Making Meaningful Clinical Use of Biomarkers

Ethanolamine as a biomarker and biomarker-based therapy for diabetic retinopathy in glucose-well-controlled diabetic patients

Diabetic retinopathy (DR) is the leading cause of blindness among the working-age population. Although controlling blood glucose levels effectively reduces the incidence and development of DR to less than 50%, there are currently no diagnostic biomarkers or effective treatments for DR development in glucose-well-controlled diabetic patients (GW-DR). In this study, we established a prospective GW-DR cohort by strictly adhering to glycemic control guidelines and maintaining regular retinal examinations over a median 2-year follow-up period. The discovery cohort encompassed 71 individuals selected from a pool of 292 recruited diabetic patients at baseline, all of whom consistently maintained hemoglobin A1c (HbA1c) levels below 7% without experiencing hypoglycemia. Within this cohort of 71 individuals, 21 subsequently experienced new-onset GW-DR, resulting in an incidence rate of 29.6%. In the validation cohort, we also observed a significant GW-DR incidence rate of 17.9%. Employing targeted metabolomics, we investigated the metabolic characteristics of serum in GW-DR, revealing a significant association between lower levels of ethanolamine and GW-DR risk. This association was corroborated in the validation cohort, exhibiting superior diagnostic performance in distinguishing GW-DR from diabetes compared to the conventional risk factor HbA1c, with AUCs of 0.954 versus 0.506 and 0.906 versus 0.521 in the discovery and validation cohorts, respectively. Furthermore, in a streptozotocin (STZ)-induced diabetic rat model, ethanolamine attenuated diabetic retinal inflammation, accompanied by suppression of microglial diacylglycerol (DAG)-dependent protein kinase C (PKC) pathway activation. In conclusion, we propose that ethanolamine is a potential biomarker and represents a viable biomarker-based therapeutic option for GW-DR.

Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Diabetes Mellitus Should Be Considered While Analysing Sarcopenia-Related Biomarkers

Sarcopenia is a chronic, progressive skeletal muscle disease characterised by low muscle strength and quantity or quality, leading to low physical performance. Patients with type 2 diabetes mellitus (T2DM) are more at risk of sarcopenia than euglycemic individuals. Because of several shared pathways between the two diseases, sarcopenia is also a risk factor for developing T2DM in older patients. Various biomarkers are under investigation as potentially valuable for sarcopenia diagnosis and treatment monitoring. Biomarkers related to sarcopenia can be divided into markers evaluating musculoskeletal status (biomarkers specific to muscle mass, markers of the neuromuscular junction, or myokines) and markers assuming causal factors (adipokines, hormones, and inflammatory markers). This paper reviews the current knowledge about how diabetes and T2DM complications affect potential sarcopenia biomarker concentrations. This review includes markers recently proposed by the expert group of the European Society for the Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) as those that may currently be useful in phase II and III clinical trials of sarcopenia: myostatin (MSTN); follistatin (FST); irisin; brain-derived neurotrophic factor (BDNF); procollagen type III N-terminal peptide (PIIINP; P3NP); sarcopenia index (serum creatinine to serum cystatin C ratio); adiponectin; leptin; insulin-like growth factor-1 (IGF-1); dehydroepiandrosterone sulphate (DHEAS); C-reactive protein (CRP); interleukin-6 (IL-6), and tumor necrosis factor α (TNF-α). A better understanding of factors influencing these biomarkers' levels, including diabetes and diabetic complications, may lead to designing future studies and implementing results in clinical practice.

Prognostic Biomarkers in Kidney Transplantation: A Systematic Review and Critical Appraisal

SIGNIFICANCE STATEMENT

Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice.

BACKGROUND

Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon.

METHODS

We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators.

RESULTS

A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8-35.5) between 2005 and 2012 and 57.5 (IQR, 53.3-59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96-629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0-6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies.

CONCLUSIONS

Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Activated carbon derived from wood biochar for Amperometric sensing of Ammonia for early screening of chronic kidney disease

Personalized medicine has emerged as an increasingly efficient and effective approach to addressing disease diagnosis and intervention. Ammonia is a waste product produced by the body during the digestion of protein. The requirement to develop an electrochemical sensing platform for monitoring skin ammonia levels holds great potential as an essential solution to pre-screen chronic kidney disease (CKD). In this research, we have manufactured an innovative electrochemical sensor by employing activated carbon derived from wood biochar as the signal transducer. We conducted a comprehensive analysis of the structural and morphological characteristics of the synthesized materials using various techniques. The hypothesized interaction was investigated using chronoamperometry as a transduction technique. To assess cross-reactivity, we conducted a study using common interferants or chemicals present in the environment. The data presented in this paper represents three replicates and is plotted with a 5 % error bar, demonstrating a 95 % confidence interval in the sensor response. In this study, we have elucidated the functionality and usefulness of a wearable microelectronic research prototype integrated with an HTC-activated carbon @RTIL-based electrochemical sensing platform for detecting ammonia levels released from the skin as a marker for chronic kidney disease screening. By enabling early detection and monitoring, these platforms can facilitate timely interventions, such as lifestyle modifications, medication adjustments, or referral to nephrology specialists. This proactive approach can potentially slow down disease progression, minimize the need for dialysis or transplantation, and ultimately improve the quality of life for CKD patients.

The multi-level outcome study of psychoanalysis for chronically depressed patients with early trauma (MODE): rationale and design of an international multicenter randomized controlled trial

BACKGROUND

Whether and how psychotherapies change brain structure and function is unknown. Its study is of great importance for contemporary psychotherapy, as it may lead to discovery of neurobiological mechanisms that predict and mediate lasting changes in psychotherapy, particularly in severely mentally ill patients, such as those with chronic depression. Previous studies have shown that psychoanalytic psychotherapies produce robust and enduring improvements in not only symptom severity but also personality organization in patients who have chronic depression and early life trauma, especially if therapy is delivered at a high weekly frequency.

METHODS/DESIGN

Patients with chronic major depression and a history of early life trauma will be recruited, assessed, and treated across 3 international sites: Germany, Switzerland, and the United States. They will be randomized to one of two treatment arms: either (1) once weekly psychoanalytic psychotherapies, or (2) 3-4 times weekly psychoanalytic psychotherapies. They will have full clinical characterization as well as undergo MRI scanning at study baseline prior to randomization and again one year later. A group of matched healthy controls will undergo similar assessments and MRI scanning at the same time points to help discern whether study treatments induce brain changes toward or away from normal values. Primary study outcomes will include anatomical MRI, functional MRI, and Diffusion Tensor Imaging measures. Study hypotheses will be tested using the treatment-by-time interaction assessed in multiple general linear models with repeated measures analyses in an intent-to-treat analysis.

DISCUSSION

MODE may allow the identification of brain-based biomarkers that may be more sensitive than traditional behavioral and clinical measures in discriminating, predicting, and mediating treatment response. These findings could help to personalize care for patients who have chronic depression patients and early life trauma, and they will provide new therapeutic targets for both psychological and biological treatments for major depressive illness.

Topoisomerase 1 Activity Is Reduced in Response to Thermal Stress in Fruit Flies and in Human HeLa Cells

In the modern world with climate changes and increasing pollution, different types of stress are becoming an increasing challenge. Hence, the identification of reliable biomarkers of stress and accessible sensors to measure such biomarkers are attracting increasing attention. In the current study, we demonstrate that the activity, but not the expression, of the ubiquitous enzyme topoisomerase 1 (TOP1), as measured in crude cell extracts by the REEAD sensor system, is markedly reduced in response to thermal stress in both fruit flies (Drosophila melanogaster) and cultivated human cells. This effect was observed in response to both mild-to-moderate long-term heat stress and more severe short-term heat stress in D. melanogaster. In cultivated HeLa cells a reduced TOP1 activity was observed in response to both cold and heat stress. The reduced TOP1 activity appeared dependent on one or more cellular pathways since the activity of purified TOP1 was unaffected by the utilized stress temperatures. We demonstrate successful quantitative measurement of TOP1 activity using an easily accessible chemiluminescence readout for REEAD pointing towards a sensor system suitable for point-of-care assessment of stress responses based on TOP1 as a biomarker.

IL-8 correlates with nonresponse to neoadjuvant nivolumab in HPV positive HNSCC via a potential extracellular vesicle miR-146a mediated mechanism

Therapy using anti-PD-1 immune checkpoint inhibitors (ICI) has revolutionized the treatment of many cancers including head and neck squamous cell carcinomas (HNSCC), but only a fraction of patients respond. To better understand the molecular mechanisms driving resistance, we performed extensive analysis of plasma and tumor tissues before and after a 4-week neoadjuvant trial in which HNSCC patients were treated with the anti-PD-1 inhibitor, nivolumab. Luminex cytokine analysis of patient plasma demonstrated that HPVpos nonresponders displayed high levels of the proinflammatory chemokine, interleukin-8 (IL-8), which decreased after ICI treatment, but remained higher than responders. miRNAseq analysis of tetraspanin-enriched small extracellular vesicles (sEV) purified from plasma of HPVpos nonresponders demonstrated significantly lower levels of seven miRNAs that target IL-8 including miR-146a. Levels of the pro-survival oncoprotein Dsg2, which has been to down-regulate miR-146a, are elevated with HPVpos tumors displaying higher levels than HPVneg tumors. Dsg2 levels decrease significantly following ICI in responders but not in nonresponders. In cultured HPVpos cells, restoration of miR-146a by forced expression or treatment with miR-146a-loaded sEV, reduced IL-8 level, blocked cell cycle progression, and promoted cell death. These findings identify Dsg2, miR-146a, and IL-8 as potential biomarkers for ICI response and suggest that the Dsg2/miR-146a/IL-8 signaling axis negatively impacts ICI treatment outcomes and could be targeted to improve ICI responsiveness in HPVpos HNSCC patients.

Biomarkers in 5q-associated spinal muscular atrophy-a narrative review

5q-associated spinal muscular atrophy (SMA) is a rare genetic disease caused by mutations in the SMN1 gene, resulting in a loss of functional SMN protein and consecutive degeneration of motor neurons in the ventral horn. The disease is clinically characterized by proximal paralysis and secondary skeletal muscle atrophy. New disease-modifying drugs driving SMN gene expression have been developed in the past decade and have revolutionized SMA treatment. The rise of treatment options led to a concomitant need of biomarkers for therapeutic guidance and an improved disease monitoring. Intensive efforts have been undertaken to develop suitable markers, and numerous candidate biomarkers for diagnostic, prognostic, and predictive values have been identified. The most promising markers include appliance-based measures such as electrophysiological and imaging-based indices as well as molecular markers including SMN-related proteins and markers of neurodegeneration and skeletal muscle integrity. However, none of the proposed biomarkers have been validated for the clinical routine yet. In this narrative review, we discuss the most promising candidate biomarkers for SMA and expand the discussion by addressing the largely unfolded potential of muscle integrity markers, especially in the context of upcoming muscle-targeting therapies. While the discussed candidate biomarkers hold potential as either diagnostic (e.g., SMN-related biomarkers), prognostic (e.g., markers of neurodegeneration, imaging-based markers), predictive (e.g., electrophysiological markers) or response markers (e.g., muscle integrity markers), no single measure seems to be suitable to cover all biomarker categories. Hence, a combination of different biomarkers and clinical assessments appears to be the most expedient solution at the time.

Metabolic Disturbances in the Gut-brain Axis of a Mouse Model of MPTP-induced Parkinsonism Evaluated by Nuclear Magnetic Resonance

Parkinson's Disease is a synucleinopathy that primarily affects the dopaminergic cells of the central nervous system, leading to motor and gastrointestinal disturbances. However, intestinal peripheral neurons undergo a similar neurodegeneration process, marked by α-synuclein (αSyn) accumulation and loss of mitochondrial homeostasis. We investigated the metabolic alterations in different biometrics that compose the gut-brain axis (blood, brain, large intestine, and feces) in an MPTP-induced mouse model of sporadic Parkinson's Disease. Animals received escalating administration of MPTP. Tissues and fecal pellets were collected, and the metabolites were identified through the untargeted Nuclear Magnetic Resonance spectroscopic (1H NMR) technique. We found differences in many metabolites from all the tissues evaluated. The differential expression of metabolites in these samples mainly reflects inflammatory aspects, cytotoxicity, and mitochondrial impairment (oxidative stress and energy metabolism) in the animal model used. The direct evaluation of fecal metabolites revealed changes in several classes of metabolites. This data reinforces previous studies showing that Parkinson's disease is associated with metabolic perturbation not only in brain-related tissues, but also in periphery structures such as the gut. In addition, the evaluation of the microbiome and metabolites from gut and feces emerge as promising sources of information for understanding the evolution and progression of sporadic Parkinson's Disease.

Biological Implications of MicroRNAs as Regulators and Biomarkers of Therapeutic Toxicities in Breast Cancer

Contemporary breast cancer management includes surgical resection combined with a multimodal approach, including chemotherapy, radiotherapy, endocrine therapy, and targeted therapies. Breast cancer treatment is now personalised in accordance with disease and host factors, which has translated to enhanced outcomes for the vast majority of patients. Unfortunately, the treatment of the disease involves patients developing treatment-induced toxicities, with cardiovascular and metabolic side effects having negative implications for long-term quality-of-life metrics. MicroRNAs (miRNAs) are a class of small non-coding ribonucleic acids that are 17 to 25 nucleotides in length, which have utility in modifying genetic expression by working at a post-transcriptional cellular level. miRNAs have involvement in modulating breast cancer development, which is well described, with these biomarkers acting as important regulators of disease, as well as potential diagnostic and therapeutic biomarkers. This review focuses on highlighting the role of miRNAs as regulators and biomarkers of disease, particularly in breast cancer management, with a specific mention of the potential value of miRNAs in predicting treatment-related cardiovascular toxicity.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next

Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.

The Clinical Utility of lncRNAs and Their Application as Molecular Biomarkers in Breast Cancer

Given their tumor-specific and stage-specific gene expression, long non-coding RNAs (lncRNAs) have demonstrated to be potential molecular biomarkers for diagnosis, prognosis, and treatment response. Particularly, the lncRNAs DSCAM-AS1 and GATA3-AS1 serve as examples of this because of their high subtype-specific expression profile in luminal B-like breast cancer. This makes them candidates to use as molecular biomarkers in clinical practice. However, lncRNA studies in breast cancer are limited in sample size and are restricted to the determination of their biological function, which represents an obstacle for its inclusion as molecular biomarkers of clinical utility. Nevertheless, due to their expression specificity among diseases, such as cancer, and their stability in body fluids, lncRNAs are promising molecular biomarkers that could improve the reliability, sensitivity, and specificity of molecular techniques used in clinical diagnosis. The development of lncRNA-based diagnostics and lncRNA-based therapeutics will be useful in routine medical practice to improve patient clinical management and quality of life.

Metabolic defects shared by Alzheimer's disease and diabetes: A focus on mitochondria

Type 2 diabetes (T2D) and Alzheimer's disease (AD) are two global epidemics that share several metabolic defects, such as insulin resistance, impaired glucose metabolism, and mitochondrial defects. Importantly, strong evidence demonstrates that T2D significantly increases the risk of cognitive decline and dementia, particularly AD. Here, we provide an overview of the metabolic defects that characterize and link both pathologies putting the focus on mitochondria. The biomarker potential of mitochondrial components and the therapeutic potential of some drugs that target and modulate mitochondria are also briefly discussed.

Exosomal proteins as a source of biomarkers in colon cancer-derived peritoneal carcinomatosis - A pilot study

PURPOSE

Peritoneal carcinomatosis (PC), metastasized from colorectal cancer (CRC), remains a highly lethal disease. Outcomes of PC is significantly influenced by the amount of intra-abdominal tumor burden and therefore diagnostic tests that facilitate earlier diagnosis could improve PC treatment and patient outcomes.

EXPERIMENTAL DESIGN

Using mass-spectrometry-based proteomics, we characterized the protein features of circulating exosomes in the context of CRC PC, CRC with liver metastasis, and primary CRC limited to the colon. We profiled exosomes isolated from patient plasma to identify exosome-associated protein cargoes released by these cancer types.

RESULTS

Analysis of the resulting data identified metastasis-specific exosome protein signatures. Bioinformatic analyses confirmed enrichment of proteins annotated to vesicle-associated processes and intracellular compartments, as well as representation of cancer hallmark functions and processes.

CONCLUSION AND CLINICAL RELEVANCE

This research yielded distinct protein profiles for the CRC patient groups and suggests the utility of plasma exosome proteomic analysis for a better understanding of PC development and metastasis.

Biochemical Markers of Musculoskeletal Health and Aging to be Assessed in Clinical Trials of Drugs Aiming at the Treatment of Sarcopenia: Consensus Paper from an Expert Group Meeting Organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) and the Centre Académique de Recherche et d'Expérimentation en Santé (CARES SPRL), Under the Auspices of the World Health Organization Collaborating Center for the Epidemiology of Musculoskeletal Conditions and Aging

In clinical trials, biochemical markers provide useful information on the drug's mode of action, therapeutic response and side effect monitoring and can act as surrogate endpoints. In pharmacological intervention development for sarcopenia management, there is an urgent need to identify biomarkers to measure in clinical trials and that could be used in the future in clinical practice. The objective of the current consensus paper is to provide a clear list of biochemical markers of musculoskeletal health and aging that can be recommended to be measured in Phase II and Phase III clinical trials evaluating new chemical entities for sarcopenia treatment. A working group of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) proposed classifying biochemical markers into 2 series: biochemical markers evaluating musculoskeletal status and biochemical markers evaluating causal factors. For series 1, the group agreed on 4 biochemical markers that should be assessed in Phase II or Phase III trials (i.e., Myostatin-Follistatin, Brain Derived Neurotrophic Factor, N-terminal Type III Procollagen and Serum Creatinine to Serum Cystatin C Ratio - or the Sarcopenia Index). For series 2, the group agreed on 6 biochemical markers that should be assessed in Phase II trials (i.e., the hormones insulin-like growth factor-1 (IGF-I), dehydroepiandrosterone sulphate, and cortisol, and the inflammatory markers C-reactive protein (CRP), interleukin-6 and tumor necrosis factor-α), and 2 in Phase III trials (i.e., IGF-I and CRP). The group also proposed optional biochemical markers that may provide insights into the mode of action of pharmacological therapies. Further research and development of new methods for biochemical marker assays may lead to the evolution of these recommendations.

Non-coding RNAs as biomarkers of myocardial infarction

Non-coding RNAs (ncRNAs) encompass a family of ubiquitous RNA molecules that lack protein-coding potential and have tissue-specific expression. A significant body of evidence indicates that ncRNA's aberrant expression plays a critical role in disease onset and development. NcRNAs' biochemical characteristics such as disease-associated concentration changes, structural stability, and high abundance in body fluids make them promising prognostic and diagnostic biomarkers. Myocardial infarction (MI) is a leading cause of mortality worldwide. Acute myocardial infarction (AMI), the term in use to describe MI's early phase, is generally diagnosed by physical examination, electrocardiogram (ECG), and the presence of specific biomarkers. In this regard, compared to standard MI biomarkers, such as the cardiac troponin isoforms (cTnT & cTnI) and the Creatinine Kinase (CK), ncRNAs appears to provide better sensitivity and specificity, ensuring a rapid and correct diagnosis, an earlier treatment, and consequently a good prognosis for the patients. This review aims to summarize and discuss the most promising and recent data on the potential clinical use of circulating ncRNAs as MI biomarkers. Specifically, we focused primarily on miRNAs and lncRNAs, highlighting their significant specificity and sensitivity, discussing their limitations, and suggesting possible overcoming approaches.

A systematic review of trials currently investigating therapeutic modalities for post-acute COVID-19 syndrome and registered on WHO International Clinical Trials Platform

BACKGROUND

Post-acute COVID-19 syndrome (PACS) is a well-recognized, complex, systemic disease which is associated with substantial morbidity. There is a paucity of established interventions for the treatment of patients with this syndrome.

OBJECTIVES

To systematically review registered trials currently investigating therapeutic modalities for PACS.

DATA SOURCES

A search was conducted up to the 16 September, 2022, using the COVID-19 section of the WHO Internal Clinical Trials Registry Platform.

STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS

Interventional clinical trials of any sample size examining any therapeutic modality targeting persistent symptoms among individuals after diagnosis with COVID-19.

METHODS

Data on trial characteristics and intervention characteristics were collected and summarized.

RESULTS

After screening 17 125 trials, 388 trials, from 42 countries, were eligible. In total, we had 406 interventions, of which 368 were mono-therapeutic strategies, whereas 38 were intervention combinations. Among 824 primary outcomes identified, there were >300 different outcomes. Rehabilitation was the most employed class of intervention in 169 trials. We encountered 76 trials examining the pharmacological agents of various classes, with the most common agent being colchicine. Complementary and alternative medicine encompassed 64 trials exploring traditional Chinese medicine, Ayurveda, homeopathic medications, naturopathic medications, vitamins, dietary supplements, and botanicals. Psychotherapeutic and educational interventions were also employed in 12 and 4 trials, respectively. Other interventions, including transcranial direct current stimulation, transcutaneous auricular vagus nerve stimulation, general electrical stimulation, cranial electrotherapy stimulation, various stem cell interventions, and oxygen therapy interventions, were also employed.

CONCLUSION

We identified 388 registered trials, with a high degree of heterogeneity, exploring 144 unique mono-therapeutic interventions for PACS. Most studies target general alleviation of symptoms. There is a need for further high-quality and methodologically robust PACS treatment trials to be conducted with standardization of outcomes while following WHO's recommendation for uniform evaluation and treatment.

Neurofilament light is associated with clinical outcome and hemorrhagic transformation in moderate to severe ischemic stroke

Background

Ischemic stroke is a leading cause of morbidity and mortality worldwide. One possible predictor is the use of biomarkers especially neurofilament light chain (NFL).

Objectives

To explore whether NFL could predict clinical outcome and hemorrhagic transformation in moderate to severe stroke.

Design

Single center prospective cohort study.

Methods

Fifty-one moderate to severe ischemic stroke patients were recruited. Blood NFL was obtained from patients at admission (First sample) and 24-96 hours later (Second sample). NFL was analyzed with the ultrasensitive single molecule array (Simoa). Later, we calculated incremental rate NFL (IRN) by changes in NFL per day from baseline. We evaluated National Institute of Health stroke scale (NIHSS), modified Rankins score (mRs), and the presence of hemorrhagic transformation (HT).

Results

IRN was found to be higher in patients with unfavorable outcome (7.12 vs 24.07, P = .04) as well as Second sample (49.06 vs 71.41, P = .011), while NFL First sample was not significant. IRN had a great correlation with mRS (r = .552, P < .001). Univariate logistic regression model showed OR of IRN and Second sample to be 1.081 (95% CI 1.016-1.149, P = .013) and 1.019 (1.002-1.037, P = .03), respectively. Multiple logistic regression model has shown to be significant. In receiver operating analysis, IRN, Second sample, combined IRN with NIHSS and combined Second sample with NIHSS showed AUC (.744, P = .004; 0.713, P = .01; 0.805, P < .001; 0.803, P < .001, respectively). For HT, First sample and Second sample had significant difference with HT (Z = 2.13, P = .033; Z = 2.487, P = .013, respectively).

Conclusion

NFL was found to correlate and predict clinical outcome. In addition, it was found to correlate with HT.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Biosensing chips for cancer diagnosis and treatment: a new wave towards clinical innovation

Recent technological advances in nanoscience and material designing have led to the development of point-of-care devices for biomolecule sensing and cancer diagnosis. In situ and portable sensing devices for bedside, diagnosis can effectively improve the patient’s clinical outcomes and reduce the mortality rate. Detection of exosomal RNAs by immuno-biochip with increased sensitivity and specificity to diagnose cancer has raised the understanding of the tumor microenvironment and many other technology-based biosensing devices hold great promise for clinical innovations to conquer the unbeatable fort of cancer metastasis. Electrochemical biosensors are the most sensitive category of biomolecule detection sensors with significantly low concentrations down to the atomic level. In this sense, this review addresses the recent advances in cancer detection and diagnosis by developing significant biological sensing devices that are believed to have better sensing potential than existing facilities.

Experimental and Clinical Biomarkers for Progressive Evaluation of Neuropathology and Therapeutic Interventions for Acute and Chronic Neurological Disorders

This article describes commonly used experimental and clinical biomarkers of neuronal injury and neurodegeneration for the evaluation of neuropathology and monitoring of therapeutic interventions. Biomarkers are vital for diagnostics of brain disease and therapeutic monitoring. A biomarker can be objectively measured and evaluated as a proxy indicator for the pathophysiological process or response to therapeutic interventions. There are complex hurdles in understanding the molecular pathophysiology of neurological disorders and the ability to diagnose them at initial stages. Novel biomarkers for neurological diseases may surpass these issues, especially for early identification of disease risk. Validated biomarkers can measure the severity and progression of both acute neuronal injury and chronic neurological diseases such as epilepsy, migraine, Alzheimer's disease, Parkinson's disease, Huntington's disease, traumatic brain injury, amyotrophic lateral sclerosis, multiple sclerosis, and other brain diseases. Biomarkers are deployed to study progression and response to treatment, including noninvasive imaging tools for both acute and chronic brain conditions. Neuronal biomarkers are classified into four core subtypes: blood-based, immunohistochemical-based, neuroimaging-based, and electrophysiological biomarkers. Neuronal conditions have progressive stages, such as acute injury, inflammation, neurodegeneration, and neurogenesis, which can serve as indices of pathological status. Biomarkers are critical for the targeted identification of specific molecules, cells, tissues, or proteins that dramatically alter throughout the progression of brain conditions. There has been tremendous progress with biomarkers in acute conditions and chronic diseases affecting the central nervous system.

Diagnostic Performance Evaluation of the Novel Index Combining Urinary Cotinine and 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol in Smoking Status Verification and Usefulness for Trend Monitoring of Tobacco Smoking Exposure

During the last decade in Korea, urinary cotinine concentrations in non-current smokers have decreased, making it difficult to distinguish secondhand smoke (SHS) exposure from nonsmokers because of overlapping values between non-current smokers with and without SHS exposure. Additionally, the importance of smoking status verification to avoid misclassification is increasing with the increased use of e-cigarettes. We developed a novel index combining urinary cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and evaluated its diagnostic performance for the classification of smoking status using the KNHANES VII dataset. A total of 10,116 and 5575 Korean participants aged >19 years with measured urinary cotinine concentrations were enrolled in a training set and validation set, respectively. When using 4.0 as the cutoff value for distinguishing current smokers from non-current smokers, urinary cotinine∙NNAL showed a better diagnostic performance than urinary cotinine or urinary NNAL. Among e-cigarette users, urinary cotinine∙NNAL showed more accurate classification rates than urinary NNAL. Furthermore, urinary cotinine∙NNAL had measurable values in non-current smokers, whereas urinary cotinine had unmeasurable values in one-fourth of all participants. This study shows that urinary cotinine∙NNAL might be a useful biomarker for smoking status verification and trend monitoring of tobacco smoking exposure with increased use of e-cigarettes.

An Optimized Procedure for Proteomic Analysis of Extracellular Vesicles Using In-Stage Tip Digestion and DIA LC-MS/MS: Application to Liquid Biopsy in Cancer

Utilizing biofluids to identify cancer biomarkers has received considerable attention in the past decade. In this regard, serum and urine are convenient biofluids to noninvasively recapitulate information usually indicated by traditional tissue biopsies. In particular, we are interested in exploring the extracellular vesicle (ECV)-containing compartment of these fluids as a targeted source for cancer biomarker discovery. ECVs are membrane-enclosed particles, comprising of various fractions including exosomes, microvesicles, and apoptotic bodies. In both physiological and pathological states such as cancer, ECVs carry a rich load of molecular and protein cargoes, which aid in mediating intercellular communication between cells from various tissue types. Here we successfully enriched ECVs using a simple, low-cost, optimized method that we have developed; it is generalizable for the analysis of ECVs from multiple sample types. Such procedures are necessary as ECVs are nanoparticles that contain a treasure trove of large numbers of biomarkers each present at very low levels. Sample processing procedures can enrich for these vesicles and allow for the enhanced detection of proteins in downstream applications such as comprehensive proteomics methods using data-independent acquisition (DIA) and LC-MS/MS.

Targeted biomarkers of progression in chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is an increasingly significant health issue worldwide. Early stages of CKD can be asymptomatic and disease trajectory difficult to predict. Not everyone with CKD progresses to kidney failure, where kidney replacement therapy is the only life-sustaining therapy. Predicting which patients will progress to kidney failure would allow better use of targeted treatments and more effective allocation of health resources. Current diagnostic tests to identify patients with progressive disease perform poorly but there is a suite of new and emerging predictive biomarkers with great clinical promise.

METHODS

This narrative review describes new and emerging biomarkers of pathophysiologic processes of CKD development and progression, accessible in blood or urine liquid biopsies. Biomarkers were selected based on their reported pathobiological functions in kidney injury, inflammation, oxidative stress, repair and fibrosis. Biomarker function and evidence of involvement in CKD development and progression are reported.

CONCLUSION

Many biomarkers reviewed here have received little attention to date, perhaps because of conflicting conclusions of their utility in CKD. The functional roles of the selected biomarkers in the underlying pathobiology of progression of CKD are a powerful rationale for advancing and validating these molecules as prognosticators and predictors of CKD trajectory.

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.

Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model

Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hampers their use in research and clinical application. Mass spectrometry measures of fifty N-glycans, on seven serum proteins in liver disease, were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized FDA-supported BioCompute Object. Using the biomarker data model allows capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan-protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers, can integrate N-glycan biomarker data with multi-source biomedical data, and can foster discovery and insight within a unified data framework for glycan biomarker representation thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).

Lifting the Veil: Characteristics, Clinical Significance, and Application of β-2-Microglobulin as Biomarkers and Its Detection with Biosensors

Because β-2-microglobulin (β₂M) is a surface protein that is present on most nucleated cells, it plays a key role in the human immune system and the kidney glomeruli to regulate homeostasis. The primary clinical significance of β₂M is in dialysis-related amyloidosis, a complication of end-stage renal disease caused by a gradual accumulation of β₂M in the blood. Therefore, the function of β₂M in kidney-related diseases has been extensively studied to evaluate its glomerular and tubular functions. Because increased β₂M shedding due to rapid cell turnover may indicate other underlying medical conditions, the possibility to use β₂M as a versatile biomarker rose in prominence across multiple disciplines for various applications. Therefore, this work has reviewed the recent use of β₂M to detect various diseases and its progress as a biomarker. While the use of state-of-the-art β₂M detection requires sophisticated tools, high maintenance, and labor cost, this work also has reported the use of biosensor to quantify β₂M over the past decade. It is hoped that a portable and highly efficient β₂M biosensor device will soon be incorporated in point-of-care testing to provide safe, rapid, and reliable test results.

Under-5-Minute Immunoblot Assays by Vortex Fluidic Device Acceleration

Unlocking the potential of personalized medicine in point-of-care settings requires a new generation of biomarker and proteomic assays. Ideally, assays could inexpensively perform hundreds of quantitative protein measurements in parallel at the bedsides of patients. This goal greatly exceeds current capabilities. Furthermore, biomarker assays are often challenging to translate from benchtop to clinic due to difficulties achieving and assessing the necessary selectivity, sensitivity, and reproducibility. To address these challenges, we developed an efficient (<5 min), robust (comparatively lower CVs), and inexpensive (decreasing reagent use and cost by >70 %) immunoassay method. Specifically, the immunoblot membrane is dotted with the sample and then developed in a vortex fluidic device (VFD) reactor. All assay steps-blocking, binding, and washing-leverage the unique thin-film microfluidics of the VFD. The approach can accelerate direct, indirect, and sandwich immunoblot assays. The applications demonstrated include assays relevant to both the laboratory and the clinic.

The Translation and Commercialisation of Biomarkers for Cardiovascular Disease—A Review

As a leading cause of mortality and morbidity worldwide, cardiovascular disease and its diagnosis, quantification, and stratification remain significant health issues. Increasingly, patients present with cardiovascular disease in the absence of known risk factors, suggesting the presence of yet unrecognized pathological processes and disease predispositions. Fortunately, a host of emerging cardiovascular biomarkers characterizing and quantifying ischaemic heart disease have shown great promise in both laboratory settings and clinical trials. These have demonstrated improved predictive value additional to widely accepted biomarkers as well as providing insight into molecular phenotypes beneath the broad umbrella of cardiovascular disease that may allow for further personalized treatment regimens. However, the process of translation into clinical practice – particularly navigating the legal and commercial landscape – poses a number of challenges. Practical and legal barriers to the biomarker translational pipeline must be further considered to develop strategies to bring novel biomarkers into the clinical sphere and apply these advances at the patient bedside. Here we review the progress of emerging biomarkers in the cardiovascular space, with particular focus on those relevant to the unmet needs in ischaemic heart disease.

The Availability of Human Biospecimens to Support Biomarker Research

Preserved biospecimens held in biobank inventories and clinical archives are important resources for biomarker research. Recent advances in technologies have led to an increase in use of clinical archives in particular, in order to study retrospective cohorts and to generate data relevant to tissue biomarkers. This raises the question of whether the current sizes of biobank inventories are appropriate to meet the demands of biomarker research. This commentary discusses this question by considering data concerning overall biobank and biospecimen numbers to estimate current biospecimen supply and use. The data suggests that biospecimen supply exceeds current demand. Therefore, it may be important for individual biobanks to reassess the targets for their inventories, consider culling unused portions of these inventories, and shift resources towards providing prospective custom biobanking services.

Pan-cancer prognostic genetic mutations and clinicopathological factors associated with survival outcomes: a systematic review

Cancer is a leading cause of death, accounting for almost 10 million deaths annually worldwide. Personalised therapies harnessing genetic and clinical information may improve survival outcomes and reduce the side effects of treatments. The aim of this study is to appraise published evidence on clinicopathological factors and genetic mutations (single nucleotide polymorphisms [SNPs]) associated with prognosis across 11 cancer types: lung, colorectal, breast, prostate, melanoma, renal, glioma, bladder, leukaemia, endometrial, ovarian. A systematic literature search of PubMed/MEDLINE and Europe PMC was conducted from database inception to July 1, 2021. 2497 publications from PubMed/MEDLINE and 288 preprints from Europe PMC were included. Subsequent reference and citation search was conducted and a further 39 articles added. 2824 articles were reviewed by title/abstract and 247 articles were selected for systematic review. Majority of the articles were retrospective cohort studies focusing on one cancer type, 8 articles were on pan-cancer level and 6 articles were reviews. Studies analysing clinicopathological factors included 908,567 patients and identified 238 factors, including age, gender, stage, grade, size, site, subtype, invasion, lymph nodes. Genetic studies included 210,802 patients and identified 440 gene mutations associated with cancer survival, including genes TP53, BRCA1, BRCA2, BRAF, KRAS, BIRC5. We generated a comprehensive knowledge base of biomarkers that can be used to tailor treatment according to patients' unique genetic and clinical characteristics. Our pan-cancer investigation uncovers the biomarker landscape and their combined influence that may help guide health practitioners and researchers across the continuum of cancer care from drug development to long-term survivorship.

Circulating Nucleic Acids as Novel Biomarkers for Pancreatic Ductal Adenocarcinoma

Despite considerable advancements in the clinical management of PDAC it remains a significant cause of mortality. PDAC is often diagnosed at advanced stages due to vague symptoms associated with early-stage disease and a lack of reliable diagnostic biomarkers. Late diagnosis results in a high proportion of cases being ineligible for surgical resection, the only potentially curative therapy for PDAC. Furthermore, a lack of prognostic biomarkers impedes clinician's ability to properly assess the efficacy of therapeutic interventions. Advances in our ability to detect circulating nucleic acids allows for the advent of novel biomarkers for PDAC. Tumor derived circulating and exosomal nucleic acids allow for the detection of PDAC-specific mutations through a non-invasive blood sample. Such biomarkers could expand upon the currently limited repertoire of tests available. This review outlines recent developments in the use of molecular techniques for the detection of these nucleic acids and their potential roles, alongside current techniques, in the diagnosis, prognosis and therapeutic governance of PDAC.

Evaluation of Sweat-Sampling Procedures for Human Stress-Biomarker Detection

Sweat is a potential biological fluid for the non-invasive analytical assessment of diverse molecules, including biomarkers. Notwithstanding, the sampling methodology is critical, and it must be assessed prior to using sweat for clinical diagnosis. In the current work, the analytical methodology was further developed taking into account the sampling step, in view of the identification and level variations of sweat components that have potential to be stress biomarkers using separation by liquid chromatography and detection by tandem mass spectrometry, in order to attain a screening profile of 26 molecules in just one stage. As such, the molecule identification was used as a test for the evaluation of the sampling procedures, including the location on the body, using patches for long-term sampling and vials for direct sampling, through a qualitative approach. From this evaluation it was possible to conclude that the sampling may be performed on the chest or back skin. Additionally, possible interference was evaluated. The long-term sampling with patches can be used under both rest and exercise conditions with variation of the detected molecule’s levels. The direct sampling, using vials, has the advantage of not having interferences but the disadvantage of only being effective after exercise in order to have enough sample for sweat analysis.

Profiling Blood Serum Extracellular Vesicles in Plaque Psoriasis and Psoriatic Arthritis Patients Reveals Potential Disease Biomarkers

Psoriasis vulgaris (PsV) and psoriatic arthritis (PsA) are inflammatory diseases with unresolved pathophysiological aspects. Extracellular vesicles (EVs) play an important role in intercellular communication. We compared the miRNA contents and surface proteome of the EVs in the blood serum of PsV and PsA patients to healthy controls. Size-exclusion chromatography was used to isolate EVs from the blood serum of 12 PsV patients, 12 PsA patients and 12 healthy control subjects. EV samples were characterized and RNA sequencing was used to identify differentially enriched EV-bound miRNAs. We found 212 differentially enriched EV-bound miRNAs present in both PsV and PsA groups—a total of 13 miRNAs at FDR ≤ 0.05. The predicted target genes of these miRNAs were significantly related to lesser known but potentially disease-relevant pathways. The EV array revealed that PsV patient EV samples were significantly enriched with CD9 EV-marker compared to controls. Analysis of EV-bound miRNAs suggests that signaling via EVs in the blood serum could play a role in the pathophysiological processes of PsV and PsA. EVs may be able to fill the void in clinically applicable diagnostic and prognostic biomarkers for PsV and PsA.

Low Tissue Creatine: A Therapeutic Target in Clinical Nutrition

Low tissue creatine characterizes many conditions, including neurodegenerative, cardiopulmonary, and metabolic diseases, with a magnitude of creatine shortfall often corresponds well to a disorder’s severity. A non-invasive monitoring of tissue metabolism with magnetic resonance spectroscopy (MRS) might be a feasible tool to evaluate suboptimal levels of creatine for both predictive, diagnostic, and therapeutic purposes. This mini review paper summarizes disorders with deficient creatine levels and provides arguments for assessing and employing tissue creatine as a relevant target in clinical nutrition.

Real-world biomarker testing rate and positivity rate in NSCLC in Spain: Prospective Central Lung Cancer Biomarker Testing Registry (LungPath) from the Spanish Society of Pathology (SEAP)

AIM

The aim of this study was to describe the testing rate and frequency of molecular alterations observed in the Lung Cancer Biomarker Testing Registry (LungPath).

METHODS

A descriptive study of NSCLC biomarker determinations collected from March 2018 to January 2019, from 38 Spanish hospitals, was carried out. Only adenocarcinoma and not otherwise specified histologies were included for epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1) and programmed death ligand-1 (PD-L1) expression. The testing rate and the positivity rate were calculated. Multivariate logistic regression was used to explore the joint relationship between independent explanatory factors and both testing and positivity rates. Two models were adjusted: one with sample type and histology as independent factors, and the other adding the testing rate or the positivity rate of the other biomarkers.

RESULTS

3226 patient samples were analysed, where EGFR, ALK, ROS1 and PD-L1 information was collected (a total of 12 904 determinations). Overall, 9118 (71.4%) determinations were finally assessed. EGFR (91.4%) and ALK (80.1%) were the mainly tested biomarkers. Positivity rates for EGFR, ALK, ROS1 and PD-L1 were 13.6%, 3.4%, 2.0% and 49.2%, respectively. Multivariate models showed a lower testing rate for ALK in surgical pieces, fine-needle aspiration or other types of samples versus biopsies.

CONCLUSIONS

Despite the high testing rate in EGFR and ALK in NSCLC, the real-world evidence obtained from the LungPath demonstrates that ROS1 and PD-L1 were not determined in a significant portion of patients. LungPath provides crucial information to improve the coverage in molecular testing in lung cancer, to monitor the positivity rate and the introduction of new biomarker testing in clinical practice.

Mechanisms, Mediators, and Moderators of the Effects of Exercise on Chemotherapy-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is an adverse effect of neurotoxic antineoplastic agents commonly used to treat cancer. Patients with CIPN experience debilitating signs and symptoms, such as combinations of tingling, numbness, pain, and cramping in the hands and feet that inhibit their daily function. Among the limited prevention and treatment options for CIPN, exercise has emerged as a promising new intervention that has been investigated in approximately two dozen clinical trials to date. As additional studies test and suggest the efficacy of exercise in treating CIPN, it is becoming more critical to develop mechanistic understanding of the effects of exercise in order to tailor it to best treat CIPN symptoms and identify who will benefit most. To address the current lack of clarity around the effect of exercise on CIPN, we reviewed the key potential mechanisms (e.g., neurophysiological and psychosocial factors), mediators (e.g., anti-inflammatory cytokines, self-efficacy, and social support), and moderators (e.g., age, sex, body mass index, physical fitness, exercise dose, exercise adherence, and timing of exercise) that may illuminate the relationship between exercise and CIPN improvement. Our review is based on the studies that tested the use of exercise for patients with CIPN, patients with other types of neuropathies, and healthy adults. The discussion presented herein may be used to (1) guide oncologists in predicting which symptoms are best targeted by specific exercise programs, (2) enable clinicians to tailor exercise prescriptions to patients based on specific characteristics, and (3) inform future research and biomarkers on the relationship between exercise and CIPN.

Development of Planar Illumination Strategies for Solving Mysteries in the Sub-Cellular Realm

Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system's point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.

A diagnostic and prognostic value of blood-based circulating long non-coding RNAs in Thyroid, Pancreatic and Ovarian Cancer

Several studies have demonstrated the potential of circulating long non-coding RNAs (lncRNAs) as promising cancer biomarkers. Herein, we addressed the regulatory role of circulating lncRNAs and their potential value as diagnostic/prognostic markers for thyroid, pancreatic and ovarian cancers. Furthermore, we analyzed and measured the clinical implications and association of lncRNAs with sensitivity, specificity, and area under the ROC curve (AUC). Based on our meta-analysis, we found that GAS8-AS1 could discriminate thyroid cancer from non-cancer and other cancers with higher accuracy (AUC = 0.746; sensitivity = 61.70%, and specificity = 90.00%). Similarly, for ovarian cancer, lncRNA RP5-837J1.2 was found to have ideal diagnostic potential with critical clinical specifications of AUC = 0.996; sensitivity = 97.30% and specificity = 94.60%. Whereas we could not find any lncRNA having high diagnostic/prognostic efficiency in pancreatic cancer. We believe that lncRNAs mentioned above may explore clinical settings for the diagnosis and prognosis of cancer patients.