<b>Department of bioinformatics in infection research ([BRICS] BIFO)</b>
head of the department: Prof. McHardy
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In vitro interaction network of a synthetic gut bacterial community.A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM12) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM12 interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM12 interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.
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Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo.Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo.
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A bipartite element with allele-specific functions safeguards DNA methylation imprints at the Dlk1-Dio3 locus.Loss of imprinting (LOI) results in severe developmental defects, but the mechanisms preventing LOI remain incompletely understood. Here, we dissect the functional components of the imprinting control region of the essential Dlk1-Dio3 locus (called IG-DMR) in pluripotent stem cells. We demonstrate that the IG-DMR consists of two antagonistic elements: a paternally methylated CpG island that prevents recruitment of TET dioxygenases and a maternally unmethylated non-canonical enhancer that ensures expression of the Gtl2 lncRNA by counteracting de novo DNA methyltransferases. Genetic or epigenetic editing of these elements leads to distinct LOI phenotypes with characteristic alternations of allele-specific gene expression, DNA methylation, and 3D chromatin topology. Although repression of the Gtl2 promoter results in dysregulated imprinting, the stability of LOI phenotypes depends on the IG-DMR, suggesting a functional hierarchy. These findings establish the IG-DMR as a bipartite control element that maintains imprinting by allele-specific restriction of the DNA (de)methylation machinery.
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Cohesin Core Complex Gene Dosage Contributes to Germinal Center Derived Lymphoma Phenotypes and Outcomes.The cohesin complex plays critical roles in genomic stability and gene expression through effects on 3D architecture. Cohesin core subunit genes are mutated across a wide cross-section of cancers, but not in germinal center (GC) derived lymphomas. In spite of this, haploinsufficiency of cohesin ATPase subunit Smc3 was shown to contribute to malignant transformation of GC B-cells in mice. Herein we explored potential mechanisms and clinical relevance of Smc3 deficiency in GC lymphomagenesis. Transcriptional profiling of Smc3 haploinsufficient murine lymphomas revealed downregulation of genes repressed by loss of epigenetic tumor suppressors Tet2 and Kmt2d. Profiling 3D chromosomal interactions in lymphomas revealed impaired enhancer-promoter interactions affecting genes like Tet2, which was aberrantly downregulated in Smc3 deficient lymphomas. Tet2 plays important roles in B-cell exit from the GC reaction, and single cell RNA-seq profiles and phenotypic trajectory analysis in Smc3 mutant mice revealed a specific defect in commitment to the final steps of plasma cell differentiation. Although Smc3 deficiency resulted in structural abnormalities in GC B-cells, there was no increase of somatic mutations or structural variants in Smc3 haploinsufficient lymphomas, suggesting that cohesin deficiency largely induces lymphomas through disruption of enhancer-promoter interactions of terminal differentiation and tumor suppressor genes. Strikingly, the presence of the Smc3 haploinsufficient GC B-cell transcriptional signature in human patients with GC-derived diffuse large B-cell lymphoma (DLBCL) was linked to inferior clinical outcome and low expression of cohesin core subunits. Reciprocally, reduced expression of cohesin subunits was an independent risk factor for worse survival int DLBCL patient cohorts. Collectively, the data suggest that Smc3 functions as a bona fide tumor suppressor for lymphomas through non-genetic mechanisms, and drives disease by disrupting the commitment of GC B-cells to the plasma cell fate.
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Offspring born to influenza A virus infected pregnant mice have increased susceptibility to viral and bacterial infections in early life.Influenza during pregnancy can affect the health of offspring in later life, among which neurocognitive disorders are among the best described. Here, we investigate whether maternal influenza infection has adverse effects on immune responses in offspring. We establish a two-hit mouse model to study the effect of maternal influenza A virus infection (first hit) on vulnerability of offspring to heterologous infections (second hit) in later life. Offspring born to influenza A virus infected mothers are stunted in growth and more vulnerable to heterologous infections (influenza B virus and MRSA) than those born to PBS- or poly(I:C)-treated mothers. Enhanced vulnerability to infection in neonates is associated with reduced haematopoetic development and immune responses. In particular, alveolar macrophages of offspring exposed to maternal influenza have reduced capacity to clear second hit pathogens. This impaired pathogen clearance is partially reversed by adoptive transfer of alveolar macrophages from healthy offspring born to uninfected dams. These findings suggest that maternal influenza infection may impair immune ontogeny and increase susceptibility to early life infections of offspring.
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Understanding and Engineering the Stereoselectivity of Humulene Synthase.The non-canonical terpene cyclase AsR6 is responsible for the formation of 2E,6E,9E-humulene during the biosynthesis of the tropolone sesquiterpenoid (TS) xenovulene A. The structures of unliganded AsR6 and of AsR6 in complex with an in crystallo cyclized reaction product and thiolodiphosphate reveal a new farnesyl diphosphate binding motif that comprises a unique binuclear Mg2+ -cluster and an essential K289 residue that is conserved in all humulene synthases involved in TS formation. Structure-based site-directed mutagenesis of AsR6 and its homologue EupR3 identify a single residue, L285/M261, that controls the production of either 2E,6E,9E- or 2Z,6E,9E-humulene. A possible mechanism for the observed stereoselectivity was investigated using different isoprenoid precursors and results demonstrate that M261 has gatekeeping control over product formation.
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EpitopeVec: Linear Epitope Prediction Using Deep Protein Sequence Embeddings.Motivation: B-cell epitopes (BCEs) play a pivotal role in the development of peptide vaccines, immuno-diagnostic reagents, and antibody production, and thus in infectious disease prevention and diagnostics in general. Experimental methods used to determine BCEs are costly and time-consuming. Therefore, it is essential to develop computational methods for the rapid identification of BCEs. Although several computational methods have been developed for this task, generalizability is still a major concern, where cross-testing of the classifiers trained and tested on different datasets has revealed accuracies of 51-53. Results: We describe a new method called EpitopeVec, which uses a combination of residue properties, modified antigenicity scales, and protein language model-based representations (protein vectors) as features of peptides for linear BCE predictions. Extensive benchmarking of EpitopeVec and other state-of-the-art methods for linear BCE prediction on several large and small datasets, as well as cross-testing, demonstrated an improvement in the performance of EpitopeVec over other methods in terms of accuracy and area under the curve (AUC). As the predictive performance depended on the species origin of the respective antigens (viral, bacterial, eukaryotic), we also trained our method on a large viral dataset to create a dedicated linear viral BCE predictor with improved cross-testing
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Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease.Background: Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors. Result: We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target. Conclusion: This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.
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Needs for an Integration of Specific Data Sources and Items - First Insights of a National Survey Within the German Center for Infection Research.State-subsidized programs develop medical data integration centers in Germany. To get infection disease (ID) researchers involved in the process of data sharing, common interests and minimum data requirements were prioritized. In 06/2019 we have initiated the German Infectious Disease Data Exchange (iDEx) project. We have developed and performed an online survey to determine prioritization of requests for data integration and exchange in ID research. The survey was designed with three sub-surveys, including a ranking of 15 data categories and 184 specific data items and a query of available 51 data collecting systems. A total of 84 researchers from 17 fields of ID research participated in the survey (predominant research fields: gastrointestinal infections n=11, healthcare-associated and antibiotic-resistant infections n=10, hepatitis n=10). 48% (40/84) of participants had experience as medical doctor. The three top ranked data categories were microbiology and parasitology, experimental data, and medication (53%, 52%, and 47% of maximal points, respectively). The most relevant data items for these categories were bloodstream infections, availability of biomaterial, and medication (88%, 87%, and 94% of maximal points, respectively). The ranking of requests of data integration and exchange is diverse and depends on the chosen measure. However, there is need to promote discipline-related digitalization and data exchange.
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Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.
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Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit.Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.
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Evaluating assembly and variant calling software for strain-resolved analysis of large DNA virusesInfection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and 6 variant callers on 10 lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data. Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive variant calls, which were strongly enriched in T to G changes in a ‘G.G’ context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.
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Hepatitis C reference viruses highlight potent antibody responses and diverse viral functional interactions with neutralising antibodies.Community-acquired pneumonia by primary or superinfections with Streptococcus pneumoniae can lead to acute respiratory distress requiring mechanical ventilation. The pore-forming toxin pneumolysin alters the alveolar-capillary barrier and causes extravasation of protein-rich fluid into the interstitial pulmonary tissue, which impairs gas exchange. Platelets usually prevent endothelial leakage in inflamed pulmonary tissue by sealing inflammation-induced endothelial gaps. We not only confirm that S pneumoniae induces CD62P expression in platelets, but we also show that, in the presence of pneumolysin, CD62P expression is not associated with platelet activation. Pneumolysin induces pores in the platelet membrane, which allow anti-CD62P antibodies to stain the intracellular CD62P without platelet activation. Pneumolysin treatment also results in calcium efflux, increase in light transmission by platelet lysis (not aggregation), loss of platelet thrombus formation in the flow chamber, and loss of pore-sealing capacity of platelets in the Boyden chamber. Specific anti-pneumolysin monoclonal and polyclonal antibodies inhibit these effects of pneumolysin on platelets as do polyvalent human immunoglobulins. In a post hoc analysis of the prospective randomized phase 2 CIGMA trial, we show that administration of a polyvalent immunoglobulin preparation was associated with a nominally higher platelet count and nominally improved survival in patients with severe S pneumoniae-related community-acquired pneumonia. Although, due to the low number of patients, no definitive conclusion can be made, our findings provide a rationale for investigation of pharmacologic immunoglobulin preparations to target pneumolysin by polyvalent immunoglobulin preparations in severe community-acquired pneumococcal pneumonia, to counteract the risk of these patients becoming ventilation dependent. This trial was registered at www.clinicaltrials.gov as #NCT01420744.
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Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories.
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Evolutionary Stabilization of Cooperative Toxin Production through a Bacterium-Plasmid-Phage Interplay.Colicins are toxins produced and released by Enterobacteriaceae to kill competitors in the gut. While group A colicins employ a division of labor strategy to liberate the toxin into the environment via colicin-specific lysis, group B colicin systems lack cognate lysis genes. In Salmonella enterica serovar Typhimurium (S. Tm), the group B colicin Ib (ColIb) is released by temperate phage-mediated bacteriolysis. Phage-mediated ColIb release promotes S. Tm fitness against competing Escherichia coli It remained unclear how prophage-mediated lysis is realized in a clonal population of ColIb producers and if prophages contribute to evolutionary stability of toxin release in S. Tm. Here, we show that prophage-mediated lysis occurs in an S. Tm subpopulation only, thereby introducing phenotypic heterogeneity to the system. We established a mathematical model to study the dynamic interplay of S. Tm, ColIb, and a temperate phage in the presence of a competing species. Using this model, we studied long-term evolution of phage lysis rates in a fluctuating infection scenario. This revealed that phage lysis evolves as bet-hedging strategy that maximizes phage spread, regardless of whether colicin is present or not. We conclude that the ColIb system, lacking its own lysis gene, is making use of the evolutionary stable phage strategy to be released. Prophage lysis genes are highly prevalent in nontyphoidal Salmonella genomes. This suggests that the release of ColIb by temperate phages is widespread. In conclusion, our findings shed new light on the evolution and ecology of group B colicin systems.IMPORTANCE Bacteria are excellent model organisms to study mechanisms of social evolution. The production of public goods, e.g., toxin release by cell lysis in clonal bacterial populations, is a frequently studied example of cooperative behavior. Here, we analyze evolutionary stabilization of toxin release by the enteric pathogen Salmonella The release of colicin Ib (ColIb), which is used by Salmonella to gain an edge against competing microbiota following infection, is coupled to bacterial lysis mediated by temperate phages. Here, we show that phage-dependent lysis and subsequent release of colicin and phage particles occurs only in part of the ColIb-expressing Salmonella population. This phenotypic heterogeneity in lysis, which represents an essential step in the temperate phage life cycle, has evolved as a bet-hedging strategy under fluctuating environments such as the gastrointestinal tract. Our findings suggest that prophages can thereby evolutionarily stabilize costly toxin release in bacterial populations.
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Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.
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Transcriptome-wide analysis uncovers the targets of the RNA-binding protein MSI2 and effects of MSI2's RNA-binding activity on IL-6 signaling.The RNA-binding protein Musashi 2 (MSI2) has emerged as an important regulator in cancer initiation, progression, and drug resistance. Translocations and deregulation of the MSI2 gene are diagnostic of certain cancers, including chronic myeloid leukemia (CML) with translocation t(7;17), acute myeloid leukemia (AML) with translocation t(10;17), and some cases of B-precursor acute lymphoblastic leukemia (pB-ALL). To better understand the function of MSI2 in leukemia, the mRNA targets that are bound and regulated by MSI2 and their MSI2-binding motifs need to be identified. To this end, using photoactivatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) and the multiple EM for motif elicitation (MEME) analysis tool, here we identified MSI2's mRNA targets and the consensus RNA-recognition element (RRE) motif recognized by MSI2 (UUAG). Of note, MSI2 knockdown altered the expression of several genes with roles in eukaryotic initiation factor 2 (eIF2), hepatocyte growth factor (HGF), and epidermal growth factor (EGF) signaling pathways. We also show that MSI2 regulates classic interleukin-6 (IL-6) signaling by promoting the degradation of the mRNA of IL-6 signal transducer (IL6ST or GP130), which, in turn, affected the phosphorylation statuses of signal transducer and activator of transcription 3 (STAT3) and the mitogen-activated protein kinase ERK. In summary, we have identified multiple MSI2-regulated mRNAs and provided evidence that MSI2 controls IL6ST activity that control oncogenic signaling networks. Our findings may help inform strategies for unraveling the role of MSI2 in leukemia to pave the way for the development of targeted therapies.
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YBX1 Indirectly Targets Heterochromatin-Repressed Inflammatory Response-Related Apoptosis Genes through Regulating CBX5 mRNA.Medulloblastomas arise from undifferentiated precursor cells in the cerebellum and account for about 20% of all solid brain tumors during childhood; standard therapies include radiation and chemotherapy, which oftentimes come with severe impairment of the cognitive development of the young patients. Here, we show that the posttranscriptional regulator Y-box binding protein 1 (YBX1), a DNA- and RNA-binding protein, acts as an oncogene in medulloblastomas by regulating cellular survival and apoptosis. We observed different cellular responses upon YBX1 knockdown in several medulloblastoma cell lines, with significantly altered transcription and subsequent apoptosis rates. Mechanistically, PAR-CLIP for YBX1 and integration with RNA-Seq data uncovered direct posttranscriptional control of the heterochromatin-associated gene CBX5; upon YBX1 knockdown and subsequent CBX5 mRNA instability, heterochromatin-regulated genes involved in inflammatory response, apoptosis and death receptor signaling were de-repressed. Thus, YBX1 acts as an oncogene in medulloblastoma through indirect transcriptional regulation of inflammatory genes regulating apoptosis and represents a promising novel therapeutic target in this tumor entity.
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Temporally feathered intensity-modulated radiation therapy: A planning technique to reduce normal tissue toxicity.Purpose: Intensity-modulated radiation therapy (IMRT) has allowed optimization of three-dimensional spatial radiation dose distributions permitting target coverage while reducing normal tissue toxicity. However, radiation-induced normal tissue toxicity is a major contributor to patients' quality of life and often a dose-limiting factor in the definitive treatment of cancer with radiation therapy. We propose the next logical step in the evolution of IMRT using canonical radiobiological principles, optimizing the temporal dimension through which radiation therapy is delivered to further reduce radiation-induced toxicity by increased time for normal tissue recovery. We term this novel treatment planning strategy "temporally feathered radiation therapy" (TFRT). Methods: Temporally feathered radiotherapy plans were generated as a composite of five simulated treatment plans each with altered constraints on particular hypothetical organs at risk (OARs) to be delivered sequentially. For each of these TFRT plans, OARs chosen for feathering receive higher doses while the remaining OARs receive lower doses than the standard fractional dose delivered in a conventional fractionated IMRT plan. Each TFRT plan is delivered a specific weekday, which in effect leads to a higher dose once weekly followed by four lower fractional doses to each temporally feathered OAR. We compared normal tissue toxicity between TFRT and conventional fractionated IMRT plans by using a dynamical mathematical model to describe radiation-induced tissue damage and repair over time. Results: Model-based simulations of TFRT demonstrated potential for reduced normal tissue toxicity compared to conventionally planned IMRT. The sequencing of high and low fractional doses delivered to OARs by TFRT plans suggested increased normal tissue recovery, and hence less overall radiation-induced toxicity, despite higher total doses delivered to OARs compared to conventional fractionated IMRT plans. The magnitude of toxicity reduction by TFRT planning was found to depend on the corresponding standard fractional dose of IMRT and organ-specific recovery rate of sublethal radiation-induced damage. Conclusions: TFRT is a novel technique for treatment planning and optimization of therapeutic radiotherapy that considers the nonlinear aspects of normal tissue repair to optimize toxicity profiles. Model-based simulations of TFRT to carefully conceptualized clinical cases have demonstrated potential for radiation-induced toxicity reduction in a previously described dynamical model of normal tissue complication probability (NTCP).