and inflammation, as well as altered microRNA expression and auto-antibodies of central nervous system markers. Diagnostic and prognostic biomarkers of remote TBI outcomes remain in the discovery phase. Current evidence does not yet support single or combination biomarkers for clinical diagnostic use remotely after injury, but there are promising candidates that require validation in larger, longitudinal studies. The use of prognostic biomarkers of future neurodegeneration, however, holds much promise and could improve treatments and/or preventive measures for serious TBI outcomes.

Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities

The machine learning community has become alert to the ways that predictive algorithms can inadvertently introduce unfairness in decision-making. Herein, we discuss how concepts of algorithmic fairness might apply in healthcare, where predictive algorithms are being increasingly used to support decision-making. Central to our discussion is the distinction between algorithmic fairness and algorithmic bias. Fairness concerns apply specifically when algorithms are used to support polar decisions (i.e., where one pole of prediction leads to decisions that are generally more desired than the other), such as when predictions are used to allocate scarce health care resources to a group of patients that could all benefit. We review different fairness criteria and demonstrate their mutual incompatibility. Even when models are used to balance benefits-harms to make optimal decisions for individuals (i.e., for non-polar decisions)-and fairness concerns are not germane-model, data or sampling issues can lead to biased predictions that support decisions that are differentially harmful/beneficial across groups. We review these potential sources of bias, and also discuss ways to diagnose and remedy algorithmic bias. We note that remedies for algorithmic fairness may be more problematic, since we lack agreed upon definitions of fairness. Finally, we propose a provisional framework for the evaluation of clinical prediction models offered for further elaboration and refinement. Given the proliferation of prediction models used to guide clinical decisions, developing consensus for how these concerns can be addressed should be prioritized.

Clinical study protocol for a low-interventional study in intermediate age-related macular degeneration developing novel clinical endpoints for interventional clinical trials with a regulatory and patient access intention-MACUSTAR

Background

There is an unmet need for treatment options in intermediate age-related macular degeneration (iAMD). However, for any new interventions to be tested in clinical trials, novel currently unavailable clinical endpoints need to be developed. Thus, the MACUSTAR study aims to develop and evaluate functional, structural, and patient-reported candidate endpoints for use in future iAMD trials.

Methods

The protocol describes a low-interventional clinical multicenter study employing a novel two-part design. The cross-sectional part (total duration, 1 month) and the longitudinal part (total duration, 36 months) include participants with iAMD and control groups with early/late/no AMD. The cross-sectional part’s primary objective is a technical evaluation of functional, structural, and patient-reported candidate outcomes. The longitudinal part’s primary objective is to assess the prognostic power of changes in functional, structural, and patient-reported outcomes for progression from iAMD to late AMD. All data will be used to support a biomarker qualification procedure by regulatory authorities.

Discussion

The MACUSTAR study characterizes and evaluates much needed novel functional, structural, and patient-reported endpoints for future clinical trials in iAMD and will improve our understanding of the natural history and prognostic markers of this condition.

Trial registration

ClinicalTrials.gov NCT03349801. Registered on 22 November 2017

Ferritin and C-reactive protein are predictive biomarkers of mortality and macrophage activation syndrome in adult onset Still's disease. Analysis of the multicentre Gruppo Italiano di Ricerca in Reumatologia Clinica e Sperimentale (GIRRCS) cohort

Objective

To assess the predictive role of ferritin and C-reactive protein (CRP) on occurrence of macrophage activation syndrome (MAS) and mortality in patients with adult onset Still’s disease (AOSD), a rare and severe disease, included in the multicentre Gruppo Italiano di Ricerca in Reumatologia Clinica e Sperimentale (GIRRCS) cohort.

Methods

The predictive role, at the time of diagnosis, of serum levels of ferritin and CRP on occurrence of MAS and mortality, was evaluated by logistic regression analyses and receiver-operating characteristic (ROC) curves were built to identify patients at high risk of MAS and mortality, respectively.

Results

In assessed 147 patients with AOSD, levels of ferritin were predictive of MAS (OR: 1.971; P: 0.002; CI 95%: 1.280–3.035). The ROC curve showed that the best cut-off for ferritin was 1225 ng/ml in predicting MAS (sensitivity 88%; specificity 57%). Levels of CRP were predictive of mortality in these patients (OR: 2.155; P: 0.007; CI 95%: 1.228–3.783). The ROC curve showed that the best cut-off for CRP was 68.7 mg/L in predicting mortality (sensitivity 80%; specificity of 65%).

Conclusions

We reported the predictive role of ferritin and CRP on MAS and mortality, respectively, in a large cohort of patients with AOSD, identifying subsets at higher risk of poor prognosis. Considering that the analysis of CRP and ferritin is widely available, these results could be readily transferable into clinical practice, thus improving the management of patients with AOSD.

Generating comparative evidence on new drugs and devices before approval

Fewer than half of new drugs have data on their comparative benefits and harms against existing treatment options at the time of regulatory approval in Europe and the USA. Even when active-comparator trials exist, they might not produce meaningful data to inform decisions in clinical practice and health policy. The uncertainty associated with the paucity of well designed active-comparator trials has been compounded by legal and regulatory changes in Europe and the USA that have created a complex mix of expedited programmes aimed at facilitating faster access to new drugs. Comparative evidence generation is even sparser for medical devices. Some have argued that the current process for regulatory approval needs to generate more evidence that is useful for patients, clinicians, and payers in health-care systems. We propose a set of five key principles relevant to the European Medicines Agency, European medical device regulatory agencies, US Food and Drug Administration, as well as payers, that we believe will provide the necessary incentives for pharmaceutical and device companies to generate comparative data on drugs and devices and assure timely availability of evidence that is useful for decision making. First, labelling should routinely inform patients and clinicians whether comparative data exist on new products. Second, regulators should be more selective in their use of programmes that facilitate drug and device approvals on the basis of incomplete benefit and harm data. Third, regulators should encourage the conduct of randomised trials with active comparators. Fourth, regulators should use prospectively designed network meta-analyses based on existing and future randomised trials. Last, payers should use their policy levers and negotiating power to incentivise the generation of comparative evidence on new and existing drugs and devices, for example, by explicitly considering proven added benefit in pricing and payment decisions.

Impact of Antibiotic Gut Exposure on the Temporal Changes in Microbiome Diversity

Although the global deleterious impact of antibiotics on the intestinal microbiota is well known, temporal changes in microbial diversity during and after an antibiotic treatment are still poorly characterized. We used plasma and fecal samples collected frequently during treatment and up to one month after from 22 healthy volunteers assigned to a 5-day treatment by moxifloxacin (n = 14) or no intervention (n = 8). Moxifloxacin concentrations were measured in both plasma and feces, and bacterial diversity was determined in feces by 16S rRNA gene profiling and quantified using the Shannon index and number of operational taxonomic units (OTUs). Nonlinear mixed effect models were used to relate drug pharmacokinetics and bacterial diversity over time. Moxifloxacin reduced bacterial diversity in a concentration-dependent manner, with a median maximal loss of 27.5% of the Shannon index (minimum [min], 17.5; maximum [max], 27.7) and 47.4% of the number of OTUs (min, 30.4; max, 48.3). As a consequence of both the long fecal half-life of moxifloxacin and the susceptibility of the gut microbiota to moxifloxacin, bacterial diversity indices did not return to their pretreatment levels until days 16 and 21, respectively. Finally, the model characterized the effect of moxifloxacin on bacterial diversity biomarkers and provides a novel framework for analyzing antibiotic effects on the intestinal microbiome.

Evidence to Support Inclusion of Pharmacogenetic Biomarkers in Randomised Controlled Trials

Pharmacogenetics and biomarkers are becoming normalised as important technologies to improve drug efficacy rates, reduce the incidence of adverse drug reactions, and make informed choices for targeted therapies. However, their wider clinical implementation has been limited by a lack of robust evidence. Suitable evidence is required before a biomarker's clinical use, and also before its use in a clinical trial. We have undertaken a review of five pharmacogenetic biomarker-guided randomised controlled trials (RCTs) and evaluated the evidence used by these trials to justify biomarker inclusion. We assessed and quantified the evidence cited in published rationale papers, or where these were not available, obtained protocols from trial authors. Very different levels of evidence were provided by the trials. We used these observations to write recommendations for future justifications of biomarker use in RCTs and encourage regulatory authorities to write clear guidelines.

Existing and novel biomarkers for precision medicine in systemic sclerosis

The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.

Gynecological Cancers Translational, Research Implementation, and Harmonization: Gynecologic Cancer InterGroup Consensus and Still Open Questions

In the era of personalized medicine, the introduction of translational studies in clinical trials has substantially increased their costs, but provides the possibility of improving the productivity of trials with a better selection of recruited patients. With the overall goal of creating a roadmap to improve translational design for future gynecological cancer trials and of defining translational goals, a main discussion was held during a brainstorming day of the Gynecologic Cancer InterGroup (GCIG) Translational Research Committee and overall conclusions are here reported. A particular emphasis was dedicated to the new frontier of the immunoprofiling of gynecological cancers. The discussion pointed out that to maximize patients' benefit, translational studies should be integral to clinical trial design with standardization and optimization of procedures including a harmonization program of Standard Operating Procedures. Pathology-reviewed sample collection should be mandatory and ensured by dedicated funding. Biomarker validation and development should be made public and transparent to ensure rapid progresses with positive outcomes for patients. Guidelines/templates for patients' informed consent are needed. Importantly for the public, recognized goals are to increase the involvement of advocates and to improve the reporting of translational data in a forum accessible to patients.

Guidelines for biomarkers in autoimmune rheumatic diseases - evidence based analysis

Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care. The overarching aim of this work was to clarify the meaning of specific biomarkers during autoimmune diseases; their possible role in confirming diagnosis, predicting outcome and suggesting specific treatments.

Gentamicin induced acute renal damage and its evaluation using urinary biomarkers in rats

•

Gentamicin induced dose dependent and temporal change in urinary biomarkers.

•

Histological changes were minimal to severe on Day 4 & 8 respectively at both doses.

•

Several fold increase in urinary biomarkers on Day 4 and 8 at both doses.

•

On Day 8, increase in urinary and serum markers and histological changes.

•

Clusterin is highly sensitive urinary biomarkers.

Consistent, sensitive biomarkers of acute kidney injury in animal models and humans have historically represented a poorly met need for investigators and clinicians. Detection of early kidney damage using urinary biomarkers is essential to assess the adversity in preclinical toxicology studies, which will help in reducing attrition of lead candidates in drug development. This study was undertaken to evaluate recently identified urinary biomarkers use in identifying acute kidney injury compared to traditional serum markers in experimentally induced nephrotoxicity in male Sprague Dawley (SD) rats. Gentamicin induced nephrotoxicity in Sprague Dawley rats is commonly detected using serum markers and histological evaluation of kidneys. Gentamicin, an aminoglycoside was administered at 30 and 100 mg/kg/day dose (subcutaneous) for seven consecutive days to induce nephrotoxicity. On day 4 and day 8 post treatment, serum and urine samples from these rats were analyzed for traditional serum/urine and novel urinary biomarkers and microscopic evaluation of kidneys.

On Day 4, no statistically significant change in serum BUN and creatinine level, but increase in urinary microalbumin (mALB) and urinary protein (UP) noticed in both doses of Gentamicin treated rats. On Day 8 significant increase in serum blood urea nitrogen (BUN), serum creatinine, UP and urinary mALB at 100 mg/kg/day, increase in total protein and decrease in albumin in 30 and 100 mg/kg/day and decrease in BUN and creatinine at 100 mg/kg of Gentamicin treated rats. The BUN and creatinine levels or fold change was comparable between control and 30 mg/kg of Gentamicin on Day 8, however, there was 5.6 and 3.4 fold change in BUN and Creatinine level noticed at 100 mg/kg/day of Gentamicin. On Day 4 and 8, significant increase in urinary levels of Clusterin was noted with animals administered both doses of Gentamicin. Similarly, significant increase in urinary levels of kidney injury molecule 1 (Kim-1), Cystatin C and neutrophil gelatinase-associated lipocalin (NGAL) were noticed with animals administered Gentamicin at 100 mg/kg/day on both Day 4 and 8. All these markers have shown dose-dependent change.

Histological changes seen on Day 4 and Day 8 were of minimal to mild and moderate to severe in nature at both doses, respectively. The results demonstrated the sensitiveness and accuracy of detecting acute renal damage with novel urinary biomarkers, and their use in diagnosing early kidney damage. This helps in adversity assessment in animal toxicology studies and advocating right treatment to patients who have early renal injury which otherwise can only be diagnosed by elevated levels of traditional biomarkers in blood only after >30% of kidneys is damaged.

miR-106a contributes to prostate carcinoma progression through PTEN

Prostate carcinoma is a global health problem and is estimated to be diagnosed in 1.1 million men/year, making this malignancy the second most frequently diagnosed cancer in males worldwide. micro RNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. miRNAs contribute to cancer development and progression, and are expressed differently in normal tissues and cancers. In the present study, the biological function of miR-106a in the human prostate carcinoma and the associated regulatory mechanisms were investigated. miR-106a was significantly upregulated in human prostate cancer tissues when compared with normal tissues (P<0.05), and the overexpression of miR-106a was identified to promote PC-3 cell growth. Additionally, miRNA-106a inhibition significantly suppressed PC-3 cell growth. Furthermore, it was observed that the phosphatase and tensin homolog (PTEN) expression level was negatively associated with miR-106a expression level, and miRNA-106a directly targeted PTEN in the PC-3 cells. PTEN overexpression has a similar effect on PC-3 cell growth as loss of miR-106a. Taken together, the results of the present study indicate that upregulated miR-106a regulates PC-3 cell proliferation through PTEN. These results suggest that appropriate manipulation of miR-106a may provide a novel strategy in the future treatment of human prostate cancer.

Herpes Simplex Virus Shedding Rate: Surrogate Outcome for Genital Herpes Recurrence Frequency and Lesion Rates, and Phase 2 Clinical Trials End Point for Evaluating Efficacy of Antivirals

Background

We tested whether genital herpes simplex virus (HSV) shedding is an appropriate surrogate outcome for the clinical outcome of genital herpes lesions in studies of HSV-2 antiviral interventions.

Methods

We analyzed prospective data from natural history studies and clinical trials of antiviral agents for HSV-2 in which HSV-2-seropositive participants provided self-collected anogenital swab specimens daily over ≥25 days for HSV DNA quantitation by polymerase chain reaction (PCR). Genital recurrences were self-reported.

Results

Among 674 participants, genital HSV shedding was detected on 17% of days, and genital lesions were reported on 10% of days. Within the same session, HSV shedding rates were strongly correlated with lesion rates (ρ = 0.61, P < .0001). The relative reduction in the recurrence rate was 72% (P = .041) for recipients of the antiviral agent pritelivir as compared to recipients of placebo, but it decreased to 21% (P = .75) after adjustment for HSV shedding rate. When evaluating valacyclovir and acyclovir, adjustment for the HSV shedding rate also led to a reduced association of these antivirals with the recurrence rate. Overall, 40%-82% of the antiviral effect on recurrences was explained by its effect on HSV shedding.

Conclusion

HSV genital shedding measured by PCR analysis in swab specimens self-collected daily is an appropriate surrogate outcome for genital herpes lesions because it is in the causal pathway to recurrences.

What evidence do we need for biomarker qualification?

Biomarkers can facilitate all aspects of the drug development process. However, biomarker qualification-the use of a biomarker that is accepted by the U.S. Food and Drug Administration-needs a clear, predictable process. We describe a multistakeholder effort including government, industry, and academia that proposes a framework for defining the amount of evidence needed for biomarker qualification. This framework is intended for broad applications across multiple biomarker categories and uses.

A Sol-gel Integrated Dual-readout Microarray Platform for Quantification and Identification of Prostate-specific Antigen

Here, we report a sol-gel integrated affinity microarray for on-chip matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) that enables capture and identification of prostate?specific antigen (PSA) in samples. An anti-PSA antibody (H117) was mixed with a sol?gel, and the mixture was spotted onto a porous silicon (pSi) surface without additional surface modifications. The antibody easily penetrates the sol-gel macropore fluidic network structure, making possible high affinities. To assess the capture affinity of the platform, we performed a direct assay using fluorescein isothiocyanate-labeled PSA. Pure PSA was subjected to on-chip MALDI-TOF-MS analysis, yielding three clear mass peptide peaks (m/z = 1272, 1407, and 1872). The sol-gel microarray platform enables dual readout of PSA both fluorometric and MALDI-TOF MS analysis in biological samples. Here we report a useful method for a means for discovery of biomarkers in complex body fluids.

A proteomic approach of biomarker candidate discovery for alcoholic liver cirrhosis

Alcoholic liver disease (ALD) progresses from steatosis to alcoholic hepatitis to fibrosis and cirrhosis. Liver biopsy is considered as the gold standard method for diagnosis of liver cirrhosis and provides useful information about damaging process which is an invasive procedure with complications. Existing biomarkers in clinical practice have narrow applicability due to lack of specificity and lack of sensitivity. The objective of this article is to identify proteomic biomarker candidates for alcoholic liver cirrhosis by differential expression analysis between alcoholic liver cirrhotic and healthy subjects. Blood samples were collected from 20 subjects (10 alcoholic liver cirrhosis and 10 healthy) from R. L. Jalapa Hospital and Research Centre, Kolar, Karnataka, India. Differential protein analysis was carried out by two-dimensional electrophoresis after albumin depletion, followed by liquid chromatography–mass spectrometry. The image analysis found 46 spots in cirrhotic gel and 69 spots in healthy gel, of which 14 spots were identified with significant altered expression levels. Based on the protein score and clinical significance, among 14 spots, a total of 28 protein biomarker candidates were identified: 13 with increased expression and 15 with decreased expression were categorized in alcoholic liver cirrhosis compared to healthy subjects. Protein biomarker candidates identified by “-omics” approach based on differential expression between alcoholic liver cirrhotic subjects and healthy subjects may give better insights for diagnosis of ALD. Prioritization of candidates identified is a prerequisite for validation regimen. Biomarker candidates require verification that demonstrates the differential expression will remain detectable by assay to be used for validation.

Biomarkers of GH action in children and adults

Growth hormone (GH) and IGF-I levels in serum are used as biomarkers in the diagnosis and management of GH-related disorders but have not been subject to structured validation. Auxological parameters in children and changes in body composition in adults, as well as metabolic parameters and patient related outcomes are used as clinical and surrogate endpoints. New treatment options, such as long acting GH and GH antagonists, require reevaluation of the currently used biochemical biomarkers. This article will review biomarkers, surrogate endpoints and clinical endpoints related to GH treatment in children and adults as well as in acromegaly.

Evolution of proteomic biomarker for chronic liver disease: Promise into reality

Liver is the vital organ for synthesis of proteins whose concentration in blood reflects liver dysfunction. Variations in protein domain can generate clinically significant biomarkers. Biomarker pipeline includes discovery of candidates, qualification, verification, assay optimization, and validation. Advances in proteomic approach can discover protein biomarker candidates based on “up-or-down” regulation or fold change in expression which is correlated with disease state. Despite numerous biomarker candidates been discovered, only few are useful in clinical practice which indicates the need for well-established validation regimen. Hence, the main purpose of this review is to understand the protein biomarker development and pitfalls. Companion diagnostics provide insights into potential cost-effective diagnosis for chronic liver disease.