Next-generation Diagnostics Research Articles

EPCT-06. PRECISION ONCOLOGY IN THE PEDIATRIC TARGETED THERAPY 2.0 PROGRAM

IntroductionPrecise diagnoses and robust detection of actionable alterations is required for individualized treatments. By using extended molecular diagnostics, the Pediatric Targeted Therapy (PTT) 2.0 program aims at the improvement of diagnostic accuracy and detection of actionable alterations for pediatric high-risk patients. The impact of these analyses on clinical management is reported. MethodsPediatric patients with relapsed or progressive tumors after standard of care treatment were included, independent of histological diagnosis. Formalin fixed paraffin embedded material and a blood sample for germline correction were requested. DNA methylation array, targeted gene panel sequencing (130 genes), RNA and Sanger sequencing in selected cases, and immunohistochemistry (IHC) of selected markers (pERK, pAKT, pS6, PD-L1) were performed. A questionnaire-based follow-up was used to determine the clinical impact of the analysis. ResultsWe enrolled n=263 patients from February 2017 to February 2019. Complete molecular analysis was possible for n=260 cases (99%). The most common entities were brain tumors (n=172/260, 65%). In brain tumors, DNA methylation array alone allowed robust diagnostic classification (score of >=0.9) in n=104/172 cases (60%). Actionable targets as detected by copy number calculation, gene panel sequencing, RNA sequencing and IHC were found in n=94/172 (55%) brain tumor cases. The most common actionable targets in brain tumors were MAPK (pERK, BRAF fusions, BRAF V600E), mTOR (pS6), PI3K (pAKT), CDK4/6 (CDKN2A/B loss), and immune checkpoints (PD-L1). Pathogenic germline alterations with clinical relevance were identified in n=12/172 brain tumor cases (6.9%) and were confirmed by Sanger sequencing, 5/12 (41%) of which were previously unknown. Clinical follow-up of subsequent treatment and outcome are ongoing. ConclusionThe combination of next-generation diagnostics such as methylation arrays and targeted sequencing in addition to selected IHC markers added robust information with regard to diagnosis and actionable alterations. The impact on clinical decision-making and on outcome is currently being evaluated.

Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2

BackgroundThe detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples.MethodsA virus panel based on the principle of biotinylated RNA baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2-positive samples. Libraries generated from complex samples were sequenced via generic HTS (without enrichment) and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted.ResultsThe VirBaits set consists of 177,471 RNA baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also points to the risk of cross-contamination between samples.ConclusionsThe VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector, or research question. The risk of cross-contamination needs to be taken into consideration. The application of the RNA-baits principle turned out to be user friendly, and even non-experts can easily use the VirBaits workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible as shown for SARS-CoV-2.6LZ7h-uA_P4fT4PgoREid-Video abstract

Recent Advancements in the Loading and Modification of Therapeutic Exosomes.

Exosomes have a rapid development of bio-nanoparticles for drug delivery and confluent advances in next-generation diagnostics, monitoring the progression of several diseases, and accurate guidance for therapy. Based on their prominent stability, cargo-carriage properties, stable circulating capability, and favorable safety profile, exosomes have great potential to regulate cellular communication by carrying variable cargoes into specific site. However, the specific loading strategies and modification methods for engineered exosomes to enhance the targeting ability are unclear. The clinical application of exosomes is still limited. In this review, we discuss both original and modified exosomes for loading specific therapeutic molecules (proteins, nucleic acids, and small molecules) and the design strategies used to target specific cells. This review can be used as a reference for further loading and modification strategies as well as for the therapeutic applications of exosomes.

Ophthalmic genetics in South America.

South America comprises of heterogeneous topographies, populations, and health care systems. Therefore, it is not surprising to see differences among the countries regarding expertise, education, and practices of ophthalmic genetics for patients with rare eye diseases. Nevertheless, common challenges such as limited genetics training in medical schools and among ophthalmologists, scarcity of diagnostic tools for phenotyping, and expensive genetic testing not covered by the public healthcare systems, are seen in all of them. Here, we provide a detailed report of the current status of ophthalmic genetics, described by the personal views of local ophthalmologists from Brazil, Colombia, Argentina, and Chile. By reporting our strengths and weaknesses as a region, we intend to highlight the need for guidelines on how to manage these patients aligned with public health policies. Our region contributes to research worldwide, with thousands of well diagnosed patients from a number of unique and genetically diverse populations. The constant expansion of ophthalmic genetics and molecular diagnostics requires us to join forces to collaborate across South America and with other countries to improve access to next-generation diagnostics and ultimately improve patient care.

Abstract IA01: Pediatric neuro-oncology: What’s next?

Abstract Based on recent discoveries and data integration in genomics and epigenomics, a lot more is known about the biology of childhood brain tumors today when compared to a decade ago. This has vastly benefitted brain tumor diagnostics, including classification and some predictive and prognostic biomarkers. Yet the gap between this newly defined diagnostic gold standard and routine clinical implementation largely remains to be bridged. Additionally, the cell of origin for a majority of brain tumor entities remains elusive. The increased granularity of understanding intertumor heterogeneity also comes with the challenge of accounting for this heterogeneity in our therapeutic approaches. Ever-smaller patient groups and, on the other hand, an ever-increasing portfolio of potentially available drugs, require a paradigm shift in how we run and evaluate preclinical and clinical trials. Academically rewarding proof-of-concept studies that are typically well published, which certainly have a different purpose and thus lack the rigor of thorough preclinical filtering (because they typically embark on one or two “representative” models, which certainly does not cover the heterogeneity of a disease by any means), should no longer be regarded “sufficient preclinical evidence” to justify a clinical trial. Thus, novel incentives and funding models for this “less academically attractive,” but highly patient-relevant studies need to be explored. Phase I trials just with the purpose of dose finding should not be carried without a path forward into efficacy testing. Drugs with no evidence for brain penetration should not “just” be tried in patients with brain tumors without even making the best effort to understand brain and tumor penetrance. Academic work-up of biologic material from every single patient being enrolled on a trial should be mandatory rather than “nice to have.” Hereditary cancer predisposition should no longer be ignored when it comes to treatment stratification. Reimbursement models for “next-generation diagnostics,” preclinical phase I and phase II studies, and academic clinical trials (focusing on combinations rather than monotherapies in end-stage disease) have to shift from traditional third-party funding to alternative funding models. If we do not manage to address this paradigm shift, high-risk brain tumor patients may still mostly die from their disease 10 years from now. Citation Format: Stefan M. Pfister. Pediatric neuro-oncology: What’s next? [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA01.

A methodology to standardize the development of FPGA-based high-performance DAQ and processing systems using OpenCL

Abstract The development of high-performance data acquisition (DAQ) and processing systems is crucial for the next-generation diagnostics used in big science experiments. In the ITER experiment, the instrumentation, control hardware, and software architecture selected for this type of application is called a fast controller. The core element of a fast controller is a chassis based on the use of the PCIe eXtension for Instrumentation (PXIe) or Micro Telecommunication Computing Architecture (MTCA). This paper presents a software framework named IRIO-OpenCL that was developed using the ITER CODAC Core System (CCS) Linux-based distribution, oriented toward the development of field-programmable gate array (FPGA)-based DAQ systems using OpenCL. State-of-the-art DAQ-FPGA systems are developed using hardware description languages (HDLs). The approach used in IRIO-OpenCL simplifies DAQ to enable the user to write C-like processing algorithms with OpenCL, minimizing the use of HDLs. The software has been implemented in C++ following ITER’s Nominal Device Support v3 (NDSv3) model that abstracts and generalizes the development of software device drivers and simplifies the interface with the Experimental Physics and Industrial Control System (EPICS). The framework has been validated in an ITER fast controller including an MTCA.4 chassis with an advanced mezzanine card (AMC) module using an Arria 10 FPGA from Intel FPGA and an FPGA mezzanine card (FMC) DAQ module from Analog Devices. The developed application solves the DAQ and processing problems associated with the neutron flux measurement and achieves a sampling rate of 1 GS/s using approximately 40 % of the FPGA resources. The methodology proposed in this paper reduces the development time of these systems while maintaining high performance.

Towards next-generation diagnostics for tuberculosis: identification of novel molecular targets by large-scale comparative genomics.

MotivationTuberculosis (TB) remains one of the main causes of death worldwide. The long and cumbersome process of culturing Mycobacterium tuberculosis complex (MTBC) bacteria has encouraged the development of specific molecular tools for detecting the pathogen. Most of these tools aim to become novel TB diagnostics, and big efforts and resources are invested in their development, looking for the endorsement of the main public health agencies. Surprisingly, no study has been conducted where the vast amount of genomic data available is used to identify the best MTBC diagnostic markers.ResultsIn this work, we used large-scale comparative genomics to identify 40 MTBC-specific loci. We assessed their genetic diversity and physiological features to select 30 that are good targets for diagnostic purposes. Some of these markers could be used to assess the physiological status of the bacilli. Remarkably, none of the most used MTBC markers is in our catalog. Illustrating the translational potential of our work, we develop a specific qPCR assay for quantification and identification of MTBC DNA. Our rational design of targeted molecular assays for TB could be used in many other fields of clinical and basic research.Availability and implementationThe database of non-tuberculous mycobacteria assemblies can be accessed at: 10.5281/zenodo.3374377.Supplementary information Supplementary data are available at Bioinformatics online.

Looking beyond the hype: Applied AI and machine learning in translational medicine.

Big data problems are becoming more prevalent for laboratory scientists who look to make clinical impact. A large part of this is due to increased computing power, in parallel with new technologies for high quality data generation. Both new and old techniques of artificial intelligence (AI) and machine learning (ML) can now help increase the success of translational studies in three areas: drug discovery, imaging, and genomic medicine. However, ML technologies do not come without their limitations and shortcomings. Current technical limitations and other limitations including governance, reproducibility, and interpretation will be discussed in this article. Overcoming these limitations will enable ML methods to be more powerful for discovery and reduce ambiguity within translational medicine, allowing data-informed decision-making to deliver the next generation of diagnostics and therapeutics to patients quicker, at lowered costs, and at scale.

Controlling the Bioreceptor Spatial Distribution at the Nanoscale for Single Molecule Counting in Microwell Arrays.

The ability to detect low concentrations of protein biomarkers is crucial for the early-stage detection of many diseases and therefore indispensable for improving diagnostic devices for healthcare. Here, we demonstrate that by integrating DNA nanotechnologies like DNA origami and aptamers, we can design innovative biosensing concepts for reproducible and sensitive detection of specific targets. DNA origami structures decorated with aptamers were studied as a novel tool to structure the biosensor surface with nanoscale precision in a digital detection bioassay, enabling control of the density, orientation, and accessibility of the bioreceptor to optimize the interaction between target and aptamer. DNA origami was used to control the spatial distribution of an in-house-generated aptamer on superparamagnetic microparticles, resulting in an origami-linked digital aptamer bioassay to detect the main peanut antigen Ara h1 with 2-fold improved signal-to-noise ratio and 15-fold improved limit of detection compared to a digital bioassay without DNA origami. Moreover, the sensitivity achieved was 4 orders of magnitude higher than commercially available and literature-reported enzyme-linked immunosorbent assay techniques. In conclusion, this novel and innovative approach to engineer biosensing interfaces will be of major interest to scientists and clinicians looking for new molecular insights and ultrasensitive detection of a broad range of targets, and, for the next generation of diagnostics.

Next Generation Precision Medicine: CRISPR-mediated Genome Editing for the Treatment of Neurodegenerative Disorders.

Despite significant advancements in the field of molecular neurobiology especially neuroinflammation and neurodegeneration, the highly complex molecular mechanisms underlying neurodegenerative diseases remain elusive. As a result, the development of the next generation neurotherapeutics has experienced a considerable lag phase. Recent advancements in the field of genome editing offer a new template for dissecting the precise molecular pathways underlying the complex neurodegenerative disorders. We believe that the innovative genome and transcriptome editing strategies offer an excellent opportunity to decipher novel therapeutic targets, develop novel neurodegenerative disease models, develop neuroimaging modalities, develop next-generation diagnostics as well as develop patient-specific precision-targeted personalized therapies to effectively treat neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, Huntington's disease, Amyotrophic lateral sclerosis, Frontotemporal dementia etc. Here, we review the latest developments in the field of CRISPR-mediated genome editing and provide unbiased futuristic insights regarding its translational potential to improve the treatment outcomes and minimize financial burden. However, despite significant advancements, we would caution the scientific community that since the CRISPR field is still evolving, currently we do not know the full spectrum of CRISPR-mediated side effects. In the wake of the recent news regarding CRISPR-edited human babies being born in China, we urge the scientific community to maintain high scientific and ethical standards and utilize CRISPR for developing in vitro disease in a dish model, in vivo testing in nonhuman primates and lower vertebrates and for the development of neurotherapeutics for the currently incurable neurodegenerative disorders. Graphical Abstract.

Programming Stimuli-Responsive Behavior into Biomaterials.

Stimuli-responsive materials undergo triggered changes when presented with specific environmental cues. These dynamic systems can leverage biological signals found locally within the body as well as exogenous cues administered with spatiotemporal control, providing powerful opportunities in next-generation diagnostics and personalized medicine. Here, we review the synthetic and strategic advances used to impart diverse responsiveness to a wide variety of biomaterials. Categorizing systems on the basis of material type, number of inputs, and response mechanism, we examine past and ongoing efforts toward endowing biomaterials with customizable sensitivity. We draw an analogy to computer science, whereby a stimuli-responsive biomaterial transduces a set of inputs into a functional output as governed by a user-specified logical operator. We discuss Boolean and non-Boolean operations, as well as the various chemical and physical modes of signal transduction. Finally, we examine current limitations and promising directions in the ongoing development of programmable stimuli-responsive biomaterials.

Toward multiomics-based next-generation diagnostics for precision medicine.

Our healthcare system is experiencing a paradigm shift to precision medicine, aiming at an early prediction of individual disease risks and targeted interventions. Whole-genome sequencing is currently gaining momentum, as it has the potential to capture all classes of genetic variation, thus providing a more complete picture of the individual's genetic makeup, which could be utilized in genetic testing; however, this will also lead to difficulties in interpreting the test results, necessitating careful integration of genomic data with other layers of information, both molecular multiomics measurements of epigenome, transcriptome, proteome, metabolome and even microbiome, as well as comprehensive information on diet, lifestyle and environment. Overall, the translation of patient-specific data into actionable diagnostic tools will be a challenging task, requiring expertise from multiple disciplines, secure data sharing in large reference databases and a strong computational infrastructure.

Molecular-level Antibody Repertoire Profiling and Engineering: Implications for Developing Next-generation Diagnostics, Therapeutics, and Vaccines

Molecular-level Antibody Repertoire Profiling and Engineering: Implications for Developing Next-generation Diagnostics, Therapeutics, and Vaccines

Next-generation diagnostics with CRISPR.

CRISPR-Cas biology promises rapid, accurate, and portable diagnostic tools

Application of nanotechnology in biosensors for enhancing pathogen detection.

Rapid detection and identification of pathogenic microorganisms is fundamental to minimizing the spread of infectious disease, and informing clinicians on patient treatment strategies. This need has led to the development of enhanced biosensors that utilize state of the art nanomaterials and nanotechnology, and represent the next generation of diagnostics. A primer on nanoscale biorecognition elements such as, nucleic acids, antibodies, and their synthetic analogs (molecular imprinted polymers), will be presented first. Next the application of various nanotechnologies for biosensor transduction will be discussed, along with the inherent nanoscale phenomenon that leads to their improved performance and capabilities in biosensor systems. A future outlook on characterization and quality assurance, nanotoxicity, and nanomaterial integration into lab-on-a-chip systems will provide the closing thoughts. This article is categorized under: Diagnostic Tools > Diagnostic Nanodevices Diagnostic Tools > Biosensing.

Targeting Biophysical Cues: a Niche Approach to Study, Diagnose, and Treat Cancer

Probing the biophysical properties of the tumor niche offers a new perspective in cancer mechanobiology, and supports the development of next-generation diagnostics and therapeutics for cancer, in particular for metastasis.

Harnessing Protease Activity to Improve Cancer Care

Proteolysis plays critical roles in normal and pathologic physiology; these enzymes are intricately involved in cancer progression and spread. Our understanding of protease function has advanced from nonspecific degrading enzymes to a modern appreciation of their diverse roles in posttranslational modification and signaling in a complex microenvironment. This new understanding has led to next-generation diagnostics and therapeutics that exploit protease activity in cancer. For diagnostics, protease activity may be measured as a biomarker of cancer, with wide-ranging utility from early detection to monitoring therapeutic response. Therapeutically, while broad inhibition of protease activity proved disappointing, new approaches that more specifically modulate proteases in concert with secondary targets might enable potent combination therapies. In addition, clinical evaluation is underway for tools that leverage protease activity to activate therapeutics, ranging from imaging agents that monitor surgical margins to immunotherapies with improved specificity. Technologies that interact with, measure, or modulate proteases are poised to improve cancer management on diagnostic and therapeutic fronts to realize the promise of precision medicine.

Detection of Diarrhea Etiology Among U.S. Military Personnel During Exercise Balikatan 2014, Philippines, Using TaqMan Array Cards.

Military personnel are vulnerable to diarrhea. Diarrheal disease is common when deployed for operations or exercise in developing countries. Although diarrheal disease is transient, cumulative time lost and medical asset can have a significant impact on military operations. Currently, diagnostics of diarrheal etiology typically relies on a mixture of conventional bacteriology, enzyme-linked immunosorbent assay, and polymerase chain reaction (PCR)-based methods including real-time PCR. These methods, however, can be time and labor intensive, although the identification of diarrheal etiology needs to be informative and rapid for treatment and prevention. Real-time PCR has been increasingly used to identify pathogens. Real-time PCR panels of common diarrheal pathogens have been developed, but several diarrheal pathogens are not included in the panel. An expanded and customizable panel to detect diarrhea etiology has been developed employing TaqMan Array Card (TAC) technology. TAC performs 384 real-time PCR reactions simultaneously. As currently configured for diarrheal disease by the University of Virginia, a maximum of 8 samples can be tested simultaneously with approximately 48 target pathogens per sample including bacteria, fungi, helminths, protozoan parasites, and viruses. TAC diarrheal disease panels have been successfully applied to detect pathogens in acute diarrheal stool samples from young children in several international multicenter diarrhea studies. In this study, TAC was applied to stool samples collected under an approved human use protocol from military personnel with acute diarrhea participating in the annual joint military exercise, Balikatan, between the Republic of the Philippines and the United States in 2014. Several established pathogen-specific real-time PCR detection assays were also performed in parallel for comparative purposes. TAC was applied to 7 stool samples. Campylobacter spp. was the most common diarrheal disease pathogen detected. Results from TAC matched 5 out of 6 pathogen specific real-time PCR assays. TAC required a total of 5-6 hours to complete all the procedures from nucleic acid extraction and data analysis, whereas a minimum of 18 hours and 4 hours are required for conventional bacteriology and enzyme-linked immunosorbent assay, respectively, per pathogen. With TAC, pathogen load can be estimated from the amount of nucleic acid present for each pathogen, which can be analyzed further to better determine pathogen attribution and to compare pathogen load between case and control samples. Unfortunately, such correlative analysis was not possible because of the limited sample size available in this study. A larger sample size is needed for further evaluation of TAC on a specific population set, including military personnel. Regardless, TAC was found to be a useful and functional diagnostic platform that is less time-consuming, easy to use with high reproducibility, and costs less per sample compared to the current typically employed methods. The successful application of TAC in acute diarrhea stool samples from a US military population in the Philippines demonstrates its versatility as a potential candidate for a next-generation diagnostics platform.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

African biomedical scientists and the promises of “big science”

An ongoing genomic revolution in biology has exponentially increased the rate, possibilities, scope and cost of biological research. Infectious disease genomics are often justified by the potential they have to ameliorate Africa’s disease burden. The molecular biology revolution that preceded genomic science widened the gap between the skill sets of many African biologists and their contemporaries elsewhere. Gap closure through genomics and the application of genomic data to health problems requires participation of, and leadership from, African scientists. However, few African scientists participate in genomics, and providing biological samples is their predominant contribution. Health-related applications are emerging from genomic activity for some infectious diseases that are endemic in Africa but not for many others. This article argues that the arrival of next-generation diagnostics, surveillance tools, drugs and vaccines could be accelerated by improving the nature and degree of participation of African scientists in genomic and post-genomic inquiry.