Use of genome-wide high-throughput technologies in biomarker development

In silico tools and databases for designing cancer immunotherapy

Immunotherapy is a rapidly growing therapy for cancer which have numerous benefits over conventional treatments like surgery, chemotherapy, and radiation. Overall survival of cancer patients has improved significantly due to the use of immunotherapy. It acts as a novel pillar for treating different malignancies from their primary to the metastatic stage. Recent preferments in high-throughput sequencing and computational immunology leads to the development of targeted immunotherapy for precision oncology. In the last few decades, several computational methods and resources have been developed for designing immunotherapy against cancer. In this review, we have summarized cancer-associated genomic, transcriptomic, and mutation profile repositories. We have also enlisted in silico methods for the prediction of vaccine candidates, HLA binders, cytokines inducing peptides, and potential neoepitopes. Of note, we have incorporated the most important bioinformatics pipelines and resources for the designing of cancer immunotherapy. Moreover, to facilitate the scientific community, we have developed a web portal entitled ImmCancer (https://webs.iiitd.edu.in/raghava/immcancer/), comprises cancer immunotherapy tools and repositories.

Preparation and evaluation of fluorescent poly(p-phenyleneethylene) covalently coated microspheres with reactive sites for bioconjugation

Fluorescent microspheres with reactive sites for interacting with biomolecules are greatly demanded in flow cytometry based suspension array. Aiming to develop a new method for preparing fluorescent microspheres, two poly(p-phenyleneethylene) (PPE) conjugated polymers (CPs) with pedant carboxylic groups were synthesized via Sonogashira coupling and followed with hydrolysis of ester groups; then the conjugated polymers were immobilized onto monodispersed amino-modified porous poly(glycidylmethacrylate) (APGMA) microspheres via coupling reaction between carboxylic and amino groups to give APGMA-CP fluorescent microspheres. The fluorescent microspheres were found to have good photo- and thermal stability as well as negligible influence from rigorous washing. The emission was uniform all across the inner and surface of the spheres. To evaluate the effectiveness of bioconjugation on the fluorescent microspheres, fluorescein isothiocyanate isomer I (FITC) labeled bovine serum albumin (BSA) (BSA-FITC) was chosen as the representative biomolecule to react with the fluorescent microspheres to give APGMA-CP-BSA-FITC. In the flow cytometry study, fluorescence compensation between the V500 and FITC detectors (receiving signals from fluorophores excited by 405 nm and 488 nm, respectively), to remove the interference between the emission of FITC and CPs, was realized using singly-stained microspheres. Finally, APGMA-CP-BSA-FITC microspheres were found to be double positive for CP and FITC with very high percentage (>95%), suggesting the bioconjugation is very effective. This study provides a facile method for simultaneous introduction of fluorescence and reactive sites onto the microspheres, which is very promising to be used as general strategy for fabricating fluorescence microspheres for application in high-throughput technology.

Diagnostics and Resistance Profiling of Bacterial Pathogens

Worldwide infectious disease is one of the leading causes of death. Despite improvements in technology and healthcare services, morbidity and mortality due to infections have remained unchanged over the past few decades. The high and increasing rate of antibiotic resistance is further aggravating the situation. Growing resistance hampers the use of conventional antibiotics, and substantial higher mortality rates are reported in patients given ineffective empiric therapy mainly due to resistance to the agents used. These infections cause suffering, incapacity, and death and impose an enormous financial burden on both healthcare systems and on society in general. The accelerating development of multidrug resistance is one of the greatest diagnostic and therapeutic challenges to modern medicine. The lack of new antibiotic options underscores the need for optimization of current diagnostics, therapies, and prevention of the spread of multidrug-resistant organisms. The so-called -omics technologies (genomics, transcriptomics, proteomics, and metabolomics) have yielded large-scale datasets that advanced the search for biomarkers of infectious diseases in the last decade. One can imagine that in the future the implementation of biomarker-driven molecular test systems will transform diagnostics of infectious diseases and will significantly accelerate the identification of the bacterial pathogens at the infected host site. Furthermore, molecular tests based on the identification of markers of antibiotic resistance will dramatically change resistance profiling. The replacement of culturing methods by molecular test systems for early diagnosis will provide the basis not only for a prompt and targeted therapy, but also for a much more effective stewardship of antibiotic agents and a reduction of the spread of multidrug resistance as well as the appearance of new antibiotic resistances.

Point-of-care testing and the control of infectious diseases

Point-of-care tests (POCTs) play an important role in bridging the gap between centralized laboratory diagnostics and peripheral healthcare service providers. Particularly in infectious diseases such as HIV/AIDS and TB where early detection is imperative to improve disease outcome, uptake of an accurate test that is simple, rapid and robust can significantly alter the epidemiology and control of the disease. However, a good POCT can only serve its full potential when adopted in a comprehensive programmatic context linking patients to on-site case management. Immunochromatographic lateral flow devices for detection of antibody or antigen currently dominate available POCTs, and development of such devices has relied on the discovery and optimization of definitive biomarkers suitable for such platforms. In the future, however, there will be an increasing need to develop cost-effective POCTs that address biomarkers that are well established in laboratory settings but are not currently amenable to point-of-care, such as molecular tests for drug resistance in TB and viral load in HIV and viral hepatitis.

Gene expression analysis in biomarker research and early drug development using function tested reverse transcription quantitative real-time PCR assays

The identification of new biomarkers is essential in the implementation of personalized health care strategies that offer new therapeutic approaches with optimized and individualized treatment. In support of hypothesis generation and testing in the course of our biomarker research an online portal and respective function-tested reverse transcription quantitative real-time PCR assays (RT-qPCR) facilitated the selection of relevant biomarker genes. We have established workflows applicable for convenient high throughput gene expression analysis in biomarker research with cell lines (in vitro studies) and xenograft mouse models (in vivo studies) as well as formalin-fixed paraffin-embedded tissue (FFPET) sections from various human research and clinical tumor samples. Out of 92 putative biomarker candidate genes selected in silico, 35 were shown to exhibit differential expression in various tumor cell lines. These were further analysed by in vivo xenograft mouse models, which identified 13 candidate genes including potential response prediction biomarkers and a potential pharmacodynamic biomarker. Six of these candidate genes were selected for further evaluation in FFPET samples, where optimized RNA isolation, reverse transcription and qPCR assays provided reliable determination of relative expression levels as precondition for differential gene expression analysis of FFPET samples derived from projected clinical studies. Thus, we successfully applied function tested RT-qPCR assays in our biomarker research for hypothesis generation with in vitro and in vivo models as well as for hypothesis testing with human FFPET samples. Hence, appropriate function-tested RT-qPCR assays are available in biomarker research accompanying the different stages of drug development, starting from target identification up to early clinical development. The workflow presented here supports the identification and validation of new biomarkers and may lead to advances in efforts to achieve the goal of personalized health care.

The role of metabolites and metabolomics in clinically applicable biomarkers of disease

Metabolomics allows the simultaneous and relative quantification of thousands of different metabolites within a given sample using sensitive and specific methodologies such as gas or liquid chromatography coupled to mass spectrometry, typically in discovery phases of studies. Biomarkers are biological characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathological processes or pharmacologic responses to a therapeutic intervention. Biomarkers are widely used in clinical practice for the diagnosis, assessment of severity and response to therapy in a number of clinical disease states. In human studies, metabolomics has been applied to define biomarkers related to prognosis or diagnosis of a disease or drug toxicity/efficacy and in doing so hopes to provide greater pathophysiological understanding of disease or therapeutic toxicity/efficacy. This review discusses the application of metabolomics in the discovery and subsequent application of biomarkers in the diagnosis and management of inborn errors of metabolism, cardiovascular disease and cancer. We critically appraise how novel biomarkers discovered through metabolomic analysis may be utilized in future clinical practice by addressing the following three fundamental questions: (1) Can the clinician measure them? (2) Do they add new information? (3) Do they help the clinician to manage patients? Although a number of novel biomarkers have been discovered through metabolomic studies of human diseases in the last decade, none have currently made the transition to routine use in clinical practice. Metabolites identified from these early studies will need to form the basis of larger, prospective, externally validated studies in clinical cohorts for their future use as biomarkers. At this stage, the absolute quantification of these biomarkers will need to be assessed epidemiologically, as will the ultimate deployment in the clinic via routine biochemistry, dip stick or similar rapid at- or near-patient care technologies.

Application of T cell-based transcriptomics to identify three candidate biomarkers for monitoring anti-TGFbetaR therapy

OBJECTIVES

The development of targeted drugs would greatly benefit from the simultaneous identification of biomarkers to determine the aspects of bioactivity, drug safety and efficacy, particularly when affecting receptor-signaling pathways. However, the establishment of appropriate systems to monitor drug-induced events requires an accessible surrogate tissue for functional read out.

METHODS

Therefore we present a universal platform based upon T cell-based gene expression profiling for the identification of biomarkers using the antitransforming growth factor beta receptor inhibitor LY2109761 as an example.

RESULTS

Our initial screen revealed 12 candidate genes specifically regulated in T cells by the inhibitor. In subsequent in-vitro and in-vivo analyses, the combined monitoring of independent gene regulation of three genes was established in peripheral blood mononuclear cells as novel pharmacodynamic candidate biomarkers for antitransforming growth factor beta receptor based therapies.

CONCLUSION

Overall, the proposed concept of biomarker identification can be easily adapted towards other drug candidates for whom gene regulation can be established in cellular components of peripheral blood.