Translational Research Settings Research Articles

Whole Blood Assay with Dual Co-Stimulation for Antigen-Specific Analysis of Host Immunity to Fungal and Viral Pathogens.

Rapid and resource-efficient sample processing, high throughput, and high robustness are critical for effective scientific and clinical application of advanced antigen-specific immunoassays. Traditionally, such immunoassays, especially antigen-specific T-cell analysis by flow cytometry or enzyme-linked immunosorbent spot assays, often rely on the isolation of peripheral blood mononuclear cells. This process is time-consuming, subject to many pre-analytic confounders, and requires large blood volumes. Whole blood-based assays provide a facile alternative with increased pre-analytic robustness and lower blood volume requirements. Furthermore, whole blood-based assays allow for the preservation of inter-cellular interactions that are not captured by assays using isolated cell subsets. Recently, a refined whole blood immunoassay with dual anti-CD28 and anti-CD49d co-stimulation for comprehensive analysis of both antigen-specific T-cell functions and complex intercellular interactions in response to various fungal and viral antigens has been proposed. This protocol provides guidance for the preparation of stimulation tubes, blood stimulation, and downstream sample processing for flow cytometry, cytokine secretion assays, and transcriptional analyses. This includes a validated and functionally equivalent, previously unpublished, low-volume protocol (250 µL) to make flow cytometric and cytokine-based T-cell monitoring more accessible for studies in pediatric patients or preclinical studies in small animals (e.g., mice). Altogether, these protocols provide a versatile toolbox for complex antigen-specific immune analysis in both clinical and translational research settings.

Metabolomics and cellular altered pathways in cancer biology: A review.

Cancer is a deadly disease that affects a cell's metabolism and surrounding tissues. Understanding the fundamental mechanisms of metabolic alterations in cancer cells would assist in developing cancer treatment targets and approaches. From this perspective, metabolomics is a great analytical tool to clarify the mechanisms of cancer therapy as well as a useful tool to investigate cancer from a distinct viewpoint. It is a powerful emerging technology that detects up to thousands of molecules in tissues and biofluids. Like other "-omics" technologies, metabolomics involves the comprehensive investigation of micromolecule metabolites and can reveal important details about the cancer state that is otherwise not apparent. Recent developments in metabolomics technologies have made it possible to investigate cancer metabolism in greater depth and comprehend how cancer cells utilize metabolic pathways to make the amino acids, nucleotides, and lipids required for tumorigenesis. These new technologies have made it possible to learn more about cancer metabolism. Here, we review the cellular and systemic effects of cancer and cancer treatments on metabolism. The current study provides an overview of metabolomics, emphasizing the current technologies and their use in clinical and translational research settings.

An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity.

In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.

The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

Polyphenol analysis in human milk by a rapid, cost-effective, and accurate micromethod: translational development.

To develop a rapid method for analysing polyphenols, which are potentially active antioxidants against neonatal oxidative stress, from small human milk (HM) volumes. Acid and alkaline extractions were compared using two dyes: Folin-Ciocalteu and Fast Blue BB. Linearity, sensitivity, recovery percentage, polyphenol content, precision, and stability were assessed in 14 HM samples and compared using the Kruskal-Wallis H test (p<0.05). The best technique was applied to 284 HM samples to determine their polyphenolic content and its association with maternal diet by multifactorial linear regression. Acidic extraction successfully recovered the gallic acid reference standard, whereas alkaline extraction overestimated it. Calibration curves for all methods were linear (R2>0.96) up to 500 mg/L. All bicarbonate-based Folin-Ciocalteu methods assayed were stable and repeatable, whereas Fast Blue BB-based variants were not. HM polyphenols (mean=94.68 mg/L) positively correlated to the dietary intake of hydroxycinnamic acids, the most consumed polyphenolic family in this population. A bicarbonate-based Folin-Ciocalteu micromethod allowed the accurate determination of polyphenols in HM, which might be useful for translational research settings and HM banks.

Topolink™: Advancing Cancer Genomics with a High-Resolution, High-Throughput Approach for Low Sequencing and Highly Sensitive Detection of Structural Variants

Despite numerous technological advances, including the widespread adoption of massively parallel genome sequencing, many clinically relevant cancer driver mutations go undetected. Additionally, even with the most comprehensive cancer profiling using a combination of whole genome and whole transcriptome sequencing, a driver mutation goes undetected in approximately 20% of cancers, making targeted treatment of these patients challenging. The reason for this gap in understanding is presumably two-fold: 1) current technologies do not have the required sensitivity for detection of the causative variants; or 2) causative variants are epigenetic or regulatory in nature, meaning the driving alteration does not result in a change to the core DNA sequence. An explanation for 1) is that structural variants (SVs) are particularly challenging to detect using shotgun-based approaches, since these depends on the presence of specific chimeric molecules within the library that directly span or bridge the breakpoint. Long-read technologies circumvent this limitation but have significant drawbacks with respect to cost and strict sample requirements. Another possibility is that standard sequencing - which results in hundreds or thousands of variants of unknown significance (VUS) - may in fact contain causative variants, but our understanding of function of these variants is limited. For 2), it is increasingly appreciated that epigenetic and chromatin topological features are fundamental in the gene regulation and disease. To address this gap in our understanding of cancer, we utilized TopoLink™ proximity ligation library protocol that yields high-quality, high-resolution, unbiased HiC libraries and that can be performed in under 8 hours. To our knowledge, TopoLink™ is the first and only assay of its kind. Proximity ligation offers enhanced sensitivity for detection of SVs, and the restriction enzyme-free digestion method ensures the uniform coverage needed for accurate detection of single nucleotide variations (SNVs) and copy number variants (CNVs). To our knowledge, TopoLink™ is the first and only assay combine the speed, throughput, and unbiased primary base coverage of WGS with the improved detection of large SVs in Hi-C data. Detection of SVs provides a critical basis for personalized therapies in hematological cancers. To test the ability of TopoLink™ to detect clinically relevant SVs, we used the BCR-ABL1 positive CML cell line K562 to determine the limit of detection of interchromosomal translocations. In addition, we calculated the sensitivity of SV detection relative to current industry-leading sequencing technologies using the breast carcinoma cell line HCC1187 gold standard. We noted enhanced sensitivity for SV detection for TopoLink™ relative to both long-read technologies and WGS. Using TopoLink™, sensitivity was greater than 95% at a genome coverage of less than 1x, whereas both long-read and WGS sensitivity drops below 95% sensitivity at approximately 10x genome coverage. Similarly, using hybridization capture of BCR-ABL1 in a TopoLink™ library of K562 cells reduced the required sequencing burden by 10-fold relative to standard shotgun approaches. Importantly, we demonstrate that TopoLink™ libraries maintain topological features consistent with biologically relevant topologically-associated domains (TADs) and chromatin loops, thus enabling insight into novel epigenetic cancer drivers. Therefore, we demonstrate TopoLink™ proximity ligation libraries as a complementary technique that offers enhanced sensitivity of clinically relevant structural variants, with the added benefit of improving discovery of novel epigenetic mechanisms. Finally, the reduced sequencing costs needed to detect clinically relevant SVs allows for improved diagnostics and personalized medicine in a clinical or translational research setting.

Abstract 4293: Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors

Abstract Conventional immunohistochemistry (IHC) is a standardized diagnostic technique used in tissue pathology. However, the capacity to label only one marker per tissue section is a critical limitation. Multiplex immunohistochemistry (mIHC) is a powerful imaging technique used in basic, translational research and clinical settings to simultaneously detect the expression of multiple epitopes in a single formalin-fixed paraffin-embedded (FFPE) tissue section, allowing for characterization and quantification of cells while maintaining their spatial location. This technique allows for a comprehensive view of the immune milieu, expression patterns, and interactions between cell types that can help elucidate the complexity of the tumor-immune microenvironment (TiME). Multiplex imaging has emerged as a powerful tool to better understand tumor progression, response or resistance to therapy, and potentially identify predictive biomarkers. However, this technique requires careful tissue considerations and generates enormous amounts of hierarchical data, including single cell marker expressions, locations, and shape features, resulting in complex and challenging analyses. We previously published a validated platform using nine matched primary and recurrent head and neck squamous cell carcinoma (HNSCC) sections stained sequentially with a panel of 29 antibodies identifying malignant tumor cells, and 17 distinct leukocyte lineages and their functional states1. Here, we have optimized and consolidated important considerations, including tissue quality and QC steps necessary for generating high quality data from multiplex imaging studies. We demonstrate strategies for a streamline analytic pipeline using our quantitative workflow developed to characterize immune cells and infiltration patterns within spatial compartments of solid tumors in FFPE tissues, and herein, provide strategies and resources to practically adapt and utilize our analytic mIHC pipeline. 1. Banik, G., et al., Methods Enzymol., 2020 Citation Format: Shamilene Sivagnanam, Courtney M. Betts, Nell Kirchberger, Konjit Betre, Lisa M. Coussens. Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4293.

Muscle stem cells get a new look: Dynamic cellular projections as sensors of the stem cell niche.

Cellular mechanisms whereby quiescent stem cells sense tissue injury and transition to an activated state are largely unknown. Quiescent skeletal muscle stem cells (MuSCs, also called satellite cells) have elaborate, heterogeneous projections that rapidly retract in response to muscle injury. They may therefore act as direct sensors of their niche environment. Retraction is driven by a Rac-to-Rho GTPase activity switch that promotes downstream MuSC activation events. These and other observations lead to several hypotheses: (1) projections are morphologically dynamic at quiescence, providing a surveillance function for muscle damage; (2) quiescent projection dynamics are regulated by the relative balance of Rac and Rho activities promoted by niche-derived cues; (3) projections, particularly their associated filopodia, sense tissue damage via changes to the biomechanical properties of the niche and/or detection of signaling cues released by damaged myofibers; and (4) the dynamic nature of projections results in a population of MuSCs with heterogeneous functional properties. These concepts may extend to other types of quiescent stem cells, as well as prove useful in translational research settings.

Slide-to-Slide Tissue Transfer and Array Assembly From Limited Samples for Comprehensive Molecular Profiling

Tissue microarrays (TMA) have become an important tool in high-throughput molecular profiling of tissue samples in the translational research setting. Unfortunately, high-throughput profiling in small biopsy specimens or rare tumor samples (eg, orphan diseases or unusual tumors) is often precluded owing to limited amounts of tissue. To overcome these challenges, we devised a method that allows tissue transfer and construction of TMAs from individual 2- to 5-μm sections for subsequent molecular profiling. We named the technique slide-to-slide (STS) transfer, and it requires a series of chemical exposures (so-called xylene-methacrylate exchange) in combination with rehydrated lifting, microdissection of donor tissues into multiple small tissue fragments (methacrylate-tissue tiles), and subsequent remounting on separate recipient slides (STS array slide). We developed the STS technique by assessing the efficacy and analytical performance using the following key metrics: (a) dropout rate, (b) transfer efficacy, (c) success rates using different antigen-retrieval methods, (d) success rates of immunohistochemical stains, (e) fluorescent in situ hybridization success rates, and (f) DNA and (g) RNA extraction yields from single slides, which all functioned appropriately. The dropout rate ranged from 0.7% to 6.2%; however, we applied the same STS technique successfully to fill these dropouts (“rescue” transfer). Hematoxylin and eosin assessment of donor slides confirmed a transfer efficacy of >93%, depending on the size of the tissue (range, 76%-100%). Fluorescent in situ hybridization success rates and nucleic acid yields were comparable with those of traditional workflows. In this study, we present a quick, reliable, and cost-effective method that offers the key advantages of TMAs and other molecular techniques—even when tissue is sparse. The perspectives of this technology in biomedical sciences and clinical practice are promising, given that it allows laboratories to create more data with less tissue.

OMIXCARE: OMICS technologies solved about 33% of the patients with heterogeneous rare neuro-developmental disorders and negative exome sequencing results and identified 13% additional candidate variants.

Purpose: Patients with rare or ultra-rare genetic diseases, which affect 350 million people worldwide, may experience a diagnostic odyssey. High-throughput sequencing leads to an etiological diagnosis in up to 50% of individuals with heterogeneous neurodevelopmental or malformation disorders. There is a growing interest in additional omics technologies in translational research settings to examine the remaining unsolved cases. Methods: We gathered 30 individuals with malformation syndromes and/or severe neurodevelopmental disorders with negative trio exome sequencing and array comparative genomic hybridization results through a multicenter project. We applied short-read genome sequencing, total RNA sequencing, and DNA methylation analysis, in that order, as complementary translational research tools for a molecular diagnosis. Results: The cohort was mainly composed of pediatric individuals with a median age of 13.7years (4years and 6months to 35years and 1month). Genome sequencing alone identified at least one variant with a high level of evidence of pathogenicity in 8/30 individuals (26.7%) and at least a candidate disease-causing variant in 7/30 other individuals (23.3%). RNA-seq data in 23 individuals allowed two additional individuals (8.7%) to be diagnosed, confirming the implication of two pathogenic variants (8.7%), and excluding one candidate variant (4.3%). Finally, DNA methylation analysis confirmed one diagnosis identified by genome sequencing (Kabuki syndrome) and identified an episignature compatible with a BAFopathy in a patient with a clinical diagnosis of Coffin-Siris with negative genome and RNA-seq results in blood. Conclusion: Overall, our integrated genome, transcriptome, and DNA methylation analysis solved 10/30 (33.3%) cases and identified a strong candidate gene in 4/30 (13.3%) of the patients with rare neurodevelopmental disorders and negative exome sequencing results.

Patient involvement in basic rheumatology research at Nijmegen: a three year’s responsive evaluation of added value, pitfalls and conditions for success

BackgroundEmpirical evidence for effective patient-researcher collaboration in basic research is lacking. This study aims to explore good working models and impact of patient involvement in basic rheumatology research and to identify barriers and facilitators.MethodA responsive evaluation of a three years’ participatory research project in a basic and translational laboratory research setting. Several working models for patient involvement were piloted and adapted if considered necessary. The study comprised surveys, interviews, training days, meeting reports, Q-sort exercises and field notes, and regular reflective team sessions with participant involvement. A qualitative analysis using thematic coding focused on impact, barriers and facilitators.ResultsThirteen patient research partners (PRPs) and fifteen basic researchers participated. PRPs experienced basic research as fascinating though complex to understand. Their initial role was mostly listening and asking questions. After several meetings equal and more meaningful relationships emerged. Researchers’ motivation increased by listening to patient stories. They learned about disease impact on daily life and to speak in understandable language. This enabled PRPs to learn about research and the pathogenesis of their disease. It inspired them to stay involved over a longer period. After three years, both parties preferred 1:1 contacts over collaboration in team meetings. A common language and respectful communication were important facilitators. Limitations were the complexity of disease processes for patients and the time commitment for researchers. Impact was reported as a sincere dialogue with multiple advantages for patients and researchers, and to a lesser extent than expected on the research process and outcomes.ConclusionPatient involvement contributes to motivating young scientists in performing basic research projects. Patients and researchers valued the benefits of long-term one-on-one collaboration. These benefits outweigh the lack of direct impact on basic research goals and performance.A plain language summary of the abstractis available (as) online Additional file 1.

Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting.

Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.

Development of a standardized and validated flow cytometry approach for monitoring of innate myeloid immune cells in human blood.

Innate myeloid cell (IMC) populations form an essential part of innate immunity. Flow cytometric (FCM) monitoring of IMCs in peripheral blood (PB) has great clinical potential for disease monitoring due to their role in maintenance of tissue homeostasis and ability to sense micro-environmental changes, such as inflammatory processes and tissue damage. However, the lack of standardized and validated approaches has hampered broad clinical implementation. For accurate identification and separation of IMC populations, 62 antibodies against 44 different proteins were evaluated. In multiple rounds of EuroFlow-based design-testing-evaluation-redesign, finally 16 antibodies were selected for their non-redundancy and separation power. Accordingly, two antibody combinations were designed for fast, sensitive, and reproducible FCM monitoring of IMC populations in PB in clinical settings (11-color; 13 antibodies) and translational research (14-color; 16 antibodies). Performance of pre-analytical and analytical variables among different instruments, together with optimized post-analytical data analysis and reference values were assessed. Overall, 265 blood samples were used for design and validation of the antibody combinations and in vitro functional assays, as well as for assessing the impact of sample preparation procedures and conditions. The two (11- and 14-color) antibody combinations allowed for robust and sensitive detection of 19 and 23 IMC populations, respectively. Highly reproducible identification and enumeration of IMC populations was achieved, independently of anticoagulant, type of FCM instrument and center, particularly when database/software-guided automated (vs. manual “expert-based”) gating was used. Whereas no significant changes were observed in identification of IMC populations for up to 24h delayed sample processing, a significant impact was observed in their absolute counts after >12h delay. Therefore, accurate identification and quantitation of IMC populations requires sample processing on the same day. Significantly different counts were observed in PB for multiple IMC populations according to age and sex. Consequently, PB samples from 116 healthy donors (8-69 years) were used for collecting age and sex related reference values for all IMC populations. In summary, the two antibody combinations and FCM approach allow for rapid, standardized, automated and reproducible identification of 19 and 23 IMC populations in PB, suited for monitoring of innate immune responses in clinical and translational research settings.

Abstract LB034: Evaluation of a novel single-cell RNA sequencing methodology for use in clinical trial settings

Abstract Bulk RNA sequencing (RNA-seq) is regularly employed for transcriptional profiling but provides only a snapshot of the average population. Particularly when studying disease, understanding differences in diverse cells is essential thus single-cell resolution is a necessity due to significant cellular heterogeneity. High-throughput droplet- and microfluidic-based approaches for performing single-cell RNA-seq (scRNA-seq) are invaluable techniques for uncovering changes in cells such as differential gene expression and epigenetic states in cancer research. A challenge for scRNA-seq, however, is sample preparation as typically tissues must be processed immediately after collection. We and others have reported alternative approaches to stabilize samples prior to analysis such as cryopreservation of cells and tissues and methanol-based fixation of cells. However, the inclusion of these approaches is still limited in many settings due to the challenging logistics involved in sample collection. To further broaden the ability of researchers to deploy scRNA-seq, we report our experiences from testing a pre-commercial workflow developed by 10x Genomics to resolve these sample management limitations. The use of paraformaldehyde (PFA) to fix samples at the collection site allows samples to be transported to remote laboratories for downstream processing without sacrificing integrity or data quality. This advance has enabled new possibilities for sample accessibility, throughput, and batched analysis in basic and translational research settings. Furthermore, this approach also allows for analysis of transcriptome-wide gene expression at high sensitivity with simultaneous cellular readouts. Here we report a case study comparing the PFA method to standard approaches, and highlight advantages and potential applications previously not possible with reported sample preparation strategies. Citation Format: David Corney, Yang Han, Yu Qiu, Yongjun Fan, Michael Stephens, Andrea O'Hara, Laure Turner, Christopher Mozdzierz, Haythem Latif, Ginger Zhou. Evaluation of a novel single-cell RNA sequencing methodology for use in clinical trial settings [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB034.

Mapping of Transdiagnostic Neuropsychiatric Phenotypes Across Patients in Two General Hospitals.

Multidimensional transdiagnostic phenotyping systems are increasingly important to neuropsychiatric phenotyping, particularly in translational research settings. The relationship the National Institute of Mental Health's Research Domain Criteria multidimensional approach to psychopathology and nonpsychiatric diagnoses has not been studied at scale but is relevant to those caring for neuropsychiatric illness in medical and surgical settings. We applied the CQH Dimensional Phenotyper natural language processing tool to estimate National Institute of Mental Health's Research Domain Criteria domain-associated symptoms of individuals admitted to nonpsychiatric wards at each of 2 large academic general hospitals over an 8-year period. We compared patterns in individual domain symptom burden, as well as a new pooled unidimensional measure, by primary medical and surgical diagnosis. Analysis included 227,243 patients from hospital 1 of whom 68,793 (30.3%) had a prior psychiatric history and 220,213 patients from hospital 2 of whom 50,818 (23.1%) had a prior psychiatric history. The distribution of Research Domain Criteria symptom burdens over primary diagnosis was similar across hospital sites and differed significantly across primary medical or surgical diagnosis. The effect of primary medical or surgical diagnosis was larger than that of prior psychiatric history on Research Domain Criteria symptom burden. Research Domain Criteria-based neuropsychiatric symptom burden estimated from general hospital patients' clinical documentation is more strongly associated with the primary hospital medical or surgical diagnosis than it is with the presence of a previous psychiatric history. The bidirectional role of psychiatric and somatic illness warrants further study through the lens of transdiagnostic phenotyping.

Metabolomics in cancer research and emerging applications in clinical oncology.

Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.

The TRACE-Seq method tracks recombination alleles and identifies clonal reconstitution dynamics of gene targeted human hematopoietic stem cells

Targeted DNA correction of disease-causing mutations in hematopoietic stem and progenitor cells (HSPCs) may enable the treatment of genetic diseases of the blood and immune system. It is now possible to correct mutations at high frequencies in HSPCs by combining CRISPR/Cas9 with homologous DNA donors. Because of the precision of gene correction, these approaches preclude clonal tracking of gene-targeted HSPCs. Here, we describe Tracking Recombination Alleles in Clonal Engraftment using sequencing (TRACE-Seq), a methodology that utilizes barcoded AAV6 donor template libraries, carrying in-frame silent mutations or semi-randomized nucleotides outside the coding region, to track the in vivo lineage contribution of gene-targeted HSPC clones. By targeting the HBB gene with an AAV6 donor template library consisting of ~20,000 possible unique exon 1 in-frame silent mutations, we track the hematopoietic reconstitution of HBB targeted myeloid-skewed, lymphoid-skewed, and balanced multi-lineage repopulating human HSPC clones in mice. We anticipate this methodology could potentially be used for HSPC clonal tracking of Cas9 RNP and AAV6-mediated gene targeting outcomes in translational and basic research settings.

Integrated, automated maintenance, expansion and differentiation of 2D and 3D patient-derived cellular models for high throughput drug screening

Patient-derived cellular models become an increasingly powerful tool to model human diseases for precision medicine approaches. The identification of robust cellular disease phenotypes in these models paved the way towards high throughput screenings (HTS) including the implementation of laboratory advanced automation. However, maintenance and expansion of cells for HTS remains largely manual work. Here, we describe an integrated, complex automated platform for HTS in a translational research setting also designed for maintenance and expansion of different cell types. The comprehensive design allows automation of all cultivation steps and is flexible for development of methods for variable cell types. We demonstrate protocols for controlled cell seeding, splitting and expansion of human fibroblasts, induced pluripotent stem cells (iPSC), and neural progenitor cells (NPC) that allow for subsequent differentiation into different cell types and image-based multiparametric screening. Furthermore, we provide automated protocols for neuronal differentiation of NPC in 2D culture and 3D midbrain organoids for HTS. The flexibility of this multitask platform makes it an ideal solution for translational research settings involving experiments on different patient-derived cellular models for precision medicine.

Analytical performance of a 25‐marker spectral cytometry immune monitoring assay in peripheral blood

AbstractHerein, we describe the development and analytical performance characteristics of a spectral flow cytometry assay for longitudinal immune monitoring biomarker applications in human whole blood and/or peripheral blood mononuclear cells (PBMCs). This 25 immune biomarker panel and robust gating strategy, developed in normal healthy volunteers, resolves memory, polarization, and activation markers on T, B, and NK cells as well as myeloid subpopulations including monocytes, dendritic cells, neutrophils, basophils, and myeloid‐derived suppressor cells (MDSCs). Three associated fluorescence‐minus‐multiple (FMM) designs are proposed as gating controls. To our knowledge, this is the first report to investigate intra‐run precision, post collection whole blood stability, and the impact of PBMC processing in the context of spectral cytometry. We achieved high intra‐run sample precision (&lt;20% CV) for &gt;95% of all gated immune cell populations analyzed across biospecimen types. Additionally, we explored the application of FlowSOM analysis and resulting impact on assay precision metrics. We observed biomarker stability in blood out to 24 h (86%), 48 h (83%), and 72 h (76%) while highlighting select markers (i.e., CXCR3) and rare cell subsets (i.e., naïve Tregs, plasmacytoid DCs, MDSCs) affected by storage and/or PBMC manipulation. Interrogation of sample type is imperative to coherent application of immune monitoring assays. Overall based on analytical performance, this 25‐biomarker spectral cytometry assay is sufficiently robust for implementation in translational research settings.

Facilitating translational team science: The project leader model.

Project management expertise is employed across many professional sectors, including clinical research organizations, to ensure that efforts undertaken by the organization are completed on time and according to specifications and are capable of achieving the needed impact. Increasingly, project leaders (PLs) who possess this expertise are being employed in academic settings to support clinical and preclinical translational research team science. Duke University's clinical and translational science enterprise has been an early adopter of project management to support clinical and preclinical programs. We review the history and evolution of project management and the PL role at Duke, examine case studies that illustrate their growing value to our academic research environment, and address challenges and solutions to employing project management in academia. Furthermore, we describe the critical role project leadership plays in accelerating and increasing the success of translational team science and team approaches frequently required for systems biology and "big data" scientific studies. Finally, we discuss perspectives from Duke project leadership professionals regarding the training needs and requirements for PLs working in academic clinical and translational science research settings.