Making Meaningful Clinical Use of Biomarkers

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.

Methylation of FBN1, SPG20, ITF2, RUNX3, SNCA, MLH1, and SEPT9 genes in circulating cell-free DNA as biomarkers of colorectal cancer

BACKGROUND

Investigating aberrant tumor-specific methylation in plasma cell-free DNA provides a promising and noninvasive biomarker for cancer detection.

OBJECTIVE

We aimed to investigate methylation status of some promoter regions in the plasma and tumor tissues to find biomarkers for early detection of colorectal cancer.

METHODS

This case-control study on seventy colorectal cancer patients and fifty matched healthy controls used Methylation-Specific High-Resolution Melting Curve analysis to evaluate the methylation of the selected promoter regions in converted genomic tissue DNA and plasma cfDNA.

RESULTS

The methylation levels in selected regions of SPG20 (+24375 to +24680, +24209 to +24399, and +23625 to +23883), SNCA (+807 to +1013, +7 to +162, and -180 to +7), FBN1 (+223 to +429, +1 to +245, and -18 to -175), ITF2 (+296 to +436 and -180 to +55), SEPT9 (-914412 to -91590 and -99083 to -92264), and MLH1 (-13 to +22) were significantly higher in tumor tissues compared with normal adjacent tissues. The methylation levels of FBN1, ITF2, SNCA, and SPG20 promoters were significantly higher in the patient's plasma compared to patient's normal tissue and plasma of healthy control subjects. FBN1, SPG20, and SEPT9 promoter methylation had a good diagnostic performance for discriminating CRC tissues from normal adjacent tissues (AUC > 0.8). A panel of SPG20, FBN1, and SEPT9 methylation had a higher diagnostic value than that of any single biomarker and other panels in tissue-based assay (AUC > 0.9). The methylation of FBN1(a) and SPG20(a) regions, as the closest region to the first coding sequence (CDS), had a good diagnostic performance in plasma cfDNA (AUC > 0.8) while a panel consisted of FBN1(a) and SPG20(a) regions showed excellent diagnostic performance for CRC detection in plasma cfDNA (AUC > 0.9).

CONCLUSION

Methylation of FBN1(a) and SPG20(a) promoter regions in the plasma cfDNA can be an excellent simple, non-invasive blood-based test for early detection of CRC.

Identification of new candidate biomarkers to support doxorubicin treatments in canine cancer patients

Background

Both human and veterinary cancer chemotherapy are undergoing a paradigm shift from a “one size fits all” approach to more personalized, patient-oriented treatment strategies. Personalized chemotherapy is dependent on the identification and validation of biomarkers that can predict treatment outcome and/or risk of toxicity. Many cytotoxic chemotherapy agents, including doxorubicin, base their mechanism of action by interaction with DNA and disruption of normal cellular processes. We developed a high-resolution/accurate-mass liquid chromatography-mass spectrometry DNA screening approach for monitoring doxorubicin-induced DNA modifications (adducts) in vitro and in vivo. We used, for the first time, a new strategy involving the use of isotope-labeled DNA, which greatly facilitates adduct discovery. The overall goal of this work was to identify doxorubicin-DNA adducts to be used as biomarkers to predict drug efficacy for use in veterinary oncology.

Results

We used our novel mass spectrometry approach to screen for adducts in purified DNA exposed to doxorubicin. This initial in vitro screening identified nine potential doxorubicin-DNA adduct masses, as well as an intense signal corresponding to DNA-intercalated doxorubicin. Two of the adduct masses, together with doxorubicin and its metabolite doxorubicinol, were subsequently detected in vivo in liver DNA extracted from mice exposed to doxorubicin. Finally, the presence of these adducts and analytes was explored in the DNA isolated from dogs undergoing treatment with doxorubicin. The previously identified nine DOX-DNA adducts were not detected in these preliminary three samples collected seven days post-treatment, however intercalated doxorubicin and doxorubicinol were detected.

Conclusions

This work sets the stage for future evaluation of doxorubicin-DNA adducts and doxorubicin-related molecules as candidate biomarkers to personalize chemotherapy protocols for canine cancer patients. It demonstrates our ability to combine in one method the analysis of DNA adducts and DNA-intercalated doxorubicin and doxorubicinol. The last two analytes interestingly, were persistent in samples from canine patients undergoing doxorubicin chemotherapy seven days after treatment. The presence of doxorubicin in all samples suggests a role for it as a promising biomarker for use in veterinary chemotherapy. Future studies will involve the analysis of more samples from canine cancer patients to elucidate optimal timepoints for monitoring intercalated doxorubicin and doxorubicin-DNA adducts and the correlation of these markers with therapy outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-021-03062-x.

Heart rate variability as a biomarker of functional outcomes in persons with acquired brain injury: Systematic review and meta-analysis

This review aimed to quantify correlations between heart rate variability (HRV) and functional outcomes after acquired brain injury (ABI). We conducted a literature search from inception to January 2020 via electronic databases, using search terms with HRV, ABI, and functional outcomes. Meta-analyses included 16 studies with 906 persons with ABI. Results demonstrated significant associations: Low frequency (LF) (r = -0.28) and SDNN (r = -0.33) with neurological function; LF (r = -0.33), High frequency (HF) (r = -0.22), SDNN (r = -0.22), and RMSSD (r = -0.23) with emotional function; and LF (r = 0.34), HF (r = 0.41 to 0.43), SDNN (r = 0.43 to 0.51), and RMSSD (r = 0.46) with behavioral function. Results indicate that higher HRV is related to better neurological, emotional, and behavioral functions after ABI. In addition, persons with stroke showed lower HF (SMD = -0.50) and SDNN (SMD = -0.75) than healthy controls. The findings support the use of HRV as a biomarker to facilitate precise monitoring of post-ABI functions.

The Challenges of Developing Biosensors for Clinical Assessment: A Review

Emerging research in biosensors has attracted much attention worldwide, particularly in response to the recent pandemic outbreak of coronavirus disease 2019 (COVID-19). Nevertheless, initiating research in biosensing applied to the diagnosis of diseases is still challenging for researchers, be it in the preferences of biosensor platforms, selection of biomarkers, detection strategies, or other aspects (e.g., cutoff values) to fulfill the clinical purpose. There are two sides to the development of a diagnostic tool: the biosensor development side and the clinical side. From the development side, the research engineers seek the typical characteristics of a biosensor: sensitivity, selectivity, linearity, stability, and reproducibility. On the other side are the physicians that expect a diagnostic tool that provides fast acquisition of patient information to obtain an early diagnosis or an efficient patient stratification, which consequently allows for making assertive and efficient clinical decisions. The development of diagnostic devices always involves assay developer researchers working as pivots to bridge both sides whose role is to find detection strategies suitable to the clinical needs by understanding (1) the intended use of the technology and its basic principle and (2) the preferable type of test: qualitative or quantitative, sample matrix challenges, biomarker(s) threshold (cutoff value), and if the system requires a mono- or multiplex assay format. This review highlights the challenges for the development of biosensors for clinical assessment and its broad application in multidisciplinary fields. This review paper highlights the following biosensor technologies: magnetoresistive (MR)-based, transistor-based, quartz crystal microbalance (QCM), and optical-based biosensors. Its working mechanisms are discussed with their pros and cons. The article also gives an overview of the most critical parameters that are optimized by developing a diagnostic tool.

A call to action: molecular pathology in Brazil

Background

Adoption of molecular pathology in Brazil is currently very limited. Of note, there are no programs for training new molecular pathologists in the country; thus, documents compiling nationally applicable information on molecular pathology are few.

Methods

A selected panel of Brazilian experts in fields related to molecular pathology were provided with a series of relevant questions to address prior to the multi-day conference. Within this conference, each narrative was discussed and edited by the entire group, through numerous drafts and rounds of discussion until a consensus was achieved.

Results

The panel proposes specific and realistic recommendations for implementing molecular pathology in cancer care in Brazil. In creating these recommendations, the authors strived to address all barriers to the widespread use and impediments to access mentioned previously within this manuscript.

Conclusion

This manuscript provides a review of molecular pathology principles as well as the current state of molecular pathology in Brazil. Additionally, the panel proposes practical and actionable recommendations for the implementation of molecular pathology throughout the country in order to increase awareness of the importance molecular pathology in Brazil.

Identifying a role for the interaction of homocysteine and copper in promoting cardiovascular-related damage

Observations that copper and homocysteine levels are simultaneously elevated in patients with cardiovascular disease has generated interest in investigating the interactions between copper and homocysteine. Several prior studies have shown that complexes of copper and homocysteine are toxic, leading to cardiovascular damage in vitro. It is not clear, however, why related effects do not occur with other structurally similar, more abundant cellular thiols such as glutathione and cysteine. Herein, a mechanism for a selective redox interaction between copper and homocysteine is demonstrated. It involves a kinetically favored intramolecular hydrogen atom transfer that results in an alpha-amino carbon-centered radical known to promote biomolecular damage.

Role of innate inflammation in traumatic brain injury

Traumatic brain injury is one of the leading causes of morbidity and mortality throughout the world. Its increasing incidence, in addition to its fundamental role in the development of neurodegenerative disease, proves especially concerning. Despite extensive preclinical and clinical studies, researchers have yet to identify a safe and effective neuroprotective strategy. Following brain trauma, secondary injury from molecular, metabolic, and cellular changes causes progressive cerebral tissue damage. Chronic neuroinflammation following traumatic brain injuries is a key player in the development of secondary injury. Targeting this phenomenon for development of effective neuroprotective therapies holds promise. This strategy warrants a concrete understanding of complex neuroinflammatory mechanisms. In this review, we discuss pathophysiological mechanisms such as the innate immune response, glial activation, blood-brain barrier disruption, activation of immune mediators, as well as biological markers of traumatic brain injury. We then review existing and emerging pharmacological therapies that target neuroinflammation to improve functional outcome.

Biomarkers of Joint Damage in Osteoarthritis: Current Status and Future Directions

Osteoarthritis (OA) is a disease of the whole joint organ, characterized by the loss of cartilage, and structural changes in bone including the formation of osteophytes, causing disability and loss of function. It is also associated with systemic mediators and low-grade inflammation. Currently, there is negligible/no availability of specific biomarkers that can be used to facilitate the diagnosis and treatment of OA. The most unmet clinical need is, however, related to the monitoring of disease progression over a short period that can be used in clinical trials. In this review, the value of biomarkers identified over the past decade has been highlighted. These biomarkers are associated with the synthesis and breakdown of cartilage, including collagenous and noncollagenous biomarkers, inflammatory and anti-inflammatory biomarkers, expressed in the biological fluid such as serum, synovial fluid, and urine. Broad validation of novel and clinically applicable biomarkers and their involvement in the pathways are particularly needed for early-stage diagnosis, monitoring disease progression, and severity and examining new drugs to mitigate the effects of this highly prevalent and debilitating condition.

Development and Characterization of a Probe Device toward Intracranial Spectroscopy of Traumatic Brain Injury

Traumatic brain injury is a leading cause of mortality worldwide, often affecting individuals at their most economically active yet no primary disease-modifying interventions exist for their treatment. Real-time direct spectroscopic examination of the brain tissue within the context of traumatic brain injury has the potential to improve the understanding of injury heterogeneity and subtypes, better target management strategies and organ penetrance of pharmacological agents, identify novel targets for intervention, and allow a clearer understanding of fundamental biochemistry evolution. Here, a novel device is designed and engineered, delivering Raman spectroscopy-based measurements from the brain through clinically established cranial access techniques. Device prototyping is undertaken within the constraints imposed by the acquisition and site dimensions (standard intracranial access holes, probe’s dimensions), and an artificial skull anatomical model with cortical impact is developed. The device shows a good agreement with the data acquired via a standard commercial Raman, and the spectra measured are comparable in terms of quality and detectable bands to the established traumatic brain injury model. The developed proof-of-concept device demonstrates the feasibility for real-time optical brain spectroscopic interface while removing the noise of extracranial tissue and with further optimization and in vivo validation, such technology will be directly translatable for integration into currently available standards of neurological care.

Bringing Onco-Innovation to Europe's Healthcare Systems: The Potential of Biomarker Testing, Real World Evidence, Tumour Agnostic Therapies to Empower Personalised Medicine

Simple Summary

The increasing number of data supporting use of a personalized approach in cancer treatment, is changing the path of patient’s management. In the same time, the availability of technologies should allow patients to receive the best test for the specific individual condition. This is theoretically true, when a specific test is designed for the specific disease condition, while it is difficult to implement in the setting of agnostic therapies. Financial sources availability related to the non homogeneous health systems working in the different countries do not allow for an immediate implementation of the technologies and test commercially available. Future perspectives for targeted oncology include tumor-agnostic drugs, which target a given mutation and could be used in treating cancers from multiple organ types. Therefore, the present paper is aimed to both underline a how much important is this new view and also to sensitize the international bodies that supervise health policies at the decision-making level, with the aim of harmonizing cancer treatment pathways in at least all European countries.

Abstract

Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre-eminently in many cancers, but also in an ever-wider range of conditions—notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country-related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real-world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients.

High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and has clinical potential as a prognostic biomarker. The objective of this work was to develop an artificial intelligence (AI) system for automated detection and localization of PTEN loss on immunohistochemically (IHC) stained sections. PTEN loss was assessed using IHC in two prostate tissue microarrays (TMA) (internal cohort, n = 272 and external cohort, n = 129 patients). TMA cores were visually scored for PTEN loss by pathologists and, if present, spatially annotated. Cores from each patient within the internal TMA cohort were split into 90% cross-validation (N = 2048) and 10% hold-out testing (N = 224) sets. ResNet-101 architecture was used to train core-based classification using a multi-resolution ensemble approach (×5, ×10, and ×20). For spatial annotations, single resolution pixel-based classification was trained from patches extracted at ×20 resolution, interpolated to ×40 resolution, and applied in a sliding-window fashion. A final AI-based prediction model was created from combining multi-resolution and pixel-based models. Performance was evaluated in 428 cores of external cohort. From both cohorts, a total of 2700 cores were studied, with a frequency of PTEN loss of 14.5% in internal (180/1239) and external 13.5% (43/319) cancer cores. The final AI-based prediction of PTEN status demonstrated 98.1% accuracy (95.0% sensitivity, 98.4% specificity; median dice score = 0.811) in internal cohort cross-validation set and 99.1% accuracy (100% sensitivity, 99.0% specificity; median dice score = 0.804) in internal cohort test set. Overall core-based classification in the external cohort was significantly improved in the external cohort (area under the curve = 0.964, 90.6% sensitivity, 95.7% specificity) when further trained (fine-tuned) using 15% of cohort data (19/124 patients). These results demonstrate a robust and fully automated method for detection and localization of PTEN loss in prostate cancer tissue samples. AI-based algorithms have potential to streamline sample assessment in research and clinical laboratories.

Polyamine biomarkers as indicators of human disease

The significant increase of periodontitis, chronic kidney disease (CKD), Alzheimer's disease and cancer can be attributed to an ageing population. Each disease produces a range of biomarkers that can be indicative of disease onset and progression. Biomarkers are defined as cellular (intra/extracellular components and whole cells), biochemical (metabolites, ions and toxins) or molecular (nucleic acids, proteins and lipids) alterations which are measurable in biological media such as human tissues, cells or fluids. An interesting group of biomarkers that merit further investigation are the polyamines. Polyamines are a group of molecules consisting of cadaverine, putrescine, spermine and spermidine and have been implicated in the development of a range of systemic diseases, in part due to their production in periodontitis. Cadaverine and putrescine within the periodontal environment have demonstrated cell signalling interfering abilities, by way of leukocyte migration disruption. The polyamines spermine and spermidine in tumour cells have been shown to inhibit cellular apoptosis, effectively prolonging tumorigenesis and continuation of cancer within the host. Polyamine degradation products such as acrolein have been shown to exacerbate renal damage in CKD patients. Thus, the use of such molecules has merit to be utilized in the early indication of such diseases in patients.

A multi-scale integrated analysis identifies KRT8 as a pan-cancer early biomarker

An early biomarker would transform our ability to screen and treat patients with cancer. The large amount of multi-scale molecular data in public repositories from various cancers provide unprecedented opportunities to find such a biomarker. However, despite identification of numerous molecular biomarkers using these public data, fewer than 1% have proven robust enough to translate into clinical practice. One of the most important factors affecting the successful translation to clinical practice is lack of real-world patient population heterogeneity in the discovery process. Almost all biomarker studies analyze only a single cohort of patients with the same cancer using a single modality. Recent studies in other diseases have demonstrated the advantage of leveraging biological and technical heterogeneity across multiple independent cohorts to identify robust disease biomarkers. Here we analyzed 17149 samples from patients with one of 23 cancers that were profiled using either DNA methylation, bulk and single-cell gene expression, or protein expression in tumor and serum. First, we analyzed DNA methylation profiles of 9855 samples across 23 cancers from The Cancer Genome Atlas (TCGA). We then examined the gene expression profile of the most significantly hypomethylated gene, KRT8, in 6781 samples from 57 independent microarray datasets from NCBI GEO. KRT8 was significantly over-expressed across cancers except colon cancer (summary effect size=1.05; p < 0.0001). Further, single-cell RNAseq analysis of 7447 single cells from lung tumors showed that genes that significantly correlated with KRT8 (p < 0.05) were involved in p53-related pathways. Immunohistochemistry in tumor biopsies from 294 patients with lung cancer showed that high protein expression of KRT8 is a prognostic marker of poor survival (HR = 1.73, p = 0.01). Finally, detectable KRT8 in serum as measured by ELISA distinguished patients with pancreatic cancer from healthy controls with an AUROC=0.94. In summary, our analysis demonstrates that KRT8 is (1) differentially expressed in several cancers across all molecular modalities and (2) may be useful as a biomarker to identify patients that should be further tested for cancer.

Clinical correlates for immune checkpoint therapy: significance for CNS malignancies

Immune checkpoint inhibitors (ICIs) have revolutionized the field of cancer immunotherapy. Most commonly, inhibitors of PD-1 and CTLA4 are used having received approval for the treatment of many cancers like melanoma, non-small-cell lung carcinoma, and leukemia. In contrast, to date, clinical studies conducted in patients with CNS malignancies have not demonstrated promising results. However, patients with CNS malignancies have several underlying factors such as treatment with supportive medications like corticosteroids and cancer therapies including radiation and chemotherapy that may negatively impact response to ICIs. Although many clinical trials have been conducted with ICIs, measures that reproducibly and reliably indicate that treatment has evoked an effective immune response have not been fully developed. In this article, we will review the history of ICI therapy and the correlative biology that has been performed in the clinical trials testing these therapies in different cancers. It is our aim to help provide an overview of the assays that may be used to gauge immunologic response. This may be particularly germane for CNS tumors, where there is currently a great need for predictive biomarkers that will allow for the selection of patients with the highest likelihood of responding.

System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation

There are many varieties of Cannabis sativa that differ from each other by composition of cannabinoids, terpenes and other molecules. The medicinal properties of these cultivars are often very different, with some being more efficient than others. This report describes the development of a method and software for the analysis of the efficiency of various cannabis extracts to detect the anti-inflammatory properties of the various cannabis extracts. The method uses high-throughput gene expression profiling data but can potentially use other omics data as well. According to the signaling pathway topology, the gene expression profiles are convoluted into the signaling pathway activities using a signaling pathway impact analysis (SPIA) method. The method was tested by inducing inflammation in human 3D epithelial tissues, including intestine, oral and skin, and then exposing these tissues to various extracts and then performing transcriptome analysis. The analysis showed a different efficiency of the various extracts in restoring the transcriptome changes to the pre-inflammation state, thus allowing to calculate a different cannabis drug efficiency index (CDEI).

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

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

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth

CD4+ T-cells represent a heterogeneous collection of specialised sub-types and are a key cell type in the pathogenesis of many diseases due to their role in the adaptive immune system. By investigating CD4+ T-cells at the single cell level, using RNA sequencing (scRNA-seq), there is the potential to identify specific cell states driving disease or treatment response. However, the impact of sequencing depth and cell numbers, two important factors in scRNA-seq, has not been determined for a complex cell population such as CD4+ T-cells. We therefore generated a high depth, high cell number dataset to determine the effect of reduced sequencing depth and cell number on the ability to accurately identify CD4+ T-cell subtypes. Furthermore, we investigated T-cell signatures under resting and stimulated conditions to assess cluster specific effects of stimulation. We found that firstly, cell number has a much more profound effect than sequencing depth on the ability to classify cells; secondly, this effect is greater when cells are unstimulated and finally, resting and stimulated samples can be combined to leverage additional power whilst still allowing differences between samples to be observed. While based on one individual, these results could inform future scRNA-seq studies to ensure the most efficient experimental design.

DNA Associated with Circulating Exosomes as a Biomarker for Glioma

Cancerous and non-cancerous cells secrete exosomes, a type of nanovesicle known to carry the molecular signature of the parent for intercellular communications. Exosomes secreted by tumor cells carry abnormal DNA, RNA, and protein molecules that reflect the cancerous status. DNA is the master molecule that ultimately affects the function of RNA and proteins. Aberrations in DNA can potentially lead a cell to malignancy. Deviant quantities and the differential sequences of exosomal DNA are useful characteristics as cancer biomarkers. Since these alterations are either associated with specific stages of cancer or caused due to a clinical treatment, exosomal DNA is valuable as a diagnostic, prognostic, predictive, and therapeutic-intervention response biomarker. Notably, the exosomes can cross an intact blood–brain barrier and anatomical compartments by transcytosis. As such, the cancer-specific trademark molecules can be detected in systemic blood circulation and other body fluids, including cerebrospinal fluid, with non-invasive or minimally invasive procedures. This comprehensive review highlights the cancer-specific modulations of DNA associated with circulating exosomes that are beneficial as glioma biomarkers.

Integrative Analysis to Identify Race-Associated Metabolite Biomarkers for Hepatocellular Carcinoma

Compared to European-Americans (EAs), the incidence of hepatocellular carcinoma (HCC) is higher in African-Americans (AAs) and is associated with more advanced tumor stage at diagnosis and lower survival rates. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis to identify candidate biomarkers that distinguish HCC from cirrhotic patients in a race specific manner. Through integrative analysis of transcriptomic and metabolomic data, we investigated candidate metabolite biomarkers that are specific to AAs and EAs. The results from this demonstrate the utility of integrating transcriptomic and metabolomic data to prioritize clinically and biologically relevant metabolite biomarkers that can increase understanding of molecular mechanisms driving HCC in different racial groups.

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.

The ZAR1 protein in cancer; from epigenetic silencing to functional characterisation and epigenetic therapy of tumour suppressors

ZAR1, zygote arrest 1, is a zinc finger protein (C-terminus), which was initially identified in mouse oocytes. Later it was found that its expression is present in various human tissues e.g. lung and kidney. Interestingly, it was observed that in various tumour types the ZAR1 transcript is missing due to hypermethylation of its CpG island promoter, but not ZAR2. Since methylation of the ZAR1 promoter is described as a frequent event in tumourigenesis, ZAR1 could serve as a useful diagnostic marker in cancer screens. ZAR1 was described as a useful prognostic/diagnostic cancer marker for lung cancer, kidney cancer, melanoma and possibly liver carcinoma. Furthermore, ZAR1 was reactivated as a tumour suppressor by epigenetic therapy using CRISPR-dCas9 method. This method holds the potential to precisely target not only ZAR1 and reactivate tumour suppressors in a tailored cancer therapy. ZAR1 is highly conserved amongst vertebrates, especially its zinc finger, which is the relevant domain for its protein and RNA binding ability. ZAR1 is implicated in various cellular mechanisms including regulation of oocyte/embryo development, cell cycle control and mRNA binding, though little was known about the underlying mechanisms. ZAR1 was reported to regulate and activate translation through the binding to TCS translation control sequences in the 3'UTRs of its target mRNA the kinase WEE1. ZAR1 has a tumour suppressing function by inhibiting cell cycle progression. Here we review the current literature on ZAR1 focusing on structural, functional and epigenetic aspects. Characterising the cellular mechanisms that regulate the signalling pathways ZAR1 is involved in, could lead to a deeper understanding of tumour development and, furthermore, to new strategies in cancer treatment.

Age-Associated Salivary MicroRNA Biomarkers for Oculopharyngeal Muscular Dystrophy

Small non-coding microRNAs (miRNAs) are involved in the regulation of mRNA stability. Their features, including high stability and secretion to biofluids, make them attractive as potential biomarkers for diverse pathologies. This is the first study reporting miRNA as potential biomarkers for oculopharyngeal muscular dystrophy (OPMD), an adult-onset myopathy. We hypothesized that miRNA that is differentially expressed in affected muscles from OPMD patients is secreted to biofluids and those miRNAs could be used as biomarkers for OPMD. We first identified candidate miRNAs from OPMD-affected muscles and from muscles from an OPMD mouse model using RNA sequencing. We then compared the OPMD-deregulated miRNAs to the literature and, subsequently, we selected a few candidates for expression studies in serum and saliva biofluids using qRT-PCR. We identified 126 miRNAs OPMD-deregulated in human muscles, but 36 deregulated miRNAs in mice only (pFDR < 0.05). Only 15 OPMD-deregulated miRNAs overlapped between the in humans and mouse studies. The majority of the OPMD-deregulated miRNAs showed opposite deregulation direction compared with known muscular dystrophies miRNAs (myoMirs), which are associated. In contrast, similar dysregulation direction was found for 13 miRNAs that are common between OPMD and aging muscles. A significant age-association (p < 0.05) was found for 17 OPMD-deregulated miRNAs (13.4%), whereas in controls, only six miRNAs (1.4%) showed a significant age-association, suggesting that miRNA expression in OPMD is highly age-associated. miRNA expression in biofluids revealed that OPMD-associated deregulation in saliva was similar to that in muscles, but not in serum. The same as in muscle, miRNA expression levels in saliva were also found to be associated with age (p < 0.05). Moreover, the majority of OPMD-miRNAs were found to be associated with dysphagia as an initial symptom. We suggest that levels of specific miRNAs in saliva can mark muscle degeneration in general and dysphagia in OPMD.

Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging

Artificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decision-making to improve patient outcomes. Imaging and radiomics play an increasingly important role in these models. This review summarizes recent developments in the field of radiomics for AI in head and neck cancer. Prediction models for oncologic outcomes, treatment toxicity, and pathological findings have all been created. Exploratory studies are promising; however, validation studies that demonstrate consistency, reproducibility, and prognostic impact remain uncommon. Prospective clinical trials with standardized procedures are required for clinical translation.

A Two-Dimensional Affinity Capture and Separation Mini-Platform for the Isolation, Enrichment, and Quantification of Biomarkers and Its Potential Use for Liquid Biopsy

Biomarker detection for disease diagnosis, prognosis, and therapeutic response is becoming increasingly reliable and accessible. Particularly, the identification of circulating cell-free chemical and biochemical substances, cellular and subcellular entities, and extracellular vesicles has demonstrated promising applications in understanding the physiologic and pathologic conditions of an individual. Traditionally, tissue biopsy has been the gold standard for the diagnosis of many diseases, especially cancer. More recently, liquid biopsy for biomarker detection has emerged as a non-invasive or minimally invasive and less costly method for diagnosis of both cancerous and non-cancerous diseases, while also offering information on the progression or improvement of disease. Unfortunately, the standardization of analytical methods to isolate and quantify circulating cells and extracellular vesicles, as well as their extracted biochemical constituents, is still cumbersome, time-consuming, and expensive. To address these limitations, we have developed a prototype of a portable, miniaturized instrument that uses immunoaffinity capillary electrophoresis (IACE) to isolate, concentrate, and analyze cell-free biomarkers and/or tissue or cell extracts present in biological fluids. Isolation and concentration of analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. When compared to other existing methods, the process of this affinity capture, enrichment, release, and separation of one or a panel of biomarkers can be carried out on-line with the advantages of being rapid, automated, and cost-effective. Additionally, it has the potential to demonstrate high analytical sensitivity, specificity, and selectivity. As the potential of liquid biopsy grows, so too does the demand for technical advances. In this review, we therefore discuss applications and limitations of liquid biopsy and hope to introduce the idea that our affinity capture-separation device could be used as a form of point-of-care (POC) diagnostic technology to isolate, concentrate, and analyze circulating cells, extracellular vesicles, and viruses.

MicroRNAs in endometriosis: biological function and emerging biomarker candidates†

MicroRNAs (miRNAs), a class of small noncoding RNA molecules, have been recognized as key post-transcriptional regulators associated with a multitude of human diseases. Global expression profiling studies have uncovered hundreds of miRNAs that are dysregulated in several diseases, and yielded many candidate biomarkers. This review will focus on miRNAs in endometriosis, a common chronic disease affecting nearly 10% of reproductive-aged women, which can cause pelvic pain, infertility, and a myriad of other symptoms. Endometriosis has delayed time to diagnosis when compared to other chronic diseases, as there is no current accurate, easily accessible, and noninvasive tool for diagnosis. Specific miRNAs have been identified as potential biomarkers for this disease in multiple studies. These and other miRNAs have been linked to target genes and functional pathways in disease-specific pathophysiology. Highlighting investigations into the roles of tissue and circulating miRNAs in endometriosis, published through June 2018, this review summarizes new connections between miRNA expression and the pathophysiology of endometriosis, including impacts on fertility. Future applications of miRNA biomarkers for precision medicine in diagnosing and managing endometriosis treatment are also discussed.

Macromolecular biomarkers of chronic obstructive pulmonary disease in exhaled breath condensate

Biomarkers provide important diagnostic and prognostic information on heterogeneous diseases such as chronic obstructive pulmonary disease (COPD). However, finding a suitable specimen for clinical analysis of biomarkers for COPD is challenging. Exhaled breath condensate (EBC) sampling is noninvasive, rapid, cost-effective and easily repeatable. EBC sampling has also provided recent progress in the identification of biological macromolecules, such as lipids, proteins and DNA in EBC samples, which has increased its utility for clinical scientists. In this article, we review applications involving EBC sampling for the analysis of COPD biomarkers and discuss its future potential.

Pharmacodynamics of immune response biomarkers of interest for evaluation of treatment effects in bacterial infections

This mini-review discusses the pharmacodynamics of immune-related biomarkers in the area of bacterial infectious diseases that could be of interest from a pharmacokinetic (PK) and pharmacokinetic/pharmacodynamic (PK/PD) perspective in the evaluation of treatment effects. The host response to an infection is often poorly defined both in preclinical assessments and in clinical practice when it comes to characterisation of PK and PK/PD relationships. Through population modelling, the time courses and variability of immune response variables can be quantified. Incorporation of such biomarker information into PK and PK/PD models may guide the evaluation of individual response to treatment (right antibiotic, more antibiotic, less antibiotic) and when to stop treatment. Furthermore, translation of results from preclinical systems to clinical scenarios may be improved with the incorporation of biomarker information. Potential biomarkers for these purposes are discussed and a few modelling examples are provided.

Characteristics of registered clinical trials assessing treatments for COVID-19: a cross-sectional analysis

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has prompted many initiatives to identify safe and efficacious treatments, yet little is known regarding where early efforts have focused. We aimed to characterise registered clinical trials assessing drugs or plasma treatments for COVID-19.

DESIGN, SETTING AND PARTICIPANTS

Cross-sectional analysis of clinical trials for the treatment of COVID-19 that were registered in the USA or in countries contributing to the WHO's International Clinical Trials Registry Platform. Relevant trial entries of drugs or plasma were downloaded on 26 March 2020, deduplicated, verified with reviews of major medical journals and WHO websites and independently analysed by two reviewers.

MAIN OUTCOMES

Trial intervention, sponsorship, critical design elements and specified outcomes RESULTS: Overall, 201 clinical trials were registered for testing the therapeutic benefits of 92 drugs or plasma, including 64 in monotherapy and 28 different combinations. Only eight (8.7%) products or combinations involved new molecular entities. The other test therapies had a wide range of prior medical uses, including as antivirals, antimalarials, immunosuppressants and oncology treatments. In 152 trials (75.7%), patients were randomised to treatment or comparator, including 55 trials with some form of blinding and 97 open-label studies. The 49 (24.4%) of trials without a randomised design included 29 single armed studies and 20 trials with some comparison group. Most trial designs featured multiple endpoints. Clinical endpoints were identified in 134 (66.7%) of trials and included COVID-19 symptoms, death, recovery, required intensive care and hospital discharge. Clinical scales were being used in 33 (16.4%) trials, most often measures of oxygenation and critical illness. Surrogate endpoints or biomarkers were studied in 88 (42.3%) of trials, primarily assays of viral load. Although the trials were initiated in more than 17 countries or regions, 100 (49.8%) were registered in China and 78 (37.8%) in the USA. Registered trials increased rapidly, with the number of registered trials doubling from 1 March to 26 March 2020.

CONCLUSIONS

While accelerating morbidity and mortality from the COVID-19 pandemic has been paralleled by early and rapid clinical investigation, many trials lack features to optimise their scientific value. Global coordination and increased funding of high-quality research may help to maximise scientific progress in rapidly discovering safe and effective treatments.

An age-independent gene signature for monitoring acute rejection in kidney transplantation

Acute rejection (AR) remains a significant problem that negatively impacts long-term renal allograft survival. Numerous therapies are used to prevent AR that differ by center and recipient age. This variability confounds diagnostic methods. Methods: To develop an age-independent gene signature for AR effective across a broad array of immunosuppressive regimens, we compiled kidney transplant biopsy (n=1091) and peripheral blood (n=392) gene expression profiles from 12 independent public datasets. After removing genes differentially expressed in pediatric and adult patients, we compared gene expression profiles from biopsy and peripheral blood samples of patients with AR to those who were stable (STA), using Mann-Whitney U Tests with validation in independent testing datasets. We confirmed this signature in pediatric and adult patients (42 AR and 47 STA) from our institutional biorepository. Results: We identified a novel age-independent gene network that identified AR from both kidney and blood samples. We developed a 90-probe set signature targeting 76 genes that differentiated AR from STA and found an 8 gene subset (DIP2C, ENOSF1, FBXO21, KCTD6, PDXDC1, REXO2, HLA-E, and RAB31) that was associated with AR. Conclusion: We used publicly available datasets to create a gene signature of AR that identified AR irrespective of immunosuppression regimen or recipient age. This study highlights a novel model to screen and validate biomarkers across multiple treatment regimens.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Immuno-imaging of ICAM-1 in tumours by SPECT

PURPOSE

Molecular imaging of cancer cells' reaction to radiation damage can provide a non-invasive measure of tumour response to treatment. The cell surface glycoprotein ICAM-1 (CD54) was identified as a potential radiation response marker. SPECT imaging using an 111In-radiolabelled anti-ICAM-1 antibody was explored.

METHODS

PSN-1 cells were irradiated (10 Gy), and protein expression changes were investigated using an antibody array on cell lysates 24 h later. Results were confirmed by western blot, flow cytometry and immunofluorescence. We confirmed the affinity of an 111In-labelled anti-ICAM-1 antibody in vitro, and in vivo, in PSN-1-xenograft bearing mice. The xenografts were irradiated (0 or 10 Gy), and [111In]In-anti-ICAM-1 SPECT/CT images were acquired 24, 48 and 72 h after intravenous administration.

RESULTS

ICAM-1 was identified as a potential marker of radiation treatment using an antibody array in PSN-1 cell lysates following irradiation, showing a significant increase in ICAM-1 signal compared to non-irradiated cells. Western blot and immunohistochemistry confirmed this upregulation, with an up to 20-fold increase in ICAM-1 signal. Radiolabelled anti-ICAM-1 bound to ICAM-1 expressing cells with good affinity (Kd = 24.0 ± 4.0 nM). [111In]In-anti-ICAM-1 uptake in tumours at 72 h post injection was approximately 3-fold higher than non-specific isotype-matched [111In]In-mIgG2a control (19.3 ± 2.5%ID/g versus 6.3 ± 2.2%ID/g, P = 0.0002). However, ICAM1 levels, and [111In]In-anti-ICAM-1 uptake in tumours was no different after irradiation (uptake 9.2%ID/g versus 14.8%ID/g). Western blots of the xenograft lysates showed no significant differences, confirming these results.

CONCLUSION

Imaging of ICAM-1 is feasible in mouse models of pancreatic cancer. Although ICAM-1 is upregulated post-irradiation in in vitro models of pancreatic cancer, it shows little change in expression in an in vivo mouse xenograft model.

Determining acute complicated and uncomplicated appendicitis using serum and urine biomarkers: interleukin-6 and neutrophil gelatinase-associated lipocalin

PURPOSE

The study aim is to determine whether serum and urine interleukin-6 (IL-6) and neutrophil gelatinase-associated lipocalin (NGAL) can be included in the early diagnostic algorithm for pediatric appendicitis.

METHODS

Prospective single-center cohort study included 92 children divided into control, acute complicated appendicitis (AcA) and acute uncomplicated appendicitis (AnA) groups. Serum and urine samples were assayed for IL-6 and NGAL preoperatively, and on the second and fifth postoperative days. Intraoperative and bacteriological findings divided the appendicitis patients.

RESULTS

Average serum biomarker levels were higher in appendicitis patients versus the control, and the following values were produced via receiver operating characteristic (ROC) analysis. NGAL and IL-6 cutoff values were 113.95 ng/ml and 24.64 pg/ml, respectively, NGAL had 68.3% sensitivity and 65.5% specificity, while IL-6 had 72.6% and 86.2%. Comparing AcA and AnA, IL-6 was the only biomarker of significance yielding 77.4% sensitivity and 58.1% specificity with a 26.43 pg/ml cutoff value. Urine biomarkers were non-specific in differentiation appendicitis severity and ultimately, between infectious and non-infectious disease.

CONCLUSION

Although NGAL provided measurable useful diagnostic information in evaluating children for appendicitis, its values were not sufficient for appendicitis severity. Serum IL-6 remains a strong biomarker for suspected acute appendicitis and has promising results predicting its severity.

Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma

The threat of Hepatocellular Carcinoma (HCC) is a growing problem, with incidence rates anticipated to near double over the next two decades. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis (CIRR) to better understand the mechanistic differences between HCC and CIRR. Through pathway and network analysis, we are able to take a systems biology approach to conduct multi-omic analysis of transcriptomic, glycoproteomic, and metabolomic data acquired through various platforms. As a result, we are able to identify the FXR/RXR Activation pathway as being represented by molecules spanning multiple molecular compartments in these samples. Specifically, serum metabolites deoxycholate and chenodeoxycholic acid and serum glycoproteins C4A/C4B, KNG1, and HPX are biomarker candidates identified from this analysis that are of interest for future targeted studies. These results demonstrate the integrative power of multi-omic analysis to prioritize clinically and biologically relevant biomarker candidates that can increase understanding of molecular mechanisms driving HCC and make an impact in patient care.

Prospects for incorporation of epigenetic biomarkers in human health and environmental risk assessment of chemicals

Epigenetic mechanisms have gained relevance in human health and environmental studies, due to their pivotal role in disease, gene × environment interactions and adaptation to environmental change and/or contamination. Epigenetic mechanisms are highly responsive to external stimuli and a wide range of chemicals has been shown to determine specific epigenetic patterns in several organisms. Furthermore, the mitotic/meiotic inheritance of such epigenetic marks as well as the resulting changes in gene expression and cell/organismal phenotypes has now been demonstrated. Therefore, epigenetic signatures are interesting candidates for linking environmental exposures to disease as well as informing on past exposures to stressors. Accordingly, epigenetic biomarkers could be useful tools in both prospective and retrospective risk assessment but epigenetic endpoints are currently not yet incorporated into risk assessments. Achieving a better understanding on this apparent impasse, as well as identifying routes to promote the application of epigenetic biomarkers within environmental risk assessment frameworks are the objectives of this review. We first compile evidence from human health studies supporting the use of epigenetic exposure-associated changes as reliable biomarkers of exposure. Then, specifically focusing on environmental science, we examine the potential and challenges of developing epigenetic biomarkers for environmental fields, and discuss useful organisms and appropriate sequencing techniques to foster their development in this context. Finally, we discuss the practical incorporation of epigenetic biomarkers in the environmental risk assessment of chemicals, highlighting critical data gaps and making key recommendations for future research within a regulatory context.

RASSF10 is frequently epigenetically inactivated in kidney cancer and its knockout promotes neoplasia in cancer prone mice

Kidney cancer incidences are rising globally, thereby fueling the demand for targeted therapies and precision medicine. In our previous work, we have identified and characterized the Ras-Association Domain Family encoding ten members that are often aberrantly expressed in human cancers. In this study, we created and analyzed the Rassf10 knockout mice. Here we show that Rassf10 haploinsufficiency promotes neoplasia formation in two established mouse cancer models (Rassf1A^-/- and p53^-/-). Haploinsufficient Rassf10 knockout mice were significantly prone to various diseases including lymphoma (Rassf1A^-/- background) and thymoma (p53^-/- background). Especially Rassf10^-/- and p53-deficient mice exhibited threefold increased rates of kidney cysts compared with p53^-/- controls. Moreover, we observed that in human kidney cancer, RASSF10 is frequently epigenetically inactivated by its CpG island promoter hypermethylation. Primary tumors of renal clear cell and papillary cell carcinoma confirmed that RASSF10 methylation is associated with decreased expression in comparison to normal kidney tissue. In independent data sets, we could validate that RASSF10 inactivation clinically correlated with decreased survival and with progressed disease state of kidney cancer patients and polycystic kidney size. Functionally, we revealed that the loss of Rassf10 was significantly associated with upregulation of KRAS signaling and MYC expression. In summary, we could show that Rassf10 functions as a haploinsufficient tumor suppressor. In combination with other markers, RASSF10 silencing can serve as diagnostic and prognostic cancer biomarker in kidney diseases.

Sputum microbiome profiling in COPD: beyond singular pathogen detection

Culture-independent microbial sequencing techniques have revealed that the respiratory tract harbours a complex microbiome not detectable by conventional culturing methods. The contribution of the microbiome to chronic obstructive pulmonary disease (COPD) pathobiology and the potential for microbiome-based clinical biomarkers in COPD are still in the early phases of investigation. Sputum is an easily obtainable sample and has provided a wealth of information on COPD pathobiology, and thus has been a preferred sample type for microbiome studies. Although the sputum microbiome likely reflects the respiratory microbiome only in part, there is increasing evidence that microbial community structure and diversity are associated with disease severity and clinical outcomes, both in stable COPD and during the exacerbations. Current evidence has been limited to mainly cross-sectional studies using 16S rRNA gene sequencing, attempting to answer the question ‘who is there?’ Longitudinal studies using standardised protocols are needed to answer outstanding questions including differences between sputum sampling techniques. Further, with advancing technologies, microbiome studies are shifting beyond the examination of the 16S rRNA gene, to include whole metagenome and metatranscriptome sequencing, as well as metabolome characterisation. Despite being technically more challenging, whole-genome profiling and metabolomics can address the questions ‘what can they do?’ and ‘what are they doing?’ This review provides an overview of the basic principles of high-throughput microbiome sequencing techniques, current literature on sputum microbiome profiling in COPD, and a discussion of the associated limitations and future perspectives.

Osteopontin in Vascular Disease

Inflammatory cytokines are necessary for an acute response to injury and the progressive healing process. However, when this acute response does not resolve and becomes chronic, the same proteins that once promoted healing then contribute to chronic inflammatory pathologies, such as atherosclerosis. OPN (Osteopontin) is a secreted matricellular cytokine that signals through integrin and CD44 receptors, is highly upregulated in acute and chronic inflammatory settings, and has been implicated in physiological and pathophysiologic processes. Evidence from the literature suggests that OPN may fit within the Goldilocks paradigm with respect to cardiovascular disease, where acute increases are protective, attenuate vascular calcification, and promote postischemic neovascularization. In contrast, chronic increases in OPN are clinically associated with an increased risk for a major adverse cardiovascular event, and OPN expression is a strong predictor of cardiovascular disease independent of traditional risk factors. With the recent finding that humans express multiple OPN isoforms as the result of alternative splicing and that these isoforms have distinct biologic functions, future studies are required to determine what OPN isoform(s) are expressed in the setting of vascular disease and what role each of these isoforms plays in vascular disease progression. This review aims to discuss our current understanding of the role(s) of OPN in vascular disease pathologies using evidence from in vitro, animal, and clinical studies. Where possible, we discuss what is known about OPN isoform expression and our understanding of OPN isoform contributions to cardiovascular disease pathologies.

Epigenetic therapy of novel tumour suppressor ZAR1 and its cancer biomarker function

Background

Cancer still is one of the leading causes of death and its death toll is predicted to rise further. We identified earlier the potential tumour suppressor zygote arrest 1 (ZAR1) to play a role in lung carcinogenesis through its epigenetic inactivation.

Results

We are the first to report that ZAR1 is epigenetically inactivated not only in lung cancer but also across cancer types, and ZAR1 methylation occurs across its complete CpG island. ZAR1 hypermethylation significantly correlates with its expression reduction in cancers. We are also the first to report that ZAR1 methylation and expression reduction are of clinical importance as a prognostic marker for lung cancer and kidney cancer. We further established that the carboxy (C)-terminally present zinc-finger of ZAR1 is relevant for its tumour suppression function and its protein partner binding associated with the mRNA/ribosomal network. Global gene expression profiling supported ZAR1's role in cell cycle arrest and p53 signalling pathway, and we could show that ZAR1 growth suppression was in part p53 dependent. Using the CRISPR-dCas9 tools, we were able to prove that epigenetic editing and reactivation of ZAR1 is possible in cancer cell lines.

Conclusion

ZAR1 is a novel cancer biomarker for lung and kidney, which is epigenetically silenced in various cancers by DNA hypermethylation. ZAR1 exerts its tumour suppressive function in part through p53 and through its zinc-finger domain. Epigenetic therapy can reactivate the ZAR1 tumour suppressor in cancer.

Biomarkers in Stress Related Diseases/Disorders: Diagnostic, Prognostic, and Therapeutic Values

Various internal and external factors negatively affect the homeostatic equilibrium of organisms at the molecular to the whole-body level, inducing the so-called state of stress. Stress affects an organism's welfare status and induces energy-consuming mechanisms to combat the subsequent ill effects; thus, the individual may be immunocompromised, making them vulnerable to pathogens. The information presented here has been extensively reviewed, compiled, and analyzed from authenticated published resources available on Medline, PubMed, PubMed Central, Science Direct, and other scientific databases. Stress levels can be monitored by the quantitative and qualitative measurement of biomarkers. Potential markers of stress include thermal stress markers, such as heat shock proteins (HSPs), innate immune markers, such as Acute Phase Proteins (APPs), oxidative stress markers, and chemical secretions in the saliva and urine. In addition, stress biomarkers also play critical roles in the prognosis of stress-related diseases and disorders, and therapy guidance. Moreover, different components have been identified as potent mediators of cardiovascular, central nervous system, hepatic, and nephrological disorders, which can also be employed to evaluate these conditions precisely, but with stringent validation and specificity. Considerable scientific advances have been made in the detection, quantitation, and application of these biomarkers. The present review describes the current progress of identifying biomarkers, their prognostic, and therapeutic values.

Biomarkers in Stress Related Diseases/Disorders: Diagnostic, Prognostic, and Therapeutic Values

Various internal and external factors negatively affect the homeostatic equilibrium of organisms at the molecular to the whole-body level, inducing the so-called state of stress. Stress affects an organism's welfare status and induces energy-consuming mechanisms to combat the subsequent ill effects; thus, the individual may be immunocompromised, making them vulnerable to pathogens. The information presented here has been extensively reviewed, compiled, and analyzed from authenticated published resources available on Medline, PubMed, PubMed Central, Science Direct, and other scientific databases. Stress levels can be monitored by the quantitative and qualitative measurement of biomarkers. Potential markers of stress include thermal stress markers, such as heat shock proteins (HSPs), innate immune markers, such as Acute Phase Proteins (APPs), oxidative stress markers, and chemical secretions in the saliva and urine. In addition, stress biomarkers also play critical roles in the prognosis of stress-related diseases and disorders, and therapy guidance. Moreover, different components have been identified as potent mediators of cardiovascular, central nervous system, hepatic, and nephrological disorders, which can also be employed to evaluate these conditions precisely, but with stringent validation and specificity. Considerable scientific advances have been made in the detection, quantitation, and application of these biomarkers. The present review describes the current progress of identifying biomarkers, their prognostic, and therapeutic values.

A Simulation Study Comparing Different Statistical Approaches for the Identification of Predictive Biomarkers

Identification of relevant biomarkers that are associated with a treatment effect is one requirement for adequate treatment stratification and consequently to improve health care by administering the best available treatment to an individual patient. Various statistical approaches were proposed that allow assessing the interaction between a continuous covariate and treatment. Nevertheless, categorization of a continuous covariate, e.g., by splitting the data at the observed median value, appears to be very prevalent in practice. In this article, we present a simulation study considering data as observed in a randomized clinical trial with a time-to-event outcome performed to compare properties of such approaches, namely, Cox regression with linear interaction, Multivariable Fractional Polynomials for Interaction (MFPI), Local Partial-Likelihood Bootstrap (LPLB), and the Subpopulation Treatment Effect Pattern Plot (STEPP) method, and of strategies based on categorization of continuous covariates (splitting the covariate at the median, splitting at quartiles, and using an "optimal" split by maximizing a corresponding test statistic). In different scenarios with no interactions, linear interactions or nonlinear interactions, type I error probability and the power for detection of a true covariate-treatment interaction were estimated. The Cox regression approach was more efficient than the other methods for scenarios with monotonous interactions, especially when the number of observed events was small to moderate. When patterns of the biomarker-treatment interaction effect were more complex, MFPI and LPLB performed well compared to the other approaches. Categorization of data generally led to a loss of power, but for very complex patterns, splitting the data into multiple categories might help to explore the nature of the interaction effect. Consequently, we recommend application of statistical methods developed for assessment of interactions between continuous biomarkers and treatment instead of arbitrary or data-driven categorization of continuous covariates.

Are innovation and new technologies in precision medicine paving a new era in patients centric care?

Healthcare is undergoing a transformation, and it is imperative to leverage new technologies to generate new data and support the advent of precision medicine (PM). Recent scientific breakthroughs and technological advancements have improved our understanding of disease pathogenesis and changed the way we diagnose and treat disease leading to more precise, predictable and powerful health care that is customized for the individual patient. Genetic, genomics, and epigenetic alterations appear to be contributing to different diseases. Deep clinical phenotyping, combined with advanced molecular phenotypic profiling, enables the construction of causal network models in which a genomic region is proposed to influence the levels of transcripts, proteins, and metabolites. Phenotypic analysis bears great importance to elucidat the pathophysiology of networks at the molecular and cellular level. Digital biomarkers (BMs) can have several applications beyond clinical trials in diagnostics-to identify patients affected by a disease or to guide treatment. Digital BMs present a big opportunity to measure clinical endpoints in a remote, objective and unbiased manner. However, the use of "omics" technologies and large sample sizes have generated massive amounts of data sets, and their analyses have become a major bottleneck requiring sophisticated computational and statistical methods. With the wealth of information for different diseases and its link to intrinsic biology, the challenge is now to turn the multi-parametric taxonomic classification of a disease into better clinical decision-making by more precisely defining a disease. As a result, the big data revolution has provided an opportunity to apply artificial intelligence (AI) and machine learning algorithms to this vast data set. The advancements in digital health opportunities have also arisen numerous questions and concerns on the future of healthcare practices in particular with what regards the reliability of AI diagnostic tools, the impact on clinical practice and vulnerability of algorithms. AI, machine learning algorithms, computational biology, and digital BMs will offer an opportunity to translate new data into actionable information thus, allowing earlier diagnosis and precise treatment options. A better understanding and cohesiveness of the different components of the knowledge network is a must to fully exploit the potential of it.

Plasma CADM1 promoter hypermethylation and D-dimer as novel metastasis predictors of cervical cancer

AIM

Cervical cancer (CC) is the fourth malignant tumor in women worldwide. The metastasis is still the major reason for the treatment failures of most CC patients. Cell adhesion molecule 1 (CADM1) promoter methylation and plasma D-dimer levels have been reported to be increased in many types of cancers. The purpose of this study was to investigate the value of combinatorial assay of plasma CADM1 promoter hypermethylation and D-dimer as a metastasis marker in CC.

METHODS

Two hundred and ninety-two patients with newly diagnosed cervical diseases and 70 healthy women were enrolled. A validation set comprised 36 Stage I CC patients and followed for 3 years. Plasma CADM1 promoter methylation and D-dimer levels were detected.

RESULTS

The total coincidence rate of CADM1 promoter methylation status was 93.3% between 45 pair-matched tissue and plasma samples. Plasma CADM1 methylation levels in CC patients were higher than other benign disease groups (P = 0.000). Plasma CADM1 methylation levels had statistically differences between CC patients with and without lymph node metastasis (P = 0.049) or in CC patients with and without distant metastasis (P = 0.000). Similarly, plasma D-dimer levels in CC patients were higher than other benign disease groups (P < 0.05). D-dimer levels were only statistically different between CC patients with and without distant metastasis (P = 0.003). Combined assay of the two parameters for metastasis prediction has high sensitivity (80.4%) and specificity (90.5%).

CONCLUSION

Combinatorial assay of plasma CADM1 methylation and D-dimer is a promising metastasis marker in cervical cancer.