Discovery and clinical translation of novel glaucoma biomarkers.
Ontology highlight
ABSTRACT:
SUBMITTER: Beykin G
PROVIDER: S-EPMC7796965 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Translating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study.We defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers.The most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more.It is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.
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Project description:Glaucoma is a neurodegenerative disease with heterogeneous causes that result in retinal ganglionic cell (RGC) death. The discovery of ocular antihypertensives has shifted glaucoma therapy, largely, from surgery to medical intervention. Indeed, several intraocular pressure (IOP)-lowering drugs, with different mechanisms of action and RGC protective property, have been developed.In this review, the authors discuss the main new class of kinase inhibitors used as glaucoma treatments, which lower IOP by enhancing drainage and/or lowering production of aqueous humor. The authors include novel inhibitors under preclinical evaluation and investigation for their anti-glaucoma treatment. Additionally, the authors look at treatments that are in clinics now and which may be available in the near future.Treatment of glaucoma remains challenging because the exact cause is yet to be delineated. Neuroprotection to the optic nerve head is undisputable. The novel Rho-associated kinase inhibitors have the capacity to lower IOP and provide optic nerve and RGC protection. In particular, the S-isomer of roscovitine has the capacity to lower IOP and provide neuroprotection. Combinations of selected drugs, which can provide maximal and sustained IOP-lowering effects as well as neuroprotection, are paramount to the prevention of glaucoma progression. In the near future, microRNA intervention may be considered as a potential therapeutic target.
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Project description:A total of 164 ccRCC patient’s specimens were used for microarray (n=12, tumor and corresponding normal tissue) or pyrosequencing (PSQ) analyses (n=152). From The Cancer Genome Atlas (TCGA) portal, microarray methylation profiles composed of 312 subjects with ccRCC were utilized (159 for gene selection and 153 for prognostic relevance). Using the methylation profiles from our and TCGA, tumor-specific hypermethylated genes were selected, and prognostic relevance of candidate markers were examined with TCGA data set and pyrosequencing analysis data from our ccRCC patients samples.
2019-12-15 | GSE92482 | GEO
Project description:The ability to predict how an individual patient will respond to a particular treatment is the ambitious goal of personalized medicine. The genetic make up of an individual has been shown to play a role in drug response. For pharmacogenomic studies, human lymphoblastoid cell lines (LCLs) comprise a useful model system for identifying genetic variants associated with pharmacologic phenotypes. The availability of extensive genotype data for many panels of LCLs derived from individuals of diverse ancestry allows for the study of genetic variants contributing to interethnic and interindividual variation in susceptibility to drugs. Many genome-wide association studies for drug-induced phenotypes have been performed in LCLs, often incorporating gene-expression data. LCLs are also being used in follow-up studies to clinical findings to determine how an associated variant functions to affect phenotype. This review describes the most recent pharmacogenomic findings made in LCLs, including the translation of some findings to clinical cohorts.
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Project description:Interindividual variability in drug efficacy and toxicity is a major challenge in clinical practice. Variations in drug pharmacokinetics (PKs) and pharmacodynamics (PDs) can be, in part, explained by polymorphic variants in genes encoding drug metabolizing enzymes and transporters (absorption, distribution, metabolism, and excretion) or in genes encoding drug receptors. Pharmacogenomics (PGx) has allowed the identification of predictive biomarkers of drug PKs and PDs and the current knowledge of genome-disease and genome-drug interactions offers the opportunity to optimize tailored drug therapy. High-throughput PGx genotyping, from targeted to more comprehensive strategies, allows the identification of PK/PD genotypes to be developed as clinical predictive biomarkers. However, a biomarker needs a robust process of validation followed by clinical-grade assay development and must comply to stringent regulatory guidelines. We here discuss the methodological challenges and the emerging technological tools in PGx biomarker discovery and validation, at the crossroad among molecular genetics, bioinformatics, and clinical medicine.
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Project description:Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked approximately 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forwards, genetic testing could enable precision medicine approaches by identifying subgroups of patients at increased risk of coronary artery disease or those with a specific driving pathophysiology in whom a therapeutic or preventive approach would be most useful.
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Project description:Purpose of review:This article summarizes the current studies on molecular biomarkers with potential implications in diagnosis, prognosis, and response to treatment in patients with glaucoma. Recent findings:Important advances have occurred in the understanding of the pathogenesis of glaucomatous neurodegeneration. Protein biomarkers associated with inflammatory, neurodegenerative, and other molecular pathways have been described in glaucoma patients in tear film, aqueous fluid, vitreous fluid, and serum, however, we are still far from having a clear picture of the whole molecular network that relates to the disease and its implications in clinical use. Summary:Although more studies are needed, current and emerging molecular biomarkers candidates in glaucoma may eventually transition into clinical use and contribute to outline the concept of precision medicine and precision health in glaucoma.
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Project description:Topical ophthalmic formulations of analogues of the endogenous arachidonic acid cyclooxygenase metabolite, PGF2α , are the standard of care treatment for the blinding disease glaucoma. These are the most potent and efficacious medical therapies for lowering intraocular pressure (IOP), the most important risk factor identified for disease progression. They have few side effects and offer the convenience of once-a-day dosing. It was initially believed that endogenous PGs raised IOP and caused substantial ocular surface adverse effects. However, carefully designed experiments demonstrated that esterification of the carboxylic acid afforded potent and efficacious topical ocular hypotensive activity. The final hurdle to be overcome was improvement of the side effect profile. A hypothesis was advanced that the IOP-lowering effect of PGF2α isopropyl ester was due to activation of its cognate PG-FP receptor, while side effects were largely due to promiscuous interaction with other PG receptors. This hypothesis was validated by modification of the ω chain (carbons 13-20) to a phenyl group. This provided the first marketed FP-class PG agonist analogue (FP-PGA) ocular hypotensive agent, latanoprost. Since the introduction of latanoprost into clinical medicine to lower and control IOP, a number of additional FP-PGAs have been discovered, characterized and marketed, including travoprost, tafluprost, unoprostone isopropyl ester and bimatoprost (an amide). LINKED ARTICLES: This article is part of a themed section on Eicosanoids 35 years from the 1982 Nobel: where are we now? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.8/issuetoc.
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Project description:Blood-based biomarkers for Alzheimer's disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%), specificity (>91%), and accuracy (>89%).
| S-EPMC4932164 | biostudies-literature
Project description:BackgroundBiomarkers and target-specific phenotypes are important to targeted drug design and individualized medicine, thus constituting an important aspect of modern pharmaceutical research and development. More and more, the discovery of relevant biomarkers is aided by in silico techniques based on applying data mining and computational chemistry on large molecular databases. However, there is an even larger source of valuable information available that can potentially be tapped for such discoveries: repositories constituted by research documents.ResultsThis paper reports on a pilot experiment to discover potential novel biomarkers and phenotypes for diabetes and obesity by self-organized text mining of about 120,000 PubMed abstracts, public clinical trial summaries, and internal Merck research documents. These documents were directly analyzed by the InfoCodex semantic engine, without prior human manipulations such as parsing. Recall and precision against established, but different benchmarks lie in ranges up to 30% and 50% respectively. Retrieval of known entities missed by other traditional approaches could be demonstrated. Finally, the InfoCodex semantic engine was shown to discover new diabetes and obesity biomarkers and phenotypes. Amongst these were many interesting candidates with a high potential, although noticeable noise (uninteresting or obvious terms) was generated.ConclusionsThe reported approach of employing autonomous self-organising semantic engines to aid biomarker discovery, supplemented by appropriate manual curation processes, shows promise and has potential to impact, conservatively, a faster alternative to vocabulary processes dependent on humans having to read and analyze all the texts. More optimistically, it could impact pharmaceutical research, for example to shorten time-to-market of novel drugs, or speed up early recognition of dead ends and adverse reactions.
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