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Background: Neoantigen vaccines can induce or enhance highly specific antitumor immune responses with minimal risk of autoimmunity. We have developed a neoantigen DNA vaccine platform capable of efficiently presenting both HLA class I and II epitopes and performed a phase 1 clinical trial in triple-negative breast cancer patients with persistent disease on surgical pathology following neoadjuvant chemotherapy, a patient population at high risk of disease recurrence., Methods: Expressed somatic mutations were identified by tumor/normal exome sequencing and tumor RNA sequencing. The pVACtools software suite of neoantigen prediction algorithms was used to identify and prioritize cancer neoantigens and facilitate vaccine design for manufacture in an academic GMP facility. Neoantigen DNA vaccines were administered via electroporation in the adjuvant setting (i.e., following surgical removal of the primary tumor and completion of standard of care therapy). Vaccines were monitored for safety and immune responses via ELISpot, intracellular cytokine production via flow cytometry, and TCR sequencing., Results: Eighteen subjects received three doses of a neoantigen DNA vaccine encoding on average 11 neoantigens per patient (range 4-20). The vaccinations were well tolerated with relatively few adverse events. Neoantigen-specific T cell responses were induced in 14/18 patients as measured by ELISpot and flow cytometry. At a median follow-up of 36 months, recurrence-free survival was 87.5% (95% CI: 72.7-100%) in the cohort of vaccinated patients., Conclusion: Our study demonstrates neoantigen DNA vaccines are safe, feasible, and capable of inducing neoantigen-specific immune responses., Clinical Trial Registration Number: NCT02348320., Competing Interests: Declarations Ethics approval and consent to participate The clinical protocol was reviewed and approved by the Institutional Review Board (ID# 201505074) at Washington University School of Medicine. The research conformed to the principles of the Helsinki/Tokyo/Venice Declaration on experimentation in humans. Consent for publication Written consent for publication was obtained from all participating patients. Competing interests K.S., M.G., and O.G. are consultants for the Jaime Leandro Foundation. All other authors declare that they have no competing interests., (© 2024. The Author(s).)

Background: Macrophages play important roles in phagocytosing tumor cells. However, tumors escape macrophage phagocytosis in part through the expression of anti-phagocytic signals, most commonly CD47. In Ewing sarcoma (ES), we found that tumor cells utilize dual mechanisms to evade macrophage clearance by simultaneously over-expressing CD47 and down-regulating cell surface calreticulin (csCRT), the pro-phagocytic signal. Here, we investigate the combination of a CD47 blockade (magrolimab, MAG) to inhibit the anti-phagocytic signal and a chemotherapy regimen (doxorubicin, DOX) to enhance the pro-phagocytic signal to induce macrophage phagocytosis of ES cells in vitro and inhibit tumor growth and metastasis in vivo., Methods: Macrophages were derived from human peripheral blood monocytes by granulocyte-macrophage colony-stimulating factor (GM-CSF) and macrophage colony-stimulating factor (M-CSF). Flow cytometry- and microscopy-based in-vitro phagocytosis assays were performed to evaluate macrophage phagocytosis of ES cells. Annexin-V assay was performed to evaluate apoptosis. CD47 was knocked out by CRISPR/Cas9 approach. ES cell-based and patient-derived-xenograft (PDX)-based mouse models were utilized to assess the effects of MAG and/or DOX on ES tumor development and animal survival. RNA-Seq combined with CIBERSORTx analysis was utilized to identify changes in tumor cell transcriptome and tumor infiltrating immune cell profiling in MAG and/or DOX treated xenograft tumors., Results: We found that MAG significantly increased macrophage phagocytosis of ES cells in vitro (p < 0.01) and had significant effect on reducing tumor burden (p < 0.01) and increasing survival in NSG mouse model (p < 0.001). The csCRT level on ES cells was significantly enhanced by DOX in a dose- and time-dependent manner (p < 0.01). Importantly, DOX combined with MAG significantly enhanced macrophage phagocytosis of ES cells in vitro (p < 0.01) and significantly decreased tumor burden (p < 0.01) and lung metastasis (p < 0.0001) and extended animal survival in vivo in two different mouse models of ES (p < 0.0001). Furthermore, we identified CD38, CD209, CD163 and CD206 as potential markers for ES-phagocytic macrophages. Moreover, we found increased M2 macrophage infiltration and decreased expression of Cd209 in the tumor microenvironment of MAG and DOX combinatorial therapy treated tumors., Conclusions: By turning "two keys" simultaneously to reactivate macrophage phagocytic activity, our data demonstrated an effective and highly translatable alternative therapeutic approach utilizing innate (tumor associated macrophages) immunotherapy against high-risk metastatic ES., (© 2024. The Author(s).)

Background: Genetic ancestry, inferred from genomic data, is a quantifiable biological parameter. While much of the human genome is identical across populations, it is estimated that as much as 0.4% of the genome can differ due to ancestry. This variation is primarily characterized by single nucleotide variants (SNVs), which are often unique to specific genetic populations. Knowledge of a patient's genetic ancestry can inform clinical decisions, from genetic testing and health screenings to medication dosages, based on ancestral disease predispositions. Nevertheless, the current reliance on self-reported ancestry can introduce subjectivity and exacerbate health disparities. While genomic sequencing data enables objective determination of a patient's genetic ancestry, existing approaches are limited to ancestry inference at the continental level., Results: To address this challenge, and create an objective, measurable metric of genetic ancestry we present SNVstory, a method built upon three independent machine learning models for accurately inferring the sub-continental ancestry of individuals. We also introduce a novel method for simulating individual samples from aggregate allele frequencies from known populations. SNVstory includes a feature-importance scheme, unique among open-source ancestral tools, which allows the user to track the ancestral signal broadcast by a given gene or locus. We successfully evaluated SNVstory using a clinical exome sequencing dataset, comparing self-reported ethnicity and race to our inferred genetic ancestry, and demonstrate the capability of the algorithm to estimate ancestry from 36 different populations with high accuracy., Conclusions: SNVstory represents a significant advance in methods to assign genetic ancestry, opening the door to ancestry-informed care. SNVstory, an open-source model, is packaged as a Docker container for enhanced reliability and interoperability. It can be accessed from https://github.com/nch-igm/snvstory ., (© 2024. The Author(s).)

Background: Cancers exhibit complex transcriptomes with aberrant splicing that induces isoform-level differential expression compared to non-diseased tissues. Transcriptomic profiling using short-read sequencing has utility in providing a cost-effective approach for evaluating isoform expression, although short-read assembly displays limitations in the accurate inference of full-length transcripts. Long-read RNA sequencing (Iso-Seq), using the Pacific Biosciences (PacBio) platform, can overcome such limitations by providing full-length isoform sequence resolution which requires no read assembly and represents native expressed transcripts. A constraint of the Iso-Seq protocol is due to fewer reads output per instrument run, which, as an example, can consequently affect the detection of lowly expressed transcripts. To address these deficiencies, we developed a concatenation workflow, PacBio Full-Length Isoform Concatemer Sequencing (PB&#95;FLIC-Seq), designed to increase the number of unique, sequenced PacBio long-reads thereby improving overall detection of unique isoforms. In addition, we anticipate that the increase in read depth will help improve the detection of moderate to low-level expressed isoforms., Results: In sequencing a commercial reference (Spike-In RNA Variants; SIRV) with known isoform complexity we demonstrated a 3.4-fold increase in read output per run and improved SIRV recall when using the PB&#95;FLIC-Seq method compared to the same samples processed with the Iso-Seq protocol. We applied this protocol to a translational cancer case, also demonstrating the utility of the PB&#95;FLIC-Seq method for identifying differential full-length isoform expression in a pediatric diffuse midline glioma compared to its adjacent non-malignant tissue. Our data analysis revealed increased expression of extracellular matrix (ECM) genes within the tumor sample, including an isoform of the Secreted Protein Acidic and Cysteine Rich (SPARC) gene that was expressed 11,676-fold higher than in the adjacent non-malignant tissue. Finally, by using the PB&#95;FLIC-Seq method, we detected several cancer-specific novel isoforms., Conclusion: This work describes a concatenation-based methodology for increasing the number of sequenced full-length isoform reads on the PacBio platform, yielding improved discovery of expressed isoforms. We applied this workflow to profile the transcriptome of a pediatric diffuse midline glioma and adjacent non-malignant tissue. Our findings of cancer-specific novel isoform expression further highlight the importance of long-read sequencing for characterization of complex tumor transcriptomes., (© 2024. The Author(s).)

Background: Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers., Methods: We combined immunohistochemistry (IHC) with RNA sequencing and whole-genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8 + T-cell infiltration of the TIME. Furthermore, we explored transcriptional features of immune archetypes and T-cell receptor sequencing diversity, assessed the relationship between CD8 + and CD4 + abundance by IHC and deconvolution predictions and assessed the common adult biomarkers such as neoantigen load and TMB., Results: A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells., Conclusions: Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME., (© 2023. The Author(s).)

Rasmussen encephalitis (RE) is a rare childhood neurological disease characterized by progressive unilateral loss of function, hemispheric atrophy and drug-resistant epilepsy. Affected brain tissue shows signs of infiltrating cytotoxic T-cells, microglial activation, and neuronal death, implicating an inflammatory disease process. Recent studies have identified molecular correlates of inflammation in RE, but cell-type-specific mechanisms remain unclear. We used single-nucleus RNA-sequencing (snRNA-seq) to assess gene expression across multiple cell types in brain tissue resected from two children with RE. We found transcriptionally distinct microglial populations enriched in RE compared to two age-matched individuals with unaffected brain tissue and two individuals with Type I focal cortical dysplasia (FCD). Specifically, microglia in RE tissues demonstrated increased expression of genes associated with cytokine signaling, interferon-mediated pathways, and T-cell activation. We extended these findings using spatial proteomic analysis of tissue from four surgical resections to examine expression profiles of microglia within their pathological context. Microglia that were spatially aggregated into nodules had increased expression of dynamic immune regulatory markers (PD-L1, CD14, CD11c), T-cell activation markers (CD40, CD80) and were physically located near distinct CD4+ and CD8+ lymphocyte populations. These findings help elucidate the complex immune microenvironment of RE., (© 2022. The Author(s).)

Primary spinal cord tumors contribute to ≤ 10% of central nervous system tumors in individuals of pediatric or adolescent age. Among intramedullary tumors, spinal ependymomas make up ~ 30% of this rare tumor population. A twelve-year-old male presented with an intradural, extramedullary mass occupying the dorsal spinal canal from C6 through T2. Gross total resection and histopathology revealed a World Health Organization (WHO) grade 2 ependymoma. He recurred eleven months later with extension from C2 through T1-T2. Subtotal resection was achieved followed by focal proton beam irradiation and chemotherapy. Histopathology was consistent with WHO grade 3 ependymoma. Molecular profiling of the primary and recurrent tumors revealed a novel amplification of the MYC (8q24) gene, which was confirmed by fluorescence in situ hybridization studies. Although MYC amplification in spinal ependymoma is exceedingly rare, a newly described classification of spinal ependymoma harboring MYCN (2p24) amplification (SP-MYCN) has been defined by DNA methylation-array based profiling. These individuals typically present with a malignant progression and dismal outcomes, contrary to the universally excellent survival outcomes seen in other spinal ependymomas. DNA methylation array-based classification confidently classified this tumor as SP-MYCN ependymoma. Notably, among the cohort of 52 tumors comprising the SP-MYCN methylation class, none harbor MYC amplification, highlighting the rarity of this genomic amplification in spinal ependymoma. A literature review comparing our individual to reported SP-MYCN tumors (n = 26) revealed similarities in clinical, histopathologic, and molecular features. Thus, we provide evidence from a single case to support the inclusion of MYC amplified spinal ependymoma within the molecular subgroup of SP-MYCN., (© 2021. The Author(s).)

Background: Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions., Results: Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient's medical record, both known and novel fusions provided medically meaningful information., Conclusions: The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies., (© 2021. The Author(s).)

Retinoblastoma is a childhood cancer of the retina involving germline or somatic alterations of the RB Transcriptional Corepressor 1 gene, RB1. Rare cases of sellar-suprasellar region retinoblastoma without evidence of ocular or pineal tumors have been described. A nine-month-old male presented with a sellar-suprasellar region mass. Histopathology showed an embryonal tumor with focal Flexner-Wintersteiner-like rosettes and loss of retinoblastoma protein (RB1) expression by immunohistochemistry. DNA array-based methylation profiling confidently classified the tumor as pineoblastoma group A/intracranial retinoblastoma. The patient was subsequently enrolled on an institutional translational cancer research protocol and underwent comprehensive molecular profiling, including paired tumor/normal exome and genome sequencing and RNA-sequencing of the tumor. Additionally, Pacific Biosciences (PacBio) Single Molecule Real Time (SMRT) sequencing was performed from comparator normal and disease-involved tissue to resolve complex structural variations. RNA-sequencing revealed multiple fusions clustered within 13q14.1-q21.3, including a novel in-frame fusion of RB1-SIAH3 predicted to prematurely truncate the RB1 protein. SMRT sequencing revealed a complex structural rearrangement spanning 13q14.11-q31.3, including two somatic structural variants within intron 17 of RB1. These events corresponded to the RB1-SIAH3 fusion and a novel RB1 rearrangement expected to correlate with the complete absence of RB1 protein expression. Comprehensive molecular analysis, including DNA array-based methylation profiling and sequencing-based methodologies, were critical for classification and understanding the complex mechanism of RB1 inactivation in this diagnostically challenging tumor.

The resurgence of immune therapies in cancer medicine has elicited a corresponding interest in understanding the basis of patient response or resistance to these treatments. One aspect of patient response clearly lies in the genomic alterations that are associated with cancer onset and progression, including those that contribute to genomic instability and the resulting creation of novel peptide sequences that may present as neoantigens. The immune reaction to these unique 'non-self' peptides is frequently suppressed by the tumor itself, but the use of checkpoint blockade therapies, personalized vaccines, or a combination of these treatments may elicit a tumor-specific immune response that results in cell death. Massively parallel sequencing, coupled with different computational analyses, provides unbiased identification of the germline and somatic alterations that drive cancer development, and of those alterations that lead to neoantigens. These range from simple point mutations that change single amino acids to complex alterations, such as frameshift insertion or deletion mutations, splice-site alterations that lead to exon skipping, structural alterations that lead to the formation of fusion proteins, and other forms of collateral damage caused by genome instability that result in new protein sequences unique to the cancer. The various genome instability phenotypes can be identified as alterations that impact DNA replication or mismatch repair pathways or by their genomic signatures. This review provides an overview of current knowledge regarding the fundamentals of genome replication and of both germline and somatic alterations that disrupt normal replication, leading to various forms of genomic instability in cancers, to the resulting generation of neoantigens and, ultimately, to immune-responsive and resistant phenotypes.

New computational and database-driven tools are emerging to aid in the interpretation of cancer genomic data as its use becomes more common in clinical evidence-based cancer medicine. Two such open source tools, published recently in Genome Medicine, provide important advances to address the clinical cancer genomics data interpretation bottleneck.

Background: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoints, standard visualizations, such as scatterplots, can be difficult to interpret. Current data visualization methods are also typically manual and laborious, and often only approximate subclonal fractions., Results: We have developed an R package that accurately and intuitively displays changes in clonal structure over time. It requires simple input data and produces illustrative and easy-to-interpret graphs suitable for diagnosis, presentation, and publication., Conclusions: The simplicity, power, and flexibility of this tool make it valuable for visualizing tumor evolution, and it has potential utility in both research and clinical settings. The fishplot package is available at https://github.com/chrisamiller/fishplot .

Cancer immunotherapy has gained significant momentum from recent clinical successes of checkpoint blockade inhibition. Massively parallel sequence analysis suggests a connection between mutational load and response to this class of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies. Here, we present a flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation and expression data (DNA- and RNA-Seq). pVAC-Seq is available at https://github.com/griffithlab/pVAC-Seq .

Background: The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories., Methods: 514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies., Results: The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online., Conclusions: The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

The introduction of next-generation sequencing technologies has dramatically impacted the life sciences, perhaps most profoundly in the area of cancer genomics. Clinical applications of next-generation sequencing and associated methods are emerging from ongoing large-scale discovery projects that have catalogued hundreds of genes as having a role in cancer susceptibility, onset and progression. For example, discovery cancer genomics has confirmed that many of the same genes are altered by mutation, copy number gain or loss, or structural variation across multiple tumor types, resulting in a gain or loss of function that likely contributes to cancer development in these tissues. Beyond these frequently mutated genes, we now know there is a 'long tail' of less frequently mutated, but probably important, genes that play roles in cancer onset or progression. Here, I discuss some of the remaining barriers to clinical translation, and look forward to new applications of these technologies in cancer care.

Background: Genomic studies in non-domestic avian models, such as the California condor and white-throated sparrow, can lead to more comprehensive conservation plans and provide clues for understanding mechanisms affecting genetic variation, adaptation and evolution.Developing genomic tools and resources including genomic libraries and a genetic map of the California condor is a prerequisite for identification of candidate loci for a heritable embryonic lethal condition. The white-throated sparrow exhibits a stable genetic polymorphism (i.e. chromosomal rearrangements) associated with variation in morphology, physiology, and behavior (e.g., aggression, social behavior, sexual behavior, parental care).In this paper we outline the utility of these species as well as report on recent advances in the study of their genomes., Results: Genotyping of the condor resource population at 17 microsatellite loci provided a better assessment of the current population's genetic variation. Specific New World vulture repeats were found in the condor genome. Using condor BAC library and clones, chicken-condor comparative maps were generated. A condor fibroblast cell line transcriptome was characterized using the 454 sequencing technology.Our karyotypic analyses of the sparrow in combination with other studies indicate that the rearrangements in both chromosomes 2m and 3a are complex and likely involve multiple inversions, interchromosomal linkage, and pleiotropy. At least a portion of the rearrangement in chromosome 2m existed in the common ancestor of the four North American species of Zonotrichia, but not in the one South American species, and that the 2m form, originally thought to be the derived condition, might actually be the ancestral one., Conclusion: Mining and characterization of candidate loci in the California condor using molecular genetic and genomic techniques as well as linkage and comparative genomic mapping will eventually enable the identification of carriers of the chondrodystrophy allele, resulting in improved genetic management of this disease.In the white-throated sparrow, genomic studies, combined with ecological data, will help elucidate the basis of genic selection in a natural population. Morphs of the sparrow provide us with a unique opportunity to study intraspecific genomic differences, which have resulted from two separate yet linked evolutionary trajectories. Such results can transform our understanding of evolutionary and conservation biology.

Background: Investigators in the biological sciences continue to exploit laboratory automation methods and have dramatically increased the rates at which they can generate data. In many environments, the methods themselves also evolve in a rapid and fluid manner. These observations point to the importance of robust information management systems in the modern laboratory. Designing and implementing such systems is non-trivial and it appears that in many cases a database project ultimately proves unserviceable., Results: We describe a general modeling framework for laboratory data and its implementation as an information management system. The model utilizes several abstraction techniques, focusing especially on the concepts of inheritance and meta-data. Traditional approaches commingle event-oriented data with regular entity data in ad hoc ways. Instead, we define distinct regular entity and event schemas, but fully integrate these via a standardized interface. The design allows straightforward definition of a "processing pipeline" as a sequence of events, obviating the need for separate workflow management systems. A layer above the event-oriented schema integrates events into a workflow by defining "processing directives", which act as automated project managers of items in the system. Directives can be added or modified in an almost trivial fashion, i.e., without the need for schema modification or re-certification of applications. Association between regular entities and events is managed via simple "many-to-many" relationships. We describe the programming interface, as well as techniques for handling input/output, process control, and state transitions., Conclusion: The implementation described here has served as the Washington University Genome Sequencing Center's primary information system for several years. It handles all transactions underlying a throughput rate of about 9 million sequencing reactions of various kinds per month and has handily weathered a number of major pipeline reconfigurations. The basic data model can be readily adapted to other high-volume processing environments.

Background: The human rhinoviruses (HRV) are one of the most common and diverse respiratory pathogens of humans. Over 100 distinct HRV serotypes are known, yet only 6 genomes are available. Due to the paucity of HRV genome sequence, little is known about the genetic diversity within HRV or the forces driving this diversity. Previous comparative genome sequence analyses indicate that recombination drives diversification in multiple genera of the picornavirus family, yet it remains unclear if this holds for HRV., Results: To resolve this and gain insight into the forces driving diversification in HRV, we generated a representative set of 34 fully sequenced HRVs. Analysis of these genomes shows consistent phylogenies across the genome, conserved non-coding elements, and only limited recombination. However, spikes of genetic diversity at both the nucleotide and amino acid level are detectable within every locus of the genome. Despite this, the HRV genome as a whole is under purifying selective pressure, with islands of diversifying pressure in the VP1, VP2, and VP3 structural genes and two non-structural genes, the 3C protease and 3D polymerase. Mapping diversifying residues in these factors onto available 3-dimensional structures revealed the diversifying capsid residues partition to the external surface of the viral particle in statistically significant proximity to antigenic sites. Diversifying pressure in the pleconaril binding site is confined to a single residue known to confer drug resistance (VP1 191). In contrast, diversifying pressure in the non-structural genes is less clear, mapping both nearby and beyond characterized functional domains of these factors., Conclusion: This work provides a foundation for understanding HRV genetic diversity and insight into the underlying biology driving evolution in HRV. It expands our knowledge of the genome sequence space that HRV reference serotypes occupy and how the pattern of genetic diversity across HRV genomes differs from other picornaviruses. It also reveals evidence of diversifying selective pressure in both structural genes known to interact with the host immune system and in domains of unassigned function in the non-structural 3C and 3D genes, raising the possibility that diversification of undiscovered functions in these essential factors may influence HRV fitness and evolution.

Background: High throughput sequencing-by-synthesis is an emerging technology that allows the rapid production of millions of bases of data. Although the sequence reads are short, they can readily be used for re-sequencing. By re-sequencing the mRNA products of a cell, one may rapidly discover polymorphisms and splice variants particular to that cell., Results: We present the utility of massively parallel sequencing by synthesis for profiling the transcriptome of a human prostate cancer cell-line, LNCaP, that has been treated with the synthetic androgen, R1881. Through the generation of approximately 20 megabases (MB) of EST data, we detect transcription from over 10,000 gene loci, 25 previously undescribed alternative splicing events involving known exons, and over 1,500 high quality single nucleotide discrepancies with the reference human sequence. Further, we map nearly 10,000 ESTs to positions on the genome where no transcription is currently predicted to occur. We also characterize various obstacles with using sequencing by synthesis for transcriptome analysis and propose solutions to these problems., Conclusion: The use of high-throughput sequencing-by-synthesis methods for transcript profiling allows the specific and sensitive detection of many of a cell's transcripts, and also allows the discovery of high quality base discrepancies, and alternative splice variants. Thus, this technology may provide an effective means of understanding various disease states, discovering novel targets for disease treatment, and discovery of novel transcripts.