Specificity and overlap in gene segment-defined antibody repertoires

BACKGROUND: To date several studies have sought to catalog the full suite of antibodies that humans naturally produce against single antigens or other specificities (repertoire). Here we analyze the properties of all sequenced repertoires in order to better understand the specificity of antibody responses. Specifically, we ask whether the large-scale sequencing of antibody repertoires might provide a diagnostic tool for detecting antigen exposure. We do this by examining the overlap in V(H)-, D-, and J(H)- segment usage among sequenced repertoires. RESULTS: We find that repertoire overlap in V(H)-, D-, and J(H)-segment use is least for V(H )segments and greatest for J(H )segments, consistent with there being more V(H )than J(H )segments in the human genome. We find that for any two antigens chosen at random, chances are 90 percent that their repertoires' V(H )segments will overlap by less than half, and 98 percent that their VDJ(H )combinations will overlap by ≤10 percent. We ran computer simulations to test whether enrichment for specific VDJ(H )combinations could be detected in "antigen-exposed" populations, and found that enrichment is detectable with moderate-to-high sensitivity and high specificity, even when some VDJ(H )combinations are not represented at all in some test sets. CONCLUSION: Thus, as large-scale sequencing becomes cost-effective for clinical testing, we suggest that sequencing an individual's expressed antibody repertoire has the potential to become a useful diagnostic modality

What we learned in kindergarten: five tips for collaboration in oncology

As you read the five tenets presented here, think about these simple truths of leading and influencing others, managing failure, thinking strategically, and resolving conflicts. Ap - ply them to the world in which we all now live and play. Far too often work (the place) is viewed simply as where work (the action) occurs. What we are saying is that, although institutional targets (such as reducing wait times to see new patients) are all laudable goals, there has to be more, and play has to become an essential component of work. What can we uncover, rediscover, and create to make the time spent with one another the best possible experience for everyone involved? Even more importantly, what must we do to ensure that what we create and share has the possibil - ity and potential to make our lives and the world a better place? Play isn’t something we do as a part of life—it is life.info:eu-repo/semantics/publishedVersio

The Future of Blood Testing Is the Immunome

It is increasingly clear that an extraordinarily diverse range of clinically important conditions-including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers-leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person's B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome

Liver transplantation for glycogen storage disease types I, III, and IV

Glycogen storage disease (GSD) types I, III, and IV can be associated with severe liver disease. The possible development of hepatocellular carcinoma and/or hepatic failure make these GSDs potential candidates for liver transplantation. Early diagnosis and initiation of effective dietary therapy have dramatically improved the outcome of GSD type I by reducing the incidence of liver adenoma and renal insufficiency. Nine type I and 3 type III patients have received liver transplants because of poor metabolic control, multiple liver adenomas, or progressive liver failure. Metabolic abnormalities were corrected in all GSD type I and type III patients, while catch-up growth was reported only in two patients. Whether liver transplantation results in reversal and/or prevention of renal disease remains unclear. Neutropenia persisted in both GSDIb patients post liver transplantation necessitating continuous granulocyte colony stimulating factor treatment. Thirteen GSD type IV patients were liver transplanted because of progressive liver cirrhosis and failure. All but one patient have not had neuromuscular or cardiac complications during follow-up periods for as long as 13 years. Four have died within a week and 5 years after transplantation. Caution should be taken in selecting GSD type IV candidates for liver transplantation because of the variable phenotype, which may include life-limiting extrahepatic manifestations. It remains to be evaluated, whether a genotype-phenotype correlation exists for GSD type IV, which may aid in the decision making. Conclusion Liver transplantation should be considered for patients with glycogen storage disease who have developed liver malignancy or hepatic failure, and for type IV patients with the classical and progressive hepatic form

Collective Epithelial Migration Drives Kidney Repair after Acute Injury

Acute kidney injury (AKI) is a common and significant medical problem. Despite the kidney’s remarkable regenerative capacity, the mortality rate for the AKI patients is high. Thus, there remains a need to better understand the cellular mechanisms of nephron repair in order to develop new strategies that would enhance the intrinsic ability of kidney tissue to regenerate. Here, using a novel, laser ablation-based, zebrafish model of AKI, we show that collective migration of kidney epithelial cells is a primary early response to acute injury. We also show that cell proliferation is a late response of regenerating kidney epithelia that follows cell migration during kidney repair. We propose a computational model that predicts this temporal relationship and suggests that cell stretch is a mechanical link between migration and proliferation, and present experimental evidence in support of this hypothesis. Overall, this study advances our understanding of kidney repair mechanisms by highlighting a primary role for collective cell migration, laying a foundation for new approaches to treatment of AKI

The next frontier: Fostering innovation by improving health data access and utilization

Beneath most lively policy debates sit dry-as-dust theoretical and methodological discussions. Current disputes over the EU Adaptive Pathways initiative and the proposed US 21st Century Cures Act may ultimately rest on addressing arcane issues of data curation, standardization, and utilization. Improved extraction of inform ation on the safety and effectiveness of drugs-in-use must parallel adjustments in evidence requirements at the time of licensing. To do otherwise may compromise safety and efficacy in the name of fostering innovation

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6-91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice

Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements

Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human beta-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the beta-globin locus. We also identified a new looping interaction in K562 cells between the beta-globin Locus Control Region and the gamma-beta-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure